[SPARK-13595][BUILD] Move docker, extras modules into external

## What changes were proposed in this pull request? Move `docker` dirs out of top level into `external/`; move `extras/*` into `external/` ## How was this patch tested? This is tested with Jenkins tests. Author: Sean Owen <sowen@cloudera.com> Closes #11523 from srowen/SPARK-13595.
author: Sean Owen <sowen@cloudera.com> 2016-03-09 18:27:44 +0000
committer: Sean Owen <sowen@cloudera.com> 2016-03-09 18:27:44 +0000
commit: 256704c771d301700af9ebf0d180c1ba7c4116c0 (patch)
tree: f9be79919b5c6ec4847c24a086fa844555e2cd12 /external
parent: 7791d0c3a9bdfe73e071266846f9ab1491fce50c (diff)
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45 files changed, 6486 insertions, 0 deletions
diff --git a/external/docker-integration-tests/pom.xml b/external/docker-integration-tests/pom.xml
new file mode 100644
index 0000000000..1764aa9465
--- /dev/null
+++ b/external/docker-integration-tests/pom.xml
@@ -0,0 +1,184 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one or more
+  ~ contributor license agreements.  See the NOTICE file distributed with
+  ~ this work for additional information regarding copyright ownership.
+  ~ The ASF licenses this file to You under the Apache License, Version 2.0
+  ~ (the "License"); you may not use this file except in compliance with
+  ~ the License.  You may obtain a copy of the License at
+  ~
+  ~    http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing, software
+  ~ distributed under the License is distributed on an "AS IS" BASIS,
+  ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  ~ See the License for the specific language governing permissions and
+  ~ limitations under the License.
+  -->
+
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <parent>
+    <groupId>org.apache.spark</groupId>
+    <artifactId>spark-parent_2.11</artifactId>
+    <version>2.0.0-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <artifactId>spark-docker-integration-tests_2.11</artifactId>
+  <packaging>jar</packaging>
+  <name>Spark Project Docker Integration Tests</name>
+  <url>http://spark.apache.org/</url>
+  <properties>
+    <sbt.project.name>docker-integration-tests</sbt.project.name>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>com.spotify</groupId>
+      <artifactId>docker-client</artifactId>
+      <classifier>shaded</classifier>
+      <scope>test</scope>
+      <!--
+        See https://github.com/spotify/docker-client/pull/272#issuecomment-155249101
+        for an explanation of why these exclusions are (necessarily) a mess.
+      -->
+      <exclusions>
+        <exclusion>
+          <groupId>com.fasterxml.jackson.jaxrs</groupId>
+          <artifactId>jackson-jaxrs-json-provider</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>com.fasterxml.jackson.datatype</groupId>
+          <artifactId>jackson-datatype-guava</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>com.fasterxml.jackson.core</groupId>
+          <artifactId>jackson-databind</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>org.glassfish.jersey.core</groupId>
+          <artifactId>jersey-client</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>org.glassfish.jersey.connectors</groupId>
+          <artifactId>jersey-apache-connector</artifactId>
+        </exclusion>
+        <exclusion>
+          <groupId>org.glassfish.jersey.media</groupId>
+          <artifactId>jersey-media-json-jackson</artifactId>
+        </exclusion>
+      </exclusions>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.httpcomponents</groupId>
+      <artifactId>httpclient</artifactId>
+      <version>4.5</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.httpcomponents</groupId>
+      <artifactId>httpcore</artifactId>
+      <version>4.4.1</version>
+      <scope>test</scope>
+    </dependency>
+    <!-- Necessary in order to avoid errors in log messages: -->
+    <dependency>
+      <groupId>com.google.guava</groupId>
+      <artifactId>guava</artifactId>
+      <version>18.0</version>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-sql_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-sql_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-test-tags_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>mysql</groupId>
+      <artifactId>mysql-connector-java</artifactId>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.postgresql</groupId>
+      <artifactId>postgresql</artifactId>
+      <scope>test</scope>
+    </dependency>
+    <!-- Oracle ojdbc jar, used for oracle  integration suite for docker testing.
+     See https://github.com/apache/spark/pull/11306 for background on why we need
+     to use a an ojdbc jar for the testcase. The maven dependency here is commented
+     because currently the maven repository does not contain the ojdbc jar mentioned.
+     Once the jar is available in maven, this could be uncommented. -->
+    <!--
+      <dependency>
+        <groupId>com.oracle</groupId>
+        <artifactId>ojdbc6</artifactId>
+        <version>11.2.0.2.0</version>
+        <scope>test</scope>
+      </dependency>
+    -->
+    <!-- Jersey dependencies, used to override version.
+     See https://github.com/apache/spark/pull/9503#issuecomment-154369560 for
+     background on why we need to use a newer Jersey only in this test module;
+     we can remove this once https://github.com/spotify/docker-client/pull/272 is
+     merged and a new docker-client release is published. -->
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-server</artifactId>
+      <version>1.19</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-core</artifactId>
+      <version>1.19</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-servlet</artifactId>
+      <version>1.19</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-json</artifactId>
+      <version>1.19</version>
+      <scope>test</scope>
+      <exclusions>
+        <exclusion>
+          <groupId>stax</groupId>
+          <artifactId>stax-api</artifactId>
+        </exclusion>
+      </exclusions>
+    </dependency>
+    <!-- End Jersey dependencies -->
+  </dependencies>
+</project>
diff --git a/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DockerJDBCIntegrationSuite.scala b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DockerJDBCIntegrationSuite.scala
new file mode 100644
index 0000000000..f73231fc80
--- /dev/null
+++ b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DockerJDBCIntegrationSuite.scala
@@ -0,0 +1,160 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.jdbc
+
+import java.net.ServerSocket
+import java.sql.Connection
+
+import scala.collection.JavaConverters._
+import scala.util.control.NonFatal
+
+import com.spotify.docker.client._
+import com.spotify.docker.client.messages.{ContainerConfig, HostConfig, PortBinding}
+import org.scalatest.BeforeAndAfterAll
+import org.scalatest.concurrent.Eventually
+import org.scalatest.time.SpanSugar._
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.test.SharedSQLContext
+import org.apache.spark.util.DockerUtils
+
+abstract class DatabaseOnDocker {
+  /**
+   * The docker image to be pulled.
+   */
+  val imageName: String
+
+  /**
+   * Environment variables to set inside of the Docker container while launching it.
+   */
+  val env: Map[String, String]
+
+  /**
+   * The container-internal JDBC port that the database listens on.
+   */
+  val jdbcPort: Int
+
+  /**
+   * Return a JDBC URL that connects to the database running at the given IP address and port.
+   */
+  def getJdbcUrl(ip: String, port: Int): String
+}
+
+abstract class DockerJDBCIntegrationSuite
+  extends SparkFunSuite
+  with BeforeAndAfterAll
+  with Eventually
+  with SharedSQLContext {
+
+  val db: DatabaseOnDocker
+
+  private var docker: DockerClient = _
+  private var containerId: String = _
+  protected var jdbcUrl: String = _
+
+  override def beforeAll() {
+    super.beforeAll()
+    try {
+      docker = DefaultDockerClient.fromEnv.build()
+      // Check that Docker is actually up
+      try {
+        docker.ping()
+      } catch {
+        case NonFatal(e) =>
+          log.error("Exception while connecting to Docker. Check whether Docker is running.")
+          throw e
+      }
+      // Ensure that the Docker image is installed:
+      try {
+        docker.inspectImage(db.imageName)
+      } catch {
+        case e: ImageNotFoundException =>
+          log.warn(s"Docker image ${db.imageName} not found; pulling image from registry")
+          docker.pull(db.imageName)
+      }
+      // Configure networking (necessary for boot2docker / Docker Machine)
+      val externalPort: Int = {
+        val sock = new ServerSocket(0)
+        val port = sock.getLocalPort
+        sock.close()
+        port
+      }
+      val dockerIp = DockerUtils.getDockerIp()
+      val hostConfig: HostConfig = HostConfig.builder()
+        .networkMode("bridge")
+        .portBindings(
+          Map(s"${db.jdbcPort}/tcp" -> List(PortBinding.of(dockerIp, externalPort)).asJava).asJava)
+        .build()
+      // Create the database container:
+      val config = ContainerConfig.builder()
+        .image(db.imageName)
+        .networkDisabled(false)
+        .env(db.env.map { case (k, v) => s"$k=$v" }.toSeq.asJava)
+        .hostConfig(hostConfig)
+        .exposedPorts(s"${db.jdbcPort}/tcp")
+        .build()
+      containerId = docker.createContainer(config).id
+      // Start the container and wait until the database can accept JDBC connections:
+      docker.startContainer(containerId)
+      jdbcUrl = db.getJdbcUrl(dockerIp, externalPort)
+      eventually(timeout(60.seconds), interval(1.seconds)) {
+        val conn = java.sql.DriverManager.getConnection(jdbcUrl)
+        conn.close()
+      }
+      // Run any setup queries:
+      val conn: Connection = java.sql.DriverManager.getConnection(jdbcUrl)
+      try {
+        dataPreparation(conn)
+      } finally {
+        conn.close()
+      }
+    } catch {
+      case NonFatal(e) =>
+        try {
+          afterAll()
+        } finally {
+          throw e
+        }
+    }
+  }
+
+  override def afterAll() {
+    try {
+      if (docker != null) {
+        try {
+          if (containerId != null) {
+            docker.killContainer(containerId)
+            docker.removeContainer(containerId)
+          }
+        } catch {
+          case NonFatal(e) =>
+            logWarning(s"Could not stop container $containerId", e)
+        } finally {
+          docker.close()
+        }
+      }
+    } finally {
+      super.afterAll()
+    }
+  }
+
+  /**
+   * Prepare databases and tables for testing.
+   */
+  def dataPreparation(connection: Connection): Unit
+}
diff --git a/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala
new file mode 100644
index 0000000000..c68e4dc493
--- /dev/null
+++ b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala
@@ -0,0 +1,153 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.jdbc
+
+import java.math.BigDecimal
+import java.sql.{Connection, Date, Timestamp}
+import java.util.Properties
+
+import org.apache.spark.tags.DockerTest
+
+@DockerTest
+class MySQLIntegrationSuite extends DockerJDBCIntegrationSuite {
+  override val db = new DatabaseOnDocker {
+    override val imageName = "mysql:5.7.9"
+    override val env = Map(
+      "MYSQL_ROOT_PASSWORD" -> "rootpass"
+    )
+    override val jdbcPort: Int = 3306
+    override def getJdbcUrl(ip: String, port: Int): String =
+      s"jdbc:mysql://$ip:$port/mysql?user=root&password=rootpass"
+  }
+
+  override def dataPreparation(conn: Connection): Unit = {
+    conn.prepareStatement("CREATE DATABASE foo").executeUpdate()
+    conn.prepareStatement("CREATE TABLE tbl (x INTEGER, y TEXT(8))").executeUpdate()
+    conn.prepareStatement("INSERT INTO tbl VALUES (42,'fred')").executeUpdate()
+    conn.prepareStatement("INSERT INTO tbl VALUES (17,'dave')").executeUpdate()
+
+    conn.prepareStatement("CREATE TABLE numbers (onebit BIT(1), tenbits BIT(10), "
+      + "small SMALLINT, med MEDIUMINT, nor INT, big BIGINT, deci DECIMAL(40,20), flt FLOAT, "
+      + "dbl DOUBLE)").executeUpdate()
+    conn.prepareStatement("INSERT INTO numbers VALUES (b'0', b'1000100101', "
+      + "17, 77777, 123456789, 123456789012345, 123456789012345.123456789012345, "
+      + "42.75, 1.0000000000000002)").executeUpdate()
+
+    conn.prepareStatement("CREATE TABLE dates (d DATE, t TIME, dt DATETIME, ts TIMESTAMP, "
+      + "yr YEAR)").executeUpdate()
+    conn.prepareStatement("INSERT INTO dates VALUES ('1991-11-09', '13:31:24', "
+      + "'1996-01-01 01:23:45', '2009-02-13 23:31:30', '2001')").executeUpdate()
+
+    // TODO: Test locale conversion for strings.
+    conn.prepareStatement("CREATE TABLE strings (a CHAR(10), b VARCHAR(10), c TINYTEXT, "
+      + "d TEXT, e MEDIUMTEXT, f LONGTEXT, g BINARY(4), h VARBINARY(10), i BLOB)"
+    ).executeUpdate()
+    conn.prepareStatement("INSERT INTO strings VALUES ('the', 'quick', 'brown', 'fox', " +
+      "'jumps', 'over', 'the', 'lazy', 'dog')").executeUpdate()
+  }
+
+  test("Basic test") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "tbl", new Properties)
+    val rows = df.collect()
+    assert(rows.length == 2)
+    val types = rows(0).toSeq.map(x => x.getClass.toString)
+    assert(types.length == 2)
+    assert(types(0).equals("class java.lang.Integer"))
+    assert(types(1).equals("class java.lang.String"))
+  }
+
+  test("Numeric types") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "numbers", new Properties)
+    val rows = df.collect()
+    assert(rows.length == 1)
+    val types = rows(0).toSeq.map(x => x.getClass.toString)
+    assert(types.length == 9)
+    assert(types(0).equals("class java.lang.Boolean"))
+    assert(types(1).equals("class java.lang.Long"))
+    assert(types(2).equals("class java.lang.Integer"))
+    assert(types(3).equals("class java.lang.Integer"))
+    assert(types(4).equals("class java.lang.Integer"))
+    assert(types(5).equals("class java.lang.Long"))
+    assert(types(6).equals("class java.math.BigDecimal"))
+    assert(types(7).equals("class java.lang.Double"))
+    assert(types(8).equals("class java.lang.Double"))
+    assert(rows(0).getBoolean(0) == false)
+    assert(rows(0).getLong(1) == 0x225)
+    assert(rows(0).getInt(2) == 17)
+    assert(rows(0).getInt(3) == 77777)
+    assert(rows(0).getInt(4) == 123456789)
+    assert(rows(0).getLong(5) == 123456789012345L)
+    val bd = new BigDecimal("123456789012345.12345678901234500000")
+    assert(rows(0).getAs[BigDecimal](6).equals(bd))
+    assert(rows(0).getDouble(7) == 42.75)
+    assert(rows(0).getDouble(8) == 1.0000000000000002)
+  }
+
+  test("Date types") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "dates", new Properties)
+    val rows = df.collect()
+    assert(rows.length == 1)
+    val types = rows(0).toSeq.map(x => x.getClass.toString)
+    assert(types.length == 5)
+    assert(types(0).equals("class java.sql.Date"))
+    assert(types(1).equals("class java.sql.Timestamp"))
+    assert(types(2).equals("class java.sql.Timestamp"))
+    assert(types(3).equals("class java.sql.Timestamp"))
+    assert(types(4).equals("class java.sql.Date"))
+    assert(rows(0).getAs[Date](0).equals(Date.valueOf("1991-11-09")))
+    assert(rows(0).getAs[Timestamp](1).equals(Timestamp.valueOf("1970-01-01 13:31:24")))
+    assert(rows(0).getAs[Timestamp](2).equals(Timestamp.valueOf("1996-01-01 01:23:45")))
+    assert(rows(0).getAs[Timestamp](3).equals(Timestamp.valueOf("2009-02-13 23:31:30")))
+    assert(rows(0).getAs[Date](4).equals(Date.valueOf("2001-01-01")))
+  }
+
+  test("String types") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "strings", new Properties)
+    val rows = df.collect()
+    assert(rows.length == 1)
+    val types = rows(0).toSeq.map(x => x.getClass.toString)
+    assert(types.length == 9)
+    assert(types(0).equals("class java.lang.String"))
+    assert(types(1).equals("class java.lang.String"))
+    assert(types(2).equals("class java.lang.String"))
+    assert(types(3).equals("class java.lang.String"))
+    assert(types(4).equals("class java.lang.String"))
+    assert(types(5).equals("class java.lang.String"))
+    assert(types(6).equals("class [B"))
+    assert(types(7).equals("class [B"))
+    assert(types(8).equals("class [B"))
+    assert(rows(0).getString(0).equals("the"))
+    assert(rows(0).getString(1).equals("quick"))
+    assert(rows(0).getString(2).equals("brown"))
+    assert(rows(0).getString(3).equals("fox"))
+    assert(rows(0).getString(4).equals("jumps"))
+    assert(rows(0).getString(5).equals("over"))
+    assert(java.util.Arrays.equals(rows(0).getAs[Array[Byte]](6), Array[Byte](116, 104, 101, 0)))
+    assert(java.util.Arrays.equals(rows(0).getAs[Array[Byte]](7), Array[Byte](108, 97, 122, 121)))
+    assert(java.util.Arrays.equals(rows(0).getAs[Array[Byte]](8), Array[Byte](100, 111, 103)))
+  }
+
+  test("Basic write test") {
+    val df1 = sqlContext.read.jdbc(jdbcUrl, "numbers", new Properties)
+    val df2 = sqlContext.read.jdbc(jdbcUrl, "dates", new Properties)
+    val df3 = sqlContext.read.jdbc(jdbcUrl, "strings", new Properties)
+    df1.write.jdbc(jdbcUrl, "numberscopy", new Properties)
+    df2.write.jdbc(jdbcUrl, "datescopy", new Properties)
+    df3.write.jdbc(jdbcUrl, "stringscopy", new Properties)
+  }
+}
diff --git a/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala
new file mode 100644
index 0000000000..8a0f938f7e
--- /dev/null
+++ b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala
@@ -0,0 +1,78 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.jdbc
+
+import java.sql.Connection
+import java.util.Properties
+
+import org.apache.spark.sql.test.SharedSQLContext
+import org.apache.spark.tags.DockerTest
+
+/**
+ * This patch was tested using the Oracle docker. Created this integration suite for the same.
+ * The ojdbc6-11.2.0.2.0.jar was to be downloaded from the maven repository. Since there was
+ * no jdbc jar available in the maven repository, the jar was downloaded from oracle site
+ * manually and installed in the local; thus tested. So, for SparkQA test case run, the
+ * ojdbc jar might be manually placed in the local maven repository(com/oracle/ojdbc6/11.2.0.2.0)
+ * while Spark QA test run.
+ *
+ * The following would be the steps to test this
+ * 1. Pull oracle 11g image - docker pull wnameless/oracle-xe-11g
+ * 2. Start docker - sudo service docker start
+ * 3. Download oracle 11g driver jar and put it in maven local repo:
+ *    (com/oracle/ojdbc6/11.2.0.2.0/ojdbc6-11.2.0.2.0.jar)
+ * 4. The timeout and interval parameter to be increased from 60,1 to a high value for oracle test
+ *    in DockerJDBCIntegrationSuite.scala (Locally tested with 200,200 and executed successfully).
+ * 5. Run spark test - ./build/sbt "test-only org.apache.spark.sql.jdbc.OracleIntegrationSuite"
+ *
+ * All tests in this suite are ignored because of the dependency with the oracle jar from maven
+ * repository.
+ */
+@DockerTest
+class OracleIntegrationSuite extends DockerJDBCIntegrationSuite with SharedSQLContext {
+  import testImplicits._
+
+  override val db = new DatabaseOnDocker {
+    override val imageName = "wnameless/oracle-xe-11g:latest"
+    override val env = Map(
+      "ORACLE_ROOT_PASSWORD" -> "oracle"
+    )
+    override val jdbcPort: Int = 1521
+    override def getJdbcUrl(ip: String, port: Int): String =
+      s"jdbc:oracle:thin:system/oracle@//$ip:$port/xe"
+  }
+
+  override def dataPreparation(conn: Connection): Unit = {
+  }
+
+  ignore("SPARK-12941: String datatypes to be mapped to Varchar in Oracle") {
+    // create a sample dataframe with string type
+    val df1 = sparkContext.parallelize(Seq(("foo"))).toDF("x")
+    // write the dataframe to the oracle table tbl
+    df1.write.jdbc(jdbcUrl, "tbl2", new Properties)
+    // read the table from the oracle
+    val dfRead = sqlContext.read.jdbc(jdbcUrl, "tbl2", new Properties)
+    // get the rows
+    val rows = dfRead.collect()
+    // verify the data type is inserted
+    val types = rows(0).toSeq.map(x => x.getClass.toString)
+    assert(types(0).equals("class java.lang.String"))
+    // verify the value is the inserted correct or not
+    assert(rows(0).getString(0).equals("foo"))
+  }
+}
diff --git a/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala
new file mode 100644
index 0000000000..d55cdcf28b
--- /dev/null
+++ b/external/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala
@@ -0,0 +1,105 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.jdbc
+
+import java.sql.Connection
+import java.util.Properties
+
+import org.apache.spark.sql.Column
+import org.apache.spark.sql.catalyst.expressions.Literal
+import org.apache.spark.sql.types.{ArrayType, DecimalType}
+import org.apache.spark.tags.DockerTest
+
+@DockerTest
+class PostgresIntegrationSuite extends DockerJDBCIntegrationSuite {
+  override val db = new DatabaseOnDocker {
+    override val imageName = "postgres:9.4.5"
+    override val env = Map(
+      "POSTGRES_PASSWORD" -> "rootpass"
+    )
+    override val jdbcPort = 5432
+    override def getJdbcUrl(ip: String, port: Int): String =
+      s"jdbc:postgresql://$ip:$port/postgres?user=postgres&password=rootpass"
+  }
+
+  override def dataPreparation(conn: Connection): Unit = {
+    conn.prepareStatement("CREATE DATABASE foo").executeUpdate()
+    conn.setCatalog("foo")
+    conn.prepareStatement("CREATE TYPE enum_type AS ENUM ('d1', 'd2')").executeUpdate()
+    conn.prepareStatement("CREATE TABLE bar (c0 text, c1 integer, c2 double precision, c3 bigint, "
+      + "c4 bit(1), c5 bit(10), c6 bytea, c7 boolean, c8 inet, c9 cidr, "
+      + "c10 integer[], c11 text[], c12 real[], c13 numeric(2,2)[], c14 enum_type)").executeUpdate()
+    conn.prepareStatement("INSERT INTO bar VALUES ('hello', 42, 1.25, 123456789012345, B'0', "
+      + "B'1000100101', E'\\\\xDEADBEEF', true, '172.16.0.42', '192.168.0.0/16', "
+      + """'{1, 2}', '{"a", null, "b"}', '{0.11, 0.22}', '{0.11, 0.22}', 'd1')""").executeUpdate()
+  }
+
+  test("Type mapping for various types") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "bar", new Properties)
+    val rows = df.collect()
+    assert(rows.length == 1)
+    val types = rows(0).toSeq.map(x => x.getClass)
+    assert(types.length == 15)
+    assert(classOf[String].isAssignableFrom(types(0)))
+    assert(classOf[java.lang.Integer].isAssignableFrom(types(1)))
+    assert(classOf[java.lang.Double].isAssignableFrom(types(2)))
+    assert(classOf[java.lang.Long].isAssignableFrom(types(3)))
+    assert(classOf[java.lang.Boolean].isAssignableFrom(types(4)))
+    assert(classOf[Array[Byte]].isAssignableFrom(types(5)))
+    assert(classOf[Array[Byte]].isAssignableFrom(types(6)))
+    assert(classOf[java.lang.Boolean].isAssignableFrom(types(7)))
+    assert(classOf[String].isAssignableFrom(types(8)))
+    assert(classOf[String].isAssignableFrom(types(9)))
+    assert(classOf[Seq[Int]].isAssignableFrom(types(10)))
+    assert(classOf[Seq[String]].isAssignableFrom(types(11)))
+    assert(classOf[Seq[Double]].isAssignableFrom(types(12)))
+    assert(classOf[Seq[BigDecimal]].isAssignableFrom(types(13)))
+    assert(classOf[String].isAssignableFrom(types(14)))
+    assert(rows(0).getString(0).equals("hello"))
+    assert(rows(0).getInt(1) == 42)
+    assert(rows(0).getDouble(2) == 1.25)
+    assert(rows(0).getLong(3) == 123456789012345L)
+    assert(!rows(0).getBoolean(4))
+    // BIT(10)'s come back as ASCII strings of ten ASCII 0's and 1's...
+    assert(java.util.Arrays.equals(rows(0).getAs[Array[Byte]](5),
+      Array[Byte](49, 48, 48, 48, 49, 48, 48, 49, 48, 49)))
+    assert(java.util.Arrays.equals(rows(0).getAs[Array[Byte]](6),
+      Array[Byte](0xDE.toByte, 0xAD.toByte, 0xBE.toByte, 0xEF.toByte)))
+    assert(rows(0).getBoolean(7))
+    assert(rows(0).getString(8) == "172.16.0.42")
+    assert(rows(0).getString(9) == "192.168.0.0/16")
+    assert(rows(0).getSeq(10) == Seq(1, 2))
+    assert(rows(0).getSeq(11) == Seq("a", null, "b"))
+    assert(rows(0).getSeq(12).toSeq == Seq(0.11f, 0.22f))
+    assert(rows(0).getSeq(13) == Seq("0.11", "0.22").map(BigDecimal(_).bigDecimal))
+    assert(rows(0).getString(14) == "d1")
+  }
+
+  test("Basic write test") {
+    val df = sqlContext.read.jdbc(jdbcUrl, "bar", new Properties)
+    // Test only that it doesn't crash.
+    df.write.jdbc(jdbcUrl, "public.barcopy", new Properties)
+    // Test that written numeric type has same DataType as input
+    assert(sqlContext.read.jdbc(jdbcUrl, "public.barcopy", new Properties).schema(13).dataType ==
+      ArrayType(DecimalType(2, 2), true))
+    // Test write null values.
+    df.select(df.queryExecution.analyzed.output.map { a =>
+      Column(Literal.create(null, a.dataType)).as(a.name)
+    }: _*).write.jdbc(jdbcUrl, "public.barcopy2", new Properties)
+  }
+}
diff --git a/external/docker-integration-tests/src/test/scala/org/apache/spark/util/DockerUtils.scala b/external/docker-integration-tests/src/test/scala/org/apache/spark/util/DockerUtils.scala
new file mode 100644
index 0000000000..fda377e032
--- /dev/null
+++ b/external/docker-integration-tests/src/test/scala/org/apache/spark/util/DockerUtils.scala
@@ -0,0 +1,68 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.util
+
+import java.net.{Inet4Address, InetAddress, NetworkInterface}
+
+import scala.collection.JavaConverters._
+import scala.sys.process._
+import scala.util.Try
+
+private[spark] object DockerUtils {
+
+  def getDockerIp(): String = {
+    /** If docker-machine is setup on this box, attempts to find the ip from it. */
+    def findFromDockerMachine(): Option[String] = {
+      sys.env.get("DOCKER_MACHINE_NAME").flatMap { name =>
+        Try(Seq("/bin/bash", "-c", s"docker-machine ip $name 2>/dev/null").!!.trim).toOption
+      }
+    }
+    sys.env.get("DOCKER_IP")
+      .orElse(findFromDockerMachine())
+      .orElse(Try(Seq("/bin/bash", "-c", "boot2docker ip 2>/dev/null").!!.trim).toOption)
+      .getOrElse {
+        // This block of code is based on Utils.findLocalInetAddress(), but is modified to blacklist
+        // certain interfaces.
+        val address = InetAddress.getLocalHost
+        // Address resolves to something like 127.0.1.1, which happens on Debian; try to find
+        // a better address using the local network interfaces
+        // getNetworkInterfaces returns ifs in reverse order compared to ifconfig output order
+        // on unix-like system. On windows, it returns in index order.
+        // It's more proper to pick ip address following system output order.
+        val blackListedIFs = Seq(
+          "vboxnet0",  // Mac
+          "docker0"    // Linux
+        )
+        val activeNetworkIFs = NetworkInterface.getNetworkInterfaces.asScala.toSeq.filter { i =>
+          !blackListedIFs.contains(i.getName)
+        }
+        val reOrderedNetworkIFs = activeNetworkIFs.reverse
+        for (ni <- reOrderedNetworkIFs) {
+          val addresses = ni.getInetAddresses.asScala
+            .filterNot(addr => addr.isLinkLocalAddress || addr.isLoopbackAddress).toSeq
+          if (addresses.nonEmpty) {
+            val addr = addresses.find(_.isInstanceOf[Inet4Address]).getOrElse(addresses.head)
+            // because of Inet6Address.toHostName may add interface at the end if it knows about it
+            val strippedAddress = InetAddress.getByAddress(addr.getAddress)
+            return strippedAddress.getHostAddress
+          }
+        }
+        address.getHostAddress
+      }
+  }
+}
diff --git a/external/docker/README.md b/external/docker/README.md
new file mode 100644
index 0000000000..40ba9c3065
--- /dev/null
+++ b/external/docker/README.md
@@ -0,0 +1,7 @@
+Spark docker files
+===========
+
+Drawn from Matt Massie's docker files (https://github.com/massie/dockerfiles),
+as well as some updates from Andre Schumacher (https://github.com/AndreSchumacher/docker).
+
+Tested with Docker version 0.8.1.
diff --git a/external/docker/build b/external/docker/build
new file mode 100755
index 0000000000..253a2fc8dd
--- /dev/null
+++ b/external/docker/build
@@ -0,0 +1,22 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+docker images > /dev/null || { echo Please install docker in non-sudo mode. ; exit; }
+
+./spark-test/build
+\ No newline at end of file
diff --git a/external/docker/spark-mesos/Dockerfile b/external/docker/spark-mesos/Dockerfile
new file mode 100644
index 0000000000..fb3f267fe5
--- /dev/null
+++ b/external/docker/spark-mesos/Dockerfile
@@ -0,0 +1,30 @@
+# This is an example Dockerfile for creating a Spark image which can be
+# references by the Spark property 'spark.mesos.executor.docker.image'
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM mesosphere/mesos:0.20.1
+
+# Update the base ubuntu image with dependencies needed for Spark
+RUN apt-get update && \
+    apt-get install -y python libnss3 openjdk-7-jre-headless curl
+
+RUN mkdir /opt/spark && \
+    curl http://www.apache.org/dyn/closer.lua/spark/spark-1.4.0/spark-1.4.0-bin-hadoop2.4.tgz \
+    | tar -xzC /opt
+ENV SPARK_HOME /opt/spark
+ENV MESOS_NATIVE_JAVA_LIBRARY /usr/local/lib/libmesos.so
diff --git a/external/docker/spark-test/README.md b/external/docker/spark-test/README.md
new file mode 100644
index 0000000000..ec0baf6e6d
--- /dev/null
+++ b/external/docker/spark-test/README.md
@@ -0,0 +1,11 @@
+Spark Docker files usable for testing and development purposes.
+
+These images are intended to be run like so:
+
+	docker run -v $SPARK_HOME:/opt/spark spark-test-master
+	docker run -v $SPARK_HOME:/opt/spark spark-test-worker spark://<master_ip>:7077
+
+Using this configuration, the containers will have their Spark directories
+mounted to your actual `SPARK_HOME`, allowing you to modify and recompile
+your Spark source and have them immediately usable in the docker images
+(without rebuilding them).
diff --git a/external/docker/spark-test/base/Dockerfile b/external/docker/spark-test/base/Dockerfile
new file mode 100644
index 0000000000..76f550f886
--- /dev/null
+++ b/external/docker/spark-test/base/Dockerfile
@@ -0,0 +1,37 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM ubuntu:precise
+
+# Upgrade package index
+# install a few other useful packages plus Open Jdk 7
+# Remove unneeded /var/lib/apt/lists/* after install to reduce the
+# docker image size (by ~30MB)
+RUN apt-get update && \
+    apt-get install -y less openjdk-7-jre-headless net-tools vim-tiny sudo openssh-server && \
+    rm -rf /var/lib/apt/lists/*
+
+ENV SCALA_VERSION 2.11.7
+ENV CDH_VERSION cdh4
+ENV SCALA_HOME /opt/scala-$SCALA_VERSION
+ENV SPARK_HOME /opt/spark
+ENV PATH $SPARK_HOME:$SCALA_HOME/bin:$PATH
+
+# Install Scala
+ADD http://www.scala-lang.org/files/archive/scala-$SCALA_VERSION.tgz /
+RUN (cd / && gunzip < scala-$SCALA_VERSION.tgz)|(cd /opt && tar -xvf -)
+RUN rm /scala-$SCALA_VERSION.tgz
diff --git a/external/docker/spark-test/build b/external/docker/spark-test/build
new file mode 100755
index 0000000000..6f9e197433
--- /dev/null
+++ b/external/docker/spark-test/build
@@ -0,0 +1,22 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+docker build -t spark-test-base spark-test/base/
+docker build -t spark-test-master spark-test/master/
+docker build -t spark-test-worker spark-test/worker/
diff --git a/external/docker/spark-test/master/Dockerfile b/external/docker/spark-test/master/Dockerfile
new file mode 100644
index 0000000000..f729534ab6
--- /dev/null
+++ b/external/docker/spark-test/master/Dockerfile
@@ -0,0 +1,21 @@
+# Spark Master
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM spark-test-base
+ADD default_cmd /root/
+CMD ["/root/default_cmd"]
diff --git a/external/docker/spark-test/master/default_cmd b/external/docker/spark-test/master/default_cmd
new file mode 100755
index 0000000000..5a7da3446f
--- /dev/null
+++ b/external/docker/spark-test/master/default_cmd
@@ -0,0 +1,28 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+IP=$(ip -o -4 addr list eth0 | perl -n -e 'if (m{inet\s([\d\.]+)\/\d+\s}xms) { print $1 }')
+echo "CONTAINER_IP=$IP"
+export SPARK_LOCAL_IP=$IP
+export SPARK_PUBLIC_DNS=$IP
+
+# Avoid the default Docker behavior of mapping our IP address to an unreachable host name
+umount /etc/hosts
+
+/opt/spark/bin/spark-class org.apache.spark.deploy.master.Master -i $IP
diff --git a/external/docker/spark-test/worker/Dockerfile b/external/docker/spark-test/worker/Dockerfile
new file mode 100644
index 0000000000..890febe7b6
--- /dev/null
+++ b/external/docker/spark-test/worker/Dockerfile
@@ -0,0 +1,22 @@
+# Spark Worker
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM spark-test-base
+ENV SPARK_WORKER_PORT 8888
+ADD default_cmd /root/
+ENTRYPOINT ["/root/default_cmd"]
diff --git a/external/docker/spark-test/worker/default_cmd b/external/docker/spark-test/worker/default_cmd
new file mode 100755
index 0000000000..31b06cb0eb
--- /dev/null
+++ b/external/docker/spark-test/worker/default_cmd
@@ -0,0 +1,28 @@
+#!/bin/bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+IP=$(ip -o -4 addr list eth0 | perl -n -e 'if (m{inet\s([\d\.]+)\/\d+\s}xms) { print $1 }')
+echo "CONTAINER_IP=$IP"
+export SPARK_LOCAL_IP=$IP
+export SPARK_PUBLIC_DNS=$IP
+
+# Avoid the default Docker behavior of mapping our IP address to an unreachable host name
+umount /etc/hosts
+
+/opt/spark/bin/spark-class org.apache.spark.deploy.worker.Worker $1
diff --git a/external/java8-tests/README.md b/external/java8-tests/README.md
new file mode 100644
index 0000000000..dc9e87f2ee
--- /dev/null
+++ b/external/java8-tests/README.md
@@ -0,0 +1,24 @@
+# Java 8 Test Suites
+
+These tests require having Java 8 installed and are isolated from the main Spark build.
+If Java 8 is not your system's default Java version, you will need to point Spark's build
+to your Java location. The set-up depends a bit on the build system:
+
+* Sbt users can either set JAVA_HOME to the location of a Java 8 JDK or explicitly pass
+  `-java-home` to the sbt launch script. If a Java 8 JDK is detected sbt will automatically
+  include the Java 8 test project.
+
+  `$ JAVA_HOME=/opt/jdk1.8.0/ build/sbt clean "test-only org.apache.spark.Java8APISuite"`
+
+* For Maven users,
+
+  Maven users can also refer to their Java 8 directory using JAVA_HOME. However, Maven will not
+  automatically detect the presence of a Java 8 JDK, so a special build profile `-Pjava8-tests`
+  must be used.
+
+  `$ JAVA_HOME=/opt/jdk1.8.0/ mvn clean install -DskipTests`
+  `$ JAVA_HOME=/opt/jdk1.8.0/ mvn test -Pjava8-tests -DwildcardSuites=org.apache.spark.Java8APISuite`
+
+  Note that the above command can only be run from project root directory since this module
+  depends on core and the test-jars of core and streaming. This means an install step is
+  required to make the test dependencies visible to the Java 8 sub-project.
diff --git a/external/java8-tests/pom.xml b/external/java8-tests/pom.xml
new file mode 100644
index 0000000000..0ad9c5303a
--- /dev/null
+++ b/external/java8-tests/pom.xml
@@ -0,0 +1,161 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+~ Licensed to the Apache Software Foundation (ASF) under one or more
+~ contributor license agreements.  See the NOTICE file distributed with
+~ this work for additional information regarding copyright ownership.
+~ The ASF licenses this file to You under the Apache License, Version 2.0
+~ (the "License"); you may not use this file except in compliance with
+~ the License.  You may obtain a copy of the License at
+~
+~    http://www.apache.org/licenses/LICENSE-2.0
+~
+~ Unless required by applicable law or agreed to in writing, software
+~ distributed under the License is distributed on an "AS IS" BASIS,
+~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+~ See the License for the specific language governing permissions and
+~ limitations under the License.
+-->
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <parent>
+    <groupId>org.apache.spark</groupId>
+    <artifactId>spark-parent_2.11</artifactId>
+    <version>2.0.0-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <groupId>org.apache.spark</groupId>
+  <artifactId>java8-tests_2.11</artifactId>
+  <packaging>pom</packaging>
+  <name>Spark Project Java8 Tests POM</name>
+
+  <properties>
+    <sbt.project.name>java8-tests</sbt.project.name>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-test-tags_${scala.binary.version}</artifactId>
+    </dependency>
+  </dependencies>
+
+  <profiles>
+    <profile>
+      <id>java8-tests</id>
+    </profile>
+  </profiles>
+  <build>
+    <plugins>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-deploy-plugin</artifactId>
+        <configuration>
+          <skip>true</skip>
+        </configuration>
+      </plugin>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-install-plugin</artifactId>
+        <configuration>
+          <skip>true</skip>
+        </configuration>
+      </plugin>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-surefire-plugin</artifactId>
+        <executions>
+          <execution>
+            <id>test</id>
+            <goals>
+              <goal>test</goal>
+            </goals>
+          </execution>
+        </executions>
+        <configuration>
+          <systemPropertyVariables>
+            <!-- For some reason surefire isn't setting this log4j file on the
+                 test classpath automatically. So we add it manually. -->
+            <log4j.configuration>
+              file:src/test/resources/log4j.properties
+            </log4j.configuration>
+          </systemPropertyVariables>
+          <skipTests>false</skipTests>
+          <includes>
+            <include>**/Suite*.java</include>
+            <include>**/*Suite.java</include>
+          </includes>
+        </configuration>
+      </plugin>
+      <plugin>
+        <groupId>org.apache.maven.plugins</groupId>
+        <artifactId>maven-compiler-plugin</artifactId>
+        <executions>
+          <execution>
+            <id>test-compile-first</id>
+            <phase>process-test-resources</phase>
+            <goals>
+              <goal>testCompile</goal>
+            </goals>
+          </execution>
+        </executions>
+        <configuration>
+          <fork>true</fork>
+          <verbose>true</verbose>
+          <forceJavacCompilerUse>true</forceJavacCompilerUse>
+          <source>1.8</source>
+          <compilerVersion>1.8</compilerVersion>
+          <target>1.8</target>
+          <encoding>UTF-8</encoding>
+          <maxmem>1024m</maxmem>
+        </configuration>
+      </plugin>
+      <plugin>
+        <!-- disabled -->
+        <groupId>net.alchim31.maven</groupId>
+        <artifactId>scala-maven-plugin</artifactId>
+        <executions>
+          <execution>
+            <phase>none</phase>
+          </execution>
+          <execution>
+            <id>scala-compile-first</id>
+            <phase>none</phase>
+          </execution>
+          <execution>
+            <id>scala-test-compile-first</id>
+            <phase>none</phase>
+          </execution>
+          <execution>
+            <id>attach-scaladocs</id>
+            <phase>none</phase>
+          </execution>
+        </executions>
+      </plugin>
+    </plugins>
+  </build>
+</project>
diff --git a/external/java8-tests/src/test/java/org/apache/spark/Java8APISuite.java b/external/java8-tests/src/test/java/org/apache/spark/Java8APISuite.java
new file mode 100644
index 0000000000..c0b58e713f
--- /dev/null
+++ b/external/java8-tests/src/test/java/org/apache/spark/Java8APISuite.java
@@ -0,0 +1,393 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark;
+
+import java.io.File;
+import java.io.Serializable;
+import java.util.*;
+
+import scala.Tuple2;
+
+import com.google.common.collect.Iterables;
+import com.google.common.io.Files;
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapred.SequenceFileOutputFormat;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+import org.apache.spark.api.java.JavaDoubleRDD;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.Optional;
+import org.apache.spark.api.java.function.*;
+import org.apache.spark.util.Utils;
+
+/**
+ * Most of these tests replicate org.apache.spark.JavaAPISuite using java 8
+ * lambda syntax.
+ */
+public class Java8APISuite implements Serializable {
+  static int foreachCalls = 0;
+  private transient JavaSparkContext sc;
+
+  @Before
+  public void setUp() {
+    sc = new JavaSparkContext("local", "JavaAPISuite");
+  }
+
+  @After
+  public void tearDown() {
+    sc.stop();
+    sc = null;
+  }
+
+  @Test
+  public void foreachWithAnonymousClass() {
+    foreachCalls = 0;
+    JavaRDD<String> rdd = sc.parallelize(Arrays.asList("Hello", "World"));
+    rdd.foreach(new VoidFunction<String>() {
+      @Override
+      public void call(String s) {
+        foreachCalls++;
+      }
+    });
+    Assert.assertEquals(2, foreachCalls);
+  }
+
+  @Test
+  public void foreach() {
+    foreachCalls = 0;
+    JavaRDD<String> rdd = sc.parallelize(Arrays.asList("Hello", "World"));
+    rdd.foreach(x -> foreachCalls++);
+    Assert.assertEquals(2, foreachCalls);
+  }
+
+  @Test
+  public void groupBy() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 1, 2, 3, 5, 8, 13));
+    Function<Integer, Boolean> isOdd = x -> x % 2 == 0;
+    JavaPairRDD<Boolean, Iterable<Integer>> oddsAndEvens = rdd.groupBy(isOdd);
+    Assert.assertEquals(2, oddsAndEvens.count());
+    Assert.assertEquals(2, Iterables.size(oddsAndEvens.lookup(true).get(0)));  // Evens
+    Assert.assertEquals(5, Iterables.size(oddsAndEvens.lookup(false).get(0))); // Odds
+
+    oddsAndEvens = rdd.groupBy(isOdd, 1);
+    Assert.assertEquals(2, oddsAndEvens.count());
+    Assert.assertEquals(2, Iterables.size(oddsAndEvens.lookup(true).get(0)));  // Evens
+    Assert.assertEquals(5, Iterables.size(oddsAndEvens.lookup(false).get(0))); // Odds
+  }
+
+  @Test
+  public void leftOuterJoin() {
+    JavaPairRDD<Integer, Integer> rdd1 = sc.parallelizePairs(Arrays.asList(
+      new Tuple2<>(1, 1),
+      new Tuple2<>(1, 2),
+      new Tuple2<>(2, 1),
+      new Tuple2<>(3, 1)
+    ));
+    JavaPairRDD<Integer, Character> rdd2 = sc.parallelizePairs(Arrays.asList(
+      new Tuple2<>(1, 'x'),
+      new Tuple2<>(2, 'y'),
+      new Tuple2<>(2, 'z'),
+      new Tuple2<>(4, 'w')
+    ));
+    List<Tuple2<Integer, Tuple2<Integer, Optional<Character>>>> joined =
+      rdd1.leftOuterJoin(rdd2).collect();
+    Assert.assertEquals(5, joined.size());
+    Tuple2<Integer, Tuple2<Integer, Optional<Character>>> firstUnmatched =
+      rdd1.leftOuterJoin(rdd2).filter(tup -> !tup._2()._2().isPresent()).first();
+    Assert.assertEquals(3, firstUnmatched._1().intValue());
+  }
+
+  @Test
+  public void foldReduce() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 1, 2, 3, 5, 8, 13));
+    Function2<Integer, Integer, Integer> add = (a, b) -> a + b;
+
+    int sum = rdd.fold(0, add);
+    Assert.assertEquals(33, sum);
+
+    sum = rdd.reduce(add);
+    Assert.assertEquals(33, sum);
+  }
+
+  @Test
+  public void foldByKey() {
+    List<Tuple2<Integer, Integer>> pairs = Arrays.asList(
+      new Tuple2<>(2, 1),
+      new Tuple2<>(2, 1),
+      new Tuple2<>(1, 1),
+      new Tuple2<>(3, 2),
+      new Tuple2<>(3, 1)
+    );
+    JavaPairRDD<Integer, Integer> rdd = sc.parallelizePairs(pairs);
+    JavaPairRDD<Integer, Integer> sums = rdd.foldByKey(0, (a, b) -> a + b);
+    Assert.assertEquals(1, sums.lookup(1).get(0).intValue());
+    Assert.assertEquals(2, sums.lookup(2).get(0).intValue());
+    Assert.assertEquals(3, sums.lookup(3).get(0).intValue());
+  }
+
+  @Test
+  public void reduceByKey() {
+    List<Tuple2<Integer, Integer>> pairs = Arrays.asList(
+      new Tuple2<>(2, 1),
+      new Tuple2<>(2, 1),
+      new Tuple2<>(1, 1),
+      new Tuple2<>(3, 2),
+      new Tuple2<>(3, 1)
+    );
+    JavaPairRDD<Integer, Integer> rdd = sc.parallelizePairs(pairs);
+    JavaPairRDD<Integer, Integer> counts = rdd.reduceByKey((a, b) -> a + b);
+    Assert.assertEquals(1, counts.lookup(1).get(0).intValue());
+    Assert.assertEquals(2, counts.lookup(2).get(0).intValue());
+    Assert.assertEquals(3, counts.lookup(3).get(0).intValue());
+
+    Map<Integer, Integer> localCounts = counts.collectAsMap();
+    Assert.assertEquals(1, localCounts.get(1).intValue());
+    Assert.assertEquals(2, localCounts.get(2).intValue());
+    Assert.assertEquals(3, localCounts.get(3).intValue());
+
+    localCounts = rdd.reduceByKeyLocally((a, b) -> a + b);
+    Assert.assertEquals(1, localCounts.get(1).intValue());
+    Assert.assertEquals(2, localCounts.get(2).intValue());
+    Assert.assertEquals(3, localCounts.get(3).intValue());
+  }
+
+  @Test
+  public void map() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5));
+    JavaDoubleRDD doubles = rdd.mapToDouble(x -> 1.0 * x).cache();
+    doubles.collect();
+    JavaPairRDD<Integer, Integer> pairs = rdd.mapToPair(x -> new Tuple2<>(x, x))
+      .cache();
+    pairs.collect();
+    JavaRDD<String> strings = rdd.map(Object::toString).cache();
+    strings.collect();
+  }
+
+  @Test
+  public void flatMap() {
+    JavaRDD<String> rdd = sc.parallelize(Arrays.asList("Hello World!",
+      "The quick brown fox jumps over the lazy dog."));
+    JavaRDD<String> words = rdd.flatMap(x -> Arrays.asList(x.split(" ")));
+
+    Assert.assertEquals("Hello", words.first());
+    Assert.assertEquals(11, words.count());
+
+    JavaPairRDD<String, String> pairs = rdd.flatMapToPair(s -> {
+      List<Tuple2<String, String>> pairs2 = new LinkedList<>();
+      for (String word : s.split(" ")) {
+        pairs2.add(new Tuple2<>(word, word));
+      }
+      return pairs2;
+    });
+
+    Assert.assertEquals(new Tuple2<>("Hello", "Hello"), pairs.first());
+    Assert.assertEquals(11, pairs.count());
+
+    JavaDoubleRDD doubles = rdd.flatMapToDouble(s -> {
+      List<Double> lengths = new LinkedList<>();
+      for (String word : s.split(" ")) {
+        lengths.add((double) word.length());
+      }
+      return lengths;
+    });
+
+    Assert.assertEquals(5.0, doubles.first(), 0.01);
+    Assert.assertEquals(11, pairs.count());
+  }
+
+  @Test
+  public void mapsFromPairsToPairs() {
+    List<Tuple2<Integer, String>> pairs = Arrays.asList(
+      new Tuple2<>(1, "a"),
+      new Tuple2<>(2, "aa"),
+      new Tuple2<>(3, "aaa")
+    );
+    JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
+
+    // Regression test for SPARK-668:
+    JavaPairRDD<String, Integer> swapped =
+      pairRDD.flatMapToPair(x -> Collections.singletonList(x.swap()));
+    swapped.collect();
+
+    // There was never a bug here, but it's worth testing:
+    pairRDD.map(Tuple2::swap).collect();
+  }
+
+  @Test
+  public void mapPartitions() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4), 2);
+    JavaRDD<Integer> partitionSums = rdd.mapPartitions(iter -> {
+      int sum = 0;
+      while (iter.hasNext()) {
+        sum += iter.next();
+      }
+      return Collections.singletonList(sum);
+    });
+
+    Assert.assertEquals("[3, 7]", partitionSums.collect().toString());
+  }
+
+  @Test
+  public void sequenceFile() {
+    File tempDir = Files.createTempDir();
+    tempDir.deleteOnExit();
+    String outputDir = new File(tempDir, "output").getAbsolutePath();
+    List<Tuple2<Integer, String>> pairs = Arrays.asList(
+      new Tuple2<>(1, "a"),
+      new Tuple2<>(2, "aa"),
+      new Tuple2<>(3, "aaa")
+    );
+    JavaPairRDD<Integer, String> rdd = sc.parallelizePairs(pairs);
+
+    rdd.mapToPair(pair -> new Tuple2<>(new IntWritable(pair._1()), new Text(pair._2())))
+      .saveAsHadoopFile(outputDir, IntWritable.class, Text.class, SequenceFileOutputFormat.class);
+
+    // Try reading the output back as an object file
+    JavaPairRDD<Integer, String> readRDD = sc.sequenceFile(outputDir, IntWritable.class, Text.class)
+      .mapToPair(pair -> new Tuple2<>(pair._1().get(), pair._2().toString()));
+    Assert.assertEquals(pairs, readRDD.collect());
+    Utils.deleteRecursively(tempDir);
+  }
+
+  @Test
+  public void zip() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5));
+    JavaDoubleRDD doubles = rdd.mapToDouble(x -> 1.0 * x);
+    JavaPairRDD<Integer, Double> zipped = rdd.zip(doubles);
+    zipped.count();
+  }
+
+  @Test
+  public void zipPartitions() {
+    JavaRDD<Integer> rdd1 = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5, 6), 2);
+    JavaRDD<String> rdd2 = sc.parallelize(Arrays.asList("1", "2", "3", "4"), 2);
+    FlatMapFunction2<Iterator<Integer>, Iterator<String>, Integer> sizesFn =
+      (Iterator<Integer> i, Iterator<String> s) -> {
+        int sizeI = 0;
+        while (i.hasNext()) {
+          sizeI += 1;
+          i.next();
+        }
+        int sizeS = 0;
+        while (s.hasNext()) {
+          sizeS += 1;
+          s.next();
+        }
+        return Arrays.asList(sizeI, sizeS).iterator();
+      };
+    JavaRDD<Integer> sizes = rdd1.zipPartitions(rdd2, sizesFn);
+    Assert.assertEquals("[3, 2, 3, 2]", sizes.collect().toString());
+  }
+
+  @Test
+  public void accumulators() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5));
+
+    Accumulator<Integer> intAccum = sc.intAccumulator(10);
+    rdd.foreach(intAccum::add);
+    Assert.assertEquals((Integer) 25, intAccum.value());
+
+    Accumulator<Double> doubleAccum = sc.doubleAccumulator(10.0);
+    rdd.foreach(x -> doubleAccum.add((double) x));
+    Assert.assertEquals((Double) 25.0, doubleAccum.value());
+
+    // Try a custom accumulator type
+    AccumulatorParam<Float> floatAccumulatorParam = new AccumulatorParam<Float>() {
+      @Override
+      public Float addInPlace(Float r, Float t) {
+        return r + t;
+      }
+      @Override
+      public Float addAccumulator(Float r, Float t) {
+        return r + t;
+      }
+      @Override
+      public Float zero(Float initialValue) {
+        return 0.0f;
+      }
+    };
+
+    Accumulator<Float> floatAccum = sc.accumulator(10.0f, floatAccumulatorParam);
+    rdd.foreach(x -> floatAccum.add((float) x));
+    Assert.assertEquals((Float) 25.0f, floatAccum.value());
+
+    // Test the setValue method
+    floatAccum.setValue(5.0f);
+    Assert.assertEquals((Float) 5.0f, floatAccum.value());
+  }
+
+  @Test
+  public void keyBy() {
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2));
+    List<Tuple2<String, Integer>> s = rdd.keyBy(Object::toString).collect();
+    Assert.assertEquals(new Tuple2<>("1", 1), s.get(0));
+    Assert.assertEquals(new Tuple2<>("2", 2), s.get(1));
+  }
+
+  @Test
+  public void mapOnPairRDD() {
+    JavaRDD<Integer> rdd1 = sc.parallelize(Arrays.asList(1, 2, 3, 4));
+    JavaPairRDD<Integer, Integer> rdd2 =
+      rdd1.mapToPair(i -> new Tuple2<>(i, i % 2));
+    JavaPairRDD<Integer, Integer> rdd3 =
+      rdd2.mapToPair(in -> new Tuple2<>(in._2(), in._1()));
+    Assert.assertEquals(Arrays.asList(
+      new Tuple2<>(1, 1),
+      new Tuple2<>(0, 2),
+      new Tuple2<>(1, 3),
+      new Tuple2<>(0, 4)), rdd3.collect());
+  }
+
+  @Test
+  public void collectPartitions() {
+    JavaRDD<Integer> rdd1 = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5, 6, 7), 3);
+
+    JavaPairRDD<Integer, Integer> rdd2 =
+      rdd1.mapToPair(i -> new Tuple2<>(i, i % 2));
+    List<Integer>[] parts = rdd1.collectPartitions(new int[]{0});
+    Assert.assertEquals(Arrays.asList(1, 2), parts[0]);
+
+    parts = rdd1.collectPartitions(new int[]{1, 2});
+    Assert.assertEquals(Arrays.asList(3, 4), parts[0]);
+    Assert.assertEquals(Arrays.asList(5, 6, 7), parts[1]);
+
+    Assert.assertEquals(Arrays.asList(new Tuple2<>(1, 1), new Tuple2<>(2, 0)),
+      rdd2.collectPartitions(new int[]{0})[0]);
+
+    List<Tuple2<Integer, Integer>>[] parts2 = rdd2.collectPartitions(new int[]{1, 2});
+    Assert.assertEquals(Arrays.asList(new Tuple2<>(3, 1), new Tuple2<>(4, 0)), parts2[0]);
+    Assert.assertEquals(Arrays.asList(new Tuple2<>(5, 1), new Tuple2<>(6, 0), new Tuple2<>(7, 1)),
+      parts2[1]);
+  }
+
+  @Test
+  public void collectAsMapWithIntArrayValues() {
+    // Regression test for SPARK-1040
+    JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1));
+    JavaPairRDD<Integer, int[]> pairRDD =
+      rdd.mapToPair(x -> new Tuple2<>(x, new int[]{x}));
+    pairRDD.collect();  // Works fine
+    pairRDD.collectAsMap();  // Used to crash with ClassCastException
+  }
+}
diff --git a/external/java8-tests/src/test/java/org/apache/spark/streaming/Java8APISuite.java b/external/java8-tests/src/test/java/org/apache/spark/streaming/Java8APISuite.java
new file mode 100644
index 0000000000..604d818ef1
--- /dev/null
+++ b/external/java8-tests/src/test/java/org/apache/spark/streaming/Java8APISuite.java
@@ -0,0 +1,905 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming;
+
+import java.io.Serializable;
+import java.util.*;
+
+import scala.Tuple2;
+
+import com.google.common.collect.Lists;
+import com.google.common.collect.Sets;
+import org.junit.Assert;
+import org.junit.Test;
+
+import org.apache.spark.Accumulator;
+import org.apache.spark.HashPartitioner;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaPairDStream;
+import org.apache.spark.streaming.api.java.JavaMapWithStateDStream;
+
+/**
+ * Most of these tests replicate org.apache.spark.streaming.JavaAPISuite using java 8
+ * lambda syntax.
+ */
+@SuppressWarnings("unchecked")
+public class Java8APISuite extends LocalJavaStreamingContext implements Serializable {
+
+  @Test
+  public void testMap() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("hello", "world"),
+      Arrays.asList("goodnight", "moon"));
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(5, 5),
+      Arrays.asList(9, 4));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<Integer> letterCount = stream.map(String::length);
+    JavaTestUtils.attachTestOutputStream(letterCount);
+    List<List<Integer>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    assertOrderInvariantEquals(expected, result);
+  }
+
+  @Test
+  public void testFilter() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("giants", "dodgers"),
+      Arrays.asList("yankees", "red sox"));
+
+    List<List<String>> expected = Arrays.asList(
+      Arrays.asList("giants"),
+      Arrays.asList("yankees"));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<String> filtered = stream.filter(s -> s.contains("a"));
+    JavaTestUtils.attachTestOutputStream(filtered);
+    List<List<String>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    assertOrderInvariantEquals(expected, result);
+  }
+
+  @Test
+  public void testMapPartitions() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("giants", "dodgers"),
+      Arrays.asList("yankees", "red sox"));
+
+    List<List<String>> expected = Arrays.asList(
+      Arrays.asList("GIANTSDODGERS"),
+      Arrays.asList("YANKEESRED SOX"));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<String> mapped = stream.mapPartitions(in -> {
+      String out = "";
+      while (in.hasNext()) {
+        out = out + in.next().toUpperCase();
+      }
+      return Lists.newArrayList(out);
+    });
+    JavaTestUtils.attachTestOutputStream(mapped);
+    List<List<String>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testReduce() {
+    List<List<Integer>> inputData = Arrays.asList(
+      Arrays.asList(1, 2, 3),
+      Arrays.asList(4, 5, 6),
+      Arrays.asList(7, 8, 9));
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(6),
+      Arrays.asList(15),
+      Arrays.asList(24));
+
+    JavaDStream<Integer> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<Integer> reduced = stream.reduce((x, y) -> x + y);
+    JavaTestUtils.attachTestOutputStream(reduced);
+    List<List<Integer>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testReduceByWindow() {
+    List<List<Integer>> inputData = Arrays.asList(
+      Arrays.asList(1, 2, 3),
+      Arrays.asList(4, 5, 6),
+      Arrays.asList(7, 8, 9));
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(6),
+      Arrays.asList(21),
+      Arrays.asList(39),
+      Arrays.asList(24));
+
+    JavaDStream<Integer> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<Integer> reducedWindowed = stream.reduceByWindow((x, y) -> x + y,
+      (x, y) -> x - y, new Duration(2000), new Duration(1000));
+    JavaTestUtils.attachTestOutputStream(reducedWindowed);
+    List<List<Integer>> result = JavaTestUtils.runStreams(ssc, 4, 4);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testTransform() {
+    List<List<Integer>> inputData = Arrays.asList(
+      Arrays.asList(1, 2, 3),
+      Arrays.asList(4, 5, 6),
+      Arrays.asList(7, 8, 9));
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(3, 4, 5),
+      Arrays.asList(6, 7, 8),
+      Arrays.asList(9, 10, 11));
+
+    JavaDStream<Integer> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<Integer> transformed = stream.transform(in -> in.map(i -> i + 2));
+
+    JavaTestUtils.attachTestOutputStream(transformed);
+    List<List<Integer>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    assertOrderInvariantEquals(expected, result);
+  }
+
+  @Test
+  public void testVariousTransform() {
+    // tests whether all variations of transform can be called from Java
+
+    List<List<Integer>> inputData = Arrays.asList(Arrays.asList(1));
+    JavaDStream<Integer> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+
+    List<List<Tuple2<String, Integer>>> pairInputData =
+      Arrays.asList(Arrays.asList(new Tuple2<>("x", 1)));
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(
+      JavaTestUtils.attachTestInputStream(ssc, pairInputData, 1));
+
+    JavaDStream<Integer> transformed1 = stream.transform(in -> null);
+    JavaDStream<Integer> transformed2 = stream.transform((x, time) -> null);
+    JavaPairDStream<String, Integer> transformed3 = stream.transformToPair(x -> null);
+    JavaPairDStream<String, Integer> transformed4 = stream.transformToPair((x, time) -> null);
+    JavaDStream<Integer> pairTransformed1 = pairStream.transform(x -> null);
+    JavaDStream<Integer> pairTransformed2 = pairStream.transform((x, time) -> null);
+    JavaPairDStream<String, String> pairTransformed3 = pairStream.transformToPair(x -> null);
+    JavaPairDStream<String, String> pairTransformed4 =
+      pairStream.transformToPair((x, time) -> null);
+
+  }
+
+  @Test
+  public void testTransformWith() {
+    List<List<Tuple2<String, String>>> stringStringKVStream1 = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>("california", "dodgers"),
+        new Tuple2<>("new york", "yankees")),
+      Arrays.asList(
+        new Tuple2<>("california", "sharks"),
+        new Tuple2<>("new york", "rangers")));
+
+    List<List<Tuple2<String, String>>> stringStringKVStream2 = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>("california", "giants"),
+        new Tuple2<>("new york", "mets")),
+      Arrays.asList(
+        new Tuple2<>("california", "ducks"),
+        new Tuple2<>("new york", "islanders")));
+
+
+    List<Set<Tuple2<String, Tuple2<String, String>>>> expected = Arrays.asList(
+      Sets.newHashSet(
+        new Tuple2<>("california",
+          new Tuple2<>("dodgers", "giants")),
+        new Tuple2<>("new york",
+          new Tuple2<>("yankees", "mets"))),
+      Sets.newHashSet(
+        new Tuple2<>("california",
+          new Tuple2<>("sharks", "ducks")),
+        new Tuple2<>("new york",
+          new Tuple2<>("rangers", "islanders"))));
+
+    JavaDStream<Tuple2<String, String>> stream1 = JavaTestUtils.attachTestInputStream(
+      ssc, stringStringKVStream1, 1);
+    JavaPairDStream<String, String> pairStream1 = JavaPairDStream.fromJavaDStream(stream1);
+
+    JavaDStream<Tuple2<String, String>> stream2 = JavaTestUtils.attachTestInputStream(
+      ssc, stringStringKVStream2, 1);
+    JavaPairDStream<String, String> pairStream2 = JavaPairDStream.fromJavaDStream(stream2);
+
+    JavaPairDStream<String, Tuple2<String, String>> joined =
+      pairStream1.transformWithToPair(pairStream2,(x, y, z) -> x.join(y));
+
+    JavaTestUtils.attachTestOutputStream(joined);
+    List<List<Tuple2<String, Tuple2<String, String>>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+    List<Set<Tuple2<String, Tuple2<String, String>>>> unorderedResult = Lists.newArrayList();
+    for (List<Tuple2<String, Tuple2<String, String>>> res : result) {
+      unorderedResult.add(Sets.newHashSet(res));
+    }
+
+    Assert.assertEquals(expected, unorderedResult);
+  }
+
+
+  @Test
+  public void testVariousTransformWith() {
+    // tests whether all variations of transformWith can be called from Java
+
+    List<List<Integer>> inputData1 = Arrays.asList(Arrays.asList(1));
+    List<List<String>> inputData2 = Arrays.asList(Arrays.asList("x"));
+    JavaDStream<Integer> stream1 = JavaTestUtils.attachTestInputStream(ssc, inputData1, 1);
+    JavaDStream<String> stream2 = JavaTestUtils.attachTestInputStream(ssc, inputData2, 1);
+
+    List<List<Tuple2<String, Integer>>> pairInputData1 =
+      Arrays.asList(Arrays.asList(new Tuple2<>("x", 1)));
+    List<List<Tuple2<Double, Character>>> pairInputData2 =
+      Arrays.asList(Arrays.asList(new Tuple2<>(1.0, 'x')));
+    JavaPairDStream<String, Integer> pairStream1 = JavaPairDStream.fromJavaDStream(
+      JavaTestUtils.attachTestInputStream(ssc, pairInputData1, 1));
+    JavaPairDStream<Double, Character> pairStream2 = JavaPairDStream.fromJavaDStream(
+      JavaTestUtils.attachTestInputStream(ssc, pairInputData2, 1));
+
+    JavaDStream<Double> transformed1 = stream1.transformWith(stream2, (x, y, z) -> null);
+    JavaDStream<Double> transformed2 = stream1.transformWith(pairStream1,(x, y, z) -> null);
+
+    JavaPairDStream<Double, Double> transformed3 =
+      stream1.transformWithToPair(stream2,(x, y, z) -> null);
+
+    JavaPairDStream<Double, Double> transformed4 =
+      stream1.transformWithToPair(pairStream1,(x, y, z) -> null);
+
+    JavaDStream<Double> pairTransformed1 = pairStream1.transformWith(stream2,(x, y, z) -> null);
+
+    JavaDStream<Double> pairTransformed2_ =
+      pairStream1.transformWith(pairStream1,(x, y, z) -> null);
+
+    JavaPairDStream<Double, Double> pairTransformed3 =
+      pairStream1.transformWithToPair(stream2,(x, y, z) -> null);
+
+    JavaPairDStream<Double, Double> pairTransformed4 =
+      pairStream1.transformWithToPair(pairStream2,(x, y, z) -> null);
+  }
+
+  @Test
+  public void testStreamingContextTransform() {
+    List<List<Integer>> stream1input = Arrays.asList(
+      Arrays.asList(1),
+      Arrays.asList(2)
+    );
+
+    List<List<Integer>> stream2input = Arrays.asList(
+      Arrays.asList(3),
+      Arrays.asList(4)
+    );
+
+    List<List<Tuple2<Integer, String>>> pairStream1input = Arrays.asList(
+      Arrays.asList(new Tuple2<>(1, "x")),
+      Arrays.asList(new Tuple2<>(2, "y"))
+    );
+
+    List<List<Tuple2<Integer, Tuple2<Integer, String>>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>(1, new Tuple2<>(1, "x"))),
+      Arrays.asList(new Tuple2<>(2, new Tuple2<>(2, "y")))
+    );
+
+    JavaDStream<Integer> stream1 = JavaTestUtils.attachTestInputStream(ssc, stream1input, 1);
+    JavaDStream<Integer> stream2 = JavaTestUtils.attachTestInputStream(ssc, stream2input, 1);
+    JavaPairDStream<Integer, String> pairStream1 = JavaPairDStream.fromJavaDStream(
+      JavaTestUtils.attachTestInputStream(ssc, pairStream1input, 1));
+
+    List<JavaDStream<?>> listOfDStreams1 = Arrays.<JavaDStream<?>>asList(stream1, stream2);
+
+    // This is just to test whether this transform to JavaStream compiles
+    JavaDStream<Long> transformed1 = ssc.transform(
+      listOfDStreams1, (List<JavaRDD<?>> listOfRDDs, Time time) -> {
+      Assert.assertEquals(2, listOfRDDs.size());
+      return null;
+    });
+
+    List<JavaDStream<?>> listOfDStreams2 =
+      Arrays.<JavaDStream<?>>asList(stream1, stream2, pairStream1.toJavaDStream());
+
+    JavaPairDStream<Integer, Tuple2<Integer, String>> transformed2 = ssc.transformToPair(
+      listOfDStreams2, (List<JavaRDD<?>> listOfRDDs, Time time) -> {
+      Assert.assertEquals(3, listOfRDDs.size());
+      JavaRDD<Integer> rdd1 = (JavaRDD<Integer>) listOfRDDs.get(0);
+      JavaRDD<Integer> rdd2 = (JavaRDD<Integer>) listOfRDDs.get(1);
+      JavaRDD<Tuple2<Integer, String>> rdd3 = (JavaRDD<Tuple2<Integer, String>>) listOfRDDs.get(2);
+      JavaPairRDD<Integer, String> prdd3 = JavaPairRDD.fromJavaRDD(rdd3);
+      PairFunction<Integer, Integer, Integer> mapToTuple =
+        (Integer i) -> new Tuple2<>(i, i);
+      return rdd1.union(rdd2).mapToPair(mapToTuple).join(prdd3);
+    });
+    JavaTestUtils.attachTestOutputStream(transformed2);
+    List<List<Tuple2<Integer, Tuple2<Integer, String>>>> result =
+      JavaTestUtils.runStreams(ssc, 2, 2);
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testFlatMap() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("go", "giants"),
+      Arrays.asList("boo", "dodgers"),
+      Arrays.asList("athletics"));
+
+    List<List<String>> expected = Arrays.asList(
+      Arrays.asList("g", "o", "g", "i", "a", "n", "t", "s"),
+      Arrays.asList("b", "o", "o", "d", "o", "d", "g", "e", "r", "s"),
+      Arrays.asList("a", "t", "h", "l", "e", "t", "i", "c", "s"));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaDStream<String> flatMapped = stream.flatMap(s -> Lists.newArrayList(s.split("(?!^)")));
+    JavaTestUtils.attachTestOutputStream(flatMapped);
+    List<List<String>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    assertOrderInvariantEquals(expected, result);
+  }
+
+  @Test
+  public void testForeachRDD() {
+    final Accumulator<Integer> accumRdd = ssc.sc().accumulator(0);
+    final Accumulator<Integer> accumEle = ssc.sc().accumulator(0);
+    List<List<Integer>> inputData = Arrays.asList(
+        Arrays.asList(1,1,1),
+        Arrays.asList(1,1,1));
+
+    JavaDStream<Integer> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaTestUtils.attachTestOutputStream(stream.count()); // dummy output
+
+    stream.foreachRDD(rdd -> {
+      accumRdd.add(1);
+      rdd.foreach(x -> accumEle.add(1));
+    });
+
+    // This is a test to make sure foreachRDD(VoidFunction2) can be called from Java
+    stream.foreachRDD((rdd, time) -> null);
+
+    JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(2, accumRdd.value().intValue());
+    Assert.assertEquals(6, accumEle.value().intValue());
+  }
+
+  @Test
+  public void testPairFlatMap() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("giants"),
+      Arrays.asList("dodgers"),
+      Arrays.asList("athletics"));
+
+    List<List<Tuple2<Integer, String>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(6, "g"),
+        new Tuple2<>(6, "i"),
+        new Tuple2<>(6, "a"),
+        new Tuple2<>(6, "n"),
+        new Tuple2<>(6, "t"),
+        new Tuple2<>(6, "s")),
+      Arrays.asList(
+        new Tuple2<>(7, "d"),
+        new Tuple2<>(7, "o"),
+        new Tuple2<>(7, "d"),
+        new Tuple2<>(7, "g"),
+        new Tuple2<>(7, "e"),
+        new Tuple2<>(7, "r"),
+        new Tuple2<>(7, "s")),
+      Arrays.asList(
+        new Tuple2<>(9, "a"),
+        new Tuple2<>(9, "t"),
+        new Tuple2<>(9, "h"),
+        new Tuple2<>(9, "l"),
+        new Tuple2<>(9, "e"),
+        new Tuple2<>(9, "t"),
+        new Tuple2<>(9, "i"),
+        new Tuple2<>(9, "c"),
+        new Tuple2<>(9, "s")));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<Integer, String> flatMapped = stream.flatMapToPair(s -> {
+      List<Tuple2<Integer, String>> out = Lists.newArrayList();
+      for (String letter : s.split("(?!^)")) {
+        out.add(new Tuple2<>(s.length(), letter));
+      }
+      return out;
+    });
+
+    JavaTestUtils.attachTestOutputStream(flatMapped);
+    List<List<Tuple2<Integer, String>>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  /*
+   * Performs an order-invariant comparison of lists representing two RDD streams. This allows
+   * us to account for ordering variation within individual RDD's which occurs during windowing.
+   */
+  public static <T extends Comparable<T>> void assertOrderInvariantEquals(
+    List<List<T>> expected, List<List<T>> actual) {
+    expected.forEach(list -> Collections.sort(list));
+    List<List<T>> sortedActual = new ArrayList<>();
+    actual.forEach(list -> {
+        List<T> sortedList = new ArrayList<>(list);
+        Collections.sort(sortedList);
+        sortedActual.add(sortedList);
+    });
+    Assert.assertEquals(expected, sortedActual);
+  }
+
+  @Test
+  public void testPairFilter() {
+    List<List<String>> inputData = Arrays.asList(
+      Arrays.asList("giants", "dodgers"),
+      Arrays.asList("yankees", "red sox"));
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("giants", 6)),
+      Arrays.asList(new Tuple2<>("yankees", 7)));
+
+    JavaDStream<String> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream =
+      stream.mapToPair(x -> new Tuple2<>(x, x.length()));
+    JavaPairDStream<String, Integer> filtered = pairStream.filter(x -> x._1().contains("a"));
+    JavaTestUtils.attachTestOutputStream(filtered);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  List<List<Tuple2<String, String>>> stringStringKVStream = Arrays.asList(
+    Arrays.asList(new Tuple2<>("california", "dodgers"),
+      new Tuple2<>("california", "giants"),
+      new Tuple2<>("new york", "yankees"),
+      new Tuple2<>("new york", "mets")),
+    Arrays.asList(new Tuple2<>("california", "sharks"),
+      new Tuple2<>("california", "ducks"),
+      new Tuple2<>("new york", "rangers"),
+      new Tuple2<>("new york", "islanders")));
+
+  List<List<Tuple2<String, Integer>>> stringIntKVStream = Arrays.asList(
+    Arrays.asList(
+      new Tuple2<>("california", 1),
+      new Tuple2<>("california", 3),
+      new Tuple2<>("new york", 4),
+      new Tuple2<>("new york", 1)),
+    Arrays.asList(
+      new Tuple2<>("california", 5),
+      new Tuple2<>("california", 5),
+      new Tuple2<>("new york", 3),
+      new Tuple2<>("new york", 1)));
+
+  @Test
+  public void testPairMap() { // Maps pair -> pair of different type
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<Integer, String>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(1, "california"),
+        new Tuple2<>(3, "california"),
+        new Tuple2<>(4, "new york"),
+        new Tuple2<>(1, "new york")),
+      Arrays.asList(
+        new Tuple2<>(5, "california"),
+        new Tuple2<>(5, "california"),
+        new Tuple2<>(3, "new york"),
+        new Tuple2<>(1, "new york")));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+    JavaPairDStream<Integer, String> reversed = pairStream.mapToPair(x -> x.swap());
+    JavaTestUtils.attachTestOutputStream(reversed);
+    List<List<Tuple2<Integer, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairMapPartitions() { // Maps pair -> pair of different type
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<Integer, String>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(1, "california"),
+        new Tuple2<>(3, "california"),
+        new Tuple2<>(4, "new york"),
+        new Tuple2<>(1, "new york")),
+      Arrays.asList(
+        new Tuple2<>(5, "california"),
+        new Tuple2<>(5, "california"),
+        new Tuple2<>(3, "new york"),
+        new Tuple2<>(1, "new york")));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+    JavaPairDStream<Integer, String> reversed = pairStream.mapPartitionsToPair(in -> {
+      LinkedList<Tuple2<Integer, String>> out = new LinkedList<>();
+      while (in.hasNext()) {
+        Tuple2<String, Integer> next = in.next();
+        out.add(next.swap());
+      }
+      return out;
+    });
+
+    JavaTestUtils.attachTestOutputStream(reversed);
+    List<List<Tuple2<Integer, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairMap2() { // Maps pair -> single
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(1, 3, 4, 1),
+      Arrays.asList(5, 5, 3, 1));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+    JavaDStream<Integer> reversed = pairStream.map(in -> in._2());
+    JavaTestUtils.attachTestOutputStream(reversed);
+    List<List<Tuple2<Integer, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairToPairFlatMapWithChangingTypes() { // Maps pair -> pair
+    List<List<Tuple2<String, Integer>>> inputData = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>("hi", 1),
+        new Tuple2<>("ho", 2)),
+      Arrays.asList(
+        new Tuple2<>("hi", 1),
+        new Tuple2<>("ho", 2)));
+
+    List<List<Tuple2<Integer, String>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(1, "h"),
+        new Tuple2<>(1, "i"),
+        new Tuple2<>(2, "h"),
+        new Tuple2<>(2, "o")),
+      Arrays.asList(
+        new Tuple2<>(1, "h"),
+        new Tuple2<>(1, "i"),
+        new Tuple2<>(2, "h"),
+        new Tuple2<>(2, "o")));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+    JavaPairDStream<Integer, String> flatMapped = pairStream.flatMapToPair(in -> {
+      List<Tuple2<Integer, String>> out = new LinkedList<>();
+      for (Character s : in._1().toCharArray()) {
+        out.add(new Tuple2<>(in._2(), s.toString()));
+      }
+      return out;
+    });
+
+    JavaTestUtils.attachTestOutputStream(flatMapped);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairReduceByKey() {
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>("california", 4),
+        new Tuple2<>("new york", 5)),
+      Arrays.asList(
+        new Tuple2<>("california", 10),
+        new Tuple2<>("new york", 4)));
+
+    JavaDStream<Tuple2<String, Integer>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, Integer> reduced = pairStream.reduceByKey((x, y) -> x + y);
+
+    JavaTestUtils.attachTestOutputStream(reduced);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testCombineByKey() {
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>("california", 4),
+        new Tuple2<>("new york", 5)),
+      Arrays.asList(
+        new Tuple2<>("california", 10),
+        new Tuple2<>("new york", 4)));
+
+    JavaDStream<Tuple2<String, Integer>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, Integer> combined = pairStream.<Integer>combineByKey(i -> i,
+      (x, y) -> x + y, (x, y) -> x + y, new HashPartitioner(2));
+
+    JavaTestUtils.attachTestOutputStream(combined);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testReduceByKeyAndWindow() {
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("california", 4),
+        new Tuple2<>("new york", 5)),
+      Arrays.asList(new Tuple2<>("california", 14),
+        new Tuple2<>("new york", 9)),
+      Arrays.asList(new Tuple2<>("california", 10),
+        new Tuple2<>("new york", 4)));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, Integer> reduceWindowed =
+      pairStream.reduceByKeyAndWindow((x, y) -> x + y, new Duration(2000), new Duration(1000));
+    JavaTestUtils.attachTestOutputStream(reduceWindowed);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testUpdateStateByKey() {
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("california", 4),
+        new Tuple2<>("new york", 5)),
+      Arrays.asList(new Tuple2<>("california", 14),
+        new Tuple2<>("new york", 9)),
+      Arrays.asList(new Tuple2<>("california", 14),
+        new Tuple2<>("new york", 9)));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, Integer> updated = pairStream.updateStateByKey((values, state) -> {
+      int out = 0;
+      if (state.isPresent()) {
+        out = out + state.get();
+      }
+      for (Integer v : values) {
+        out = out + v;
+      }
+      return Optional.of(out);
+    });
+
+    JavaTestUtils.attachTestOutputStream(updated);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testReduceByKeyAndWindowWithInverse() {
+    List<List<Tuple2<String, Integer>>> inputData = stringIntKVStream;
+
+    List<List<Tuple2<String, Integer>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("california", 4),
+        new Tuple2<>("new york", 5)),
+      Arrays.asList(new Tuple2<>("california", 14),
+        new Tuple2<>("new york", 9)),
+      Arrays.asList(new Tuple2<>("california", 10),
+        new Tuple2<>("new york", 4)));
+
+    JavaDStream<Tuple2<String, Integer>> stream =
+      JavaTestUtils.attachTestInputStream(ssc, inputData, 1);
+    JavaPairDStream<String, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, Integer> reduceWindowed =
+      pairStream.reduceByKeyAndWindow((x, y) -> x + y, (x, y) -> x - y, new Duration(2000),
+        new Duration(1000));
+    JavaTestUtils.attachTestOutputStream(reduceWindowed);
+    List<List<Tuple2<String, Integer>>> result = JavaTestUtils.runStreams(ssc, 3, 3);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairTransform() {
+    List<List<Tuple2<Integer, Integer>>> inputData = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(3, 5),
+        new Tuple2<>(1, 5),
+        new Tuple2<>(4, 5),
+        new Tuple2<>(2, 5)),
+      Arrays.asList(
+        new Tuple2<>(2, 5),
+        new Tuple2<>(3, 5),
+        new Tuple2<>(4, 5),
+        new Tuple2<>(1, 5)));
+
+    List<List<Tuple2<Integer, Integer>>> expected = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(1, 5),
+        new Tuple2<>(2, 5),
+        new Tuple2<>(3, 5),
+        new Tuple2<>(4, 5)),
+      Arrays.asList(
+        new Tuple2<>(1, 5),
+        new Tuple2<>(2, 5),
+        new Tuple2<>(3, 5),
+        new Tuple2<>(4, 5)));
+
+    JavaDStream<Tuple2<Integer, Integer>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<Integer, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<Integer, Integer> sorted = pairStream.transformToPair(in -> in.sortByKey());
+
+    JavaTestUtils.attachTestOutputStream(sorted);
+    List<List<Tuple2<String, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testPairToNormalRDDTransform() {
+    List<List<Tuple2<Integer, Integer>>> inputData = Arrays.asList(
+      Arrays.asList(
+        new Tuple2<>(3, 5),
+        new Tuple2<>(1, 5),
+        new Tuple2<>(4, 5),
+        new Tuple2<>(2, 5)),
+      Arrays.asList(
+        new Tuple2<>(2, 5),
+        new Tuple2<>(3, 5),
+        new Tuple2<>(4, 5),
+        new Tuple2<>(1, 5)));
+
+    List<List<Integer>> expected = Arrays.asList(
+      Arrays.asList(3, 1, 4, 2),
+      Arrays.asList(2, 3, 4, 1));
+
+    JavaDStream<Tuple2<Integer, Integer>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<Integer, Integer> pairStream = JavaPairDStream.fromJavaDStream(stream);
+    JavaDStream<Integer> firstParts = pairStream.transform(in -> in.map(x -> x._1()));
+    JavaTestUtils.attachTestOutputStream(firstParts);
+    List<List<Integer>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testMapValues() {
+    List<List<Tuple2<String, String>>> inputData = stringStringKVStream;
+
+    List<List<Tuple2<String, String>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("california", "DODGERS"),
+        new Tuple2<>("california", "GIANTS"),
+        new Tuple2<>("new york", "YANKEES"),
+        new Tuple2<>("new york", "METS")),
+      Arrays.asList(new Tuple2<>("california", "SHARKS"),
+        new Tuple2<>("california", "DUCKS"),
+        new Tuple2<>("new york", "RANGERS"),
+        new Tuple2<>("new york", "ISLANDERS")));
+
+    JavaDStream<Tuple2<String, String>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<String, String> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, String> mapped = pairStream.mapValues(String::toUpperCase);
+    JavaTestUtils.attachTestOutputStream(mapped);
+    List<List<Tuple2<String, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+
+    Assert.assertEquals(expected, result);
+  }
+
+  @Test
+  public void testFlatMapValues() {
+    List<List<Tuple2<String, String>>> inputData = stringStringKVStream;
+
+    List<List<Tuple2<String, String>>> expected = Arrays.asList(
+      Arrays.asList(new Tuple2<>("california", "dodgers1"),
+        new Tuple2<>("california", "dodgers2"),
+        new Tuple2<>("california", "giants1"),
+        new Tuple2<>("california", "giants2"),
+        new Tuple2<>("new york", "yankees1"),
+        new Tuple2<>("new york", "yankees2"),
+        new Tuple2<>("new york", "mets1"),
+        new Tuple2<>("new york", "mets2")),
+      Arrays.asList(new Tuple2<>("california", "sharks1"),
+        new Tuple2<>("california", "sharks2"),
+        new Tuple2<>("california", "ducks1"),
+        new Tuple2<>("california", "ducks2"),
+        new Tuple2<>("new york", "rangers1"),
+        new Tuple2<>("new york", "rangers2"),
+        new Tuple2<>("new york", "islanders1"),
+        new Tuple2<>("new york", "islanders2")));
+
+    JavaDStream<Tuple2<String, String>> stream = JavaTestUtils.attachTestInputStream(
+      ssc, inputData, 1);
+    JavaPairDStream<String, String> pairStream = JavaPairDStream.fromJavaDStream(stream);
+
+    JavaPairDStream<String, String> flatMapped =
+      pairStream.flatMapValues(in -> Arrays.asList(in + "1", in + "2"));
+    JavaTestUtils.attachTestOutputStream(flatMapped);
+    List<List<Tuple2<String, String>>> result = JavaTestUtils.runStreams(ssc, 2, 2);
+    Assert.assertEquals(expected, result);
+  }
+
+  /**
+   * This test is only for testing the APIs. It's not necessary to run it.
+   */
+  public void testMapWithStateAPI() {
+    JavaPairRDD<String, Boolean> initialRDD = null;
+    JavaPairDStream<String, Integer> wordsDstream = null;
+
+    JavaMapWithStateDStream<String, Integer, Boolean, Double> stateDstream =
+        wordsDstream.mapWithState(
+            StateSpec.<String, Integer, Boolean, Double> function((time, key, value, state) -> {
+              // Use all State's methods here
+              state.exists();
+              state.get();
+              state.isTimingOut();
+              state.remove();
+              state.update(true);
+              return Optional.of(2.0);
+            }).initialState(initialRDD)
+                .numPartitions(10)
+                .partitioner(new HashPartitioner(10))
+                .timeout(Durations.seconds(10)));
+
+    JavaPairDStream<String, Boolean> emittedRecords = stateDstream.stateSnapshots();
+
+    JavaMapWithStateDStream<String, Integer, Boolean, Double> stateDstream2 =
+        wordsDstream.mapWithState(
+            StateSpec.<String, Integer, Boolean, Double>function((key, value, state) -> {
+              state.exists();
+              state.get();
+              state.isTimingOut();
+              state.remove();
+              state.update(true);
+              return 2.0;
+            }).initialState(initialRDD)
+                .numPartitions(10)
+                .partitioner(new HashPartitioner(10))
+                .timeout(Durations.seconds(10)));
+
+    JavaPairDStream<String, Boolean> mappedDStream = stateDstream2.stateSnapshots();
+  }
+}
diff --git a/external/java8-tests/src/test/resources/log4j.properties b/external/java8-tests/src/test/resources/log4j.properties
new file mode 100644
index 0000000000..eb3b1999eb
--- /dev/null
+++ b/external/java8-tests/src/test/resources/log4j.properties
@@ -0,0 +1,28 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Set everything to be logged to the file target/unit-tests.log
+log4j.rootCategory=INFO, file
+log4j.appender.file=org.apache.log4j.FileAppender
+log4j.appender.file.append=true
+log4j.appender.file.file=target/unit-tests.log
+log4j.appender.file.layout=org.apache.log4j.PatternLayout
+log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
+
+# Ignore messages below warning level from Jetty, because it's a bit verbose
+log4j.logger.org.spark-project.jetty=WARN
+org.spark-project.jetty.LEVEL=WARN
diff --git a/external/java8-tests/src/test/scala/org/apache/spark/JDK8ScalaSuite.scala b/external/java8-tests/src/test/scala/org/apache/spark/JDK8ScalaSuite.scala
new file mode 100644
index 0000000000..fa0681db41
--- /dev/null
+++ b/external/java8-tests/src/test/scala/org/apache/spark/JDK8ScalaSuite.scala
@@ -0,0 +1,27 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark
+
+/**
+ * Test cases where JDK8-compiled Scala user code is used with Spark.
+ */
+class JDK8ScalaSuite extends SparkFunSuite with SharedSparkContext {
+  test("basic RDD closure test (SPARK-6152)") {
+    sc.parallelize(1 to 1000).map(x => x * x).count()
+  }
+}
diff --git a/external/kinesis-asl-assembly/pom.xml b/external/kinesis-asl-assembly/pom.xml
new file mode 100644
index 0000000000..d1c38c7ca5
--- /dev/null
+++ b/external/kinesis-asl-assembly/pom.xml
@@ -0,0 +1,181 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one or more
+  ~ contributor license agreements.  See the NOTICE file distributed with
+  ~ this work for additional information regarding copyright ownership.
+  ~ The ASF licenses this file to You under the Apache License, Version 2.0
+  ~ (the "License"); you may not use this file except in compliance with
+  ~ the License.  You may obtain a copy of the License at
+  ~
+  ~    http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing, software
+  ~ distributed under the License is distributed on an "AS IS" BASIS,
+  ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  ~ See the License for the specific language governing permissions and
+  ~ limitations under the License.
+  -->
+
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <parent>
+    <groupId>org.apache.spark</groupId>
+    <artifactId>spark-parent_2.11</artifactId>
+    <version>2.0.0-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <groupId>org.apache.spark</groupId>
+  <artifactId>spark-streaming-kinesis-asl-assembly_2.11</artifactId>
+  <packaging>jar</packaging>
+  <name>Spark Project Kinesis Assembly</name>
+  <url>http://spark.apache.org/</url>
+
+  <properties>
+    <sbt.project.name>streaming-kinesis-asl-assembly</sbt.project.name>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming-kinesis-asl_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <scope>provided</scope>
+    </dependency>
+    <!--
+      Demote already included in the Spark assembly.
+    -->
+    <dependency>
+      <groupId>com.fasterxml.jackson.core</groupId>
+      <artifactId>jackson-databind</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>commons-lang</groupId>
+      <artifactId>commons-lang</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.google.protobuf</groupId>
+      <artifactId>protobuf-java</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-server</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.sun.jersey</groupId>
+      <artifactId>jersey-core</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>log4j</groupId>
+      <artifactId>log4j</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>net.java.dev.jets3t</groupId>
+      <artifactId>jets3t</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.hadoop</groupId>
+      <artifactId>hadoop-client</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.avro</groupId>
+      <artifactId>avro-ipc</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.avro</groupId>
+      <artifactId>avro-mapred</artifactId>
+      <classifier>${avro.mapred.classifier}</classifier>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.curator</groupId>
+      <artifactId>curator-recipes</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.zookeeper</groupId>
+      <artifactId>zookeeper</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.slf4j</groupId>
+      <artifactId>slf4j-api</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.slf4j</groupId>
+      <artifactId>slf4j-log4j12</artifactId>
+      <scope>provided</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.xerial.snappy</groupId>
+      <artifactId>snappy-java</artifactId>
+      <scope>provided</scope>
+    </dependency>
+  </dependencies>
+
+  <build>
+  <outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
+  <testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
+  <plugins>
+    <plugin>
+      <groupId>org.apache.maven.plugins</groupId>
+      <artifactId>maven-shade-plugin</artifactId>
+      <configuration>
+        <shadedArtifactAttached>false</shadedArtifactAttached>
+        <artifactSet>
+          <includes>
+            <include>*:*</include>
+          </includes>
+        </artifactSet>
+        <filters>
+          <filter>
+            <artifact>*:*</artifact>
+            <excludes>
+              <exclude>META-INF/*.SF</exclude>
+              <exclude>META-INF/*.DSA</exclude>
+              <exclude>META-INF/*.RSA</exclude>
+            </excludes>
+          </filter>
+        </filters>
+      </configuration>
+      <executions>
+        <execution>
+          <phase>package</phase>
+          <goals>
+            <goal>shade</goal>
+          </goals>
+          <configuration>
+            <transformers>
+              <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
+              <transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
+                <resource>reference.conf</resource>
+              </transformer>
+              <transformer implementation="org.apache.maven.plugins.shade.resource.DontIncludeResourceTransformer">
+                <resource>log4j.properties</resource>
+              </transformer>
+              <transformer implementation="org.apache.maven.plugins.shade.resource.ApacheLicenseResourceTransformer"/>
+              <transformer implementation="org.apache.maven.plugins.shade.resource.ApacheNoticeResourceTransformer"/>
+            </transformers>
+          </configuration>
+        </execution>
+      </executions>
+    </plugin>
+  </plugins>
+</build>
+</project>
+
diff --git a/external/kinesis-asl/pom.xml b/external/kinesis-asl/pom.xml
new file mode 100644
index 0000000000..935155eb5d
--- /dev/null
+++ b/external/kinesis-asl/pom.xml
@@ -0,0 +1,87 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+~ Licensed to the Apache Software Foundation (ASF) under one or more
+~ contributor license agreements.  See the NOTICE file distributed with
+~ this work for additional information regarding copyright ownership.
+~ The ASF licenses this file to You under the Apache License, Version 2.0
+~ (the "License"); you may not use this file except in compliance with
+~ the License.  You may obtain a copy of the License at
+~
+~    http://www.apache.org/licenses/LICENSE-2.0
+~
+~ Unless required by applicable law or agreed to in writing, software
+~ distributed under the License is distributed on an "AS IS" BASIS,
+~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+~ See the License for the specific language governing permissions and
+~ limitations under the License.
+-->
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <parent>
+    <groupId>org.apache.spark</groupId>
+    <artifactId>spark-parent_2.11</artifactId>
+    <version>2.0.0-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <!-- Kinesis integration is not included by default due to ASL-licensed code. -->
+  <groupId>org.apache.spark</groupId>
+  <artifactId>spark-streaming-kinesis-asl_2.11</artifactId>
+  <packaging>jar</packaging>
+  <name>Spark Kinesis Integration</name>
+
+  <properties>
+    <sbt.project.name>streaming-kinesis-asl</sbt.project.name>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+      <type>test-jar</type>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.amazonaws</groupId>
+      <artifactId>amazon-kinesis-client</artifactId>
+      <version>${aws.kinesis.client.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>com.amazonaws</groupId>
+      <artifactId>amazon-kinesis-producer</artifactId>
+      <version>${aws.kinesis.producer.version}</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.mockito</groupId>
+      <artifactId>mockito-core</artifactId>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.scalacheck</groupId>
+      <artifactId>scalacheck_${scala.binary.version}</artifactId>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-test-tags_${scala.binary.version}</artifactId>
+    </dependency>
+  </dependencies>
+  <build>
+    <outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
+    <testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
+  </build>
+</project>
diff --git a/external/kinesis-asl/src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java b/external/kinesis-asl/src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java
new file mode 100644
index 0000000000..5dc825dfdc
--- /dev/null
+++ b/external/kinesis-asl/src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java
@@ -0,0 +1,189 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.examples.streaming;
+
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Iterator;
+import java.util.List;
+import java.util.regex.Pattern;
+
+import com.amazonaws.regions.RegionUtils;
+import org.apache.log4j.Logger;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.api.java.function.Function2;
+import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.Duration;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaPairDStream;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+import org.apache.spark.streaming.kinesis.KinesisUtils;
+
+import scala.Tuple2;
+
+import com.amazonaws.auth.DefaultAWSCredentialsProviderChain;
+import com.amazonaws.services.kinesis.AmazonKinesisClient;
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream;
+
+/**
+ * Consumes messages from a Amazon Kinesis streams and does wordcount.
+ *
+ * This example spins up 1 Kinesis Receiver per shard for the given stream.
+ * It then starts pulling from the last checkpointed sequence number of the given stream.
+ *
+ * Usage: JavaKinesisWordCountASL [app-name] [stream-name] [endpoint-url] [region-name]
+ *   [app-name] is the name of the consumer app, used to track the read data in DynamoDB
+ *   [stream-name] name of the Kinesis stream (ie. mySparkStream)
+ *   [endpoint-url] endpoint of the Kinesis service
+ *     (e.g. https://kinesis.us-east-1.amazonaws.com)
+ *
+ *
+ * Example:
+ *      # export AWS keys if necessary
+ *      $ export AWS_ACCESS_KEY_ID=[your-access-key]
+ *      $ export AWS_SECRET_KEY=<your-secret-key>
+ *
+ *      # run the example
+ *      $ SPARK_HOME/bin/run-example   streaming.JavaKinesisWordCountASL myAppName  mySparkStream \
+ *             https://kinesis.us-east-1.amazonaws.com
+ *
+ * There is a companion helper class called KinesisWordProducerASL which puts dummy data
+ * onto the Kinesis stream.
+ *
+ * This code uses the DefaultAWSCredentialsProviderChain to find credentials
+ * in the following order:
+ *    Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
+ *    Java System Properties - aws.accessKeyId and aws.secretKey
+ *    Credential profiles file - default location (~/.aws/credentials) shared by all AWS SDKs
+ *    Instance profile credentials - delivered through the Amazon EC2 metadata service
+ * For more information, see
+ * http://docs.aws.amazon.com/AWSSdkDocsJava/latest/DeveloperGuide/credentials.html
+ *
+ * See http://spark.apache.org/docs/latest/streaming-kinesis-integration.html for more details on
+ * the Kinesis Spark Streaming integration.
+ */
+public final class JavaKinesisWordCountASL { // needs to be public for access from run-example
+  private static final Pattern WORD_SEPARATOR = Pattern.compile(" ");
+  private static final Logger logger = Logger.getLogger(JavaKinesisWordCountASL.class);
+
+  public static void main(String[] args) {
+    // Check that all required args were passed in.
+    if (args.length != 3) {
+      System.err.println(
+          "Usage: JavaKinesisWordCountASL <stream-name> <endpoint-url>\n\n" +
+          "    <app-name> is the name of the app, used to track the read data in DynamoDB\n" +
+          "    <stream-name> is the name of the Kinesis stream\n" +
+          "    <endpoint-url> is the endpoint of the Kinesis service\n" +
+          "                   (e.g. https://kinesis.us-east-1.amazonaws.com)\n" +
+          "Generate data for the Kinesis stream using the example KinesisWordProducerASL.\n" +
+          "See http://spark.apache.org/docs/latest/streaming-kinesis-integration.html for more\n" +
+          "details.\n"
+      );
+      System.exit(1);
+    }
+
+    // Set default log4j logging level to WARN to hide Spark logs
+    StreamingExamples.setStreamingLogLevels();
+
+    // Populate the appropriate variables from the given args
+    String kinesisAppName = args[0];
+    String streamName = args[1];
+    String endpointUrl = args[2];
+
+    // Create a Kinesis client in order to determine the number of shards for the given stream
+    AmazonKinesisClient kinesisClient =
+        new AmazonKinesisClient(new DefaultAWSCredentialsProviderChain());
+    kinesisClient.setEndpoint(endpointUrl);
+    int numShards =
+        kinesisClient.describeStream(streamName).getStreamDescription().getShards().size();
+
+
+    // In this example, we're going to create 1 Kinesis Receiver/input DStream for each shard.
+    // This is not a necessity; if there are less receivers/DStreams than the number of shards,
+    // then the shards will be automatically distributed among the receivers and each receiver
+    // will receive data from multiple shards.
+    int numStreams = numShards;
+
+    // Spark Streaming batch interval
+    Duration batchInterval = new Duration(2000);
+
+    // Kinesis checkpoint interval.  Same as batchInterval for this example.
+    Duration kinesisCheckpointInterval = batchInterval;
+
+    // Get the region name from the endpoint URL to save Kinesis Client Library metadata in
+    // DynamoDB of the same region as the Kinesis stream
+    String regionName = RegionUtils.getRegionByEndpoint(endpointUrl).getName();
+
+    // Setup the Spark config and StreamingContext
+    SparkConf sparkConfig = new SparkConf().setAppName("JavaKinesisWordCountASL");
+    JavaStreamingContext jssc = new JavaStreamingContext(sparkConfig, batchInterval);
+
+    // Create the Kinesis DStreams
+    List<JavaDStream<byte[]>> streamsList = new ArrayList<>(numStreams);
+    for (int i = 0; i < numStreams; i++) {
+      streamsList.add(
+          KinesisUtils.createStream(jssc, kinesisAppName, streamName, endpointUrl, regionName,
+              InitialPositionInStream.LATEST, kinesisCheckpointInterval, StorageLevel.MEMORY_AND_DISK_2())
+      );
+    }
+
+    // Union all the streams if there is more than 1 stream
+    JavaDStream<byte[]> unionStreams;
+    if (streamsList.size() > 1) {
+      unionStreams = jssc.union(streamsList.get(0), streamsList.subList(1, streamsList.size()));
+    } else {
+      // Otherwise, just use the 1 stream
+      unionStreams = streamsList.get(0);
+    }
+
+    // Convert each line of Array[Byte] to String, and split into words
+    JavaDStream<String> words = unionStreams.flatMap(new FlatMapFunction<byte[], String>() {
+      @Override
+      public Iterator<String> call(byte[] line) {
+        String s = new String(line, StandardCharsets.UTF_8);
+        return Arrays.asList(WORD_SEPARATOR.split(s)).iterator();
+      }
+    });
+
+    // Map each word to a (word, 1) tuple so we can reduce by key to count the words
+    JavaPairDStream<String, Integer> wordCounts = words.mapToPair(
+        new PairFunction<String, String, Integer>() {
+          @Override
+          public Tuple2<String, Integer> call(String s) {
+            return new Tuple2<String, Integer>(s, 1);
+          }
+        }
+    ).reduceByKey(
+        new Function2<Integer, Integer, Integer>() {
+          @Override
+          public Integer call(Integer i1, Integer i2) {
+            return i1 + i2;
+          }
+        }
+    );
+
+    // Print the first 10 wordCounts
+    wordCounts.print();
+
+    // Start the streaming context and await termination
+    jssc.start();
+    jssc.awaitTermination();
+  }
+}
diff --git a/external/kinesis-asl/src/main/python/examples/streaming/kinesis_wordcount_asl.py b/external/kinesis-asl/src/main/python/examples/streaming/kinesis_wordcount_asl.py
new file mode 100644
index 0000000000..4d7fc9a549
--- /dev/null
+++ b/external/kinesis-asl/src/main/python/examples/streaming/kinesis_wordcount_asl.py
@@ -0,0 +1,83 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+  Consumes messages from a Amazon Kinesis streams and does wordcount.
+
+  This example spins up 1 Kinesis Receiver per shard for the given stream.
+  It then starts pulling from the last checkpointed sequence number of the given stream.
+
+  Usage: kinesis_wordcount_asl.py <app-name> <stream-name> <endpoint-url> <region-name>
+    <app-name> is the name of the consumer app, used to track the read data in DynamoDB
+    <stream-name> name of the Kinesis stream (ie. mySparkStream)
+    <endpoint-url> endpoint of the Kinesis service
+      (e.g. https://kinesis.us-east-1.amazonaws.com)
+
+
+  Example:
+      # export AWS keys if necessary
+      $ export AWS_ACCESS_KEY_ID=<your-access-key>
+      $ export AWS_SECRET_KEY=<your-secret-key>
+
+      # run the example
+      $ bin/spark-submit -jar external/kinesis-asl/target/scala-*/\
+        spark-streaming-kinesis-asl-assembly_*.jar \
+        external/kinesis-asl/src/main/python/examples/streaming/kinesis_wordcount_asl.py \
+        myAppName mySparkStream https://kinesis.us-east-1.amazonaws.com
+
+  There is a companion helper class called KinesisWordProducerASL which puts dummy data
+  onto the Kinesis stream.
+
+  This code uses the DefaultAWSCredentialsProviderChain to find credentials
+  in the following order:
+      Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
+      Java System Properties - aws.accessKeyId and aws.secretKey
+      Credential profiles file - default location (~/.aws/credentials) shared by all AWS SDKs
+      Instance profile credentials - delivered through the Amazon EC2 metadata service
+  For more information, see
+      http://docs.aws.amazon.com/AWSSdkDocsJava/latest/DeveloperGuide/credentials.html
+
+  See http://spark.apache.org/docs/latest/streaming-kinesis-integration.html for more details on
+  the Kinesis Spark Streaming integration.
+"""
+from __future__ import print_function
+
+import sys
+
+from pyspark import SparkContext
+from pyspark.streaming import StreamingContext
+from pyspark.streaming.kinesis import KinesisUtils, InitialPositionInStream
+
+if __name__ == "__main__":
+    if len(sys.argv) != 5:
+        print(
+            "Usage: kinesis_wordcount_asl.py <app-name> <stream-name> <endpoint-url> <region-name>",
+            file=sys.stderr)
+        sys.exit(-1)
+
+    sc = SparkContext(appName="PythonStreamingKinesisWordCountAsl")
+    ssc = StreamingContext(sc, 1)
+    appName, streamName, endpointUrl, regionName = sys.argv[1:]
+    lines = KinesisUtils.createStream(
+        ssc, appName, streamName, endpointUrl, regionName, InitialPositionInStream.LATEST, 2)
+    counts = lines.flatMap(lambda line: line.split(" ")) \
+        .map(lambda word: (word, 1)) \
+        .reduceByKey(lambda a, b: a+b)
+    counts.pprint()
+
+    ssc.start()
+    ssc.awaitTermination()
diff --git a/external/kinesis-asl/src/main/resources/log4j.properties b/external/kinesis-asl/src/main/resources/log4j.properties
new file mode 100644
index 0000000000..6cdc9286c5
--- /dev/null
+++ b/external/kinesis-asl/src/main/resources/log4j.properties
@@ -0,0 +1,37 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+log4j.rootCategory=WARN, console
+
+# File appender
+log4j.appender.file=org.apache.log4j.FileAppender
+log4j.appender.file.append=false
+log4j.appender.file.file=target/unit-tests.log
+log4j.appender.file.layout=org.apache.log4j.PatternLayout
+log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %p %c{1}: %m%n
+
+# Console appender
+log4j.appender.console=org.apache.log4j.ConsoleAppender
+log4j.appender.console.target=System.out
+log4j.appender.console.layout=org.apache.log4j.PatternLayout
+log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
+
+# Settings to quiet third party logs that are too verbose
+log4j.logger.org.spark-project.jetty=WARN
+log4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERROR
+log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
+log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO
+\ No newline at end of file
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala
new file mode 100644
index 0000000000..6a73bc0e30
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/examples/streaming/KinesisWordCountASL.scala
@@ -0,0 +1,276 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+// scalastyle:off println
+package org.apache.spark.examples.streaming
+
+import java.nio.ByteBuffer
+
+import scala.util.Random
+
+import com.amazonaws.auth.{BasicAWSCredentials, DefaultAWSCredentialsProviderChain}
+import com.amazonaws.regions.RegionUtils
+import com.amazonaws.services.kinesis.AmazonKinesisClient
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream
+import com.amazonaws.services.kinesis.model.PutRecordRequest
+import org.apache.log4j.{Level, Logger}
+
+import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.streaming.{Milliseconds, StreamingContext}
+import org.apache.spark.streaming.dstream.DStream.toPairDStreamFunctions
+import org.apache.spark.streaming.kinesis.KinesisUtils
+
+
+/**
+ * Consumes messages from a Amazon Kinesis streams and does wordcount.
+ *
+ * This example spins up 1 Kinesis Receiver per shard for the given stream.
+ * It then starts pulling from the last checkpointed sequence number of the given stream.
+ *
+ * Usage: KinesisWordCountASL <app-name> <stream-name> <endpoint-url> <region-name>
+ *   <app-name> is the name of the consumer app, used to track the read data in DynamoDB
+ *   <stream-name> name of the Kinesis stream (ie. mySparkStream)
+ *   <endpoint-url> endpoint of the Kinesis service
+ *     (e.g. https://kinesis.us-east-1.amazonaws.com)
+ *
+ *
+ * Example:
+ *      # export AWS keys if necessary
+ *      $ export AWS_ACCESS_KEY_ID=<your-access-key>
+ *      $ export AWS_SECRET_KEY=<your-secret-key>
+ *
+ *      # run the example
+ *      $ SPARK_HOME/bin/run-example  streaming.KinesisWordCountASL myAppName  mySparkStream \
+ *              https://kinesis.us-east-1.amazonaws.com
+ *
+ * There is a companion helper class called KinesisWordProducerASL which puts dummy data
+ * onto the Kinesis stream.
+ *
+ * This code uses the DefaultAWSCredentialsProviderChain to find credentials
+ * in the following order:
+ *    Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
+ *    Java System Properties - aws.accessKeyId and aws.secretKey
+ *    Credential profiles file - default location (~/.aws/credentials) shared by all AWS SDKs
+ *    Instance profile credentials - delivered through the Amazon EC2 metadata service
+ * For more information, see
+ * http://docs.aws.amazon.com/AWSSdkDocsJava/latest/DeveloperGuide/credentials.html
+ *
+ * See http://spark.apache.org/docs/latest/streaming-kinesis-integration.html for more details on
+ * the Kinesis Spark Streaming integration.
+ */
+object KinesisWordCountASL extends Logging {
+  def main(args: Array[String]) {
+    // Check that all required args were passed in.
+    if (args.length != 3) {
+      System.err.println(
+        """
+          |Usage: KinesisWordCountASL <app-name> <stream-name> <endpoint-url> <region-name>
+          |
+          |    <app-name> is the name of the consumer app, used to track the read data in DynamoDB
+          |    <stream-name> is the name of the Kinesis stream
+          |    <endpoint-url> is the endpoint of the Kinesis service
+          |                   (e.g. https://kinesis.us-east-1.amazonaws.com)
+          |
+          |Generate input data for Kinesis stream using the example KinesisWordProducerASL.
+          |See http://spark.apache.org/docs/latest/streaming-kinesis-integration.html for more
+          |details.
+        """.stripMargin)
+      System.exit(1)
+    }
+
+    StreamingExamples.setStreamingLogLevels()
+
+    // Populate the appropriate variables from the given args
+    val Array(appName, streamName, endpointUrl) = args
+
+
+    // Determine the number of shards from the stream using the low-level Kinesis Client
+    // from the AWS Java SDK.
+    val credentials = new DefaultAWSCredentialsProviderChain().getCredentials()
+    require(credentials != null,
+      "No AWS credentials found. Please specify credentials using one of the methods specified " +
+        "in http://docs.aws.amazon.com/AWSSdkDocsJava/latest/DeveloperGuide/credentials.html")
+    val kinesisClient = new AmazonKinesisClient(credentials)
+    kinesisClient.setEndpoint(endpointUrl)
+    val numShards = kinesisClient.describeStream(streamName).getStreamDescription().getShards().size
+
+
+    // In this example, we're going to create 1 Kinesis Receiver/input DStream for each shard.
+    // This is not a necessity; if there are less receivers/DStreams than the number of shards,
+    // then the shards will be automatically distributed among the receivers and each receiver
+    // will receive data from multiple shards.
+    val numStreams = numShards
+
+    // Spark Streaming batch interval
+    val batchInterval = Milliseconds(2000)
+
+    // Kinesis checkpoint interval is the interval at which the DynamoDB is updated with information
+    // on sequence number of records that have been received. Same as batchInterval for this
+    // example.
+    val kinesisCheckpointInterval = batchInterval
+
+    // Get the region name from the endpoint URL to save Kinesis Client Library metadata in
+    // DynamoDB of the same region as the Kinesis stream
+    val regionName = RegionUtils.getRegionByEndpoint(endpointUrl).getName()
+
+    // Setup the SparkConfig and StreamingContext
+    val sparkConfig = new SparkConf().setAppName("KinesisWordCountASL")
+    val ssc = new StreamingContext(sparkConfig, batchInterval)
+
+    // Create the Kinesis DStreams
+    val kinesisStreams = (0 until numStreams).map { i =>
+      KinesisUtils.createStream(ssc, appName, streamName, endpointUrl, regionName,
+        InitialPositionInStream.LATEST, kinesisCheckpointInterval, StorageLevel.MEMORY_AND_DISK_2)
+    }
+
+    // Union all the streams
+    val unionStreams = ssc.union(kinesisStreams)
+
+    // Convert each line of Array[Byte] to String, and split into words
+    val words = unionStreams.flatMap(byteArray => new String(byteArray).split(" "))
+
+    // Map each word to a (word, 1) tuple so we can reduce by key to count the words
+    val wordCounts = words.map(word => (word, 1)).reduceByKey(_ + _)
+
+    // Print the first 10 wordCounts
+    wordCounts.print()
+
+    // Start the streaming context and await termination
+    ssc.start()
+    ssc.awaitTermination()
+  }
+}
+
+/**
+ * Usage: KinesisWordProducerASL <stream-name> <endpoint-url> \
+ *   <records-per-sec> <words-per-record>
+ *
+ *   <stream-name> is the name of the Kinesis stream (ie. mySparkStream)
+ *   <endpoint-url> is the endpoint of the Kinesis service
+ *     (ie. https://kinesis.us-east-1.amazonaws.com)
+ *   <records-per-sec> is the rate of records per second to put onto the stream
+ *   <words-per-record> is the rate of records per second to put onto the stream
+ *
+ * Example:
+ *    $ SPARK_HOME/bin/run-example streaming.KinesisWordProducerASL mySparkStream \
+ *         https://kinesis.us-east-1.amazonaws.com us-east-1 10 5
+ */
+object KinesisWordProducerASL {
+  def main(args: Array[String]) {
+    if (args.length != 4) {
+      System.err.println(
+        """
+          |Usage: KinesisWordProducerASL <stream-name> <endpoint-url> <records-per-sec>
+                                         <words-per-record>
+          |
+          |    <stream-name> is the name of the Kinesis stream
+          |    <endpoint-url> is the endpoint of the Kinesis service
+          |                   (e.g. https://kinesis.us-east-1.amazonaws.com)
+          |    <records-per-sec> is the rate of records per second to put onto the stream
+          |    <words-per-record> is the rate of records per second to put onto the stream
+          |
+        """.stripMargin)
+
+      System.exit(1)
+    }
+
+    // Set default log4j logging level to WARN to hide Spark logs
+    StreamingExamples.setStreamingLogLevels()
+
+    // Populate the appropriate variables from the given args
+    val Array(stream, endpoint, recordsPerSecond, wordsPerRecord) = args
+
+    // Generate the records and return the totals
+    val totals = generate(stream, endpoint, recordsPerSecond.toInt,
+        wordsPerRecord.toInt)
+
+    // Print the array of (word, total) tuples
+    println("Totals for the words sent")
+    totals.foreach(println(_))
+  }
+
+  def generate(stream: String,
+      endpoint: String,
+      recordsPerSecond: Int,
+      wordsPerRecord: Int): Seq[(String, Int)] = {
+
+    val randomWords = List("spark", "you", "are", "my", "father")
+    val totals = scala.collection.mutable.Map[String, Int]()
+
+    // Create the low-level Kinesis Client from the AWS Java SDK.
+    val kinesisClient = new AmazonKinesisClient(new DefaultAWSCredentialsProviderChain())
+    kinesisClient.setEndpoint(endpoint)
+
+    println(s"Putting records onto stream $stream and endpoint $endpoint at a rate of" +
+        s" $recordsPerSecond records per second and $wordsPerRecord words per record")
+
+    // Iterate and put records onto the stream per the given recordPerSec and wordsPerRecord
+    for (i <- 1 to 10) {
+      // Generate recordsPerSec records to put onto the stream
+      val records = (1 to recordsPerSecond.toInt).foreach { recordNum =>
+        // Randomly generate wordsPerRecord number of words
+        val data = (1 to wordsPerRecord.toInt).map(x => {
+          // Get a random index to a word
+          val randomWordIdx = Random.nextInt(randomWords.size)
+          val randomWord = randomWords(randomWordIdx)
+
+          // Increment total count to compare to server counts later
+          totals(randomWord) = totals.getOrElse(randomWord, 0) + 1
+
+          randomWord
+        }).mkString(" ")
+
+        // Create a partitionKey based on recordNum
+        val partitionKey = s"partitionKey-$recordNum"
+
+        // Create a PutRecordRequest with an Array[Byte] version of the data
+        val putRecordRequest = new PutRecordRequest().withStreamName(stream)
+            .withPartitionKey(partitionKey)
+            .withData(ByteBuffer.wrap(data.getBytes()))
+
+        // Put the record onto the stream and capture the PutRecordResult
+        val putRecordResult = kinesisClient.putRecord(putRecordRequest)
+      }
+
+      // Sleep for a second
+      Thread.sleep(1000)
+      println("Sent " + recordsPerSecond + " records")
+    }
+     // Convert the totals to (index, total) tuple
+    totals.toSeq.sortBy(_._1)
+  }
+}
+
+/**
+ *  Utility functions for Spark Streaming examples.
+ *  This has been lifted from the examples/ project to remove the circular dependency.
+ */
+private[streaming] object StreamingExamples extends Logging {
+  // Set reasonable logging levels for streaming if the user has not configured log4j.
+  def setStreamingLogLevels() {
+    val log4jInitialized = Logger.getRootLogger.getAllAppenders.hasMoreElements
+    if (!log4jInitialized) {
+      // We first log something to initialize Spark's default logging, then we override the
+      // logging level.
+      logInfo("Setting log level to [WARN] for streaming example." +
+        " To override add a custom log4j.properties to the classpath.")
+      Logger.getRootLogger.setLevel(Level.WARN)
+    }
+  }
+}
+// scalastyle:on println
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDD.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDD.scala
new file mode 100644
index 0000000000..3996f168e6
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDD.scala
@@ -0,0 +1,288 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import scala.collection.JavaConverters._
+import scala.reflect.ClassTag
+import scala.util.control.NonFatal
+
+import com.amazonaws.auth.{AWSCredentials, DefaultAWSCredentialsProviderChain}
+import com.amazonaws.services.kinesis.AmazonKinesisClient
+import com.amazonaws.services.kinesis.clientlibrary.types.UserRecord
+import com.amazonaws.services.kinesis.model._
+
+import org.apache.spark._
+import org.apache.spark.rdd.{BlockRDD, BlockRDDPartition}
+import org.apache.spark.storage.BlockId
+import org.apache.spark.util.NextIterator
+
+
+/** Class representing a range of Kinesis sequence numbers. Both sequence numbers are inclusive. */
+private[kinesis]
+case class SequenceNumberRange(
+    streamName: String, shardId: String, fromSeqNumber: String, toSeqNumber: String)
+
+/** Class representing an array of Kinesis sequence number ranges */
+private[kinesis]
+case class SequenceNumberRanges(ranges: Seq[SequenceNumberRange]) {
+  def isEmpty(): Boolean = ranges.isEmpty
+
+  def nonEmpty(): Boolean = ranges.nonEmpty
+
+  override def toString(): String = ranges.mkString("SequenceNumberRanges(", ", ", ")")
+}
+
+private[kinesis]
+object SequenceNumberRanges {
+  def apply(range: SequenceNumberRange): SequenceNumberRanges = {
+    new SequenceNumberRanges(Seq(range))
+  }
+}
+
+
+/** Partition storing the information of the ranges of Kinesis sequence numbers to read */
+private[kinesis]
+class KinesisBackedBlockRDDPartition(
+    idx: Int,
+    blockId: BlockId,
+    val isBlockIdValid: Boolean,
+    val seqNumberRanges: SequenceNumberRanges
+  ) extends BlockRDDPartition(blockId, idx)
+
+/**
+ * A BlockRDD where the block data is backed by Kinesis, which can accessed using the
+ * sequence numbers of the corresponding blocks.
+ */
+private[kinesis]
+class KinesisBackedBlockRDD[T: ClassTag](
+    sc: SparkContext,
+    val regionName: String,
+    val endpointUrl: String,
+    @transient private val _blockIds: Array[BlockId],
+    @transient val arrayOfseqNumberRanges: Array[SequenceNumberRanges],
+    @transient private val isBlockIdValid: Array[Boolean] = Array.empty,
+    val retryTimeoutMs: Int = 10000,
+    val messageHandler: Record => T = KinesisUtils.defaultMessageHandler _,
+    val awsCredentialsOption: Option[SerializableAWSCredentials] = None
+  ) extends BlockRDD[T](sc, _blockIds) {
+
+  require(_blockIds.length == arrayOfseqNumberRanges.length,
+    "Number of blockIds is not equal to the number of sequence number ranges")
+
+  override def isValid(): Boolean = true
+
+  override def getPartitions: Array[Partition] = {
+    Array.tabulate(_blockIds.length) { i =>
+      val isValid = if (isBlockIdValid.length == 0) true else isBlockIdValid(i)
+      new KinesisBackedBlockRDDPartition(i, _blockIds(i), isValid, arrayOfseqNumberRanges(i))
+    }
+  }
+
+  override def compute(split: Partition, context: TaskContext): Iterator[T] = {
+    val blockManager = SparkEnv.get.blockManager
+    val partition = split.asInstanceOf[KinesisBackedBlockRDDPartition]
+    val blockId = partition.blockId
+
+    def getBlockFromBlockManager(): Option[Iterator[T]] = {
+      logDebug(s"Read partition data of $this from block manager, block $blockId")
+      blockManager.get(blockId).map(_.data.asInstanceOf[Iterator[T]])
+    }
+
+    def getBlockFromKinesis(): Iterator[T] = {
+      val credentials = awsCredentialsOption.getOrElse {
+        new DefaultAWSCredentialsProviderChain().getCredentials()
+      }
+      partition.seqNumberRanges.ranges.iterator.flatMap { range =>
+        new KinesisSequenceRangeIterator(credentials, endpointUrl, regionName,
+          range, retryTimeoutMs).map(messageHandler)
+      }
+    }
+    if (partition.isBlockIdValid) {
+      getBlockFromBlockManager().getOrElse { getBlockFromKinesis() }
+    } else {
+      getBlockFromKinesis()
+    }
+  }
+}
+
+
+/**
+ * An iterator that return the Kinesis data based on the given range of sequence numbers.
+ * Internally, it repeatedly fetches sets of records starting from the fromSequenceNumber,
+ * until the endSequenceNumber is reached.
+ */
+private[kinesis]
+class KinesisSequenceRangeIterator(
+    credentials: AWSCredentials,
+    endpointUrl: String,
+    regionId: String,
+    range: SequenceNumberRange,
+    retryTimeoutMs: Int) extends NextIterator[Record] with Logging {
+
+  private val client = new AmazonKinesisClient(credentials)
+  private val streamName = range.streamName
+  private val shardId = range.shardId
+
+  private var toSeqNumberReceived = false
+  private var lastSeqNumber: String = null
+  private var internalIterator: Iterator[Record] = null
+
+  client.setEndpoint(endpointUrl, "kinesis", regionId)
+
+  override protected def getNext(): Record = {
+    var nextRecord: Record = null
+    if (toSeqNumberReceived) {
+      finished = true
+    } else {
+
+      if (internalIterator == null) {
+
+        // If the internal iterator has not been initialized,
+        // then fetch records from starting sequence number
+        internalIterator = getRecords(ShardIteratorType.AT_SEQUENCE_NUMBER, range.fromSeqNumber)
+      } else if (!internalIterator.hasNext) {
+
+        // If the internal iterator does not have any more records,
+        // then fetch more records after the last consumed sequence number
+        internalIterator = getRecords(ShardIteratorType.AFTER_SEQUENCE_NUMBER, lastSeqNumber)
+      }
+
+      if (!internalIterator.hasNext) {
+
+        // If the internal iterator still does not have any data, then throw exception
+        // and terminate this iterator
+        finished = true
+        throw new SparkException(
+          s"Could not read until the end sequence number of the range: $range")
+      } else {
+
+        // Get the record, copy the data into a byte array and remember its sequence number
+        nextRecord = internalIterator.next()
+        lastSeqNumber = nextRecord.getSequenceNumber()
+
+        // If the this record's sequence number matches the stopping sequence number, then make sure
+        // the iterator is marked finished next time getNext() is called
+        if (nextRecord.getSequenceNumber == range.toSeqNumber) {
+          toSeqNumberReceived = true
+        }
+      }
+    }
+    nextRecord
+  }
+
+  override protected def close(): Unit = {
+    client.shutdown()
+  }
+
+  /**
+   * Get records starting from or after the given sequence number.
+   */
+  private def getRecords(iteratorType: ShardIteratorType, seqNum: String): Iterator[Record] = {
+    val shardIterator = getKinesisIterator(iteratorType, seqNum)
+    val result = getRecordsAndNextKinesisIterator(shardIterator)
+    result._1
+  }
+
+  /**
+   * Get the records starting from using a Kinesis shard iterator (which is a progress handle
+   * to get records from Kinesis), and get the next shard iterator for next consumption.
+   */
+  private def getRecordsAndNextKinesisIterator(
+      shardIterator: String): (Iterator[Record], String) = {
+    val getRecordsRequest = new GetRecordsRequest
+    getRecordsRequest.setRequestCredentials(credentials)
+    getRecordsRequest.setShardIterator(shardIterator)
+    val getRecordsResult = retryOrTimeout[GetRecordsResult](
+      s"getting records using shard iterator") {
+        client.getRecords(getRecordsRequest)
+      }
+    // De-aggregate records, if KPL was used in producing the records. The KCL automatically
+    // handles de-aggregation during regular operation. This code path is used during recovery
+    val recordIterator = UserRecord.deaggregate(getRecordsResult.getRecords)
+    (recordIterator.iterator().asScala, getRecordsResult.getNextShardIterator)
+  }
+
+  /**
+   * Get the Kinesis shard iterator for getting records starting from or after the given
+   * sequence number.
+   */
+  private def getKinesisIterator(
+      iteratorType: ShardIteratorType,
+      sequenceNumber: String): String = {
+    val getShardIteratorRequest = new GetShardIteratorRequest
+    getShardIteratorRequest.setRequestCredentials(credentials)
+    getShardIteratorRequest.setStreamName(streamName)
+    getShardIteratorRequest.setShardId(shardId)
+    getShardIteratorRequest.setShardIteratorType(iteratorType.toString)
+    getShardIteratorRequest.setStartingSequenceNumber(sequenceNumber)
+    val getShardIteratorResult = retryOrTimeout[GetShardIteratorResult](
+        s"getting shard iterator from sequence number $sequenceNumber") {
+          client.getShardIterator(getShardIteratorRequest)
+        }
+    getShardIteratorResult.getShardIterator
+  }
+
+  /** Helper method to retry Kinesis API request with exponential backoff and timeouts */
+  private def retryOrTimeout[T](message: String)(body: => T): T = {
+    import KinesisSequenceRangeIterator._
+
+    var startTimeMs = System.currentTimeMillis()
+    var retryCount = 0
+    var waitTimeMs = MIN_RETRY_WAIT_TIME_MS
+    var result: Option[T] = None
+    var lastError: Throwable = null
+
+    def isTimedOut = (System.currentTimeMillis() - startTimeMs) >= retryTimeoutMs
+    def isMaxRetryDone = retryCount >= MAX_RETRIES
+
+    while (result.isEmpty && !isTimedOut && !isMaxRetryDone) {
+      if (retryCount > 0) {  // wait only if this is a retry
+        Thread.sleep(waitTimeMs)
+        waitTimeMs *= 2  // if you have waited, then double wait time for next round
+      }
+      try {
+        result = Some(body)
+      } catch {
+        case NonFatal(t) =>
+          lastError = t
+           t match {
+             case ptee: ProvisionedThroughputExceededException =>
+               logWarning(s"Error while $message [attempt = ${retryCount + 1}]", ptee)
+             case e: Throwable =>
+               throw new SparkException(s"Error while $message", e)
+           }
+      }
+      retryCount += 1
+    }
+    result.getOrElse {
+      if (isTimedOut) {
+        throw new SparkException(
+          s"Timed out after $retryTimeoutMs ms while $message, last exception: ", lastError)
+      } else {
+        throw new SparkException(
+          s"Gave up after $retryCount retries while $message, last exception: ", lastError)
+      }
+    }
+  }
+}
+
+private[streaming]
+object KinesisSequenceRangeIterator {
+  val MAX_RETRIES = 3
+  val MIN_RETRY_WAIT_TIME_MS = 100
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointer.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointer.scala
new file mode 100644
index 0000000000..1ca6d4302c
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointer.scala
@@ -0,0 +1,133 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import java.util.concurrent._
+
+import scala.util.control.NonFatal
+
+import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessorCheckpointer
+import com.amazonaws.services.kinesis.clientlibrary.types.ShutdownReason
+
+import org.apache.spark.Logging
+import org.apache.spark.streaming.Duration
+import org.apache.spark.streaming.util.RecurringTimer
+import org.apache.spark.util.{Clock, SystemClock, ThreadUtils}
+
+/**
+ * This is a helper class for managing Kinesis checkpointing.
+ *
+ * @param receiver The receiver that keeps track of which sequence numbers we can checkpoint
+ * @param checkpointInterval How frequently we will checkpoint to DynamoDB
+ * @param workerId Worker Id of KCL worker for logging purposes
+ * @param clock In order to use ManualClocks for the purpose of testing
+ */
+private[kinesis] class KinesisCheckpointer(
+    receiver: KinesisReceiver[_],
+    checkpointInterval: Duration,
+    workerId: String,
+    clock: Clock = new SystemClock) extends Logging {
+
+  // a map from shardId's to checkpointers
+  private val checkpointers = new ConcurrentHashMap[String, IRecordProcessorCheckpointer]()
+
+  private val lastCheckpointedSeqNums = new ConcurrentHashMap[String, String]()
+
+  private val checkpointerThread: RecurringTimer = startCheckpointerThread()
+
+  /** Update the checkpointer instance to the most recent one for the given shardId. */
+  def setCheckpointer(shardId: String, checkpointer: IRecordProcessorCheckpointer): Unit = {
+    checkpointers.put(shardId, checkpointer)
+  }
+
+  /**
+   * Stop tracking the specified shardId.
+   *
+   * If a checkpointer is provided, e.g. on IRecordProcessor.shutdown [[ShutdownReason.TERMINATE]],
+   * we will use that to make the final checkpoint. If `null` is provided, we will not make the
+   * checkpoint, e.g. in case of [[ShutdownReason.ZOMBIE]].
+   */
+  def removeCheckpointer(shardId: String, checkpointer: IRecordProcessorCheckpointer): Unit = {
+    synchronized {
+      checkpointers.remove(shardId)
+      checkpoint(shardId, checkpointer)
+    }
+  }
+
+  /** Perform the checkpoint. */
+  private def checkpoint(shardId: String, checkpointer: IRecordProcessorCheckpointer): Unit = {
+    try {
+      if (checkpointer != null) {
+        receiver.getLatestSeqNumToCheckpoint(shardId).foreach { latestSeqNum =>
+          val lastSeqNum = lastCheckpointedSeqNums.get(shardId)
+          // Kinesis sequence numbers are monotonically increasing strings, therefore we can do
+          // safely do the string comparison
+          if (lastSeqNum == null || latestSeqNum > lastSeqNum) {
+            /* Perform the checkpoint */
+            KinesisRecordProcessor.retryRandom(checkpointer.checkpoint(latestSeqNum), 4, 100)
+            logDebug(s"Checkpoint:  WorkerId $workerId completed checkpoint at sequence number" +
+              s" $latestSeqNum for shardId $shardId")
+            lastCheckpointedSeqNums.put(shardId, latestSeqNum)
+          }
+        }
+      } else {
+        logDebug(s"Checkpointing skipped for shardId $shardId. Checkpointer not set.")
+      }
+    } catch {
+      case NonFatal(e) =>
+        logWarning(s"Failed to checkpoint shardId $shardId to DynamoDB.", e)
+    }
+  }
+
+  /** Checkpoint the latest saved sequence numbers for all active shardId's. */
+  private def checkpointAll(): Unit = synchronized {
+    // if this method throws an exception, then the scheduled task will not run again
+    try {
+      val shardIds = checkpointers.keys()
+      while (shardIds.hasMoreElements) {
+        val shardId = shardIds.nextElement()
+        checkpoint(shardId, checkpointers.get(shardId))
+      }
+    } catch {
+      case NonFatal(e) =>
+        logWarning("Failed to checkpoint to DynamoDB.", e)
+    }
+  }
+
+  /**
+   * Start the checkpointer thread with the given checkpoint duration.
+   */
+  private def startCheckpointerThread(): RecurringTimer = {
+    val period = checkpointInterval.milliseconds
+    val threadName = s"Kinesis Checkpointer - Worker $workerId"
+    val timer = new RecurringTimer(clock, period, _ => checkpointAll(), threadName)
+    timer.start()
+    logDebug(s"Started checkpointer thread: $threadName")
+    timer
+  }
+
+  /**
+   * Shutdown the checkpointer. Should be called on the onStop of the Receiver.
+   */
+  def shutdown(): Unit = {
+    // the recurring timer checkpoints for us one last time.
+    checkpointerThread.stop(interruptTimer = false)
+    checkpointers.clear()
+    lastCheckpointedSeqNums.clear()
+    logInfo("Successfully shutdown Kinesis Checkpointer.")
+  }
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisInputDStream.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisInputDStream.scala
new file mode 100644
index 0000000000..5223c81a8e
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisInputDStream.scala
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import scala.reflect.ClassTag
+
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream
+import com.amazonaws.services.kinesis.model.Record
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.storage.{BlockId, StorageLevel}
+import org.apache.spark.streaming.{Duration, StreamingContext, Time}
+import org.apache.spark.streaming.dstream.ReceiverInputDStream
+import org.apache.spark.streaming.receiver.Receiver
+import org.apache.spark.streaming.scheduler.ReceivedBlockInfo
+
+private[kinesis] class KinesisInputDStream[T: ClassTag](
+    _ssc: StreamingContext,
+    streamName: String,
+    endpointUrl: String,
+    regionName: String,
+    initialPositionInStream: InitialPositionInStream,
+    checkpointAppName: String,
+    checkpointInterval: Duration,
+    storageLevel: StorageLevel,
+    messageHandler: Record => T,
+    awsCredentialsOption: Option[SerializableAWSCredentials]
+  ) extends ReceiverInputDStream[T](_ssc) {
+
+  private[streaming]
+  override def createBlockRDD(time: Time, blockInfos: Seq[ReceivedBlockInfo]): RDD[T] = {
+
+    // This returns true even for when blockInfos is empty
+    val allBlocksHaveRanges = blockInfos.map { _.metadataOption }.forall(_.nonEmpty)
+
+    if (allBlocksHaveRanges) {
+      // Create a KinesisBackedBlockRDD, even when there are no blocks
+      val blockIds = blockInfos.map { _.blockId.asInstanceOf[BlockId] }.toArray
+      val seqNumRanges = blockInfos.map {
+        _.metadataOption.get.asInstanceOf[SequenceNumberRanges] }.toArray
+      val isBlockIdValid = blockInfos.map { _.isBlockIdValid() }.toArray
+      logDebug(s"Creating KinesisBackedBlockRDD for $time with ${seqNumRanges.length} " +
+          s"seq number ranges: ${seqNumRanges.mkString(", ")} ")
+      new KinesisBackedBlockRDD(
+        context.sc, regionName, endpointUrl, blockIds, seqNumRanges,
+        isBlockIdValid = isBlockIdValid,
+        retryTimeoutMs = ssc.graph.batchDuration.milliseconds.toInt,
+        messageHandler = messageHandler,
+        awsCredentialsOption = awsCredentialsOption)
+    } else {
+      logWarning("Kinesis sequence number information was not present with some block metadata," +
+        " it may not be possible to recover from failures")
+      super.createBlockRDD(time, blockInfos)
+    }
+  }
+
+  override def getReceiver(): Receiver[T] = {
+    new KinesisReceiver(streamName, endpointUrl, regionName, initialPositionInStream,
+      checkpointAppName, checkpointInterval, storageLevel, messageHandler, awsCredentialsOption)
+  }
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala
new file mode 100644
index 0000000000..48ee2a9597
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisReceiver.scala
@@ -0,0 +1,361 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import java.util.UUID
+import java.util.concurrent.ConcurrentHashMap
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+import scala.util.control.NonFatal
+
+import com.amazonaws.auth.{AWSCredentials, AWSCredentialsProvider, DefaultAWSCredentialsProviderChain}
+import com.amazonaws.services.kinesis.clientlibrary.interfaces.{IRecordProcessor, IRecordProcessorCheckpointer, IRecordProcessorFactory}
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.{InitialPositionInStream, KinesisClientLibConfiguration, Worker}
+import com.amazonaws.services.kinesis.model.Record
+
+import org.apache.spark.storage.{StorageLevel, StreamBlockId}
+import org.apache.spark.streaming.Duration
+import org.apache.spark.streaming.receiver.{BlockGenerator, BlockGeneratorListener, Receiver}
+import org.apache.spark.util.Utils
+import org.apache.spark.Logging
+
+private[kinesis]
+case class SerializableAWSCredentials(accessKeyId: String, secretKey: String)
+  extends AWSCredentials {
+  override def getAWSAccessKeyId: String = accessKeyId
+  override def getAWSSecretKey: String = secretKey
+}
+
+/**
+ * Custom AWS Kinesis-specific implementation of Spark Streaming's Receiver.
+ * This implementation relies on the Kinesis Client Library (KCL) Worker as described here:
+ * https://github.com/awslabs/amazon-kinesis-client
+ *
+ * The way this Receiver works is as follows:
+ *
+ *  - The receiver starts a KCL Worker, which is essentially runs a threadpool of multiple
+ *    KinesisRecordProcessor
+ *  - Each KinesisRecordProcessor receives data from a Kinesis shard in batches. Each batch is
+ *    inserted into a Block Generator, and the corresponding range of sequence numbers is recorded.
+ *  - When the block generator defines a block, then the recorded sequence number ranges that were
+ *    inserted into the block are recorded separately for being used later.
+ *  - When the block is ready to be pushed, the block is pushed and the ranges are reported as
+ *    metadata of the block. In addition, the ranges are used to find out the latest sequence
+ *    number for each shard that can be checkpointed through the DynamoDB.
+ *  - Periodically, each KinesisRecordProcessor checkpoints the latest successfully stored sequence
+ *    number for it own shard.
+ *
+ * @param streamName   Kinesis stream name
+ * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+ * @param regionName  Region name used by the Kinesis Client Library for
+ *                    DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+ * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+ *                                 worker's initial starting position in the stream.
+ *                                 The values are either the beginning of the stream
+ *                                 per Kinesis' limit of 24 hours
+ *                                 (InitialPositionInStream.TRIM_HORIZON) or
+ *                                 the tip of the stream (InitialPositionInStream.LATEST).
+ * @param checkpointAppName  Kinesis application name. Kinesis Apps are mapped to Kinesis Streams
+ *                 by the Kinesis Client Library.  If you change the App name or Stream name,
+ *                 the KCL will throw errors.  This usually requires deleting the backing
+ *                 DynamoDB table with the same name this Kinesis application.
+ * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+ *                            See the Kinesis Spark Streaming documentation for more
+ *                            details on the different types of checkpoints.
+ * @param storageLevel Storage level to use for storing the received objects
+ * @param awsCredentialsOption Optional AWS credentials, used when user directly specifies
+ *                             the credentials
+ */
+private[kinesis] class KinesisReceiver[T](
+    val streamName: String,
+    endpointUrl: String,
+    regionName: String,
+    initialPositionInStream: InitialPositionInStream,
+    checkpointAppName: String,
+    checkpointInterval: Duration,
+    storageLevel: StorageLevel,
+    messageHandler: Record => T,
+    awsCredentialsOption: Option[SerializableAWSCredentials])
+  extends Receiver[T](storageLevel) with Logging { receiver =>
+
+  /*
+   * =================================================================================
+   * The following vars are initialize in the onStart() method which executes in the
+   * Spark worker after this Receiver is serialized and shipped to the worker.
+   * =================================================================================
+   */
+
+  /**
+   * workerId is used by the KCL should be based on the ip address of the actual Spark Worker
+   * where this code runs (not the driver's IP address.)
+   */
+  @volatile private var workerId: String = null
+
+  /**
+   * Worker is the core client abstraction from the Kinesis Client Library (KCL).
+   * A worker can process more than one shards from the given stream.
+   * Each shard is assigned its own IRecordProcessor and the worker run multiple such
+   * processors.
+   */
+  @volatile private var worker: Worker = null
+  @volatile private var workerThread: Thread = null
+
+  /** BlockGenerator used to generates blocks out of Kinesis data */
+  @volatile private var blockGenerator: BlockGenerator = null
+
+  /**
+   * Sequence number ranges added to the current block being generated.
+   * Accessing and updating of this map is synchronized by locks in BlockGenerator.
+   */
+  private val seqNumRangesInCurrentBlock = new mutable.ArrayBuffer[SequenceNumberRange]
+
+  /** Sequence number ranges of data added to each generated block */
+  private val blockIdToSeqNumRanges = new ConcurrentHashMap[StreamBlockId, SequenceNumberRanges]
+
+  /**
+   * The centralized kinesisCheckpointer that checkpoints based on the given checkpointInterval.
+   */
+  @volatile private var kinesisCheckpointer: KinesisCheckpointer = null
+
+  /**
+   * Latest sequence number ranges that have been stored successfully.
+   * This is used for checkpointing through KCL */
+  private val shardIdToLatestStoredSeqNum = new ConcurrentHashMap[String, String]
+
+  /**
+   * This is called when the KinesisReceiver starts and must be non-blocking.
+   * The KCL creates and manages the receiving/processing thread pool through Worker.run().
+   */
+  override def onStart() {
+    blockGenerator = supervisor.createBlockGenerator(new GeneratedBlockHandler)
+
+    workerId = Utils.localHostName() + ":" + UUID.randomUUID()
+
+    kinesisCheckpointer = new KinesisCheckpointer(receiver, checkpointInterval, workerId)
+    // KCL config instance
+    val awsCredProvider = resolveAWSCredentialsProvider()
+    val kinesisClientLibConfiguration =
+      new KinesisClientLibConfiguration(checkpointAppName, streamName, awsCredProvider, workerId)
+      .withKinesisEndpoint(endpointUrl)
+      .withInitialPositionInStream(initialPositionInStream)
+      .withTaskBackoffTimeMillis(500)
+      .withRegionName(regionName)
+
+   /*
+    *  RecordProcessorFactory creates impls of IRecordProcessor.
+    *  IRecordProcessor adapts the KCL to our Spark KinesisReceiver via the
+    *  IRecordProcessor.processRecords() method.
+    *  We're using our custom KinesisRecordProcessor in this case.
+    */
+    val recordProcessorFactory = new IRecordProcessorFactory {
+      override def createProcessor: IRecordProcessor =
+        new KinesisRecordProcessor(receiver, workerId)
+    }
+
+    worker = new Worker(recordProcessorFactory, kinesisClientLibConfiguration)
+    workerThread = new Thread() {
+      override def run(): Unit = {
+        try {
+          worker.run()
+        } catch {
+          case NonFatal(e) =>
+            restart("Error running the KCL worker in Receiver", e)
+        }
+      }
+    }
+
+    blockIdToSeqNumRanges.clear()
+    blockGenerator.start()
+
+    workerThread.setName(s"Kinesis Receiver ${streamId}")
+    workerThread.setDaemon(true)
+    workerThread.start()
+
+    logInfo(s"Started receiver with workerId $workerId")
+  }
+
+  /**
+   * This is called when the KinesisReceiver stops.
+   * The KCL worker.shutdown() method stops the receiving/processing threads.
+   * The KCL will do its best to drain and checkpoint any in-flight records upon shutdown.
+   */
+  override def onStop() {
+    if (workerThread != null) {
+      if (worker != null) {
+        worker.shutdown()
+        worker = null
+      }
+      workerThread.join()
+      workerThread = null
+      logInfo(s"Stopped receiver for workerId $workerId")
+    }
+    workerId = null
+    if (kinesisCheckpointer != null) {
+      kinesisCheckpointer.shutdown()
+      kinesisCheckpointer = null
+    }
+  }
+
+  /** Add records of the given shard to the current block being generated */
+  private[kinesis] def addRecords(shardId: String, records: java.util.List[Record]): Unit = {
+    if (records.size > 0) {
+      val dataIterator = records.iterator().asScala.map(messageHandler)
+      val metadata = SequenceNumberRange(streamName, shardId,
+        records.get(0).getSequenceNumber(), records.get(records.size() - 1).getSequenceNumber())
+      blockGenerator.addMultipleDataWithCallback(dataIterator, metadata)
+    }
+  }
+
+  /** Get the latest sequence number for the given shard that can be checkpointed through KCL */
+  private[kinesis] def getLatestSeqNumToCheckpoint(shardId: String): Option[String] = {
+    Option(shardIdToLatestStoredSeqNum.get(shardId))
+  }
+
+  /**
+   * Set the checkpointer that will be used to checkpoint sequence numbers to DynamoDB for the
+   * given shardId.
+   */
+  def setCheckpointer(shardId: String, checkpointer: IRecordProcessorCheckpointer): Unit = {
+    assert(kinesisCheckpointer != null, "Kinesis Checkpointer not initialized!")
+    kinesisCheckpointer.setCheckpointer(shardId, checkpointer)
+  }
+
+  /**
+   * Remove the checkpointer for the given shardId. The provided checkpointer will be used to
+   * checkpoint one last time for the given shard. If `checkpointer` is `null`, then we will not
+   * checkpoint.
+   */
+  def removeCheckpointer(shardId: String, checkpointer: IRecordProcessorCheckpointer): Unit = {
+    assert(kinesisCheckpointer != null, "Kinesis Checkpointer not initialized!")
+    kinesisCheckpointer.removeCheckpointer(shardId, checkpointer)
+  }
+
+  /**
+   * Remember the range of sequence numbers that was added to the currently active block.
+   * Internally, this is synchronized with `finalizeRangesForCurrentBlock()`.
+   */
+  private def rememberAddedRange(range: SequenceNumberRange): Unit = {
+    seqNumRangesInCurrentBlock += range
+  }
+
+  /**
+   * Finalize the ranges added to the block that was active and prepare the ranges buffer
+   * for next block. Internally, this is synchronized with `rememberAddedRange()`.
+   */
+  private def finalizeRangesForCurrentBlock(blockId: StreamBlockId): Unit = {
+    blockIdToSeqNumRanges.put(blockId, SequenceNumberRanges(seqNumRangesInCurrentBlock.toArray))
+    seqNumRangesInCurrentBlock.clear()
+    logDebug(s"Generated block $blockId has $blockIdToSeqNumRanges")
+  }
+
+  /** Store the block along with its associated ranges */
+  private def storeBlockWithRanges(
+      blockId: StreamBlockId, arrayBuffer: mutable.ArrayBuffer[T]): Unit = {
+    val rangesToReportOption = Option(blockIdToSeqNumRanges.remove(blockId))
+    if (rangesToReportOption.isEmpty) {
+      stop("Error while storing block into Spark, could not find sequence number ranges " +
+        s"for block $blockId")
+      return
+    }
+
+    val rangesToReport = rangesToReportOption.get
+    var attempt = 0
+    var stored = false
+    var throwable: Throwable = null
+    while (!stored && attempt <= 3) {
+      try {
+        store(arrayBuffer, rangesToReport)
+        stored = true
+      } catch {
+        case NonFatal(th) =>
+          attempt += 1
+          throwable = th
+      }
+    }
+    if (!stored) {
+      stop("Error while storing block into Spark", throwable)
+    }
+
+    // Update the latest sequence number that have been successfully stored for each shard
+    // Note that we are doing this sequentially because the array of sequence number ranges
+    // is assumed to be
+    rangesToReport.ranges.foreach { range =>
+      shardIdToLatestStoredSeqNum.put(range.shardId, range.toSeqNumber)
+    }
+  }
+
+  /**
+   * If AWS credential is provided, return a AWSCredentialProvider returning that credential.
+   * Otherwise, return the DefaultAWSCredentialsProviderChain.
+   */
+  private def resolveAWSCredentialsProvider(): AWSCredentialsProvider = {
+    awsCredentialsOption match {
+      case Some(awsCredentials) =>
+        logInfo("Using provided AWS credentials")
+        new AWSCredentialsProvider {
+          override def getCredentials: AWSCredentials = awsCredentials
+          override def refresh(): Unit = { }
+        }
+      case None =>
+        logInfo("Using DefaultAWSCredentialsProviderChain")
+        new DefaultAWSCredentialsProviderChain()
+    }
+  }
+
+
+  /**
+   * Class to handle blocks generated by this receiver's block generator. Specifically, in
+   * the context of the Kinesis Receiver, this handler does the following.
+   *
+   * - When an array of records is added to the current active block in the block generator,
+   *   this handler keeps track of the corresponding sequence number range.
+   * - When the currently active block is ready to sealed (not more records), this handler
+   *   keep track of the list of ranges added into this block in another H
+   */
+  private class GeneratedBlockHandler extends BlockGeneratorListener {
+
+    /**
+     * Callback method called after a data item is added into the BlockGenerator.
+     * The data addition, block generation, and calls to onAddData and onGenerateBlock
+     * are all synchronized through the same lock.
+     */
+    def onAddData(data: Any, metadata: Any): Unit = {
+      rememberAddedRange(metadata.asInstanceOf[SequenceNumberRange])
+    }
+
+    /**
+     * Callback method called after a block has been generated.
+     * The data addition, block generation, and calls to onAddData and onGenerateBlock
+     * are all synchronized through the same lock.
+     */
+    def onGenerateBlock(blockId: StreamBlockId): Unit = {
+      finalizeRangesForCurrentBlock(blockId)
+    }
+
+    /** Callback method called when a block is ready to be pushed / stored. */
+    def onPushBlock(blockId: StreamBlockId, arrayBuffer: mutable.ArrayBuffer[_]): Unit = {
+      storeBlockWithRanges(blockId,
+        arrayBuffer.asInstanceOf[mutable.ArrayBuffer[T]])
+    }
+
+    /** Callback called in case of any error in internal of the BlockGenerator */
+    def onError(message: String, throwable: Throwable): Unit = {
+      reportError(message, throwable)
+    }
+  }
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisRecordProcessor.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisRecordProcessor.scala
new file mode 100644
index 0000000000..b5b76cb92d
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisRecordProcessor.scala
@@ -0,0 +1,177 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import java.util.List
+
+import scala.util.Random
+import scala.util.control.NonFatal
+
+import com.amazonaws.services.kinesis.clientlibrary.exceptions.{InvalidStateException, KinesisClientLibDependencyException, ShutdownException, ThrottlingException}
+import com.amazonaws.services.kinesis.clientlibrary.interfaces.{IRecordProcessor, IRecordProcessorCheckpointer}
+import com.amazonaws.services.kinesis.clientlibrary.types.ShutdownReason
+import com.amazonaws.services.kinesis.model.Record
+
+import org.apache.spark.Logging
+import org.apache.spark.streaming.Duration
+
+/**
+ * Kinesis-specific implementation of the Kinesis Client Library (KCL) IRecordProcessor.
+ * This implementation operates on the Array[Byte] from the KinesisReceiver.
+ * The Kinesis Worker creates an instance of this KinesisRecordProcessor for each
+ * shard in the Kinesis stream upon startup.  This is normally done in separate threads,
+ * but the KCLs within the KinesisReceivers will balance themselves out if you create
+ * multiple Receivers.
+ *
+ * @param receiver Kinesis receiver
+ * @param workerId for logging purposes
+ */
+private[kinesis] class KinesisRecordProcessor[T](receiver: KinesisReceiver[T], workerId: String)
+  extends IRecordProcessor with Logging {
+
+  // shardId populated during initialize()
+  @volatile
+  private var shardId: String = _
+
+  /**
+   * The Kinesis Client Library calls this method during IRecordProcessor initialization.
+   *
+   * @param shardId assigned by the KCL to this particular RecordProcessor.
+   */
+  override def initialize(shardId: String) {
+    this.shardId = shardId
+    logInfo(s"Initialized workerId $workerId with shardId $shardId")
+  }
+
+  /**
+   * This method is called by the KCL when a batch of records is pulled from the Kinesis stream.
+   * This is the record-processing bridge between the KCL's IRecordProcessor.processRecords()
+   * and Spark Streaming's Receiver.store().
+   *
+   * @param batch list of records from the Kinesis stream shard
+   * @param checkpointer used to update Kinesis when this batch has been processed/stored
+   *   in the DStream
+   */
+  override def processRecords(batch: List[Record], checkpointer: IRecordProcessorCheckpointer) {
+    if (!receiver.isStopped()) {
+      try {
+        receiver.addRecords(shardId, batch)
+        logDebug(s"Stored: Worker $workerId stored ${batch.size} records for shardId $shardId")
+        receiver.setCheckpointer(shardId, checkpointer)
+      } catch {
+        case NonFatal(e) => {
+          /*
+           *  If there is a failure within the batch, the batch will not be checkpointed.
+           *  This will potentially cause records since the last checkpoint to be processed
+           *     more than once.
+           */
+          logError(s"Exception:  WorkerId $workerId encountered and exception while storing " +
+              s" or checkpointing a batch for workerId $workerId and shardId $shardId.", e)
+
+          /* Rethrow the exception to the Kinesis Worker that is managing this RecordProcessor. */
+          throw e
+        }
+      }
+    } else {
+      /* RecordProcessor has been stopped. */
+      logInfo(s"Stopped:  KinesisReceiver has stopped for workerId $workerId" +
+          s" and shardId $shardId.  No more records will be processed.")
+    }
+  }
+
+  /**
+   * Kinesis Client Library is shutting down this Worker for 1 of 2 reasons:
+   * 1) the stream is resharding by splitting or merging adjacent shards
+   *     (ShutdownReason.TERMINATE)
+   * 2) the failed or latent Worker has stopped sending heartbeats for whatever reason
+   *     (ShutdownReason.ZOMBIE)
+   *
+   * @param checkpointer used to perform a Kinesis checkpoint for ShutdownReason.TERMINATE
+   * @param reason for shutdown (ShutdownReason.TERMINATE or ShutdownReason.ZOMBIE)
+   */
+  override def shutdown(checkpointer: IRecordProcessorCheckpointer, reason: ShutdownReason) {
+    logInfo(s"Shutdown:  Shutting down workerId $workerId with reason $reason")
+    reason match {
+      /*
+       * TERMINATE Use Case.  Checkpoint.
+       * Checkpoint to indicate that all records from the shard have been drained and processed.
+       * It's now OK to read from the new shards that resulted from a resharding event.
+       */
+      case ShutdownReason.TERMINATE =>
+        receiver.removeCheckpointer(shardId, checkpointer)
+
+      /*
+       * ZOMBIE Use Case or Unknown reason.  NoOp.
+       * No checkpoint because other workers may have taken over and already started processing
+       *    the same records.
+       * This may lead to records being processed more than once.
+       */
+      case _ =>
+        receiver.removeCheckpointer(shardId, null) // return null so that we don't checkpoint
+    }
+
+  }
+}
+
+private[kinesis] object KinesisRecordProcessor extends Logging {
+  /**
+   * Retry the given amount of times with a random backoff time (millis) less than the
+   *   given maxBackOffMillis
+   *
+   * @param expression expression to evalute
+   * @param numRetriesLeft number of retries left
+   * @param maxBackOffMillis: max millis between retries
+   *
+   * @return evaluation of the given expression
+   * @throws Unretryable exception, unexpected exception,
+   *  or any exception that persists after numRetriesLeft reaches 0
+   */
+  @annotation.tailrec
+  def retryRandom[T](expression: => T, numRetriesLeft: Int, maxBackOffMillis: Int): T = {
+    util.Try { expression } match {
+      /* If the function succeeded, evaluate to x. */
+      case util.Success(x) => x
+      /* If the function failed, either retry or throw the exception */
+      case util.Failure(e) => e match {
+        /* Retry:  Throttling or other Retryable exception has occurred */
+        case _: ThrottlingException | _: KinesisClientLibDependencyException if numRetriesLeft > 1
+          => {
+               val backOffMillis = Random.nextInt(maxBackOffMillis)
+               Thread.sleep(backOffMillis)
+               logError(s"Retryable Exception:  Random backOffMillis=${backOffMillis}", e)
+               retryRandom(expression, numRetriesLeft - 1, maxBackOffMillis)
+             }
+        /* Throw:  Shutdown has been requested by the Kinesis Client Library. */
+        case _: ShutdownException => {
+          logError(s"ShutdownException:  Caught shutdown exception, skipping checkpoint.", e)
+          throw e
+        }
+        /* Throw:  Non-retryable exception has occurred with the Kinesis Client Library */
+        case _: InvalidStateException => {
+          logError(s"InvalidStateException:  Cannot save checkpoint to the DynamoDB table used" +
+              s" by the Amazon Kinesis Client Library.  Table likely doesn't exist.", e)
+          throw e
+        }
+        /* Throw:  Unexpected exception has occurred */
+        case _ => {
+          logError(s"Unexpected, non-retryable exception.", e)
+          throw e
+        }
+      }
+    }
+  }
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisTestUtils.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisTestUtils.scala
new file mode 100644
index 0000000000..0ace453ee9
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisTestUtils.scala
@@ -0,0 +1,260 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import java.nio.ByteBuffer
+import java.util.concurrent.TimeUnit
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+import scala.collection.mutable.ArrayBuffer
+import scala.util.{Failure, Random, Success, Try}
+
+import com.amazonaws.auth.{AWSCredentials, DefaultAWSCredentialsProviderChain}
+import com.amazonaws.regions.RegionUtils
+import com.amazonaws.services.dynamodbv2.AmazonDynamoDBClient
+import com.amazonaws.services.dynamodbv2.document.DynamoDB
+import com.amazonaws.services.kinesis.AmazonKinesisClient
+import com.amazonaws.services.kinesis.model._
+
+import org.apache.spark.Logging
+
+/**
+ * Shared utility methods for performing Kinesis tests that actually transfer data.
+ *
+ * PLEASE KEEP THIS FILE UNDER src/main AS PYTHON TESTS NEED ACCESS TO THIS FILE!
+ */
+private[kinesis] class KinesisTestUtils extends Logging {
+
+  val endpointUrl = KinesisTestUtils.endpointUrl
+  val regionName = RegionUtils.getRegionByEndpoint(endpointUrl).getName()
+  val streamShardCount = 2
+
+  private val createStreamTimeoutSeconds = 300
+  private val describeStreamPollTimeSeconds = 1
+
+  @volatile
+  private var streamCreated = false
+
+  @volatile
+  private var _streamName: String = _
+
+  protected lazy val kinesisClient = {
+    val client = new AmazonKinesisClient(KinesisTestUtils.getAWSCredentials())
+    client.setEndpoint(endpointUrl)
+    client
+  }
+
+  private lazy val dynamoDB = {
+    val dynamoDBClient = new AmazonDynamoDBClient(new DefaultAWSCredentialsProviderChain())
+    dynamoDBClient.setRegion(RegionUtils.getRegion(regionName))
+    new DynamoDB(dynamoDBClient)
+  }
+
+  protected def getProducer(aggregate: Boolean): KinesisDataGenerator = {
+    if (!aggregate) {
+      new SimpleDataGenerator(kinesisClient)
+    } else {
+      throw new UnsupportedOperationException("Aggregation is not supported through this code path")
+    }
+  }
+
+  def streamName: String = {
+    require(streamCreated, "Stream not yet created, call createStream() to create one")
+    _streamName
+  }
+
+  def createStream(): Unit = {
+    require(!streamCreated, "Stream already created")
+    _streamName = findNonExistentStreamName()
+
+    // Create a stream. The number of shards determines the provisioned throughput.
+    logInfo(s"Creating stream ${_streamName}")
+    val createStreamRequest = new CreateStreamRequest()
+    createStreamRequest.setStreamName(_streamName)
+    createStreamRequest.setShardCount(2)
+    kinesisClient.createStream(createStreamRequest)
+
+    // The stream is now being created. Wait for it to become active.
+    waitForStreamToBeActive(_streamName)
+    streamCreated = true
+    logInfo(s"Created stream ${_streamName}")
+  }
+
+  /**
+   * Push data to Kinesis stream and return a map of
+   * shardId -> seq of (data, seq number) pushed to corresponding shard
+   */
+  def pushData(testData: Seq[Int], aggregate: Boolean): Map[String, Seq[(Int, String)]] = {
+    require(streamCreated, "Stream not yet created, call createStream() to create one")
+    val producer = getProducer(aggregate)
+    val shardIdToSeqNumbers = producer.sendData(streamName, testData)
+    logInfo(s"Pushed $testData:\n\t ${shardIdToSeqNumbers.mkString("\n\t")}")
+    shardIdToSeqNumbers.toMap
+  }
+
+  /**
+   * Expose a Python friendly API.
+   */
+  def pushData(testData: java.util.List[Int]): Unit = {
+    pushData(testData.asScala, aggregate = false)
+  }
+
+  def deleteStream(): Unit = {
+    try {
+      if (streamCreated) {
+        kinesisClient.deleteStream(streamName)
+      }
+    } catch {
+      case e: Exception =>
+        logWarning(s"Could not delete stream $streamName")
+    }
+  }
+
+  def deleteDynamoDBTable(tableName: String): Unit = {
+    try {
+      val table = dynamoDB.getTable(tableName)
+      table.delete()
+      table.waitForDelete()
+    } catch {
+      case e: Exception =>
+        logWarning(s"Could not delete DynamoDB table $tableName")
+    }
+  }
+
+  private def describeStream(streamNameToDescribe: String): Option[StreamDescription] = {
+    try {
+      val describeStreamRequest = new DescribeStreamRequest().withStreamName(streamNameToDescribe)
+      val desc = kinesisClient.describeStream(describeStreamRequest).getStreamDescription()
+      Some(desc)
+    } catch {
+      case rnfe: ResourceNotFoundException =>
+        None
+    }
+  }
+
+  private def findNonExistentStreamName(): String = {
+    var testStreamName: String = null
+    do {
+      Thread.sleep(TimeUnit.SECONDS.toMillis(describeStreamPollTimeSeconds))
+      testStreamName = s"KinesisTestUtils-${math.abs(Random.nextLong())}"
+    } while (describeStream(testStreamName).nonEmpty)
+    testStreamName
+  }
+
+  private def waitForStreamToBeActive(streamNameToWaitFor: String): Unit = {
+    val startTime = System.currentTimeMillis()
+    val endTime = startTime + TimeUnit.SECONDS.toMillis(createStreamTimeoutSeconds)
+    while (System.currentTimeMillis() < endTime) {
+      Thread.sleep(TimeUnit.SECONDS.toMillis(describeStreamPollTimeSeconds))
+      describeStream(streamNameToWaitFor).foreach { description =>
+        val streamStatus = description.getStreamStatus()
+        logDebug(s"\t- current state: $streamStatus\n")
+        if ("ACTIVE".equals(streamStatus)) {
+          return
+        }
+      }
+    }
+    require(false, s"Stream $streamName never became active")
+  }
+}
+
+private[kinesis] object KinesisTestUtils {
+
+  val envVarNameForEnablingTests = "ENABLE_KINESIS_TESTS"
+  val endVarNameForEndpoint = "KINESIS_TEST_ENDPOINT_URL"
+  val defaultEndpointUrl = "https://kinesis.us-west-2.amazonaws.com"
+
+  lazy val shouldRunTests = {
+    val isEnvSet = sys.env.get(envVarNameForEnablingTests) == Some("1")
+    if (isEnvSet) {
+      // scalastyle:off println
+      // Print this so that they are easily visible on the console and not hidden in the log4j logs.
+      println(
+        s"""
+          |Kinesis tests that actually send data has been enabled by setting the environment
+          |variable $envVarNameForEnablingTests to 1. This will create Kinesis Streams and
+          |DynamoDB tables in AWS. Please be aware that this may incur some AWS costs.
+          |By default, the tests use the endpoint URL $defaultEndpointUrl to create Kinesis streams.
+          |To change this endpoint URL to a different region, you can set the environment variable
+          |$endVarNameForEndpoint to the desired endpoint URL
+          |(e.g. $endVarNameForEndpoint="https://kinesis.us-west-2.amazonaws.com").
+        """.stripMargin)
+      // scalastyle:on println
+    }
+    isEnvSet
+  }
+
+  lazy val endpointUrl = {
+    val url = sys.env.getOrElse(endVarNameForEndpoint, defaultEndpointUrl)
+    // scalastyle:off println
+    // Print this so that they are easily visible on the console and not hidden in the log4j logs.
+    println(s"Using endpoint URL $url for creating Kinesis streams for tests.")
+    // scalastyle:on println
+    url
+  }
+
+  def isAWSCredentialsPresent: Boolean = {
+    Try { new DefaultAWSCredentialsProviderChain().getCredentials() }.isSuccess
+  }
+
+  def getAWSCredentials(): AWSCredentials = {
+    assert(shouldRunTests,
+      "Kinesis test not enabled, should not attempt to get AWS credentials")
+    Try { new DefaultAWSCredentialsProviderChain().getCredentials() } match {
+      case Success(cred) => cred
+      case Failure(e) =>
+        throw new Exception(
+          s"""
+             |Kinesis tests enabled using environment variable $envVarNameForEnablingTests
+             |but could not find AWS credentials. Please follow instructions in AWS documentation
+             |to set the credentials in your system such that the DefaultAWSCredentialsProviderChain
+             |can find the credentials.
+           """.stripMargin)
+    }
+  }
+}
+
+/** A wrapper interface that will allow us to consolidate the code for synthetic data generation. */
+private[kinesis] trait KinesisDataGenerator {
+  /** Sends the data to Kinesis and returns the metadata for everything that has been sent. */
+  def sendData(streamName: String, data: Seq[Int]): Map[String, Seq[(Int, String)]]
+}
+
+private[kinesis] class SimpleDataGenerator(
+    client: AmazonKinesisClient) extends KinesisDataGenerator {
+  override def sendData(streamName: String, data: Seq[Int]): Map[String, Seq[(Int, String)]] = {
+    val shardIdToSeqNumbers = new mutable.HashMap[String, ArrayBuffer[(Int, String)]]()
+    data.foreach { num =>
+      val str = num.toString
+      val data = ByteBuffer.wrap(str.getBytes())
+      val putRecordRequest = new PutRecordRequest().withStreamName(streamName)
+        .withData(data)
+        .withPartitionKey(str)
+
+      val putRecordResult = client.putRecord(putRecordRequest)
+      val shardId = putRecordResult.getShardId
+      val seqNumber = putRecordResult.getSequenceNumber()
+      val sentSeqNumbers = shardIdToSeqNumbers.getOrElseUpdate(shardId,
+        new ArrayBuffer[(Int, String)]())
+      sentSeqNumbers += ((num, seqNumber))
+    }
+
+    shardIdToSeqNumbers.toMap
+  }
+}
diff --git a/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisUtils.scala b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisUtils.scala
new file mode 100644
index 0000000000..15ac588b82
--- /dev/null
+++ b/external/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisUtils.scala
@@ -0,0 +1,560 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import scala.reflect.ClassTag
+
+import com.amazonaws.regions.RegionUtils
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream
+import com.amazonaws.services.kinesis.model.Record
+
+import org.apache.spark.api.java.function.{Function => JFunction}
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.streaming.{Duration, StreamingContext}
+import org.apache.spark.streaming.api.java.{JavaReceiverInputDStream, JavaStreamingContext}
+import org.apache.spark.streaming.dstream.ReceiverInputDStream
+
+object KinesisUtils {
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note: The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   * on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   * gets the AWS credentials.
+   *
+   * @param ssc StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param messageHandler A custom message handler that can generate a generic output from a
+   *                       Kinesis `Record`, which contains both message data, and metadata.
+   */
+  def createStream[T: ClassTag](
+      ssc: StreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      messageHandler: Record => T): ReceiverInputDStream[T] = {
+    val cleanedHandler = ssc.sc.clean(messageHandler)
+    // Setting scope to override receiver stream's scope of "receiver stream"
+    ssc.withNamedScope("kinesis stream") {
+      new KinesisInputDStream[T](ssc, streamName, endpointUrl, validateRegion(regionName),
+        initialPositionInStream, kinesisAppName, checkpointInterval, storageLevel,
+        cleanedHandler, None)
+    }
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   *  The given AWS credentials will get saved in DStream checkpoints if checkpointing
+   *  is enabled. Make sure that your checkpoint directory is secure.
+   *
+   * @param ssc StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param messageHandler A custom message handler that can generate a generic output from a
+   *                       Kinesis `Record`, which contains both message data, and metadata.
+   * @param awsAccessKeyId  AWS AccessKeyId (if null, will use DefaultAWSCredentialsProviderChain)
+   * @param awsSecretKey  AWS SecretKey (if null, will use DefaultAWSCredentialsProviderChain)
+   */
+  // scalastyle:off
+  def createStream[T: ClassTag](
+      ssc: StreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      messageHandler: Record => T,
+      awsAccessKeyId: String,
+      awsSecretKey: String): ReceiverInputDStream[T] = {
+    // scalastyle:on
+    val cleanedHandler = ssc.sc.clean(messageHandler)
+    ssc.withNamedScope("kinesis stream") {
+      new KinesisInputDStream[T](ssc, streamName, endpointUrl, validateRegion(regionName),
+        initialPositionInStream, kinesisAppName, checkpointInterval, storageLevel,
+        cleanedHandler, Some(SerializableAWSCredentials(awsAccessKeyId, awsSecretKey)))
+    }
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note: The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   * on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   * gets the AWS credentials.
+   *
+   * @param ssc StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   */
+  def createStream(
+      ssc: StreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel): ReceiverInputDStream[Array[Byte]] = {
+    // Setting scope to override receiver stream's scope of "receiver stream"
+    ssc.withNamedScope("kinesis stream") {
+      new KinesisInputDStream[Array[Byte]](ssc, streamName, endpointUrl, validateRegion(regionName),
+        initialPositionInStream, kinesisAppName, checkpointInterval, storageLevel,
+        defaultMessageHandler, None)
+    }
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   *  The given AWS credentials will get saved in DStream checkpoints if checkpointing
+   *  is enabled. Make sure that your checkpoint directory is secure.
+   *
+   * @param ssc StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param awsAccessKeyId  AWS AccessKeyId (if null, will use DefaultAWSCredentialsProviderChain)
+   * @param awsSecretKey  AWS SecretKey (if null, will use DefaultAWSCredentialsProviderChain)
+   */
+  def createStream(
+      ssc: StreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      awsAccessKeyId: String,
+      awsSecretKey: String): ReceiverInputDStream[Array[Byte]] = {
+    ssc.withNamedScope("kinesis stream") {
+      new KinesisInputDStream[Array[Byte]](ssc, streamName, endpointUrl, validateRegion(regionName),
+        initialPositionInStream, kinesisAppName, checkpointInterval, storageLevel,
+        defaultMessageHandler, Some(SerializableAWSCredentials(awsAccessKeyId, awsSecretKey)))
+    }
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   *
+   *  - The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   *    on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   *    gets AWS credentials.
+   *  - The region of the `endpointUrl` will be used for DynamoDB and CloudWatch.
+   *  - The Kinesis application name used by the Kinesis Client Library (KCL) will be the app name
+   *    in [[org.apache.spark.SparkConf]].
+   *
+   * @param ssc StreamingContext object
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Endpoint url of Kinesis service
+   *                     (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param storageLevel Storage level to use for storing the received objects
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   */
+  @deprecated("use other forms of createStream", "1.4.0")
+  def createStream(
+      ssc: StreamingContext,
+      streamName: String,
+      endpointUrl: String,
+      checkpointInterval: Duration,
+      initialPositionInStream: InitialPositionInStream,
+      storageLevel: StorageLevel
+    ): ReceiverInputDStream[Array[Byte]] = {
+    ssc.withNamedScope("kinesis stream") {
+      new KinesisInputDStream[Array[Byte]](ssc, streamName, endpointUrl,
+        getRegionByEndpoint(endpointUrl), initialPositionInStream, ssc.sc.appName,
+        checkpointInterval, storageLevel, defaultMessageHandler, None)
+    }
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note: The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   * on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   * gets the AWS credentials.
+   *
+   * @param jssc Java StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param messageHandler A custom message handler that can generate a generic output from a
+   *                       Kinesis `Record`, which contains both message data, and metadata.
+   * @param recordClass Class of the records in DStream
+   */
+  def createStream[T](
+      jssc: JavaStreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      messageHandler: JFunction[Record, T],
+      recordClass: Class[T]): JavaReceiverInputDStream[T] = {
+    implicit val recordCmt: ClassTag[T] = ClassTag(recordClass)
+    val cleanedHandler = jssc.sparkContext.clean(messageHandler.call(_))
+    createStream[T](jssc.ssc, kinesisAppName, streamName, endpointUrl, regionName,
+      initialPositionInStream, checkpointInterval, storageLevel, cleanedHandler)
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   * The given AWS credentials will get saved in DStream checkpoints if checkpointing
+   * is enabled. Make sure that your checkpoint directory is secure.
+   *
+   * @param jssc Java StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param messageHandler A custom message handler that can generate a generic output from a
+   *                       Kinesis `Record`, which contains both message data, and metadata.
+   * @param recordClass Class of the records in DStream
+   * @param awsAccessKeyId  AWS AccessKeyId (if null, will use DefaultAWSCredentialsProviderChain)
+   * @param awsSecretKey  AWS SecretKey (if null, will use DefaultAWSCredentialsProviderChain)
+   */
+  // scalastyle:off
+  def createStream[T](
+      jssc: JavaStreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      messageHandler: JFunction[Record, T],
+      recordClass: Class[T],
+      awsAccessKeyId: String,
+      awsSecretKey: String): JavaReceiverInputDStream[T] = {
+    // scalastyle:on
+    implicit val recordCmt: ClassTag[T] = ClassTag(recordClass)
+    val cleanedHandler = jssc.sparkContext.clean(messageHandler.call(_))
+    createStream[T](jssc.ssc, kinesisAppName, streamName, endpointUrl, regionName,
+      initialPositionInStream, checkpointInterval, storageLevel, cleanedHandler,
+      awsAccessKeyId, awsSecretKey)
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note: The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   * on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   * gets the AWS credentials.
+   *
+   * @param jssc Java StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   */
+  def createStream(
+      jssc: JavaStreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel
+    ): JavaReceiverInputDStream[Array[Byte]] = {
+    createStream[Array[Byte]](jssc.ssc, kinesisAppName, streamName, endpointUrl, regionName,
+      initialPositionInStream, checkpointInterval, storageLevel, defaultMessageHandler(_))
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   * The given AWS credentials will get saved in DStream checkpoints if checkpointing
+   * is enabled. Make sure that your checkpoint directory is secure.
+   *
+   * @param jssc Java StreamingContext object
+   * @param kinesisAppName  Kinesis application name used by the Kinesis Client Library
+   *                        (KCL) to update DynamoDB
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Url of Kinesis service (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param regionName   Name of region used by the Kinesis Client Library (KCL) to update
+   *                     DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics)
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param storageLevel Storage level to use for storing the received objects.
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   * @param awsAccessKeyId  AWS AccessKeyId (if null, will use DefaultAWSCredentialsProviderChain)
+   * @param awsSecretKey  AWS SecretKey (if null, will use DefaultAWSCredentialsProviderChain)
+   */
+  def createStream(
+      jssc: JavaStreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: InitialPositionInStream,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      awsAccessKeyId: String,
+      awsSecretKey: String): JavaReceiverInputDStream[Array[Byte]] = {
+    createStream[Array[Byte]](jssc.ssc, kinesisAppName, streamName, endpointUrl, regionName,
+      initialPositionInStream, checkpointInterval, storageLevel,
+      defaultMessageHandler(_), awsAccessKeyId, awsSecretKey)
+  }
+
+  /**
+   * Create an input stream that pulls messages from a Kinesis stream.
+   * This uses the Kinesis Client Library (KCL) to pull messages from Kinesis.
+   *
+   * Note:
+   * - The AWS credentials will be discovered using the DefaultAWSCredentialsProviderChain
+   *   on the workers. See AWS documentation to understand how DefaultAWSCredentialsProviderChain
+   *   gets AWS credentials.
+   * - The region of the `endpointUrl` will be used for DynamoDB and CloudWatch.
+   * - The Kinesis application name used by the Kinesis Client Library (KCL) will be the app name in
+   *   [[org.apache.spark.SparkConf]].
+   *
+   * @param jssc Java StreamingContext object
+   * @param streamName   Kinesis stream name
+   * @param endpointUrl  Endpoint url of Kinesis service
+   *                     (e.g., https://kinesis.us-east-1.amazonaws.com)
+   * @param checkpointInterval  Checkpoint interval for Kinesis checkpointing.
+   *                            See the Kinesis Spark Streaming documentation for more
+   *                            details on the different types of checkpoints.
+   * @param initialPositionInStream  In the absence of Kinesis checkpoint info, this is the
+   *                                 worker's initial starting position in the stream.
+   *                                 The values are either the beginning of the stream
+   *                                 per Kinesis' limit of 24 hours
+   *                                 (InitialPositionInStream.TRIM_HORIZON) or
+   *                                 the tip of the stream (InitialPositionInStream.LATEST).
+   * @param storageLevel Storage level to use for storing the received objects
+   *                     StorageLevel.MEMORY_AND_DISK_2 is recommended.
+   */
+  @deprecated("use other forms of createStream", "1.4.0")
+  def createStream(
+      jssc: JavaStreamingContext,
+      streamName: String,
+      endpointUrl: String,
+      checkpointInterval: Duration,
+      initialPositionInStream: InitialPositionInStream,
+      storageLevel: StorageLevel
+    ): JavaReceiverInputDStream[Array[Byte]] = {
+    createStream(
+      jssc.ssc, streamName, endpointUrl, checkpointInterval, initialPositionInStream, storageLevel)
+  }
+
+  private def getRegionByEndpoint(endpointUrl: String): String = {
+    RegionUtils.getRegionByEndpoint(endpointUrl).getName()
+  }
+
+  private def validateRegion(regionName: String): String = {
+    Option(RegionUtils.getRegion(regionName)).map { _.getName }.getOrElse {
+      throw new IllegalArgumentException(s"Region name '$regionName' is not valid")
+    }
+  }
+
+  private[kinesis] def defaultMessageHandler(record: Record): Array[Byte] = {
+    if (record == null) return null
+    val byteBuffer = record.getData()
+    val byteArray = new Array[Byte](byteBuffer.remaining())
+    byteBuffer.get(byteArray)
+    byteArray
+  }
+}
+
+/**
+ * This is a helper class that wraps the methods in KinesisUtils into more Python-friendly class and
+ * function so that it can be easily instantiated and called from Python's KinesisUtils.
+ */
+private class KinesisUtilsPythonHelper {
+
+  def getInitialPositionInStream(initialPositionInStream: Int): InitialPositionInStream = {
+    initialPositionInStream match {
+      case 0 => InitialPositionInStream.LATEST
+      case 1 => InitialPositionInStream.TRIM_HORIZON
+      case _ => throw new IllegalArgumentException(
+        "Illegal InitialPositionInStream. Please use " +
+          "InitialPositionInStream.LATEST or InitialPositionInStream.TRIM_HORIZON")
+    }
+  }
+
+  def createStream(
+      jssc: JavaStreamingContext,
+      kinesisAppName: String,
+      streamName: String,
+      endpointUrl: String,
+      regionName: String,
+      initialPositionInStream: Int,
+      checkpointInterval: Duration,
+      storageLevel: StorageLevel,
+      awsAccessKeyId: String,
+      awsSecretKey: String
+      ): JavaReceiverInputDStream[Array[Byte]] = {
+    if (awsAccessKeyId == null && awsSecretKey != null) {
+      throw new IllegalArgumentException("awsSecretKey is set but awsAccessKeyId is null")
+    }
+    if (awsAccessKeyId != null && awsSecretKey == null) {
+      throw new IllegalArgumentException("awsAccessKeyId is set but awsSecretKey is null")
+    }
+    if (awsAccessKeyId == null && awsSecretKey == null) {
+      KinesisUtils.createStream(jssc, kinesisAppName, streamName, endpointUrl, regionName,
+        getInitialPositionInStream(initialPositionInStream), checkpointInterval, storageLevel)
+    } else {
+      KinesisUtils.createStream(jssc, kinesisAppName, streamName, endpointUrl, regionName,
+        getInitialPositionInStream(initialPositionInStream), checkpointInterval, storageLevel,
+        awsAccessKeyId, awsSecretKey)
+    }
+  }
+
+}
diff --git a/external/kinesis-asl/src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java b/external/kinesis-asl/src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java
new file mode 100644
index 0000000000..5c2371c543
--- /dev/null
+++ b/external/kinesis-asl/src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java
@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis;
+
+import com.amazonaws.services.kinesis.model.Record;
+import org.junit.Test;
+
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.Duration;
+import org.apache.spark.streaming.LocalJavaStreamingContext;
+import org.apache.spark.streaming.api.java.JavaDStream;
+
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream;
+
+/**
+ * Demonstrate the use of the KinesisUtils Java API
+ */
+public class JavaKinesisStreamSuite extends LocalJavaStreamingContext {
+  @Test
+  public void testKinesisStream() {
+    // Tests the API, does not actually test data receiving
+    JavaDStream<byte[]> kinesisStream = KinesisUtils.createStream(ssc, "mySparkStream",
+        "https://kinesis.us-west-2.amazonaws.com", new Duration(2000),
+        InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2());
+
+    ssc.stop();
+  }
+
+
+  private static Function<Record, String> handler = new Function<Record, String>() {
+    @Override
+    public String call(Record record) {
+      return record.getPartitionKey() + "-" + record.getSequenceNumber();
+    }
+  };
+
+  @Test
+  public void testCustomHandler() {
+    // Tests the API, does not actually test data receiving
+    JavaDStream<String> kinesisStream = KinesisUtils.createStream(ssc, "testApp", "mySparkStream",
+        "https://kinesis.us-west-2.amazonaws.com", "us-west-2", InitialPositionInStream.LATEST,
+        new Duration(2000), StorageLevel.MEMORY_AND_DISK_2(), handler, String.class);
+
+    ssc.stop();
+  }
+}
diff --git a/external/kinesis-asl/src/test/resources/log4j.properties b/external/kinesis-asl/src/test/resources/log4j.properties
new file mode 100644
index 0000000000..edbecdae92
--- /dev/null
+++ b/external/kinesis-asl/src/test/resources/log4j.properties
@@ -0,0 +1,27 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Set everything to be logged to the file target/unit-tests.log
+log4j.rootCategory=INFO, file
+log4j.appender.file=org.apache.log4j.FileAppender
+log4j.appender.file.append=true
+log4j.appender.file.file=target/unit-tests.log
+log4j.appender.file.layout=org.apache.log4j.PatternLayout
+log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
+
+# Ignore messages below warning level from Jetty, because it's a bit verbose
+log4j.logger.org.spark-project.jetty=WARN
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala
new file mode 100644
index 0000000000..fdb270eaad
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala
@@ -0,0 +1,72 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import java.nio.ByteBuffer
+
+import scala.collection.mutable
+import scala.collection.mutable.ArrayBuffer
+
+import com.amazonaws.services.kinesis.producer.{KinesisProducer => KPLProducer, KinesisProducerConfiguration, UserRecordResult}
+import com.google.common.util.concurrent.{FutureCallback, Futures}
+
+private[kinesis] class KPLBasedKinesisTestUtils extends KinesisTestUtils {
+  override protected def getProducer(aggregate: Boolean): KinesisDataGenerator = {
+    if (!aggregate) {
+      new SimpleDataGenerator(kinesisClient)
+    } else {
+      new KPLDataGenerator(regionName)
+    }
+  }
+}
+
+/** A wrapper for the KinesisProducer provided in the KPL. */
+private[kinesis] class KPLDataGenerator(regionName: String) extends KinesisDataGenerator {
+
+  private lazy val producer: KPLProducer = {
+    val conf = new KinesisProducerConfiguration()
+      .setRecordMaxBufferedTime(1000)
+      .setMaxConnections(1)
+      .setRegion(regionName)
+      .setMetricsLevel("none")
+
+    new KPLProducer(conf)
+  }
+
+  override def sendData(streamName: String, data: Seq[Int]): Map[String, Seq[(Int, String)]] = {
+    val shardIdToSeqNumbers = new mutable.HashMap[String, ArrayBuffer[(Int, String)]]()
+    data.foreach { num =>
+      val str = num.toString
+      val data = ByteBuffer.wrap(str.getBytes())
+      val future = producer.addUserRecord(streamName, str, data)
+      val kinesisCallBack = new FutureCallback[UserRecordResult]() {
+        override def onFailure(t: Throwable): Unit = {} // do nothing
+
+        override def onSuccess(result: UserRecordResult): Unit = {
+          val shardId = result.getShardId
+          val seqNumber = result.getSequenceNumber()
+          val sentSeqNumbers = shardIdToSeqNumbers.getOrElseUpdate(shardId,
+            new ArrayBuffer[(Int, String)]())
+          sentSeqNumbers += ((num, seqNumber))
+        }
+      }
+      Futures.addCallback(future, kinesisCallBack)
+    }
+    producer.flushSync()
+    shardIdToSeqNumbers.toMap
+  }
+}
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDDSuite.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDDSuite.scala
new file mode 100644
index 0000000000..2555332d22
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDDSuite.scala
@@ -0,0 +1,259 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import org.scalatest.BeforeAndAfterEach
+
+import org.apache.spark.{LocalSparkContext, SparkConf, SparkContext, SparkException}
+import org.apache.spark.storage.{BlockId, BlockManager, StorageLevel, StreamBlockId}
+
+abstract class KinesisBackedBlockRDDTests(aggregateTestData: Boolean)
+  extends KinesisFunSuite with BeforeAndAfterEach with LocalSparkContext {
+
+  private val testData = 1 to 8
+
+  private var testUtils: KinesisTestUtils = null
+  private var shardIds: Seq[String] = null
+  private var shardIdToData: Map[String, Seq[Int]] = null
+  private var shardIdToSeqNumbers: Map[String, Seq[String]] = null
+  private var shardIdToDataAndSeqNumbers: Map[String, Seq[(Int, String)]] = null
+  private var shardIdToRange: Map[String, SequenceNumberRange] = null
+  private var allRanges: Seq[SequenceNumberRange] = null
+
+  private var blockManager: BlockManager = null
+
+  override def beforeAll(): Unit = {
+    super.beforeAll()
+    runIfTestsEnabled("Prepare KinesisTestUtils") {
+      testUtils = new KPLBasedKinesisTestUtils()
+      testUtils.createStream()
+
+      shardIdToDataAndSeqNumbers = testUtils.pushData(testData, aggregate = aggregateTestData)
+      require(shardIdToDataAndSeqNumbers.size > 1, "Need data to be sent to multiple shards")
+
+      shardIds = shardIdToDataAndSeqNumbers.keySet.toSeq
+      shardIdToData = shardIdToDataAndSeqNumbers.mapValues { _.map { _._1 }}
+      shardIdToSeqNumbers = shardIdToDataAndSeqNumbers.mapValues { _.map { _._2 }}
+      shardIdToRange = shardIdToSeqNumbers.map { case (shardId, seqNumbers) =>
+        val seqNumRange = SequenceNumberRange(
+          testUtils.streamName, shardId, seqNumbers.head, seqNumbers.last)
+        (shardId, seqNumRange)
+      }
+      allRanges = shardIdToRange.values.toSeq
+    }
+  }
+
+  override def beforeEach(): Unit = {
+    super.beforeEach()
+    val conf = new SparkConf().setMaster("local[4]").setAppName("KinesisBackedBlockRDDSuite")
+    sc = new SparkContext(conf)
+    blockManager = sc.env.blockManager
+  }
+
+  override def afterAll(): Unit = {
+    try {
+      if (testUtils != null) {
+        testUtils.deleteStream()
+      }
+    } finally {
+      super.afterAll()
+    }
+  }
+
+  testIfEnabled("Basic reading from Kinesis") {
+    // Verify all data using multiple ranges in a single RDD partition
+    val receivedData1 = new KinesisBackedBlockRDD[Array[Byte]](sc, testUtils.regionName,
+      testUtils.endpointUrl, fakeBlockIds(1),
+      Array(SequenceNumberRanges(allRanges.toArray))
+    ).map { bytes => new String(bytes).toInt }.collect()
+    assert(receivedData1.toSet === testData.toSet)
+
+    // Verify all data using one range in each of the multiple RDD partitions
+    val receivedData2 = new KinesisBackedBlockRDD[Array[Byte]](sc, testUtils.regionName,
+      testUtils.endpointUrl, fakeBlockIds(allRanges.size),
+      allRanges.map { range => SequenceNumberRanges(Array(range)) }.toArray
+    ).map { bytes => new String(bytes).toInt }.collect()
+    assert(receivedData2.toSet === testData.toSet)
+
+    // Verify ordering within each partition
+    val receivedData3 = new KinesisBackedBlockRDD[Array[Byte]](sc, testUtils.regionName,
+      testUtils.endpointUrl, fakeBlockIds(allRanges.size),
+      allRanges.map { range => SequenceNumberRanges(Array(range)) }.toArray
+    ).map { bytes => new String(bytes).toInt }.collectPartitions()
+    assert(receivedData3.length === allRanges.size)
+    for (i <- 0 until allRanges.size) {
+      assert(receivedData3(i).toSeq === shardIdToData(allRanges(i).shardId))
+    }
+  }
+
+  testIfEnabled("Read data available in both block manager and Kinesis") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 2, numPartitionsInKinesis = 2)
+  }
+
+  testIfEnabled("Read data available only in block manager, not in Kinesis") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 2, numPartitionsInKinesis = 0)
+  }
+
+  testIfEnabled("Read data available only in Kinesis, not in block manager") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 0, numPartitionsInKinesis = 2)
+  }
+
+  testIfEnabled("Read data available partially in block manager, rest in Kinesis") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 1, numPartitionsInKinesis = 1)
+  }
+
+  testIfEnabled("Test isBlockValid skips block fetching from block manager") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 2, numPartitionsInKinesis = 0,
+      testIsBlockValid = true)
+  }
+
+  testIfEnabled("Test whether RDD is valid after removing blocks from block anager") {
+    testRDD(numPartitions = 2, numPartitionsInBM = 2, numPartitionsInKinesis = 2,
+      testBlockRemove = true)
+  }
+
+  /**
+   * Test the WriteAheadLogBackedRDD, by writing some partitions of the data to block manager
+   * and the rest to a write ahead log, and then reading reading it all back using the RDD.
+   * It can also test if the partitions that were read from the log were again stored in
+   * block manager.
+   *
+   *
+   *
+   * @param numPartitions Number of partitions in RDD
+   * @param numPartitionsInBM Number of partitions to write to the BlockManager.
+   *                          Partitions 0 to (numPartitionsInBM-1) will be written to BlockManager
+   * @param numPartitionsInKinesis Number of partitions to write to the Kinesis.
+   *                           Partitions (numPartitions - 1 - numPartitionsInKinesis) to
+   *                           (numPartitions - 1) will be written to Kinesis
+   * @param testIsBlockValid Test whether setting isBlockValid to false skips block fetching
+   * @param testBlockRemove Test whether calling rdd.removeBlock() makes the RDD still usable with
+   *                        reads falling back to the WAL
+   * Example with numPartitions = 5, numPartitionsInBM = 3, and numPartitionsInWAL = 4
+   *
+   *   numPartitionsInBM = 3
+   *   |------------------|
+   *   |                  |
+   *    0       1       2       3       4
+   *           |                         |
+   *           |-------------------------|
+   *              numPartitionsInKinesis = 4
+   */
+  private def testRDD(
+      numPartitions: Int,
+      numPartitionsInBM: Int,
+      numPartitionsInKinesis: Int,
+      testIsBlockValid: Boolean = false,
+      testBlockRemove: Boolean = false
+    ): Unit = {
+    require(shardIds.size > 1, "Need at least 2 shards to test")
+    require(numPartitionsInBM <= shardIds.size,
+      "Number of partitions in BlockManager cannot be more than the Kinesis test shards available")
+    require(numPartitionsInKinesis <= shardIds.size,
+      "Number of partitions in Kinesis cannot be more than the Kinesis test shards available")
+    require(numPartitionsInBM <= numPartitions,
+      "Number of partitions in BlockManager cannot be more than that in RDD")
+    require(numPartitionsInKinesis <= numPartitions,
+      "Number of partitions in Kinesis cannot be more than that in RDD")
+
+    // Put necessary blocks in the block manager
+    val blockIds = fakeBlockIds(numPartitions)
+    blockIds.foreach(blockManager.removeBlock(_))
+    (0 until numPartitionsInBM).foreach { i =>
+      val blockData = shardIdToData(shardIds(i)).iterator.map { _.toString.getBytes() }
+      blockManager.putIterator(blockIds(i), blockData, StorageLevel.MEMORY_ONLY)
+    }
+
+    // Create the necessary ranges to use in the RDD
+    val fakeRanges = Array.fill(numPartitions - numPartitionsInKinesis)(
+      SequenceNumberRanges(SequenceNumberRange("fakeStream", "fakeShardId", "xxx", "yyy")))
+    val realRanges = Array.tabulate(numPartitionsInKinesis) { i =>
+      val range = shardIdToRange(shardIds(i + (numPartitions - numPartitionsInKinesis)))
+      SequenceNumberRanges(Array(range))
+    }
+    val ranges = (fakeRanges ++ realRanges)
+
+
+    // Make sure that the left `numPartitionsInBM` blocks are in block manager, and others are not
+    require(
+      blockIds.take(numPartitionsInBM).forall(blockManager.get(_).nonEmpty),
+      "Expected blocks not in BlockManager"
+    )
+
+    require(
+      blockIds.drop(numPartitionsInBM).forall(blockManager.get(_).isEmpty),
+      "Unexpected blocks in BlockManager"
+    )
+
+    // Make sure that the right sequence `numPartitionsInKinesis` are configured, and others are not
+    require(
+      ranges.takeRight(numPartitionsInKinesis).forall {
+        _.ranges.forall { _.streamName == testUtils.streamName }
+      }, "Incorrect configuration of RDD, expected ranges not set: "
+    )
+
+    require(
+      ranges.dropRight(numPartitionsInKinesis).forall {
+        _.ranges.forall { _.streamName != testUtils.streamName }
+      }, "Incorrect configuration of RDD, unexpected ranges set"
+    )
+
+    val rdd = new KinesisBackedBlockRDD[Array[Byte]](
+      sc, testUtils.regionName, testUtils.endpointUrl, blockIds, ranges)
+    val collectedData = rdd.map { bytes =>
+      new String(bytes).toInt
+    }.collect()
+    assert(collectedData.toSet === testData.toSet)
+
+    // Verify that the block fetching is skipped when isBlockValid is set to false.
+    // This is done by using a RDD whose data is only in memory but is set to skip block fetching
+    // Using that RDD will throw exception, as it skips block fetching even if the blocks are in
+    // in BlockManager.
+    if (testIsBlockValid) {
+      require(numPartitionsInBM === numPartitions, "All partitions must be in BlockManager")
+      require(numPartitionsInKinesis === 0, "No partitions must be in Kinesis")
+      val rdd2 = new KinesisBackedBlockRDD[Array[Byte]](
+        sc, testUtils.regionName, testUtils.endpointUrl, blockIds.toArray, ranges,
+        isBlockIdValid = Array.fill(blockIds.length)(false))
+      intercept[SparkException] {
+        rdd2.collect()
+      }
+    }
+
+    // Verify that the RDD is not invalid after the blocks are removed and can still read data
+    // from write ahead log
+    if (testBlockRemove) {
+      require(numPartitions === numPartitionsInKinesis,
+        "All partitions must be in WAL for this test")
+      require(numPartitionsInBM > 0, "Some partitions must be in BlockManager for this test")
+      rdd.removeBlocks()
+      assert(rdd.map { bytes => new String(bytes).toInt }.collect().toSet === testData.toSet)
+    }
+  }
+
+  /** Generate fake block ids */
+  private def fakeBlockIds(num: Int): Array[BlockId] = {
+    Array.tabulate(num) { i => new StreamBlockId(0, i) }
+  }
+}
+
+class WithAggregationKinesisBackedBlockRDDSuite
+  extends KinesisBackedBlockRDDTests(aggregateTestData = true)
+
+class WithoutAggregationKinesisBackedBlockRDDSuite
+  extends KinesisBackedBlockRDDTests(aggregateTestData = false)
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointerSuite.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointerSuite.scala
new file mode 100644
index 0000000000..e1499a8220
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisCheckpointerSuite.scala
@@ -0,0 +1,152 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import java.util.concurrent.{ExecutorService, TimeoutException}
+
+import scala.concurrent.{Await, ExecutionContext, Future}
+import scala.concurrent.duration._
+import scala.language.postfixOps
+
+import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessorCheckpointer
+import org.mockito.Matchers._
+import org.mockito.Mockito._
+import org.mockito.invocation.InvocationOnMock
+import org.mockito.stubbing.Answer
+import org.scalatest.{BeforeAndAfterEach, PrivateMethodTester}
+import org.scalatest.concurrent.Eventually
+import org.scalatest.concurrent.Eventually._
+import org.scalatest.mock.MockitoSugar
+
+import org.apache.spark.streaming.{Duration, TestSuiteBase}
+import org.apache.spark.util.ManualClock
+
+class KinesisCheckpointerSuite extends TestSuiteBase
+  with MockitoSugar
+  with BeforeAndAfterEach
+  with PrivateMethodTester
+  with Eventually {
+
+  private val workerId = "dummyWorkerId"
+  private val shardId = "dummyShardId"
+  private val seqNum = "123"
+  private val otherSeqNum = "245"
+  private val checkpointInterval = Duration(10)
+  private val someSeqNum = Some(seqNum)
+  private val someOtherSeqNum = Some(otherSeqNum)
+
+  private var receiverMock: KinesisReceiver[Array[Byte]] = _
+  private var checkpointerMock: IRecordProcessorCheckpointer = _
+  private var kinesisCheckpointer: KinesisCheckpointer = _
+  private var clock: ManualClock = _
+
+  private val checkpoint = PrivateMethod[Unit]('checkpoint)
+
+  override def beforeEach(): Unit = {
+    receiverMock = mock[KinesisReceiver[Array[Byte]]]
+    checkpointerMock = mock[IRecordProcessorCheckpointer]
+    clock = new ManualClock()
+    kinesisCheckpointer = new KinesisCheckpointer(receiverMock, checkpointInterval, workerId, clock)
+  }
+
+  test("checkpoint is not called twice for the same sequence number") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+    kinesisCheckpointer.invokePrivate(checkpoint(shardId, checkpointerMock))
+    kinesisCheckpointer.invokePrivate(checkpoint(shardId, checkpointerMock))
+
+    verify(checkpointerMock, times(1)).checkpoint(anyString())
+  }
+
+  test("checkpoint is called after sequence number increases") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId))
+      .thenReturn(someSeqNum).thenReturn(someOtherSeqNum)
+    kinesisCheckpointer.invokePrivate(checkpoint(shardId, checkpointerMock))
+    kinesisCheckpointer.invokePrivate(checkpoint(shardId, checkpointerMock))
+
+    verify(checkpointerMock, times(1)).checkpoint(seqNum)
+    verify(checkpointerMock, times(1)).checkpoint(otherSeqNum)
+  }
+
+  test("should checkpoint if we have exceeded the checkpoint interval") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId))
+      .thenReturn(someSeqNum).thenReturn(someOtherSeqNum)
+
+    kinesisCheckpointer.setCheckpointer(shardId, checkpointerMock)
+    clock.advance(5 * checkpointInterval.milliseconds)
+
+    eventually(timeout(1 second)) {
+      verify(checkpointerMock, times(1)).checkpoint(seqNum)
+      verify(checkpointerMock, times(1)).checkpoint(otherSeqNum)
+    }
+  }
+
+  test("shouldn't checkpoint if we have not exceeded the checkpoint interval") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+
+    kinesisCheckpointer.setCheckpointer(shardId, checkpointerMock)
+    clock.advance(checkpointInterval.milliseconds / 2)
+
+    verify(checkpointerMock, never()).checkpoint(anyString())
+  }
+
+  test("should not checkpoint for the same sequence number") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+
+    kinesisCheckpointer.setCheckpointer(shardId, checkpointerMock)
+
+    clock.advance(checkpointInterval.milliseconds * 5)
+    eventually(timeout(1 second)) {
+      verify(checkpointerMock, atMost(1)).checkpoint(anyString())
+    }
+  }
+
+  test("removing checkpointer checkpoints one last time") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+
+    kinesisCheckpointer.removeCheckpointer(shardId, checkpointerMock)
+    verify(checkpointerMock, times(1)).checkpoint(anyString())
+  }
+
+  test("if checkpointing is going on, wait until finished before removing and checkpointing") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId))
+      .thenReturn(someSeqNum).thenReturn(someOtherSeqNum)
+    when(checkpointerMock.checkpoint(anyString)).thenAnswer(new Answer[Unit] {
+      override def answer(invocations: InvocationOnMock): Unit = {
+        clock.waitTillTime(clock.getTimeMillis() + checkpointInterval.milliseconds / 2)
+      }
+    })
+
+    kinesisCheckpointer.setCheckpointer(shardId, checkpointerMock)
+    clock.advance(checkpointInterval.milliseconds)
+    eventually(timeout(1 second)) {
+      verify(checkpointerMock, times(1)).checkpoint(anyString())
+    }
+    // don't block test thread
+    val f = Future(kinesisCheckpointer.removeCheckpointer(shardId, checkpointerMock))(
+      ExecutionContext.global)
+
+    intercept[TimeoutException] {
+      Await.ready(f, 50 millis)
+    }
+
+    clock.advance(checkpointInterval.milliseconds / 2)
+    eventually(timeout(1 second)) {
+      verify(checkpointerMock, times(2)).checkpoint(anyString())
+    }
+  }
+}
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisFunSuite.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisFunSuite.scala
new file mode 100644
index 0000000000..ee428f31d6
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisFunSuite.scala
@@ -0,0 +1,46 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import org.apache.spark.SparkFunSuite
+
+/**
+ * Helper class that runs Kinesis real data transfer tests or
+ * ignores them based on env variable is set or not.
+ */
+trait KinesisFunSuite extends SparkFunSuite  {
+  import KinesisTestUtils._
+
+  /** Run the test if environment variable is set or ignore the test */
+  def testIfEnabled(testName: String)(testBody: => Unit) {
+    if (shouldRunTests) {
+      test(testName)(testBody)
+    } else {
+      ignore(s"$testName [enable by setting env var $envVarNameForEnablingTests=1]")(testBody)
+    }
+  }
+
+  /** Run the give body of code only if Kinesis tests are enabled */
+  def runIfTestsEnabled(message: String)(body: => Unit): Unit = {
+    if (shouldRunTests) {
+      body
+    } else {
+      ignore(s"$message [enable by setting env var $envVarNameForEnablingTests=1]")()
+    }
+  }
+}
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisReceiverSuite.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisReceiverSuite.scala
new file mode 100644
index 0000000000..fd15b6ccdc
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisReceiverSuite.scala
@@ -0,0 +1,210 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.kinesis
+
+import java.nio.ByteBuffer
+import java.nio.charset.StandardCharsets
+import java.util.Arrays
+
+import com.amazonaws.services.kinesis.clientlibrary.exceptions._
+import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessorCheckpointer
+import com.amazonaws.services.kinesis.clientlibrary.types.ShutdownReason
+import com.amazonaws.services.kinesis.model.Record
+import org.mockito.Matchers._
+import org.mockito.Matchers.{eq => meq}
+import org.mockito.Mockito._
+import org.scalatest.{BeforeAndAfter, Matchers}
+import org.scalatest.mock.MockitoSugar
+
+import org.apache.spark.streaming.{Duration, TestSuiteBase}
+import org.apache.spark.util.Utils
+
+/**
+ * Suite of Kinesis streaming receiver tests focusing mostly on the KinesisRecordProcessor
+ */
+class KinesisReceiverSuite extends TestSuiteBase with Matchers with BeforeAndAfter
+    with MockitoSugar {
+
+  val app = "TestKinesisReceiver"
+  val stream = "mySparkStream"
+  val endpoint = "endpoint-url"
+  val workerId = "dummyWorkerId"
+  val shardId = "dummyShardId"
+  val seqNum = "dummySeqNum"
+  val checkpointInterval = Duration(10)
+  val someSeqNum = Some(seqNum)
+
+  val record1 = new Record()
+  record1.setData(ByteBuffer.wrap("Spark In Action".getBytes(StandardCharsets.UTF_8)))
+  val record2 = new Record()
+  record2.setData(ByteBuffer.wrap("Learning Spark".getBytes(StandardCharsets.UTF_8)))
+  val batch = Arrays.asList(record1, record2)
+
+  var receiverMock: KinesisReceiver[Array[Byte]] = _
+  var checkpointerMock: IRecordProcessorCheckpointer = _
+
+  override def beforeFunction(): Unit = {
+    receiverMock = mock[KinesisReceiver[Array[Byte]]]
+    checkpointerMock = mock[IRecordProcessorCheckpointer]
+  }
+
+  test("check serializability of SerializableAWSCredentials") {
+    Utils.deserialize[SerializableAWSCredentials](
+      Utils.serialize(new SerializableAWSCredentials("x", "y")))
+  }
+
+  test("process records including store and set checkpointer") {
+    when(receiverMock.isStopped()).thenReturn(false)
+
+    val recordProcessor = new KinesisRecordProcessor(receiverMock, workerId)
+    recordProcessor.initialize(shardId)
+    recordProcessor.processRecords(batch, checkpointerMock)
+
+    verify(receiverMock, times(1)).isStopped()
+    verify(receiverMock, times(1)).addRecords(shardId, batch)
+    verify(receiverMock, times(1)).setCheckpointer(shardId, checkpointerMock)
+  }
+
+  test("shouldn't store and update checkpointer when receiver is stopped") {
+    when(receiverMock.isStopped()).thenReturn(true)
+
+    val recordProcessor = new KinesisRecordProcessor(receiverMock, workerId)
+    recordProcessor.processRecords(batch, checkpointerMock)
+
+    verify(receiverMock, times(1)).isStopped()
+    verify(receiverMock, never).addRecords(anyString, anyListOf(classOf[Record]))
+    verify(receiverMock, never).setCheckpointer(anyString, meq(checkpointerMock))
+  }
+
+  test("shouldn't update checkpointer when exception occurs during store") {
+    when(receiverMock.isStopped()).thenReturn(false)
+    when(
+      receiverMock.addRecords(anyString, anyListOf(classOf[Record]))
+    ).thenThrow(new RuntimeException())
+
+    intercept[RuntimeException] {
+      val recordProcessor = new KinesisRecordProcessor(receiverMock, workerId)
+      recordProcessor.initialize(shardId)
+      recordProcessor.processRecords(batch, checkpointerMock)
+    }
+
+    verify(receiverMock, times(1)).isStopped()
+    verify(receiverMock, times(1)).addRecords(shardId, batch)
+    verify(receiverMock, never).setCheckpointer(anyString, meq(checkpointerMock))
+  }
+
+  test("shutdown should checkpoint if the reason is TERMINATE") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+
+    val recordProcessor = new KinesisRecordProcessor(receiverMock, workerId)
+    recordProcessor.initialize(shardId)
+    recordProcessor.shutdown(checkpointerMock, ShutdownReason.TERMINATE)
+
+    verify(receiverMock, times(1)).removeCheckpointer(meq(shardId), meq(checkpointerMock))
+  }
+
+
+  test("shutdown should not checkpoint if the reason is something other than TERMINATE") {
+    when(receiverMock.getLatestSeqNumToCheckpoint(shardId)).thenReturn(someSeqNum)
+
+    val recordProcessor = new KinesisRecordProcessor(receiverMock, workerId)
+    recordProcessor.initialize(shardId)
+    recordProcessor.shutdown(checkpointerMock, ShutdownReason.ZOMBIE)
+    recordProcessor.shutdown(checkpointerMock, null)
+
+    verify(receiverMock, times(2)).removeCheckpointer(meq(shardId),
+      meq[IRecordProcessorCheckpointer](null))
+  }
+
+  test("retry success on first attempt") {
+    val expectedIsStopped = false
+    when(receiverMock.isStopped()).thenReturn(expectedIsStopped)
+
+    val actualVal = KinesisRecordProcessor.retryRandom(receiverMock.isStopped(), 2, 100)
+    assert(actualVal == expectedIsStopped)
+
+    verify(receiverMock, times(1)).isStopped()
+  }
+
+  test("retry success on second attempt after a Kinesis throttling exception") {
+    val expectedIsStopped = false
+    when(receiverMock.isStopped())
+        .thenThrow(new ThrottlingException("error message"))
+        .thenReturn(expectedIsStopped)
+
+    val actualVal = KinesisRecordProcessor.retryRandom(receiverMock.isStopped(), 2, 100)
+    assert(actualVal == expectedIsStopped)
+
+    verify(receiverMock, times(2)).isStopped()
+  }
+
+  test("retry success on second attempt after a Kinesis dependency exception") {
+    val expectedIsStopped = false
+    when(receiverMock.isStopped())
+        .thenThrow(new KinesisClientLibDependencyException("error message"))
+        .thenReturn(expectedIsStopped)
+
+    val actualVal = KinesisRecordProcessor.retryRandom(receiverMock.isStopped(), 2, 100)
+    assert(actualVal == expectedIsStopped)
+
+    verify(receiverMock, times(2)).isStopped()
+  }
+
+  test("retry failed after a shutdown exception") {
+    when(checkpointerMock.checkpoint()).thenThrow(new ShutdownException("error message"))
+
+    intercept[ShutdownException] {
+      KinesisRecordProcessor.retryRandom(checkpointerMock.checkpoint(), 2, 100)
+    }
+
+    verify(checkpointerMock, times(1)).checkpoint()
+  }
+
+  test("retry failed after an invalid state exception") {
+    when(checkpointerMock.checkpoint()).thenThrow(new InvalidStateException("error message"))
+
+    intercept[InvalidStateException] {
+      KinesisRecordProcessor.retryRandom(checkpointerMock.checkpoint(), 2, 100)
+    }
+
+    verify(checkpointerMock, times(1)).checkpoint()
+  }
+
+  test("retry failed after unexpected exception") {
+    when(checkpointerMock.checkpoint()).thenThrow(new RuntimeException("error message"))
+
+    intercept[RuntimeException] {
+      KinesisRecordProcessor.retryRandom(checkpointerMock.checkpoint(), 2, 100)
+    }
+
+    verify(checkpointerMock, times(1)).checkpoint()
+  }
+
+  test("retry failed after exhausing all retries") {
+    val expectedErrorMessage = "final try error message"
+    when(checkpointerMock.checkpoint())
+        .thenThrow(new ThrottlingException("error message"))
+        .thenThrow(new ThrottlingException(expectedErrorMessage))
+
+    val exception = intercept[RuntimeException] {
+      KinesisRecordProcessor.retryRandom(checkpointerMock.checkpoint(), 2, 100)
+    }
+    exception.getMessage().shouldBe(expectedErrorMessage)
+
+    verify(checkpointerMock, times(2)).checkpoint()
+  }
+}
diff --git a/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisStreamSuite.scala b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisStreamSuite.scala
new file mode 100644
index 0000000000..ca5d13da46
--- /dev/null
+++ b/external/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisStreamSuite.scala
@@ -0,0 +1,297 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.kinesis
+
+import scala.collection.mutable
+import scala.concurrent.duration._
+import scala.language.postfixOps
+import scala.util.Random
+
+import com.amazonaws.regions.RegionUtils
+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream
+import com.amazonaws.services.kinesis.model.Record
+import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll}
+import org.scalatest.Matchers._
+import org.scalatest.concurrent.Eventually
+
+import org.apache.spark.{SparkConf, SparkContext}
+import org.apache.spark.network.util.JavaUtils
+import org.apache.spark.rdd.RDD
+import org.apache.spark.storage.{StorageLevel, StreamBlockId}
+import org.apache.spark.streaming._
+import org.apache.spark.streaming.dstream.ReceiverInputDStream
+import org.apache.spark.streaming.kinesis.KinesisTestUtils._
+import org.apache.spark.streaming.receiver.BlockManagerBasedStoreResult
+import org.apache.spark.streaming.scheduler.ReceivedBlockInfo
+import org.apache.spark.util.Utils
+
+abstract class KinesisStreamTests(aggregateTestData: Boolean) extends KinesisFunSuite
+  with Eventually with BeforeAndAfter with BeforeAndAfterAll {
+
+  // This is the name that KCL will use to save metadata to DynamoDB
+  private val appName = s"KinesisStreamSuite-${math.abs(Random.nextLong())}"
+  private val batchDuration = Seconds(1)
+
+  // Dummy parameters for API testing
+  private val dummyEndpointUrl = defaultEndpointUrl
+  private val dummyRegionName = RegionUtils.getRegionByEndpoint(dummyEndpointUrl).getName()
+  private val dummyAWSAccessKey = "dummyAccessKey"
+  private val dummyAWSSecretKey = "dummySecretKey"
+
+  private var testUtils: KinesisTestUtils = null
+  private var ssc: StreamingContext = null
+  private var sc: SparkContext = null
+
+  override def beforeAll(): Unit = {
+    val conf = new SparkConf()
+      .setMaster("local[4]")
+      .setAppName("KinesisStreamSuite") // Setting Spark app name to Kinesis app name
+    sc = new SparkContext(conf)
+
+    runIfTestsEnabled("Prepare KinesisTestUtils") {
+      testUtils = new KPLBasedKinesisTestUtils()
+      testUtils.createStream()
+    }
+  }
+
+  override def afterAll(): Unit = {
+    if (ssc != null) {
+      ssc.stop()
+    }
+    if (sc != null) {
+      sc.stop()
+    }
+    if (testUtils != null) {
+      // Delete the Kinesis stream as well as the DynamoDB table generated by
+      // Kinesis Client Library when consuming the stream
+      testUtils.deleteStream()
+      testUtils.deleteDynamoDBTable(appName)
+    }
+  }
+
+  before {
+    ssc = new StreamingContext(sc, batchDuration)
+  }
+
+  after {
+    if (ssc != null) {
+      ssc.stop(stopSparkContext = false)
+      ssc = null
+    }
+    if (testUtils != null) {
+      testUtils.deleteDynamoDBTable(appName)
+    }
+  }
+
+  test("KinesisUtils API") {
+    // Tests the API, does not actually test data receiving
+    val kinesisStream1 = KinesisUtils.createStream(ssc, "mySparkStream",
+      dummyEndpointUrl, Seconds(2),
+      InitialPositionInStream.LATEST, StorageLevel.MEMORY_AND_DISK_2)
+    val kinesisStream2 = KinesisUtils.createStream(ssc, "myAppNam", "mySparkStream",
+      dummyEndpointUrl, dummyRegionName,
+      InitialPositionInStream.LATEST, Seconds(2), StorageLevel.MEMORY_AND_DISK_2)
+    val kinesisStream3 = KinesisUtils.createStream(ssc, "myAppNam", "mySparkStream",
+      dummyEndpointUrl, dummyRegionName,
+      InitialPositionInStream.LATEST, Seconds(2), StorageLevel.MEMORY_AND_DISK_2,
+      dummyAWSAccessKey, dummyAWSSecretKey)
+  }
+
+  test("RDD generation") {
+    val inputStream = KinesisUtils.createStream(ssc, appName, "dummyStream",
+      dummyEndpointUrl, dummyRegionName, InitialPositionInStream.LATEST, Seconds(2),
+      StorageLevel.MEMORY_AND_DISK_2, dummyAWSAccessKey, dummyAWSSecretKey)
+    assert(inputStream.isInstanceOf[KinesisInputDStream[Array[Byte]]])
+
+    val kinesisStream = inputStream.asInstanceOf[KinesisInputDStream[Array[Byte]]]
+    val time = Time(1000)
+
+    // Generate block info data for testing
+    val seqNumRanges1 = SequenceNumberRanges(
+      SequenceNumberRange("fakeStream", "fakeShardId", "xxx", "yyy"))
+    val blockId1 = StreamBlockId(kinesisStream.id, 123)
+    val blockInfo1 = ReceivedBlockInfo(
+      0, None, Some(seqNumRanges1), new BlockManagerBasedStoreResult(blockId1, None))
+
+    val seqNumRanges2 = SequenceNumberRanges(
+      SequenceNumberRange("fakeStream", "fakeShardId", "aaa", "bbb"))
+    val blockId2 = StreamBlockId(kinesisStream.id, 345)
+    val blockInfo2 = ReceivedBlockInfo(
+      0, None, Some(seqNumRanges2), new BlockManagerBasedStoreResult(blockId2, None))
+
+    // Verify that the generated KinesisBackedBlockRDD has the all the right information
+    val blockInfos = Seq(blockInfo1, blockInfo2)
+    val nonEmptyRDD = kinesisStream.createBlockRDD(time, blockInfos)
+    nonEmptyRDD shouldBe a [KinesisBackedBlockRDD[_]]
+    val kinesisRDD = nonEmptyRDD.asInstanceOf[KinesisBackedBlockRDD[_]]
+    assert(kinesisRDD.regionName === dummyRegionName)
+    assert(kinesisRDD.endpointUrl === dummyEndpointUrl)
+    assert(kinesisRDD.retryTimeoutMs === batchDuration.milliseconds)
+    assert(kinesisRDD.awsCredentialsOption ===
+      Some(SerializableAWSCredentials(dummyAWSAccessKey, dummyAWSSecretKey)))
+    assert(nonEmptyRDD.partitions.size === blockInfos.size)
+    nonEmptyRDD.partitions.foreach { _ shouldBe a [KinesisBackedBlockRDDPartition] }
+    val partitions = nonEmptyRDD.partitions.map {
+      _.asInstanceOf[KinesisBackedBlockRDDPartition] }.toSeq
+    assert(partitions.map { _.seqNumberRanges } === Seq(seqNumRanges1, seqNumRanges2))
+    assert(partitions.map { _.blockId } === Seq(blockId1, blockId2))
+    assert(partitions.forall { _.isBlockIdValid === true })
+
+    // Verify that KinesisBackedBlockRDD is generated even when there are no blocks
+    val emptyRDD = kinesisStream.createBlockRDD(time, Seq.empty)
+    emptyRDD shouldBe a [KinesisBackedBlockRDD[Array[Byte]]]
+    emptyRDD.partitions shouldBe empty
+
+    // Verify that the KinesisBackedBlockRDD has isBlockValid = false when blocks are invalid
+    blockInfos.foreach { _.setBlockIdInvalid() }
+    kinesisStream.createBlockRDD(time, blockInfos).partitions.foreach { partition =>
+      assert(partition.asInstanceOf[KinesisBackedBlockRDDPartition].isBlockIdValid === false)
+    }
+  }
+
+
+  /**
+   * Test the stream by sending data to a Kinesis stream and receiving from it.
+   * This test is not run by default as it requires AWS credentials that the test
+   * environment may not have. Even if there is AWS credentials available, the user
+   * may not want to run these tests to avoid the Kinesis costs. To enable this test,
+   * you must have AWS credentials available through the default AWS provider chain,
+   * and you have to set the system environment variable RUN_KINESIS_TESTS=1 .
+   */
+  testIfEnabled("basic operation") {
+    val awsCredentials = KinesisTestUtils.getAWSCredentials()
+    val stream = KinesisUtils.createStream(ssc, appName, testUtils.streamName,
+      testUtils.endpointUrl, testUtils.regionName, InitialPositionInStream.LATEST,
+      Seconds(10), StorageLevel.MEMORY_ONLY,
+      awsCredentials.getAWSAccessKeyId, awsCredentials.getAWSSecretKey)
+
+    val collected = new mutable.HashSet[Int] with mutable.SynchronizedSet[Int]
+    stream.map { bytes => new String(bytes).toInt }.foreachRDD { rdd =>
+      collected ++= rdd.collect()
+      logInfo("Collected = " + collected.mkString(", "))
+    }
+    ssc.start()
+
+    val testData = 1 to 10
+    eventually(timeout(120 seconds), interval(10 second)) {
+      testUtils.pushData(testData, aggregateTestData)
+      assert(collected === testData.toSet, "\nData received does not match data sent")
+    }
+    ssc.stop(stopSparkContext = false)
+  }
+
+  testIfEnabled("custom message handling") {
+    val awsCredentials = KinesisTestUtils.getAWSCredentials()
+    def addFive(r: Record): Int = JavaUtils.bytesToString(r.getData).toInt + 5
+    val stream = KinesisUtils.createStream(ssc, appName, testUtils.streamName,
+      testUtils.endpointUrl, testUtils.regionName, InitialPositionInStream.LATEST,
+      Seconds(10), StorageLevel.MEMORY_ONLY, addFive,
+      awsCredentials.getAWSAccessKeyId, awsCredentials.getAWSSecretKey)
+
+    stream shouldBe a [ReceiverInputDStream[_]]
+
+    val collected = new mutable.HashSet[Int] with mutable.SynchronizedSet[Int]
+    stream.foreachRDD { rdd =>
+      collected ++= rdd.collect()
+      logInfo("Collected = " + collected.mkString(", "))
+    }
+    ssc.start()
+
+    val testData = 1 to 10
+    eventually(timeout(120 seconds), interval(10 second)) {
+      testUtils.pushData(testData, aggregateTestData)
+      val modData = testData.map(_ + 5)
+      assert(collected === modData.toSet, "\nData received does not match data sent")
+    }
+    ssc.stop(stopSparkContext = false)
+  }
+
+  testIfEnabled("failure recovery") {
+    val sparkConf = new SparkConf().setMaster("local[4]").setAppName(this.getClass.getSimpleName)
+    val checkpointDir = Utils.createTempDir().getAbsolutePath
+
+    ssc = new StreamingContext(sc, Milliseconds(1000))
+    ssc.checkpoint(checkpointDir)
+
+    val awsCredentials = KinesisTestUtils.getAWSCredentials()
+    val collectedData = new mutable.HashMap[Time, (Array[SequenceNumberRanges], Seq[Int])]
+
+    val kinesisStream = KinesisUtils.createStream(ssc, appName, testUtils.streamName,
+      testUtils.endpointUrl, testUtils.regionName, InitialPositionInStream.LATEST,
+      Seconds(10), StorageLevel.MEMORY_ONLY,
+      awsCredentials.getAWSAccessKeyId, awsCredentials.getAWSSecretKey)
+
+    // Verify that the generated RDDs are KinesisBackedBlockRDDs, and collect the data in each batch
+    kinesisStream.foreachRDD((rdd: RDD[Array[Byte]], time: Time) => {
+      val kRdd = rdd.asInstanceOf[KinesisBackedBlockRDD[Array[Byte]]]
+      val data = rdd.map { bytes => new String(bytes).toInt }.collect().toSeq
+      collectedData.synchronized {
+        collectedData(time) = (kRdd.arrayOfseqNumberRanges, data)
+      }
+    })
+
+    ssc.remember(Minutes(60)) // remember all the batches so that they are all saved in checkpoint
+    ssc.start()
+
+    def numBatchesWithData: Int =
+      collectedData.synchronized { collectedData.count(_._2._2.nonEmpty) }
+
+    def isCheckpointPresent: Boolean = Checkpoint.getCheckpointFiles(checkpointDir).nonEmpty
+
+    // Run until there are at least 10 batches with some data in them
+    // If this times out because numBatchesWithData is empty, then its likely that foreachRDD
+    // function failed with exceptions, and nothing got added to `collectedData`
+    eventually(timeout(2 minutes), interval(1 seconds)) {
+      testUtils.pushData(1 to 5, aggregateTestData)
+      assert(isCheckpointPresent && numBatchesWithData > 10)
+    }
+    ssc.stop(stopSparkContext = true)  // stop the SparkContext so that the blocks are not reused
+
+    // Restart the context from checkpoint and verify whether the
+    logInfo("Restarting from checkpoint")
+    ssc = new StreamingContext(checkpointDir)
+    ssc.start()
+    val recoveredKinesisStream = ssc.graph.getInputStreams().head
+
+    // Verify that the recomputed RDDs are KinesisBackedBlockRDDs with the same sequence ranges
+    // and return the same data
+    collectedData.synchronized {
+      val times = collectedData.keySet
+      times.foreach { time =>
+        val (arrayOfSeqNumRanges, data) = collectedData(time)
+        val rdd = recoveredKinesisStream.getOrCompute(time).get.asInstanceOf[RDD[Array[Byte]]]
+        rdd shouldBe a[KinesisBackedBlockRDD[_]]
+
+        // Verify the recovered sequence ranges
+        val kRdd = rdd.asInstanceOf[KinesisBackedBlockRDD[Array[Byte]]]
+        assert(kRdd.arrayOfseqNumberRanges.size === arrayOfSeqNumRanges.size)
+        arrayOfSeqNumRanges.zip(kRdd.arrayOfseqNumberRanges).foreach { case (expected, found) =>
+          assert(expected.ranges.toSeq === found.ranges.toSeq)
+        }
+
+        // Verify the recovered data
+        assert(rdd.map { bytes => new String(bytes).toInt }.collect().toSeq === data)
+      }
+    }
+    ssc.stop()
+  }
+}
+
+class WithAggregationKinesisStreamSuite extends KinesisStreamTests(aggregateTestData = true)
+
+class WithoutAggregationKinesisStreamSuite extends KinesisStreamTests(aggregateTestData = false)
diff --git a/external/spark-ganglia-lgpl/pom.xml b/external/spark-ganglia-lgpl/pom.xml
new file mode 100644
index 0000000000..bfb92791de
--- /dev/null
+++ b/external/spark-ganglia-lgpl/pom.xml
@@ -0,0 +1,49 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!--
+~ Licensed to the Apache Software Foundation (ASF) under one or more
+~ contributor license agreements.  See the NOTICE file distributed with
+~ this work for additional information regarding copyright ownership.
+~ The ASF licenses this file to You under the Apache License, Version 2.0
+~ (the "License"); you may not use this file except in compliance with
+~ the License.  You may obtain a copy of the License at
+~
+~    http://www.apache.org/licenses/LICENSE-2.0
+~
+~ Unless required by applicable law or agreed to in writing, software
+~ distributed under the License is distributed on an "AS IS" BASIS,
+~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+~ See the License for the specific language governing permissions and
+~ limitations under the License.
+-->
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <parent>
+    <groupId>org.apache.spark</groupId>
+    <artifactId>spark-parent_2.11</artifactId>
+    <version>2.0.0-SNAPSHOT</version>
+    <relativePath>../../pom.xml</relativePath>
+  </parent>
+
+  <!-- Ganglia integration is not included by default due to LGPL-licensed code -->
+  <groupId>org.apache.spark</groupId>
+  <artifactId>spark-ganglia-lgpl_2.11</artifactId>
+  <packaging>jar</packaging>
+  <name>Spark Ganglia Integration</name>
+
+  <properties>
+    <sbt.project.name>ganglia-lgpl</sbt.project.name>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-core_${scala.binary.version}</artifactId>
+      <version>${project.version}</version>
+    </dependency>
+
+    <dependency>
+      <groupId>io.dropwizard.metrics</groupId>
+      <artifactId>metrics-ganglia</artifactId>
+    </dependency>
+  </dependencies>
+</project>
diff --git a/external/spark-ganglia-lgpl/src/main/scala/org/apache/spark/metrics/sink/GangliaSink.scala b/external/spark-ganglia-lgpl/src/main/scala/org/apache/spark/metrics/sink/GangliaSink.scala
new file mode 100644
index 0000000000..3b1880e143
--- /dev/null
+++ b/external/spark-ganglia-lgpl/src/main/scala/org/apache/spark/metrics/sink/GangliaSink.scala
@@ -0,0 +1,90 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.metrics.sink
+
+import java.util.Properties
+import java.util.concurrent.TimeUnit
+
+import com.codahale.metrics.MetricRegistry
+import com.codahale.metrics.ganglia.GangliaReporter
+import info.ganglia.gmetric4j.gmetric.GMetric
+import info.ganglia.gmetric4j.gmetric.GMetric.UDPAddressingMode
+
+import org.apache.spark.SecurityManager
+import org.apache.spark.metrics.MetricsSystem
+
+class GangliaSink(val property: Properties, val registry: MetricRegistry,
+    securityMgr: SecurityManager) extends Sink {
+  val GANGLIA_KEY_PERIOD = "period"
+  val GANGLIA_DEFAULT_PERIOD = 10
+
+  val GANGLIA_KEY_UNIT = "unit"
+  val GANGLIA_DEFAULT_UNIT: TimeUnit = TimeUnit.SECONDS
+
+  val GANGLIA_KEY_MODE = "mode"
+  val GANGLIA_DEFAULT_MODE: UDPAddressingMode = GMetric.UDPAddressingMode.MULTICAST
+
+  // TTL for multicast messages. If listeners are X hops away in network, must be at least X.
+  val GANGLIA_KEY_TTL = "ttl"
+  val GANGLIA_DEFAULT_TTL = 1
+
+  val GANGLIA_KEY_HOST = "host"
+  val GANGLIA_KEY_PORT = "port"
+
+  def propertyToOption(prop: String): Option[String] = Option(property.getProperty(prop))
+
+  if (!propertyToOption(GANGLIA_KEY_HOST).isDefined) {
+    throw new Exception("Ganglia sink requires 'host' property.")
+  }
+
+  if (!propertyToOption(GANGLIA_KEY_PORT).isDefined) {
+    throw new Exception("Ganglia sink requires 'port' property.")
+  }
+
+  val host = propertyToOption(GANGLIA_KEY_HOST).get
+  val port = propertyToOption(GANGLIA_KEY_PORT).get.toInt
+  val ttl = propertyToOption(GANGLIA_KEY_TTL).map(_.toInt).getOrElse(GANGLIA_DEFAULT_TTL)
+  val mode: UDPAddressingMode = propertyToOption(GANGLIA_KEY_MODE)
+    .map(u => GMetric.UDPAddressingMode.valueOf(u.toUpperCase)).getOrElse(GANGLIA_DEFAULT_MODE)
+  val pollPeriod = propertyToOption(GANGLIA_KEY_PERIOD).map(_.toInt)
+    .getOrElse(GANGLIA_DEFAULT_PERIOD)
+  val pollUnit: TimeUnit = propertyToOption(GANGLIA_KEY_UNIT)
+    .map(u => TimeUnit.valueOf(u.toUpperCase))
+    .getOrElse(GANGLIA_DEFAULT_UNIT)
+
+  MetricsSystem.checkMinimalPollingPeriod(pollUnit, pollPeriod)
+
+  val ganglia = new GMetric(host, port, mode, ttl)
+  val reporter: GangliaReporter = GangliaReporter.forRegistry(registry)
+      .convertDurationsTo(TimeUnit.MILLISECONDS)
+      .convertRatesTo(TimeUnit.SECONDS)
+      .build(ganglia)
+
+  override def start() {
+    reporter.start(pollPeriod, pollUnit)
+  }
+
+  override def stop() {
+    reporter.stop()
+  }
+
+  override def report() {
+    reporter.report()
+  }
+}
+
author	Sean Owen <sowen@cloudera.com>	2016-03-09 18:27:44 +0000
committer	Sean Owen <sowen@cloudera.com>	2016-03-09 18:27:44 +0000
commit	256704c771d301700af9ebf0d180c1ba7c4116c0 (patch)
tree	f9be79919b5c6ec4847c24a086fa844555e2cd12 /external
parent	7791d0c3a9bdfe73e071266846f9ab1491fce50c (diff)
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