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/*
* 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.execution.streaming.state
import java.io.File
import java.nio.file.Files
import scala.util.Random
import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll}
import org.scalatest.concurrent.Eventually._
import org.scalatest.time.SpanSugar._
import org.apache.spark.{SparkConf, SparkContext, SparkFunSuite}
import org.apache.spark.LocalSparkContext._
import org.apache.spark.rdd.RDD
import org.apache.spark.scheduler.ExecutorCacheTaskLocation
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.util.quietly
import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}
import org.apache.spark.util.Utils
class StateStoreRDDSuite extends SparkFunSuite with BeforeAndAfter with BeforeAndAfterAll {
private val sparkConf = new SparkConf().setMaster("local").setAppName(this.getClass.getSimpleName)
private var tempDir = Files.createTempDirectory("StateStoreRDDSuite").toString
private val keySchema = StructType(Seq(StructField("key", StringType, true)))
private val valueSchema = StructType(Seq(StructField("value", IntegerType, true)))
import StateStoreSuite._
after {
StateStore.stop()
}
override def afterAll(): Unit = {
super.afterAll()
Utils.deleteRecursively(new File(tempDir))
}
test("versioning and immutability") {
quietly {
withSpark(new SparkContext(sparkConf)) { sc =>
implicit val sqlContet = new SQLContext(sc)
val path = Utils.createDirectory(tempDir, Random.nextString(10)).toString
val increment = (store: StateStore, iter: Iterator[String]) => {
iter.foreach { s =>
store.update(
stringToRow(s), oldRow => {
val oldValue = oldRow.map(rowToInt).getOrElse(0)
intToRow(oldValue + 1)
})
}
store.commit()
store.iterator().map(rowsToStringInt)
}
val opId = 0
val rdd1 = makeRDD(sc, Seq("a", "b", "a")).mapPartitionWithStateStore(
increment, path, opId, storeVersion = 0, keySchema, valueSchema)
assert(rdd1.collect().toSet === Set("a" -> 2, "b" -> 1))
// Generate next version of stores
val rdd2 = makeRDD(sc, Seq("a", "c")).mapPartitionWithStateStore(
increment, path, opId, storeVersion = 1, keySchema, valueSchema)
assert(rdd2.collect().toSet === Set("a" -> 3, "b" -> 1, "c" -> 1))
// Make sure the previous RDD still has the same data.
assert(rdd1.collect().toSet === Set("a" -> 2, "b" -> 1))
}
}
}
test("recovering from files") {
quietly {
val opId = 0
val path = Utils.createDirectory(tempDir, Random.nextString(10)).toString
def makeStoreRDD(
sc: SparkContext,
seq: Seq[String],
storeVersion: Int): RDD[(String, Int)] = {
implicit val sqlContext = new SQLContext(sc)
makeRDD(sc, Seq("a")).mapPartitionWithStateStore(
increment, path, opId, storeVersion, keySchema, valueSchema)
}
// Generate RDDs and state store data
withSpark(new SparkContext(sparkConf)) { sc =>
for (i <- 1 to 20) {
require(makeStoreRDD(sc, Seq("a"), i - 1).collect().toSet === Set("a" -> i))
}
}
// With a new context, try using the earlier state store data
withSpark(new SparkContext(sparkConf)) { sc =>
assert(makeStoreRDD(sc, Seq("a"), 20).collect().toSet === Set("a" -> 21))
}
}
}
test("preferred locations using StateStoreCoordinator") {
quietly {
val opId = 0
val path = Utils.createDirectory(tempDir, Random.nextString(10)).toString
withSpark(new SparkContext(sparkConf)) { sc =>
implicit val sqlContext = new SQLContext(sc)
val coordinatorRef = sqlContext.streams.stateStoreCoordinator
coordinatorRef.reportActiveInstance(StateStoreId(path, opId, 0), "host1", "exec1")
coordinatorRef.reportActiveInstance(StateStoreId(path, opId, 1), "host2", "exec2")
assert(
coordinatorRef.getLocation(StateStoreId(path, opId, 0)) ===
Some(ExecutorCacheTaskLocation("host1", "exec1").toString))
val rdd = makeRDD(sc, Seq("a", "b", "a")).mapPartitionWithStateStore(
increment, path, opId, storeVersion = 0, keySchema, valueSchema)
require(rdd.partitions.length === 2)
assert(
rdd.preferredLocations(rdd.partitions(0)) ===
Seq(ExecutorCacheTaskLocation("host1", "exec1").toString))
assert(
rdd.preferredLocations(rdd.partitions(1)) ===
Seq(ExecutorCacheTaskLocation("host2", "exec2").toString))
rdd.collect()
}
}
}
test("distributed test") {
quietly {
withSpark(new SparkContext(sparkConf.setMaster("local-cluster[2, 1, 1024]"))) { sc =>
implicit val sqlContet = new SQLContext(sc)
val path = Utils.createDirectory(tempDir, Random.nextString(10)).toString
val increment = (store: StateStore, iter: Iterator[String]) => {
iter.foreach { s =>
store.update(
stringToRow(s), oldRow => {
val oldValue = oldRow.map(rowToInt).getOrElse(0)
intToRow(oldValue + 1)
})
}
store.commit()
store.iterator().map(rowsToStringInt)
}
val opId = 0
val rdd1 = makeRDD(sc, Seq("a", "b", "a")).mapPartitionWithStateStore(
increment, path, opId, storeVersion = 0, keySchema, valueSchema)
assert(rdd1.collect().toSet === Set("a" -> 2, "b" -> 1))
// Generate next version of stores
val rdd2 = makeRDD(sc, Seq("a", "c")).mapPartitionWithStateStore(
increment, path, opId, storeVersion = 1, keySchema, valueSchema)
assert(rdd2.collect().toSet === Set("a" -> 3, "b" -> 1, "c" -> 1))
// Make sure the previous RDD still has the same data.
assert(rdd1.collect().toSet === Set("a" -> 2, "b" -> 1))
}
}
}
private def makeRDD(sc: SparkContext, seq: Seq[String]): RDD[String] = {
sc.makeRDD(seq, 2).groupBy(x => x).flatMap(_._2)
}
private val increment = (store: StateStore, iter: Iterator[String]) => {
iter.foreach { s =>
store.update(
stringToRow(s), oldRow => {
val oldValue = oldRow.map(rowToInt).getOrElse(0)
intToRow(oldValue + 1)
})
}
store.commit()
store.iterator().map(rowsToStringInt)
}
}
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