flink处理函数--副输出功能

背景

在flink中，如果你想要访问记录的处理时间或者事件时间，注册定时器，或者是将记录输出到多个输出流中，你都需要处理函数的帮助，本文就来通过一个例子来讲解下副输出

副输出

本文还是基于streaming-with-flink这本书的例子作为演示，它实现一个把温度低于32度的记录输出到副输出的功能，正常的记录还是从主输出中输出.代码如下：

package wikiedits.processfunc.job;

import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.OutputTag;

import wikiedits.processfunc.pojo.SensorReading;
import wikiedits.processfunc.process.FreezingMonitor;
import wikiedits.processfunc.source.SensorSource;

public class SideOutPutJob {

    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment see = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<SensorReading> readings = see.addSource(new SensorSource());

        SingleOutputStreamOperator<SensorReading> monitoredReadings = readings.process(new FreezingMonitor());
        // 打印附输出
        monitoredReadings.getSideOutput(new OutputTag<String>("freezing-alarms"){}).print();
        // 打印主输出
        monitoredReadings.print();
        see.execute();
    }
}


package wikiedits.processfunc.process;

import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;

import wikiedits.processfunc.pojo.SensorReading;

public class FreezingMonitor extends ProcessFunction<SensorReading, SensorReading> {

    private OutputTag<String> freezingAlarmOutput = new OutputTag<String>("freezing-alarms") {};


    @Override
    public void processElement(SensorReading value, Context ctx, Collector<SensorReading> out) throws Exception {
        if (value.temperature < 32.0) {
            ctx.output(freezingAlarmOutput, "freezing alarm for " + value.id + " :" + value.temperature);
        }
        out.collect(value);
    }

}
package wikiedits.processfunc.source;

/*
 * Copyright 2015 Fabian Hueske / Vasia Kalavri
 *
 * Licensed 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.
 */
import org.apache.flink.streaming.api.functions.source.RichParallelSourceFunction;
import wikiedits.processfunc.pojo.SensorReading;

import java.util.Calendar;
import java.util.Random;

/**
 * Flink SourceFunction to generate SensorReadings with random temperature values.
 *
 * Each parallel instance of the source simulates 10 sensors which emit one sensor reading every 100 ms.
 *
 * Note: This is a simple data-generating source function that does not checkpoint its state.
 * In case of a failure, the source does not replay any data.
 */
public class SensorSource extends RichParallelSourceFunction<SensorReading> {

    // flag indicating whether source is still running
    private boolean running = true;

    /** run() continuously emits SensorReadings by emitting them through the SourceContext. */
    @Override
    public void run(SourceContext<SensorReading> srcCtx) throws Exception {

        // initialize random number generator
        Random rand = new Random();
        // look up index of this parallel task
        int taskIdx = this.getRuntimeContext().getIndexOfThisSubtask();

        // initialize sensor ids and temperatures
        String[] sensorIds = new String[10];
        double[] curFTemp = new double[10];
        for (int i = 0; i < 10; i++) {
            sensorIds[i] = "sensor_" + (taskIdx * 10 + i);
            curFTemp[i] = 65 + (rand.nextGaussian() * 20);
        }

        while (running) {

            // get current time
            long curTime = Calendar.getInstance().getTimeInMillis();

            // emit SensorReadings
            for (int i = 0; i < 10; i++) {
                // update current temperature
                curFTemp[i] += rand.nextGaussian() * 0.5;
                // emit reading
                srcCtx.collect(new SensorReading(sensorIds[i], curTime, curFTemp[i]));
            }

            // wait for 100 ms
            Thread.sleep(3000);
        }
    }

    /** Cancels this SourceFunction. */
    @Override
    public void cancel() {
        this.running = false;
    }
}

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程序运行结果：