Java TwitterSource类代码示例

import org.apache.flink.streaming.connectors.twitter.TwitterSource; //导入依赖的package包/类
public static void main(String[] args) throws Exception {
    // set up the execution environment
    final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

    Properties props = new Properties();
    props.setProperty(TwitterSource.CONSUMER_KEY, "...");
    props.setProperty(TwitterSource.CONSUMER_SECRET, "...");
    props.setProperty(TwitterSource.TOKEN, "...");
    props.setProperty(TwitterSource.TOKEN_SECRET, "...");

    env.addSource(new TwitterSource(props))
        .flatMap(new ExtractHashTags())
        .keyBy(0)
        .timeWindow(Time.seconds(30))
        .sum(1)
        .filter(new FilterHashTags())
        .timeWindowAll(Time.seconds(30))
        .apply(new GetTopHashTag())
        .print();

    env.execute();
}
 

import org.apache.flink.streaming.connectors.twitter.TwitterSource; //导入依赖的package包/类
public static void main(String args[]) throws Exception {
    ParameterTool tool = ParameterTool.fromArgs(args);

    Properties p = new Properties();
    p.setProperty(TwitterSource.CONSUMER_KEY, tool.getRequired("consumer.key"));
    p.setProperty(TwitterSource.CONSUMER_SECRET, tool.getRequired("consumer.secret"));
    p.setProperty(TwitterSource.TOKEN, tool.getRequired("token"));
    p.setProperty(TwitterSource.TOKEN_SECRET, tool.getRequired("token.secret"));

    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);

    DataStream<String> streamSource = env.addSource(new TwitterSource(p));

    // Every 10 minutes, most trending of last 1 hour of tweets.
    SlidingEventTimeWindows windowSpec = SlidingEventTimeWindows.of(Time.hours(1), Time.minutes(10));

    streamSource.flatMap(hashTagExtraction())
            .keyBy(0)
            .sum(1)
            .windowAll(windowSpec)
            .maxBy(1)
            .writeAsText("file:///Users/abij/projects/tryouts/flink-streaming-xke/hot-hashtags.log", OVERWRITE);

    env.execute("Twitter Stream");
}
 

import org.apache.flink.streaming.connectors.twitter.TwitterSource; //导入依赖的package包/类
public static void main(String[] args) throws Exception {
	// set up the streaming execution environment
	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

	ParameterTool params = ParameterTool.fromPropertiesFile(args[0]);
	DataStream<String> twitterStreamString = env.addSource(new TwitterSource(params.getProperties()));
	DataStream<String> filteredStream = twitterStreamString.flatMap(new ParseJson());
	filteredStream.flatMap(new ThroughputLogger(5000L)).setParallelism(1);

	filteredStream.addSink(new FlinkKafkaProducer09<>("twitter", new SimpleStringSchema(), params.getProperties()));

	// execute program
	env.execute("Ingest data from Twitter to Kafka");
}
 

import org.apache.flink.streaming.connectors.twitter.TwitterSource; //导入依赖的package包/类
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);
	}
}
 

import org.apache.flink.streaming.connectors.twitter.TwitterSource; //导入依赖的package包/类
public static void main(String[] args) throws Exception {

		// Checking input parameters
		final ParameterTool params = ParameterTool.fromArgs(args);
		System.out.println("Usage: TwitterExample [--output <path>] " +
				"[--twitter-source.consumerKey <key> --twitter-source.consumerSecret <secret> --twitter-source.token <token> --twitter-source.tokenSecret <tokenSecret>]");

		// set up the execution environment
		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

		// make parameters available in the web interface
		env.getConfig().setGlobalJobParameters(params);

		env.setParallelism(params.getInt("parallelism", 1));

		// get input data
		DataStream<String> streamSource;
		if (params.has(TwitterSource.CONSUMER_KEY) &&
				params.has(TwitterSource.CONSUMER_SECRET) &&
				params.has(TwitterSource.TOKEN) &&
				params.has(TwitterSource.TOKEN_SECRET)
				) {
			streamSource = env.addSource(new TwitterSource(params.getProperties()));
		} else {
			System.out.println("Executing TwitterStream example with default props.");
			System.out.println("Use --twitter-source.consumerKey <key> --twitter-source.consumerSecret <secret> " +
					"--twitter-source.token <token> --twitter-source.tokenSecret <tokenSecret> specify the authentication info.");
			// get default test text data
			streamSource = env.fromElements(TwitterExampleData.TEXTS);
		}

		DataStream<Tuple2<String, Integer>> tweets = streamSource
				// selecting English tweets and splitting to (word, 1)
				.flatMap(new SelectEnglishAndTokenizeFlatMap())
				// group by words and sum their occurrences
				.keyBy(0).sum(1);

		// emit result
		if (params.has("output")) {
			tweets.writeAsText(params.get("output"));
		} else {
			System.out.println("Printing result to stdout. Use --output to specify output path.");
			tweets.print();
		}

		// execute program
		env.execute("Twitter Streaming Example");
	}