[SPARK-16114][SQL] structured streaming event time window example

## What changes were proposed in this pull request?

A structured streaming example with event time windowing.

## How was this patch tested?

Run locally

Author: James Thomas <jamesjoethomas@gmail.com>

Closes #13957 from jjthomas/current.

2 files changed, 118 insertions, 2 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCount.java b/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCount.java
index a2cf938954..346d2182c7 100644
--- a/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCount.java
+++ b/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCount.java
@@ -24,7 +24,7 @@ import java.util.Arrays;
 import java.util.Iterator;
 
 /**
- * Counts words in UTF8 encoded, '\n' delimited text received from the network every second.
+ * Counts words in UTF8 encoded, '\n' delimited text received from the network.
  *
  * Usage: JavaStructuredNetworkWordCount <hostname> <port>
  * <hostname> and <port> describe the TCP server that Structured Streaming
@@ -40,7 +40,7 @@ public final class JavaStructuredNetworkWordCount {
 
   public static void main(String[] args) throws Exception {
     if (args.length < 2) {
-      System.err.println("Usage: JavaNetworkWordCount <hostname> <port>");
+      System.err.println("Usage: JavaStructuredNetworkWordCount <hostname> <port>");
       System.exit(1);
     }
 
diff --git a/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCountWindowed.java b/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCountWindowed.java
new file mode 100644
index 0000000000..557d36cff3
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCountWindowed.java
@@ -0,0 +1,116 @@
+/*
+ * 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.sql.streaming;
+
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.sql.*;
+import org.apache.spark.sql.functions;
+import org.apache.spark.sql.streaming.StreamingQuery;
+import scala.Tuple2;
+
+import java.sql.Timestamp;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+
+/**
+ * Counts words in UTF8 encoded, '\n' delimited text received from the network over a
+ * sliding window of configurable duration. Each line from the network is tagged
+ * with a timestamp that is used to determine the windows into which it falls.
+ *
+ * Usage: JavaStructuredNetworkWordCountWindowed <hostname> <port> <window duration>
+ *   [<slide duration>]
+ * <hostname> and <port> describe the TCP server that Structured Streaming
+ * would connect to receive data.
+ * <window duration> gives the size of window, specified as integer number of seconds
+ * <slide duration> gives the amount of time successive windows are offset from one another,
+ * given in the same units as above. <slide duration> should be less than or equal to
+ * <window duration>. If the two are equal, successive windows have no overlap. If
+ * <slide duration> is not provided, it defaults to <window duration>.
+ *
+ * To run this on your local machine, you need to first run a Netcat server
+ *    `$ nc -lk 9999`
+ * and then run the example
+ *    `$ bin/run-example sql.streaming.JavaStructuredNetworkWordCountWindowed
+ *    localhost 9999 <window duration in seconds> [<slide duration in seconds>]`
+ *
+ * One recommended <window duration>, <slide duration> pair is 10, 5
+ */
+public final class JavaStructuredNetworkWordCountWindowed {
+
+  public static void main(String[] args) throws Exception {
+    if (args.length < 3) {
+      System.err.println("Usage: JavaStructuredNetworkWordCountWindowed <hostname> <port>" +
+        " <window duration in seconds> [<slide duration in seconds>]");
+      System.exit(1);
+    }
+
+    String host = args[0];
+    int port = Integer.parseInt(args[1]);
+    int windowSize = Integer.parseInt(args[2]);
+    int slideSize = (args.length == 3) ? windowSize : Integer.parseInt(args[3]);
+    if (slideSize > windowSize) {
+      System.err.println("<slide duration> must be less than or equal to <window duration>");
+    }
+    String windowDuration = windowSize + " seconds";
+    String slideDuration = slideSize + " seconds";
+
+    SparkSession spark = SparkSession
+      .builder()
+      .appName("JavaStructuredNetworkWordCountWindowed")
+      .getOrCreate();
+
+    // Create DataFrame representing the stream of input lines from connection to host:port
+    Dataset<Tuple2<String, Timestamp>> lines = spark
+      .readStream()
+      .format("socket")
+      .option("host", host)
+      .option("port", port)
+      .option("includeTimestamp", true)
+      .load().as(Encoders.tuple(Encoders.STRING(), Encoders.TIMESTAMP()));
+
+    // Split the lines into words, retaining timestamps
+    Dataset<Row> words = lines.flatMap(
+      new FlatMapFunction<Tuple2<String, Timestamp>, Tuple2<String, Timestamp>>() {
+        @Override
+        public Iterator<Tuple2<String, Timestamp>> call(Tuple2<String, Timestamp> t) {
+          List<Tuple2<String, Timestamp>> result = new ArrayList<>();
+          for (String word : t._1.split(" ")) {
+            result.add(new Tuple2<>(word, t._2));
+          }
+          return result.iterator();
+        }
+      },
+      Encoders.tuple(Encoders.STRING(), Encoders.TIMESTAMP())
+    ).toDF("word", "timestamp");
+
+    // Group the data by window and word and compute the count of each group
+    Dataset<Row> windowedCounts = words.groupBy(
+      functions.window(words.col("timestamp"), windowDuration, slideDuration),
+      words.col("word")
+    ).count().orderBy("window");
+
+    // Start running the query that prints the windowed word counts to the console
+    StreamingQuery query = windowedCounts.writeStream()
+      .outputMode("complete")
+      .format("console")
+      .option("truncate", "false")
+      .start();
+
+    query.awaitTermination();
+  }
+}