package org.apache.flink.streaming.examples.http;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.examples.socket.SocketWindowWordCount.WordWithCount;
import org.apache.flink.util.Collector;
import org.apache.http.HttpException;
import org.apache.http.HttpRequest;
import org.apache.http.HttpResponse;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.bootstrap.HttpServer;
import org.apache.http.impl.bootstrap.ServerBootstrap;
import org.apache.http.protocol.HttpContext;
import org.apache.http.protocol.HttpRequestHandler;
import java.io.IOException;
import java.util.concurrent.TimeUnit;
import static org.apache.flink.util.Preconditions.checkArgument;
import static org.apache.flink.util.Preconditions.checkNotNull;
public class HttpRequestCount {
public static void main(String[] args) throws Exception {
// the host and the port to connect to
final String path;
final int port;
try {
final ParameterTool params = ParameterTool.fromArgs(args);
path = params.has("path") ? params.get("path") : "*";
port = params.getInt("port");
} catch (Exception e) {
System.err.println("No port specified. Please run 'SocketWindowWordCount "
+ "--path <hostname> --port <port>', where path (* by default) "
+ "and port is the address of the text server");
System.err.println("To start a simple text server, run 'netcat -l <port>' and "
+ "type the input text into the command line");
return;
}
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// get input data by connecting to the socket
DataStream<String> text = env.addSource(new OneHourHttpTextStreamFunction(path, port));
// parse the data, group it, window it, and aggregate the counts
DataStream<WordWithCount> windowCounts = text
.flatMap(new FlatMapFunction<String, WordWithCount>() {
@Override
public void flatMap(String value, Collector<WordWithCount> out) {
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
for (String word : value.split("\\s")) {
out.collect(new WordWithCount(word, 1L));
}
}
})
.keyBy("word").timeWindow(Time.seconds(5))
.reduce(new ReduceFunction<WordWithCount>() {
@Override
public WordWithCount reduce(WordWithCount a, WordWithCount b) {
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
return new WordWithCount(a.word, a.count + b.count);
}
});
// print the results with a single thread, rather than in parallel
windowCounts.print().setParallelism(1);
env.execute("Http Request Count");
}
}
class OneHourHttpTextStreamFunction implements SourceFunction<String> {
private static final long serialVersionUID = 1L;
private final String path;
private final int port;
private transient HttpServer server;
public OneHourHttpTextStreamFunction(String path, int port) {
checkArgument(port > 0 && port < 65536, "port is out of range");
this.path = checkNotNull(path, "path must not be null");
this.port = port;
}
@Override
public void run(SourceContext<String> ctx) throws Exception {
server = ServerBootstrap.bootstrap().setListenerPort(port).registerHandler(path, new HttpRequestHandler(){
@Override
public void handle(HttpRequest req, HttpResponse rep, HttpContext context) throws HttpException, IOException {
ctx.collect(req.getRequestLine().getUri());
rep.setStatusCode(200);
rep.setEntity(new StringEntity("OK"));
}
}).create();
server.start();
server.awaitTermination(1, TimeUnit.HOURS);
}
@Override
public void cancel() {
server.stop();
}
}
2条答案
按热度按时间h43kikqp1#
为flink创建一个httpsink连接器有一个openjira票证,但是我没有看到关于创建一个源连接器的讨论。
此外,还不清楚这是个好主意。flink的容错方法需要可以重绕和重放的源,因此它最适合于表现为消息队列的输入源。我建议在分布式日志中缓冲传入的http请求。
例如,看看drivetribe如何在data artisans博客和youtube上使用flink为他们的网站提供动力。
mlmc2os52#
我编写了一个自定义的http源代码。请参考
OneHourHttpTextStreamFunction
. 如果您想运行我的代码,您需要创建一个胖jar来包含apachehttpserver类。留下你的评论,如果你想演示jar。