【flink番外篇】12、ParameterTool使用示例

---

文章目录

• Flink 系列文章
• 一、示例：ParameterTool几种的应用示例

• 1、maven依赖
• 2、实现及验证

• 1）、测试文件准备
• 2）、实现

---

本文介绍了ParameterTool 的获取以及在应用程序中的使用方式。

本文除了maven依赖外，没有其他依赖。

一、示例：ParameterTool几种的应用示例

本示例是演示ParameterTool的几种用法。

1、maven依赖

<properties>
	<encoding>UTF-8</encoding>
	<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
	<maven.compiler.source>1.8</maven.compiler.source>
	<maven.compiler.target>1.8</maven.compiler.target>
	<java.version>1.8</java.version>
	<scala.version>2.12</scala.version>
	<flink.version>1.17.0</flink.version>
</properties>

<dependencies>
	<!-- https://mvnrepository.com/artifact/org.apache.flink/flink-clients -->
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-clients</artifactId>
		<version>${flink.version}</version>
		<scope>provided</scope>
	</dependency>
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-java</artifactId>
		<version>${flink.version}</version>
		<scope>provided</scope>
	</dependency>
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-table-common</artifactId>
		<version>${flink.version}</version>
		<scope>provided</scope>
	</dependency>
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-streaming-java</artifactId>
		<version>${flink.version}</version>
		<!-- <scope>provided</scope> -->
	</dependency>
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-csv</artifactId>
		<version>${flink.version}</version>
		<scope>provided</scope>
	</dependency>
	<dependency>
		<groupId>org.apache.flink</groupId>
		<artifactId>flink-json</artifactId>
		<version>${flink.version}</version>
		<scope>provided</scope>
	</dependency>
</dependencies>

2、实现及验证

本处是通过ParameterTool读取配置文件的内容，其他命令行、系统参数可以在运行时直接设置，没有进行截图。

1）、测试文件准备

文件目录及名称：tablesql/src/main/resources/testproperties.properties

jobmanager.rpc.address=server1
jobmanager.rpc.port=6123
jobmanager.memory.process.size=1600m
taskmanager.memory.process.size=4096m
taskmanager.numberOfTaskSlots=3
parallelism.default=1

high-availability=zookeeper
high-availability.storageDir=hdfs://HadoopHAcluster/flink13_5/ha/
high-availability.zookeeper.quorum=server1:2118,server2:2118,server3:2118

##单位毫秒，checkpoint时间间隔
execution.checkpointing.interval=5000
##单位个，保存checkpoint的个数
state.checkpoints.num-retained=20

execution.checkpointing.mode=EXACTLY_ONCE
execution.checkpointing.externalized-checkpoint-retention=RETAIN_ON_CANCELLATION

state.savepoints.dir=hdfs:///flink/checkpoints
execution.checkpointing.timeout=600000
execution.checkpointing.min-pause=500
execution.checkpointing.max-concurrent-checkpoints=1

state.backend=filesystem
#state.checkpoints.dir=hdfs://server1:8020/flink13_5-checkpoints
state.checkpoints.dir=hdfs://HadoopHAcluster/flink13_5-checkpoints
jobmanager.execution.failover-strategy=region

web.submit.enable=true


jobmanager.archive.fs.dir=hdfs://HadoopHAcluster/flink13_5/completed-jobs/
historyserver.web.address=server1
historyserver.web.port=9082
#historyserver.archive.fs.dir=hdfs://server1:8020/flink13_5/completed-jobs/
historyserver.archive.fs.dir=hdfs://HadoopHAcluster/flink13_5/completed-jobs/

historyserver.archive.fs.refresh-interval=10000

2）、实现

/*
 * @Author: alanchan
 * @LastEditors: alanchan
 * @Description: 
 */
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.Map;

import org.apache.flink.api.common.functions.RichMapFunction;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

public class TestParameterToolDemo {

    static void test1() throws Exception {
        String propertiesFilePath = "tablesql/src/main/resources/testproperties.properties";

        // 方式一：直接通过配置文件的路径获取
        ParameterTool parameter = ParameterTool.fromPropertiesFile(propertiesFilePath);

        // 方式二：通过配置文件路径构造File的方式获取
        File propertiesFile = new File(propertiesFilePath);
        ParameterTool parameter2 = ParameterTool.fromPropertiesFile(propertiesFile);

        // 方式三：通过配置文件路径构造InputStream的方式获取
        InputStream propertiesFileInputStream = new FileInputStream(propertiesFilePath);
        ParameterTool parameter3 = ParameterTool.fromPropertiesFile(propertiesFileInputStream);

        // 遍历配置文件内容
        Map<String, String> parameterMap = parameter.toMap();
        for (String key : parameterMap.keySet()) {
            System.out.println("parameter :" + key + " = " + parameterMap.get(key));
        }

        // 获取必须的参数，否则会出现异常
        System.out.println("jobmanager.rpc.address--->" + parameter.getRequired("jobmanager.rpc.address"));
        // 获取参数，并设有默认值
        System.out.println("state.checkpoints.num-retained--->" + parameter.get("state.checkpoints.num-retained", "30"));
        // 获取Long类型的参数，并设置默认值
        System.out.println("parallelism.default--->" + parameter.getLong("parallelism.default", 4L));
        // 获取配置文件中有效参数的总行数
        System.out.println("getNumberOfParameters--->" + parameter.getNumberOfParameters());

        // 运行输出：
        // parameter :historyserver.web.address = server1
        // parameter :state.checkpoints.num-retained = 20
        // parameter :historyserver.web.port = 9082
        // parameter :jobmanager.execution.failover-strategy = region
        // parameter :jobmanager.rpc.address = server1
        // parameter :state.savepoints.dir = hdfs:///flink/checkpoints
        // parameter :high-availability.storageDir =
        // hdfs://HadoopHAcluster/flink13_5/ha/
        // parameter :parallelism.default = 1
        // parameter :taskmanager.numberOfTaskSlots = 3
        // parameter :historyserver.archive.fs.dir =
        // hdfs://HadoopHAcluster/flink13_5/completed-jobs/
        // parameter :jobmanager.archive.fs.dir =
        // hdfs://HadoopHAcluster/flink13_5/completed-jobs/
        // parameter :execution.checkpointing.mode = EXACTLY_ONCE
        // parameter :taskmanager.memory.process.size = 4096m
        // parameter :jobmanager.memory.process.size = 1600m
        // parameter :historyserver.archive.fs.refresh-interval = 10000
        // parameter :jobmanager.rpc.port = 6123
        // parameter :execution.checkpointing.timeout = 600000
        // parameter :execution.checkpointing.interval = 5000
        // parameter :high-availability.zookeeper.quorum =
        // server1:2118,server2:2118,server3:2118
        // parameter :high-availability = zookeeper
        // parameter :execution.checkpointing.externalized-checkpoint-retention =
        // RETAIN_ON_CANCELLATION
        // parameter :web.submit.enable = true
        // parameter :state.backend = filesystem
        // parameter :execution.checkpointing.min-pause = 500
        // parameter :execution.checkpointing.max-concurrent-checkpoints = 1
        // parameter :state.checkpoints.dir =
        // hdfs://HadoopHAcluster/flink13_5-checkpoints
        // jobmanager.rpc.address--->server1
        // state.checkpoints.num-retained--->20
        // parallelism.default--->1
        // getNumberOfParameters--->26
    }

    static void test2() throws Exception {
        ParameterTool parameter = ParameterTool.fromSystemProperties();
        // 遍历配置系统属性内容
        Map<String, String> parameterMap = parameter.toMap();
        for (String key : parameterMap.keySet()) {
            System.out.println("parameter :" + key + " = " + parameterMap.get(key));
        }
    }

    static void test3(String[] args) throws Exception {
        ParameterTool parameter = ParameterTool.fromArgs(args);
        // 遍历配配置值来自命令行内容
        Map<String, String> parameterMap = parameter.toMap();
        for (String key : parameterMap.keySet()) {
            System.out.println("parameter :" + key + " = " + parameterMap.get(key));
        }
    }

    static void test4(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        ParameterTool parameters = ParameterTool.fromArgs(args);

        // 遍历配配置值来自命令行内容
        Map<String, String> parameterMap = parameters.toMap();
        for (String key : parameterMap.keySet()) {
            System.out.println("parameter :" + key + " = " + parameterMap.get(key));
        }

        // 获取命令行参数mapParallelism的值（默认设置为2）并设置map的并行度
        int parallelism = parameters.getInt("mapParallelism", 2);

        DataStream<String> source = env.socketTextStream("192.168.10.42", 8888)
                .map(o -> {
                    String[] lines = o.split(",");
                    return "name:" + lines[0] + " age: " + lines[1];
                }).setParallelism(parallelism);

        source.print();

        env.execute();
    }

    // 注册全局参数
    static void test5(String[] args) throws Exception {
        ParameterTool parameters = ParameterTool.fromArgs(args);

        // 遍历配配置值来自命令行内容
        Map<String, String> parameterMap = parameters.toMap();
        for (String key : parameterMap.keySet()) {
            System.out.println("parameter :" + key + " = " + parameterMap.get(key));
        }
        // set up the execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.getConfig().setGlobalJobParameters(parameters);

        DataStream<String> source = env.socketTextStream("192.168.10.42", 8888)
                .map(new RichMapFunction<String, String>() {

                    @Override
                    public String map(String value) throws Exception {
                        ParameterTool parameters = (ParameterTool) getRuntimeContext().getExecutionConfig()
                                .getGlobalJobParameters();
                        // 获取命令行中的 prefix 参数值
                        String prefix = parameters.getRequired("prefix");

                        String[] lines = value.split(",");
                        // 将prefix加在name的前面进行拼接
                        return "name:" + prefix + "_" + lines[0] + " age: " + lines[1];
                    }

                });

        source.print();

        env.execute();
    }

    public static void main(String[] args) throws Exception {
        test2();
    }
}

以上，本文介绍了ParameterTool 的获取以及在应用程序中的使用方式。