我正在按照Spark 客户接收器提供的 spark 站点中给出的使用客户接收器的 spark 流式传输示例进行操作。
但是，这项工作似乎丢弃了我的大部分数据。无论我流传输的数据量是多少，消费者都会成功接收到它。但是，当我对其进行任何地图/平面地图操作时，我只会看到 10 行数据。无论我传输多少数据，情况总是如此。
我已修改此程序以从ActiveMQ队列中读取。如果我查看 ActiveMQ Web 界面，火花作业成功地使用了我生成的所有数据。但是，每批只处理 10 个数据。我尝试将批量大小更改为各种值，并在本地以及 6 节点 Spark 集群上进行了尝试——到处都是相同的结果。
这真的很令人沮丧，因为我不知道为什么要处理有限数量的数据。我在这里缺少什么吗？
这是我的火花程序。包括自定义接收器。此外，我并没有真正创建任何套接字连接。相反，我为测试目的对消息进行了硬编码。行为与为流创建套接字连接时相同。
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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,
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package com.rzt.main;
import com.google.common.collect.Lists;
import org.apache.spark.SparkConf;
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.storage.StorageLevel;
import org.apache.spark.streaming.Duration;
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.receiver.Receiver;
import scala.Tuple2;
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.ConnectException;
import java.net.Socket;
import java.util.regex.Pattern;
/**
* Custom Receiver that receives data over a socket. Received bytes is
* interpreted as text and \n delimited lines are considered as records. They
* are then counted and printed.
*
* Usage: TestReceiv3 <master> <hostname> <port> <master> is the Spark master
* URL. In local mode, <master> should be 'local[n]' with n > 1. <hostname> and
* <port> of the TCP server that Spark Streaming would connect to receive data.
*
* To run this on your local machine, you need to first run a Netcat server `$
* nc -lk 9999` and then run the example `$ bin/run-example
* org.apache.spark.examples.streaming.TestReceiv3 localhost 9999`
*/
public class TestReceiv3 extends Receiver<String> {
private static final Pattern SPACE = Pattern.compile(" ");
public static void main(String[] args) {
// Create the context with a 1 second batch size
SparkConf sparkConf = new SparkConf().setAppName("TestReceiv3").setMaster("local[4]");
JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, new Duration(1000));
// Create a input stream with the custom receiver on target ip:port and
// count the
// words in input stream of \n delimited text (eg. generated by 'nc')
JavaReceiverInputDStream<String> lines = ssc.receiverStream(new TestReceiv3("TEST", 1));
JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
public Iterable<String> call(String x) {
System.out.println("Message received" + x);
return Lists.newArrayList(x);
}
});
words.print();
ssc.start();
ssc.awaitTermination();
}
// ============= Receiver code that receives data over a socket
// ==============
String host = null;
int port = -1;
public TestReceiv3(String host_, int port_) {
super(StorageLevel.MEMORY_AND_DISK_2());
host = host_;
port = port_;
}
public void onStart() {
// Start the thread that receives data over a connection
new Thread() {
@Override
public void run() {
receive();
}
}.start();
}
public void onStop() {
// There is nothing much to do as the thread calling receive()
// is designed to stop by itself isStopped() returns false
}
/** Create a socket connection and receive data until receiver is stopped */
private void receive() {
Socket socket = null;
String userInput = null;
try {
int i = 0;
// Until stopped or connection broken continue reading
while (true) {
i++;
store("MESSAGE " + i);
if (i == 1000)
break;
}
// Restart in an attempt to connect again when server is active
// again
restart("Trying to connect again");
} catch (Throwable t) {
restart("Error receiving data", t);
}
}
}