【极数系列】Flink集成DataSource读取集合数据（07）

01 引言

源码地址,一键下载可用：https://gitee.com/shawsongyue/aurora.git
模块：aurora_flink
主类：FlinkListSourceJob（集合）

02 简介概述

1.Source 是Flink程序从中读取其输入数据的地方。你可以用 StreamExecutionEnvironment.addSource(sourceFunction) 将一个 source 关联到你的程序。2.Flink 自带了许多预先实现的 source functions，不过你仍然可以通过实现 SourceFunction 接口编写自定义的非并行 source。3.也可以通过实现 ParallelSourceFunction 接口或者继承 RichParallelSourceFunction 类编写自定义的并行 sources。

03 基于集合读取数据

3.1 集合创建数据流

fromCollection(Collection)函数
从 Java Java.util.Collection 创建数据流。集合中的所有元素必须属于同一类型

3.2 迭代器创建数据流

fromCollection(Iterator, Class) 
从迭代器创建数据流。class 参数指定迭代器返回元素的数据类型。

3.3 给定对象创建数据流

fromElements(T ...)
从给定的对象序列中创建数据流。所有的对象必须属于同一类型。

3.4 迭代并行器创建数据流

注意！使用迭代器的时候对象必须是实现持久化的，否则报错，详情可以看我的另外一篇文章、

错误：org.apache.flink.api.common.InvalidProgramException: java.util.Arrays$ArrayItr@784c3487 is not serializable

fromParallelCollection(SplittableIterator, Class) 
从迭代器并行创建数据流。class 参数指定迭代器返回元素的数据类型

3.5 基于时间间隔创建数据流

generateSequence 
基于给定间隔内的数字序列并行生成数据流。

3.6 自定义数据流

addSource - 关联一个新的 source function。例如，你可以使用 addSource(new FlinkKafkaConsumer<>(...)) 来从 Apache Kafka 获取数据。更多详细信息见连接器。

04 源码实战demo

4.1 pom.xml依赖

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"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>com.xsy</groupId><artifactId>aurora_flink</artifactId><version>1.0-SNAPSHOT</version><!--属性设置--><properties><!--java_JDK版本--><java.version>11</java.version><!--maven打包插件--><maven.plugin.version>3.8.1</maven.plugin.version><!--编译编码UTF-8--><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><!--输出报告编码UTF-8--><project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding><!--json数据格式处理工具--><fastjson.version>1.2.75</fastjson.version><!--log4j版本--><log4j.version>2.17.1</log4j.version><!--flink版本--><flink.version>1.18.0</flink.version><!--scala版本--><scala.binary.version>2.11</scala.binary.version><!--log4j依赖--><log4j.version>2.17.1</log4j.version></properties><!--通用依赖--><dependencies><!-- json --><dependency><groupId>com.alibaba</groupId><artifactId>fastjson</artifactId><version>${fastjson.version}</version></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-java --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-java</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-scala_2.12</artifactId><version>${flink.version}</version></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-clients --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-clients</artifactId><version>${flink.version}</version></dependency><!--================================集成外部依赖==========================================--><!--集成日志框架 start--><dependency><groupId>org.apache.logging.log4j</groupId><artifactId>log4j-slf4j-impl</artifactId><version>${log4j.version}</version></dependency><dependency><groupId>org.apache.logging.log4j</groupId><artifactId>log4j-api</artifactId><version>${log4j.version}</version></dependency><dependency><groupId>org.apache.logging.log4j</groupId><artifactId>log4j-core</artifactId><version>${log4j.version}</version></dependency><!--集成日志框架 end--></dependencies><!--编译打包--><build><finalName>${project.name}</finalName><!--资源文件打包--><resources><resource><directory>src/main/resources</directory></resource><resource><directory>src/main/java</directory><includes><include>**/*.xml</include></includes></resource></resources><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-shade-plugin</artifactId><version>3.1.1</version><executions><execution><phase>package</phase><goals><goal>shade</goal></goals><configuration><artifactSet><excludes><exclude>org.apache.flink:force-shading</exclude><exclude>org.google.code.flindbugs:jar305</exclude><exclude>org.slf4j:*</exclude><excluder>org.apache.logging.log4j:*</excluder></excludes></artifactSet><filters><filter><artifact>*:*</artifact><excludes><exclude>META-INF/*.SF</exclude><exclude>META-INF/*.DSA</exclude><exclude>META-INF/*.RSA</exclude></excludes></filter></filters><transformers><transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer"><mainClass>org.xsy.sevenhee.flink.TestStreamJob</mainClass></transformer></transformers></configuration></execution></executions></plugin></plugins><!--插件统一管理--><pluginManagement><plugins><!--maven打包插件--><plugin><groupId>org.springframework.boot</groupId><artifactId>spring-boot-maven-plugin</artifactId><version>${spring.boot.version}</version><configuration><fork>true</fork><finalName>${project.build.finalName}</finalName></configuration><executions><execution><goals><goal>repackage</goal></goals></execution></executions></plugin><!--编译打包插件--><plugin><artifactId>maven-compiler-plugin</artifactId><version>${maven.plugin.version}</version><configuration><source>${java.version}</source><target>${java.version}</target><encoding>UTF-8</encoding><compilerArgs><arg>-parameters</arg></compilerArgs></configuration></plugin></plugins></pluginManagement></build><!--配置Maven项目中需要使用的远程仓库--><repositories><repository><id>aliyun-repos</id><url>https://maven.aliyun.com/nexus/content/groups/public/</url><snapshots><enabled>false</enabled></snapshots></repository></repositories><!--用来配置maven插件的远程仓库--><pluginRepositories><pluginRepository><id>aliyun-plugin</id><url>https://maven.aliyun.com/nexus/content/groups/public/</url><snapshots><enabled>false</enabled></snapshots></pluginRepository></pluginRepositories></project>

4.2 创建集合数据流作业

注意：Flink根据集群撇嘴可能会启动多个并行度运行，可能导致数据重复处理，可以通过.setParallelism(1)设置为一个平行度运行即可

package com.aurora.source;import org.apache.flink.api.common.RuntimeExecutionMode;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.util.NumberSequenceIterator;
import org.apache.flink.util.SplittableIterator;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;import javax.sql.DataSource;
import java.util.*;/*** @description flink的list集合source应用* @author 浅夏的猫* @datetime 23:03 2024/1/28
*/
public class FlinkListSourceJob {private static final Logger logger = LoggerFactory.getLogger(FlinkListSourceJob.class);public static void main(String[] args) throws Exception {//1.创建Flink运行环境StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();//2.设置Flink运行模式：//STREAMING-流模式，BATCH-批模式，AUTOMATIC-自动模式(根据数据源的边界性来决定使用哪种模式)env.setRuntimeMode(RuntimeExecutionMode.AUTOMATIC);List<String> list = Arrays.asList("测试", "开发", "运维");// 01 从集合创建数据流DataStreamSource<String> dataStreamSource_01 = env.fromCollection(list);// 02 从迭代器创建数据流,这里直接使用list的迭代器会报错,因为没有ArrayList没有进行持久化,需要深入了解的,可以看我的另外一篇文章
//        DataStreamSource<String> dataStreamSource_02 = env.fromCollection(list.iterator(),String.class);// 03 从给定的对象序列中创建数据流DataStreamSource<String> dataStreamSource_03 = env.fromElements("测试", "开发", "运维");// 04 从迭代器并行创建数据流NumberSequenceIterator splittableIterator = new NumberSequenceIterator(1,10);DataStreamSource dataStreamSource_04=env.fromParallelCollection(splittableIterator,Long.TYPE);// 05 基于给定间隔内的数字序列并行生成数据流DataStreamSource<Long> dataStreamSource_05 = env.generateSequence(1, 10);//自定义数据流DataStreamSource<String> dataStreamSource_06 = env.addSource(new SourceFunction<String>() {@Overridepublic void run(SourceContext<String> sourceContext) throws Exception {//自定义你自己的数据来源for (int i = 0; i < 10; i++) {sourceContext.collect("测试数据" + i);}}@Overridepublic void cancel() {}});//5.输出打印dataStreamSource_01.print();
//        dataStreamSource_02.print();dataStreamSource_03.print();dataStreamSource_04.print();dataStreamSource_05.print();dataStreamSource_06.print();//6.启动运行env.execute();}}

4.3 运行结果日志