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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.flink.streaming.examples.twitter;
import java.util.StringTokenizer;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.json.JSONParseFlatMap;
import org.apache.flink.streaming.connectors.twitter.TwitterSource;
import org.apache.flink.streaming.examples.twitter.util.TwitterStreamData;
import org.apache.flink.util.Collector;
import org.apache.sling.commons.json.JSONException;
/**
* Implements the "TwitterStream" program that computes a most used word occurrence
* histogram over JSON files in a streaming fashion.
*
* <p>
* The input is a JSON text file with lines separated by newline characters.
*
* <p>
* Usage: <code>TwitterStream <text path></code><br>
* If no parameters are provided, the program is run with default data from
* {@link TwitterStreamData}.
*
* <p>
* This example shows how to:
* <ul>
* <li>write a simple Flink Streaming program.
* <li>use Tuple data types.
* <li>write and use user-defined functions.
* </ul>
*
*/
public class TwitterStream {
private static final int PARALLELISM = 1;
// *************************************************************************
// PROGRAM
// *************************************************************************
public static void main(String[] args) throws Exception {
if (!parseParameters(args)) {
return;
}
// set up the execution environment
StreamExecutionEnvironment env = StreamExecutionEnvironment
.createLocalEnvironment(PARALLELISM);
env.setBufferTimeout(1000);
// get input data
DataStream<String> streamSource = getTextDataStream(env);
DataStream<Tuple2<String, Integer>> dataStream = streamSource
// selecting english tweets and split to words
.flatMap(new SelectEnglishAndTokenizeFlatMap())
.partitionBy(0)
// returning (word, 1)
.map(new MapFunction<String, Tuple2<String, Integer>>() {
private static final long serialVersionUID = 1L;
@Override
public Tuple2<String, Integer> map(String value)
throws Exception {
return new Tuple2<String, Integer>(value, 1);
}
})
// group by words and sum their occurence
.groupBy(0)
.sum(1)
// select maximum occurenced word
.flatMap(new SelectMaxOccurence());
// emit result
dataStream.print();
// execute program
env.execute();
}
// *************************************************************************
// USER FUNCTIONS
// *************************************************************************
/**
* Make sentence from english tweets.
*
* Implements the string tokenizer that splits sentences into words as a
* user-defined FlatMapFunction. The function takes a line (String) and
* splits it into multiple pairs in the form of "(word,1)" (Tuple2<String,
* Integer>).
*/
public static class SelectEnglishAndTokenizeFlatMap extends
JSONParseFlatMap<String, String> {
private static final long serialVersionUID = 1L;
/**
* Select the language from the incoming JSON text
*/
@Override
public void flatMap(String value, Collector<String> out)
throws Exception {
try {
if (getString(value, "lang").equals("en")) {
// message of tweet
StringTokenizer tokenizer = new StringTokenizer(getString(
value, "text"));
// split the message
while (tokenizer.hasMoreTokens()) {
String result = tokenizer.nextToken().replaceAll(
"\\s*", "");
if (result != null && !result.equals("")) {
out.collect(result);
}
}
}
} catch (JSONException e) {
}
}
}
/**
*
* Implements a user-defined FlatMapFunction that check if the word's current occurence
* is higher than the maximum occurence. If it is, return with the word and change the maximum.
*
*/
public static class SelectMaxOccurence implements
FlatMapFunction<Tuple2<String, Integer>, Tuple2<String, Integer>> {
private static final long serialVersionUID = 1L;
private Integer maximum;
public SelectMaxOccurence() {
this.maximum = 0;
}
@Override
public void flatMap(Tuple2<String, Integer> value,
Collector<Tuple2<String, Integer>> out) throws Exception {
if ((Integer) value.getField(1) >= maximum) {
out.collect(value);
maximum = (Integer) value.getField(1);
}
}
}
// *************************************************************************
// UTIL METHODS
// *************************************************************************
private static boolean fromFile = false;
private static String path;
private static boolean parseParameters(String[] args) {
if (args.length > 0) {
if (args.length == 1) {
fromFile = true;
path = args[0];
} else {
System.err.println("USAGE:\nTwitterStream <pathToPropertiesFile>");
return false;
}
} else {
System.out.println("Executing TwitterStream example with built-in default data.");
System.out.println(" Provide parameters to read input data from a file.");
System.out.println(" USAGE: TwitterStream <pathToPropertiesFile>");
}
return true;
}
private static DataStream<String> getTextDataStream(
StreamExecutionEnvironment env) {
if (fromFile) {
// read the text file from given input path
return env.addSource(new TwitterSource(path));
} else {
// get default test text data
return env.fromElements(TwitterStreamData.TEXTS);
}
}
}