Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/1434#discussion_r15726533
--- Diff:
extras/kinesis-asl/src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java
---
@@ -0,0 +1,187 @@
+/*
+ * 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.util.ArrayList;
+import java.util.List;
+import java.util.regex.Pattern;
+
+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;
+import com.google.common.collect.Lists;
+
+/**
+ * Java-friendly Kinesis Spark Streaming WordCount example
+ *
+ * See http://spark.apache.org/docs/latest/streaming-kinesis.html for more
details
+ * on the Kinesis Spark Streaming integration.
+ *
+ * This example spins up 1 Kinesis Worker (Spark Streaming Receiver) per
shard
+ * for the given stream.
+ * It then starts pulling from the last checkpointed sequence number of
the given
+ * <stream-name> and <endpoint-url>.
+ *
+ * Valid endpoint urls:
http://docs.aws.amazon.com/general/latest/gr/rande.html#ak_region
+ *
+ * This code uses the DefaultAWSCredentialsProviderChain and searches for
credentials
+ * in the following order of precedence:
+ * 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
+ *
+ * Usage: JavaKinesisWordCountASL <stream-name> <endpoint-url>
+ * <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)
+ *
+ * Example:
+ * $ export AWS_ACCESS_KEY_ID=<your-access-key>
+ * $ export AWS_SECRET_KEY=<your-secret-key>
+ * $ $SPARK_HOME/bin/run-example \
+ * org.apache.spark.examples.streaming.JavaKinesisWordCountASL
mySparkStream \
+ * https://kinesis.us-east-1.amazonaws.com
+ *
+ * There is a companion helper class called KinesisWordCountProducerASL
which puts dummy data
+ * onto the Kinesis stream.
+ * Usage instructions for KinesisWordCountProducerASL are provided in the
class definition.
+ */
+public final class JavaKinesisWordCountASL {
+ private static final Pattern WORD_SEPARATOR = Pattern.compile(" ");
+ private static final Logger logger =
Logger.getLogger(JavaKinesisWordCountASL.class);
+
+ /*
+ * Make the constructor private to enforce singleton
+ */
+ private JavaKinesisWordCountASL() {
+ }
+
+ public static void main(String[] args) {
+ /*
+ * Check that all required args were passed in.
+ */
+ if (args.length < 2) {
+ System.err.println(
+ "|Usage: KinesisWordCount <stream-name> <endpoint-url>\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");
+ System.exit(1);
+ }
+
+ StreamingExamples.setStreamingLogLevels();
+
+ /* Populate the appropriate variables from the given args */
+ String streamName = args[0];
+ String endpointUrl = args[1];
+ /* Set the batch interval to a fixed 2000 millis (2 seconds) */
+ Duration batchInterval = new Duration(2000);
+
+ /* 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);
+
+ /* Determine the number of shards from the stream */
+ int numShards = kinesisClient.describeStream(streamName)
+ .getStreamDescription().getShards().size();
+
+ /* In this example, we're going to create 1 Kinesis
Worker/Receiver/DStream for each shard */
+ int numStreams = numShards;
+
+ /* Must add 1 more thread than the number of receivers or the
output won't show properly from the driver */
+ int numSparkThreads = numStreams + 1;
+
+ /* Setup the Spark config. */
+ SparkConf sparkConfig = new
SparkConf().setAppName("KinesisWordCount").setMaster(
+ "local[" + numSparkThreads + "]");
+
+ /* Kinesis checkpoint interval. Same as batchInterval for this
example. */
+ Duration checkpointInterval = batchInterval;
+
+ /* Setup the StreamingContext */
+ JavaStreamingContext jssc = new JavaStreamingContext(sparkConfig,
batchInterval);
+
+ /* Setup the checkpoint directory used by Spark Streaming */
+ jssc.checkpoint("/tmp/checkpoint");
+
+ /* Create the same number of Kinesis DStreams/Receivers as Kinesis
stream's shards */
+ List<JavaDStream<byte[]>> streamsList = new
ArrayList<JavaDStream<byte[]>>(numStreams);
+ for (int i = 0; i < numStreams; i++) {
+ streamsList.add(
+ KinesisUtils.createStream(jssc, streamName, endpointUrl,
checkpointInterval,
+ InitialPositionInStream.LATEST,
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);
+ }
+
+ /*
+ * Split each line of the union'd DStreams into multiple words
using flatMap to produce the collection.
+ * Convert lines of byte[] to multiple Strings by first converting
to String, then splitting on WORD_SEPARATOR.
+ */
+ JavaDStream<String> words = unionStreams.flatMap(new
FlatMapFunction<byte[], String>() {
+ @Override
+ public Iterable<String> call(byte[] line) {
+ return Lists.newArrayList(WORD_SEPARATOR.split(new
String(line)));
+ }
+ });
+
+ /* Map each word to a (word, 1) tuple, then reduce/aggregate by
key. */
+ 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 by key */
--- End diff --
nit: word counts by key doesnt make sense.
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