flink设置保存点和恢复保存点

增加了hdfs

package com.qyt;import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;import org.apache.flink.runtime.state.storage.FileSystemCheckpointStorage;import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;import org.apache.flink.streaming.api.environment.CheckpointConfig;import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;/*** DataStreamSource API使用*/
public class StreamWordCount {public static void main(String[] args) throws Exception {//TODO 1、获取流的类final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();System.setProperty("HADOOP_USER_NAME", "root");env.enableCheckpointing(3000);// 配置存储检查点到文件系统env.getCheckpointConfig().setCheckpointStorage(new FileSystemCheckpointStorage("hdfs://hadoop01:9000/flink"));env.getCheckpointConfig().setCheckpointTimeout(2000l);env.getCheckpointConfig().setExternalizedCheckpointCleanup(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);//TODO 2、获取无界流DataStreamSource<String> stringDataStreamSource = env.socketTextStream("192.168.1.10", 9000, "\n");//TODO 3 ETL//TODO 3.1 转换成二元数组,简单ETL的过程SingleOutputStreamOperator<Tuple2<String, Integer>> process = stringDataStreamSource.process(new ProcessFunction<String, Tuple2<String, Integer>>() {@Overridepublic void processElement(String value, ProcessFunction<String, Tuple2<String, Integer>>.Context ctx, Collector<Tuple2<String, Integer>> out) throws Exception {String[] words = value.split(" ");for (String word : words) {Tuple2<String, Integer> tuple2 = Tuple2.of(word, 1);out.collect(tuple2);}}}).uid("etl");//TODO 3.1 分组KeyedStream<Tuple2<String, Integer>, String> tuple2StringKeyedStream = process.keyBy(new KeySelector<Tuple2<String, Integer>, String>() {@Overridepublic String getKey(Tuple2<String, Integer> value) throws Exception {return value.f0;}});//TODO 3.2 聚合计算SingleOutputStreamOperator<Tuple2<String, Integer>> sum = tuple2StringKeyedStream.sum(1);//TODO 4、打印sum.print();//TODO 5、无界流需要这个不断执行的方法env.execute();}
}

要增加hadoop客户端的使用

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xmlns="http://maven.apache.org/POM/4.0.0"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><groupId>org.example</groupId><artifactId>flink-demo</artifactId><version>1.0-SNAPSHOT</version><properties><maven.compiler.source>8</maven.compiler.source><maven.compiler.target>8</maven.compiler.target><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><flink.version>1.17.0</flink.version></properties><dependencies><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-java</artifactId><version>${flink.version}</version><scope>provided</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-clients</artifactId><version>${flink.version}</version><scope>provided</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-kafka</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-client</artifactId><version>3.3.4</version></dependency></dependencies><build><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-shade-plugin</artifactId><version>3.2.4</version><executions><execution><phase>package</phase><goals><goal>shade</goal></goals><configuration><artifactSet><excludes><exclude>com.google.code.findbugs:jsr305</exclude><exclude>org.slf4j:*</exclude><exclude>log4j:*</exclude></excludes></artifactSet><filters><filter><!-- Do not copy the signatures in the META-INF folder.Otherwise, this might cause SecurityExceptions when using the JAR. --><artifact>*:*</artifact><excludes><exclude>META-INF/*.SF</exclude><exclude>META-INF/*.DSA</exclude><exclude>META-INF/*.RSA</exclude></excludes></filter></filters><transformers combine.children="append"><transformerimplementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"></transformer></transformers></configuration></execution></executions></plugin></plugins>
</build>
</project>

提交flink集群

#生成对应的任务
./flink run -m 192.168.1.161:8081 -c com.qyt.StreamWordCount /root/soft/flink-demo-1.0-SNAPSHOT.jar
# 恢复上一次保存点，bc5fae2e282247486003ed259f2f37a7为jobID
./flink run -s hdfs://hadoop01:9000/flink/bc5fae2e282247486003ed259f2f37a7/chk-33 -m 192.168.1.161:8081 -c com.qyt.StreamWordCount /root/soft/flink-demo-1.0-SNAPSHOT.jar

查看对应的jobId