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SPARK-2548 [STREAMING] JavaRecoverableWordCount is missing #2564
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160 changes: 160 additions & 0 deletions
160
...es/src/main/java/org/apache/spark/examples/streaming/JavaRecoverableNetworkWordCount.java
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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. | ||
*/ | ||
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package org.apache.spark.examples.streaming; | ||
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import java.io.File; | ||
import java.io.IOException; | ||
import java.nio.charset.Charset; | ||
import java.util.Arrays; | ||
import java.util.regex.Pattern; | ||
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import scala.Tuple2; | ||
import com.google.common.collect.Lists; | ||
import com.google.common.io.Files; | ||
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import org.apache.spark.SparkConf; | ||
import org.apache.spark.api.java.JavaPairRDD; | ||
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.streaming.Durations; | ||
import org.apache.spark.streaming.Time; | ||
import org.apache.spark.streaming.api.java.JavaDStream; | ||
import org.apache.spark.streaming.api.java.JavaPairDStream; | ||
import org.apache.spark.streaming.api.java.JavaReceiverInputDStream; | ||
import org.apache.spark.streaming.api.java.JavaStreamingContext; | ||
import org.apache.spark.streaming.api.java.JavaStreamingContextFactory; | ||
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/** | ||
* Counts words in text encoded with UTF8 received from the network every second. | ||
* | ||
* Usage: JavaRecoverableNetworkWordCount <hostname> <port> <checkpoint-directory> <output-file> | ||
* <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive | ||
* data. <checkpoint-directory> directory to HDFS-compatible file system which checkpoint data | ||
* <output-file> file to which the word counts will be appended | ||
* | ||
* <checkpoint-directory> and <output-file> must be absolute paths | ||
* | ||
* To run this on your local machine, you need to first run a Netcat server | ||
* | ||
* `$ nc -lk 9999` | ||
* | ||
* and run the example as | ||
* | ||
* `$ ./bin/run-example org.apache.spark.examples.streaming.JavaRecoverableNetworkWordCount \ | ||
* localhost 9999 ~/checkpoint/ ~/out` | ||
* | ||
* If the directory ~/checkpoint/ does not exist (e.g. running for the first time), it will create | ||
* a new StreamingContext (will print "Creating new context" to the console). Otherwise, if | ||
* checkpoint data exists in ~/checkpoint/, then it will create StreamingContext from | ||
* the checkpoint data. | ||
* | ||
* To run this example in a local standalone cluster with automatic driver recovery, | ||
* | ||
* `$ bin/spark-class org.apache.spark.deploy.Client -s launch <cluster-url> \ | ||
* <path-to-examples-jar> \ | ||
* org.apache.spark.examples.streaming.JavaRecoverableNetworkWordCount <cluster-url> \ | ||
* localhost 9999 ~/checkpoint ~/out` | ||
* | ||
* <path-to-examples-jar> would typically be | ||
* <spark-dir>/examples/target/scala-XX/spark-examples....jar | ||
* | ||
* Refer to the online documentation for more details. | ||
*/ | ||
public final class JavaRecoverableNetworkWordCount { | ||
private static final Pattern SPACE = Pattern.compile(" "); | ||
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private static JavaStreamingContext createContext(String ip, int port, String outputPath) { | ||
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// If you do not see this printed, that means the StreamingContext has been loaded | ||
// from the new checkpoint | ||
System.out.println("Creating new context"); | ||
final File outputFile = new File(outputPath); | ||
if (outputFile.exists()) { | ||
outputFile.delete(); | ||
} | ||
SparkConf sparkConf = new SparkConf().setAppName("JavaRecoverableNetworkWordCount"); | ||
// Create the context with a 1 second batch size | ||
JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1)); | ||
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// Create a socket stream on target ip:port and count the | ||
// words in input stream of \n delimited text (eg. generated by 'nc') | ||
JavaReceiverInputDStream<String> lines = ssc.socketTextStream(ip, port); | ||
JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() { | ||
@Override | ||
public Iterable<String> call(String x) { | ||
return Lists.newArrayList(SPACE.split(x)); | ||
} | ||
}); | ||
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; | ||
} | ||
}); | ||
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wordCounts.foreachRDD(new Function2<JavaPairRDD<String, Integer>, Time, Void>() { | ||
@Override | ||
public Void call(JavaPairRDD<String, Integer> rdd, Time time) throws IOException { | ||
String counts = "Counts at time " + time + " " + rdd.collect(); | ||
System.out.println(counts); | ||
System.out.println("Appending to " + outputFile.getAbsolutePath()); | ||
Files.append(counts + "\n", outputFile, Charset.defaultCharset()); | ||
return null; | ||
} | ||
}); | ||
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return ssc; | ||
} | ||
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public static void main(String[] args) { | ||
if (args.length != 4) { | ||
System.err.println("You arguments were " + Arrays.asList(args)); | ||
System.err.println( | ||
"Usage: JavaRecoverableNetworkWordCount <hostname> <port> <checkpoint-directory>\n" + | ||
" <output-file>. <hostname> and <port> describe the TCP server that Spark\n" + | ||
" Streaming would connect to receive data. <checkpoint-directory> directory to\n" + | ||
" HDFS-compatible file system which checkpoint data <output-file> file to which\n" + | ||
" the word counts will be appended\n" + | ||
"\n" + | ||
"In local mode, <master> should be 'local[n]' with n > 1\n" + | ||
"Both <checkpoint-directory> and <output-file> must be absolute paths"); | ||
System.exit(1); | ||
} | ||
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final String ip = args[0]; | ||
final int port = Integer.parseInt(args[1]); | ||
String checkpointDirectory = args[2]; | ||
final String outputPath = args[3]; | ||
JavaStreamingContextFactory factory = new JavaStreamingContextFactory() { | ||
@Override | ||
public JavaStreamingContext create() { | ||
return createContext(ip, port, outputPath); | ||
} | ||
}; | ||
JavaStreamingContext ssc = JavaStreamingContext.getOrCreate(checkpointDirectory, factory); | ||
ssc.start(); | ||
ssc.awaitTermination(); | ||
} | ||
} |
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Can you remove this reference to spark standalone cluster mode? These instructions are old and irrelevant. Please remove from both examples :)