[SPARK-18410][STREAMING] Add structured kafka example

## What changes were proposed in this pull request?

This PR provides structured kafka wordcount examples

## How was this patch tested?

Author: uncleGen <hustyugm@gmail.com>

Closes #15849 from uncleGen/SPARK-18410.

examples/src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredKafkaWordCount.java

+/*
+ * 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.Dataset;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.streaming.StreamingQuery;
+
+import java.util.Arrays;
+import java.util.Iterator;
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: JavaStructuredKafkaWordCount <bootstrap-servers> <subscribe-type> <topics>
+ *   <bootstrap-servers> The Kafka "bootstrap.servers" configuration. A
+ *   comma-separated list of host:port.
+ *   <subscribe-type> There are three kinds of type, i.e. 'assign', 'subscribe',
+ *   'subscribePattern'.
+ *   |- <assign> Specific TopicPartitions to consume. Json string
+ *   |  {"topicA":[0,1],"topicB":[2,4]}.
+ *   |- <subscribe> The topic list to subscribe. A comma-separated list of
+ *   |  topics.
+ *   |- <subscribePattern> The pattern used to subscribe to topic(s).
+ *   |  Java regex string.
+ *   |- Only one of "assign, "subscribe" or "subscribePattern" options can be
+ *   |  specified for Kafka source.
+ *   <topics> Different value format depends on the value of 'subscribe-type'.
+ *
+ * Example:
+ *    `$ bin/run-example \
+ *      sql.streaming.JavaStructuredKafkaWordCount host1:port1,host2:port2 \
+ *      subscribe topic1,topic2`
+ */
+public final class JavaStructuredKafkaWordCount {
+
+  public static void main(String[] args) throws Exception {
+    if (args.length < 3) {
+      System.err.println("Usage: JavaStructuredKafkaWordCount <bootstrap-servers> " +
+        "<subscribe-type> <topics>");
+      System.exit(1);
+    }
+
+    String bootstrapServers = args[0];
+    String subscribeType = args[1];
+    String topics = args[2];
+
+    SparkSession spark = SparkSession
+      .builder()
+      .appName("JavaStructuredKafkaWordCount")
+      .getOrCreate();
+
+    // Create DataSet representing the stream of input lines from kafka
+    Dataset<String> lines = spark
+      .readStream()
+      .format("kafka")
+      .option("kafka.bootstrap.servers", bootstrapServers)
+      .option(subscribeType, topics)
+      .load()
+      .selectExpr("CAST(value AS STRING)")
+      .as(Encoders.STRING());
+
+    // Generate running word count
+    Dataset<Row> wordCounts = lines.flatMap(new FlatMapFunction<String, String>() {
+      @Override
+      public Iterator<String> call(String x) {
+        return Arrays.asList(x.split(" ")).iterator();
+      }
+    }, Encoders.STRING()).groupBy("value").count();
+
+    // Start running the query that prints the running counts to the console
+    StreamingQuery query = wordCounts.writeStream()
+      .outputMode("complete")
+      .format("console")
+      .start();
+
+    query.awaitTermination();
+  }
+}

examples/src/main/python/sql/streaming/structured_kafka_wordcount.py

+#
+# 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 one or more topics in Kafka and does wordcount.
+ Usage: structured_kafka_wordcount.py <bootstrap-servers> <subscribe-type> <topics>
+   <bootstrap-servers> The Kafka "bootstrap.servers" configuration. A
+   comma-separated list of host:port.
+   <subscribe-type> There are three kinds of type, i.e. 'assign', 'subscribe',
+   'subscribePattern'.
+   |- <assign> Specific TopicPartitions to consume. Json string
+   |  {"topicA":[0,1],"topicB":[2,4]}.
+   |- <subscribe> The topic list to subscribe. A comma-separated list of
+   |  topics.
+   |- <subscribePattern> The pattern used to subscribe to topic(s).
+   |  Java regex string.
+   |- Only one of "assign, "subscribe" or "subscribePattern" options can be
+   |  specified for Kafka source.
+   <topics> Different value format depends on the value of 'subscribe-type'.
+
+ Run the example
+    `$ bin/spark-submit examples/src/main/python/sql/streaming/structured_kafka_wordcount.py \
+    host1:port1,host2:port2 subscribe topic1,topic2`
+"""
+from __future__ import print_function
+
+import sys
+
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import explode
+from pyspark.sql.functions import split
+
+if __name__ == "__main__":
+    if len(sys.argv) != 4:
+        print("""
+        Usage: structured_kafka_wordcount.py <bootstrap-servers> <subscribe-type> <topics>
+        """, file=sys.stderr)
+        exit(-1)
+
+    bootstrapServers = sys.argv[1]
+    subscribeType = sys.argv[2]
+    topics = sys.argv[3]
+
+    spark = SparkSession\
+        .builder\
+        .appName("StructuredKafkaWordCount")\
+        .getOrCreate()
+
+    # Create DataSet representing the stream of input lines from kafka
+    lines = spark\
+        .readStream\
+        .format("kafka")\
+        .option("kafka.bootstrap.servers", bootstrapServers)\
+        .option(subscribeType, topics)\
+        .load()\
+        .selectExpr("CAST(value AS STRING)")
+
+    # Split the lines into words
+    words = lines.select(
+        # explode turns each item in an array into a separate row
+        explode(
+            split(lines.value, ' ')
+        ).alias('word')
+    )
+
+    # Generate running word count
+    wordCounts = words.groupBy('word').count()
+
+    # Start running the query that prints the running counts to the console
+    query = wordCounts\
+        .writeStream\
+        .outputMode('complete')\
+        .format('console')\
+        .start()
+
+    query.awaitTermination()

examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKafkaWordCount.scala

+/*
+ * 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.sql.streaming
+
+import org.apache.spark.sql.SparkSession
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: StructuredKafkaWordCount <bootstrap-servers> <subscribe-type> <topics>
+ *   <bootstrap-servers> The Kafka "bootstrap.servers" configuration. A
+ *   comma-separated list of host:port.
+ *   <subscribe-type> There are three kinds of type, i.e. 'assign', 'subscribe',
+ *   'subscribePattern'.
+ *   |- <assign> Specific TopicPartitions to consume. Json string
+ *   |  {"topicA":[0,1],"topicB":[2,4]}.
+ *   |- <subscribe> The topic list to subscribe. A comma-separated list of
+ *   |  topics.
+ *   |- <subscribePattern> The pattern used to subscribe to topic(s).
+ *   |  Java regex string.
+ *   |- Only one of "assign, "subscribe" or "subscribePattern" options can be
+ *   |  specified for Kafka source.
+ *   <topics> Different value format depends on the value of 'subscribe-type'.
+ *
+ * Example:
+ *    `$ bin/run-example \
+ *      sql.streaming.StructuredKafkaWordCount host1:port1,host2:port2 \
+ *      subscribe topic1,topic2`
+ */
+object StructuredKafkaWordCount {
+  def main(args: Array[String]): Unit = {
+    if (args.length < 3) {
+      System.err.println("Usage: StructuredKafkaWordCount <bootstrap-servers> " +
+        "<subscribe-type> <topics>")
+      System.exit(1)
+    }
+
+    val Array(bootstrapServers, subscribeType, topics) = args
+
+    val spark = SparkSession
+      .builder
+      .appName("StructuredKafkaWordCount")
+      .getOrCreate()
+
+    import spark.implicits._
+
+    // Create DataSet representing the stream of input lines from kafka
+    val lines = spark
+      .readStream
+      .format("kafka")
+      .option("kafka.bootstrap.servers", bootstrapServers)
+      .option(subscribeType, topics)
+      .load()
+      .selectExpr("CAST(value AS STRING)")
+      .as[String]
+
+    // Generate running word count
+    val wordCounts = lines.flatMap(_.split(" ")).groupBy("value").count()
+
+    // Start running the query that prints the running counts to the console
+    val query = wordCounts.writeStream
+      .outputMode("complete")
+      .format("console")
+      .start()
+
+    query.awaitTermination()
+  }
+
+}
+// scalastyle:on println