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大数据Hadoop之——搭建本地flink开发环境详解(window10)_大数据老司机_flink win10

大大的周 7379

文章目录 一、下载安装IDEA二、搭建本地hadoop环境(window10)三、安装Maven四、新建项目和模块1)新建maven项目2)新建flink模块 五、配置IDEA环境(scala)1)下载安装scala插件2)配置scala插件到模块或者全局环境3)创建scala项目4)DataStream API配置1、Maven配置2、示例演示 5)Table API & SQL配置1、Maven配置2、示例演示 6)HiveCatalog1、Maven配置2、Hadoop与Hive Guava冲突问题3、示例演示 7)下载flink并本地启动集群(window)8)完成版配置1、maven配置2、log4j2.xml配置3、hive-site.xml配置 六、配置IDEA环境(java)1)maven配置2)log4j2.xml配置3)hive-site.xml配置

一、下载安装IDEA

可以参考我之前的文章:https://liugp.blog.csdn.net/article/details/123058589

二、搭建本地hadoop环境(window10)

可以看我之前的文章:大数据Hadoop之——部署hadoop+hive环境(window10环境)

三、安装Maven

可以看我之前的文章:Java-Maven详解

四、新建项目和模块 1)新建maven项目

因为之前我创建过了,所以会标红 把自动生成的src删掉,以后是通过模块来管理项目,因为一个项目一般会包含很多模块。

2)新建flink模块

目录结构,新建没有的目录 设置目录属性 因为之前创建过项目,所以这里创建一个新项目来演示:bigdata-test2023

五、配置IDEA环境(scala) 1)下载安装scala插件

File-》Settings

intellij IDEA本来是不能开发Scala程序的,但是通过配置是可以的,我之前已经装过了,没装过的小伙伴,点击这里安装即可。

2)配置scala插件到模块或者全局环境

添加完scala插件之后就可以创建scala项目了

3)创建scala项目

创建Object类

【温馨提示】类只会被编译,不能直接被执行。

4)DataStream API配置 1、Maven配置

在flink模块目录下pom.xml配置如下内容:

【温馨提示】这里的scala版本要与上面插件版本一致

<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- https://mvnrepository.com/artifact/org.apache.flink/flink-streaming-scala --> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency>

【问题】IDEA 在使用Maven项目时,未加载 provided 范围的依赖包,导致启动时报错 【原因】就是 Run Application时,IDEA未加载 provided 范围的依赖包,导致启动时报错,这是IDEA的bug 【解决】在IDEA中设置

2、示例演示

(官网示例)

package com import org.apache.flink.streaming.api.scala._ import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows import org.apache.flink.streaming.api.windowing.time.Time object WindowWordCount { def main(args: Array[String]) { val env = StreamExecutionEnvironment.getExecutionEnvironment val text = env.socketTextStream("localhost", 9999) val counts = text.flatMap { _.toLowerCase.split("\\W+") filter { _.nonEmpty } } .map { (_, 1) } .keyBy(_._1) .window(TumblingProcessingTimeWindows.of(Time.seconds(5))) .sum(1) counts.print() env.execute("Window Stream WordCount") } }

在命令行起一个9999端口的服务

$ nc -lk 9999

运行测试

5)Table API & SQL配置 1、Maven配置 <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-planner_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-common</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> 2、示例演示

这里使用filesystem,不需要引用相应得maven配置,像kafka,ES等连接器是需要引入相应的maven配置,但是这里使用到了format csv,所以得引入相应得配置,配置如下:

更多连接器的介绍,你看官方文档

<!-- format csv 下面会用到--> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-csv</artifactId> <version>1.14.3</version> </dependency>

源码

package com import org.apache.flink.table.api._ object TableSQL { def main(args: Array[String]): Unit = { val settings = EnvironmentSettings.inStreamingMode() val tableEnv = TableEnvironment.create(settings) // create an output Table val schema = Schema.newBuilder() .column("a", DataTypes.STRING()) .column("b", DataTypes.STRING()) .column("c", DataTypes.STRING()) .build() tableEnv.createTemporaryTable("CsvSourceTable", TableDescriptor.forConnector("filesystem") .schema(schema) .option("path", "flink/data/source") .format(FormatDescriptor.forFormat("csv") .option("field-delimiter", "|") .build()) .build()) tableEnv.createTemporaryTable("CsvSinkTable", TableDescriptor.forConnector("filesystem") .schema(schema) .option("path", "flink/data/") .format(FormatDescriptor.forFormat("csv") .option("field-delimiter", "|") .build()) .build()) // 创建一个查询语句 val sourceTable = tableEnv.sqlQuery("SELECT * FROM CsvSourceTable limit 2") // 将查询到的数据转到下游存储 sourceTable.executeInsert("CsvSinkTable") } }

6)HiveCatalog 1、Maven配置 基础配置 <!-- Flink Dependency --> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-connector-hive_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-api-java-bridge_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- Hive Dependency --> <dependency> <groupId>org.apache.hive</groupId> <artifactId>hive-exec</artifactId> <version>3.1.2</version> <scope>provided</scope> </dependency>

【温馨提示】在IDEA中scope设置provided的时候,必须对应的运行文件设置加载provided的依赖到classpath

Log4j2 配置(log4j2.xml) <?xml version="1.0" encoding="UTF-8"?> <Configuration status="WARN"> <Appenders> <Console name="Console" target="SYSTEM_OUT"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> </Console> <RollingFile name="RollingFile" filename="log/test.log" filepattern="${logPath}/%d{YYYYMMddHHmmss}-fargo.log"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> <Policies> <SizeBasedTriggeringPolicy size="10 MB" /> </Policies> <DefaultRolloverStrategy max="20" /> </RollingFile> </Appenders> <Loggers> <Root level="info"> <AppenderRef ref="Console" /> <AppenderRef ref="RollingFile" /> </Root> </Loggers> </Configuration>

配置hive-site.xml <?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <!-- 所连接的 MySQL 数据库的地址,hive_remote2是数据库,程序会自动创建,自定义就行 --> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&amp;useSSL=false&amp;serverTimezone=Asia/Shanghai</value> </property> <!-- MySQL 驱动 --> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> <description>MySQL JDBC driver class</description> </property> <!-- mysql连接用户 --> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>root</value> <description>user name for connecting to mysql server</description> </property> <!-- mysql连接密码 --> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>123456</value> <description>password for connecting to mysql server</description> </property> <property> <name>hive.metastore.uris</name> <value>thrift://localhost:9083</value> <description>IP address (or fully-qualified domain name) and port of the metastore host</description> </property> <!-- host --> <property> <name>hive.server2.thrift.bind.host</name> <value>localhost</value> <description>Bind host on which to run the HiveServer2 Thrift service.</description> </property> <!-- hs2端口 默认是1000,为了区别,我这里不使用默认端口--> <property> <name>hive.server2.thrift.port</name> <value>10001</value> </property> <property> <name>hive.metastore.schema.verification</name> <value>true</value> </property> </configuration>

【温馨提示】必须启动metastore和hiveserver2服务,不清楚的小伙拍可以参考我之前的文章:大数据Hadoop之——部署hadoop+hive环境(window10环境)

$ hive --service metastore $ hive --service hiveserver2 2、Hadoop与Hive Guava冲突问题

【问题】Hadoop和hive-exec-3.1.2的Guava的版本冲突导致Flink任务启动异常 【解决】删掉%HIVE_HOME%\lib目录下的guava-19.0.jar,再把%HADOOP_HOME%\share\hadoop\common\lib\guava-27.0-jre.jar复制到%HIVE_HOME%\lib目录下。

3、示例演示 package com import org.apache.flink.table.api.{EnvironmentSettings, TableEnvironment} import org.apache.flink.table.catalog.hive.HiveCatalog object HiveCatalogTest { def main(args: Array[String]): Unit = { val settings = EnvironmentSettings.inStreamingMode() val tableEnv = TableEnvironment.create(settings) val name = "myhive" val defaultDatabase = "default" val hiveConfDir = "flink/data/" val hive = new HiveCatalog(name, defaultDatabase, hiveConfDir) // 注册catalog,会话结束自动消失 tableEnv.registerCatalog("myhive", hive) // 显示有多少个catalog tableEnv.executeSql("show catalogs").print() // 切换到myhive 的catalog tableEnv.useCatalog("myhive") // 创建库,已经持久化到hive了,会话结束依然存在 tableEnv.executeSql("CREATE DATABASE IF NOT EXISTS mydatabase") // 显示有多少个database tableEnv.executeSql("show databases").print() // 切换数据库 tableEnv.useDatabase("mydatabase") // 切换表 tableEnv.executeSql("CREATE TABLE IF NOT EXISTS user_behavior (\n user_id BIGINT,\n item_id BIGINT,\n category_id BIGINT,\n behavior STRING,\n ts TIMESTAMP(3)\n) WITH (\n 'connector' = 'kafka',\n 'topic' = 'user_behavior',\n 'properties.bootstrap.servers' = 'hadoop-node1:9092',\n 'properties.group.id' = 'testGroup',\n 'format' = 'json',\n 'json.fail-on-missing-field' = 'false',\n 'json.ignore-parse-errors' = 'true'\n)") tableEnv.executeSql("show tables").print() } }

看下面通过hive客户端连接查看上面程序创建的库和表,依然是存在的 从上面验证显示,一切ok,记得开发的时候引入连接器的时候需要引入对应的maven配置

7)下载flink并本地启动集群(window)

下载地址:https://flink.apache.org/downloads.html

flink-1.14.3:https://dlcdn.apache.org/flink/flink-1.14.3/flink-1.14.3-bin-scala_2.12.tgz 【温馨提示】在新版中start-cluster.cmd和flink.cmd已经找不到了,但是可以从以前的版本中复制过来。下载下面的老版本 flink-1.9.1:https://archive.apache.org/dist/flink/flink-1.9.1/flink-1.9.1-bin-scala_2.11.tgz

其实主要从flink-1.9.1中copy以下两个文件到新版本中 下载比较慢,所以我这里还是提供一下这两个文件

flink.cmd ::############################################################################### :: 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, :: 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. ::############################################################################### @echo off setlocal SET bin=%~dp0 SET FLINK_HOME=%bin%.. SET FLINK_LIB_DIR=%FLINK_HOME%\lib SET FLINK_PLUGINS_DIR=%FLINK_HOME%\plugins SET JVM_ARGS=-Xmx512m SET FLINK_JM_CLASSPATH=%FLINK_LIB_DIR%\* java %JVM_ARGS% -cp "%FLINK_JM_CLASSPATH%"; org.apache.flink.client.cli.CliFrontend %* endlocal start-cluster.bat ::############################################################################### :: 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, :: 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. ::############################################################################### @echo off setlocal EnableDelayedExpansion SET bin=%~dp0 SET FLINK_HOME=%bin%.. SET FLINK_LIB_DIR=%FLINK_HOME%\lib SET FLINK_PLUGINS_DIR=%FLINK_HOME%\plugins SET FLINK_CONF_DIR=%FLINK_HOME%\conf SET FLINK_LOG_DIR=%FLINK_HOME%\log SET JVM_ARGS=-Xms1024m -Xmx1024m SET FLINK_CLASSPATH=%FLINK_LIB_DIR%\* SET logname_jm=flink-%username%-jobmanager.log SET logname_tm=flink-%username%-taskmanager.log SET log_jm=%FLINK_LOG_DIR%\%logname_jm% SET log_tm=%FLINK_LOG_DIR%\%logname_tm% SET outname_jm=flink-%username%-jobmanager.out SET outname_tm=flink-%username%-taskmanager.out SET out_jm=%FLINK_LOG_DIR%\%outname_jm% SET out_tm=%FLINK_LOG_DIR%\%outname_tm% SET log_setting_jm=-Dlog.file="%log_jm%" -Dlogback.configurationFile=file:"%FLINK_CONF_DIR%/logback.xml" -Dlog4j.configuration=file:"%FLINK_CONF_DIR%/log4j.properties" SET log_setting_tm=-Dlog.file="%log_tm%" -Dlogback.configurationFile=file:"%FLINK_CONF_DIR%/logback.xml" -Dlog4j.configuration=file:"%FLINK_CONF_DIR%/log4j.properties" :: Log rotation (quick and dirty) CD "%FLINK_LOG_DIR%" for /l %%x in (5, -1, 1) do ( SET /A y = %%x+1 RENAME "%logname_jm%.%%x" "%logname_jm%.!y!" 2> nul RENAME "%logname_tm%.%%x" "%logname_tm%.!y!" 2> nul RENAME "%outname_jm%.%%x" "%outname_jm%.!y!" 2> nul RENAME "%outname_tm%.%%x" "%outname_tm%.!y!" 2> nul ) RENAME "%logname_jm%" "%logname_jm%.0" 2> nul RENAME "%logname_tm%" "%logname_tm%.0" 2> nul RENAME "%outname_jm%" "%outname_jm%.0" 2> nul RENAME "%outname_tm%" "%outname_tm%.0" 2> nul DEL "%logname_jm%.6" 2> nul DEL "%logname_tm%.6" 2> nul DEL "%outname_jm%.6" 2> nul DEL "%outname_tm%.6" 2> nul for %%X in (java.exe) do (set FOUND=%%~$PATH:X) if not defined FOUND ( echo java.exe was not found in PATH variable goto :eof ) echo Starting a local cluster with one JobManager process and one TaskManager process. echo You can terminate the processes via CTRL-C in the spawned shell windows. echo Web interface by default on http://localhost:8081/. start java %JVM_ARGS% %log_setting_jm% -cp "%FLINK_CLASSPATH%"; org.apache.flink.runtime.entrypoint.StandaloneSessionClusterEntrypoint --configDir "%FLINK_CONF_DIR%" > "%out_jm%" 2>&1 start java %JVM_ARGS% %log_setting_tm% -cp "%FLINK_CLASSPATH%"; org.apache.flink.runtime.taskexecutor.TaskManagerRunner --configDir "%FLINK_CONF_DIR%" > "%out_tm%" 2>&1 endlocal

启动flink集群很简单,只要双击start-cluster.bat 通过sql客户端验证一下

$ SELECT 'Hello World';

【错误】NoResourceAvailableException: Could not acquire the minimum required resources 【解决】是因为资源太小,不足以跑任务,扩大配置,修改如下配置:

jobmanager.memory.process.size: 3200m taskmanager.memory.process.size: 2728m taskmanager.memory.flink.size: 2280m

但是我这里调大了还是太小了,自己电脑配置有限,如果有小伙伴的配置高,可以再调大验证一下。

8)完成版配置 1、maven配置 <?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"> <parent> <artifactId>bigdata-test2023</artifactId> <groupId>com.bigdata.test2023</groupId> <version>1.0-SNAPSHOT</version> </parent> <modelVersion>4.0.0</modelVersion> <artifactId>flink</artifactId> <!-- DataStream API maven settings begin --> <dependencies> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.12</artifactId> <version>1.14.3</version> </dependency> <!-- DataStream API maven settings end --> <!-- Table and SQL maven settings begin--> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-planner_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- 上面已经设置过了 --> <!--<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-scala_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency>--> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-common</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-csv</artifactId> <version>1.14.3</version> </dependency> <!-- Table and SQL maven settings end--> <!-- Hive Catalog maven settings begin --> <!-- Flink Dependency --> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-connector-hive_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-api-java-bridge_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- Hive Dependency --> <dependency> <groupId>org.apache.hive</groupId> <artifactId>hive-exec</artifactId> <version>3.1.2</version> <scope>provided</scope> </dependency> <!-- Hive Catalog maven settings end --> <!--hadoop start--> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-core</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-common</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-common</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-jobclient</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <!--hadoop end--> </dependencies> </project> 2、log4j2.xml配置 <?xml version="1.0" encoding="UTF-8"?> <Configuration status="WARN"> <Appenders> <Console name="Console" target="SYSTEM_OUT"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> </Console> <RollingFile name="RollingFile" filename="log/test.log" filepattern="${logPath}/%d{YYYYMMddHHmmss}-fargo.log"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> <Policies> <SizeBasedTriggeringPolicy size="10 MB" /> </Policies> <DefaultRolloverStrategy max="20" /> </RollingFile> </Appenders> <Loggers> <Root level="info"> <AppenderRef ref="Console" /> <AppenderRef ref="RollingFile" /> </Root> </Loggers> </Configuration> 3、hive-site.xml配置 <?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <!-- 所连接的 MySQL 数据库的地址,hive_remote2是数据库,程序会自动创建,自定义就行 --> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&amp;useSSL=false&amp;serverTimezone=Asia/Shanghai</value> </property> <!-- MySQL 驱动 --> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> <description>MySQL JDBC driver class</description> </property> <!-- mysql连接用户 --> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>root</value> <description>user name for connecting to mysql server</description> </property> <!-- mysql连接密码 --> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>123456</value> <description>password for connecting to mysql server</description> </property> <property> <name>hive.metastore.uris</name> <value>thrift://localhost:9083</value> <description>IP address (or fully-qualified domain name) and port of the metastore host</description> </property> <!-- host --> <property> <name>hive.server2.thrift.bind.host</name> <value>localhost</value> <description>Bind host on which to run the HiveServer2 Thrift service.</description> </property> <!-- hs2端口 默认是1000,为了区别,我这里不使用默认端口--> <property> <name>hive.server2.thrift.port</name> <value>10001</value> </property> <property> <name>hive.metastore.schema.verification</name> <value>true</value> </property> </configuration> 六、配置IDEA环境(java) 1)maven配置 <?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"> <parent> <artifactId>bigdata-test2023</artifactId> <groupId>com.bigdata.test2023</groupId> <version>1.0-SNAPSHOT</version> </parent> <modelVersion>4.0.0</modelVersion> <artifactId>flink</artifactId> <!-- DataStream API maven settings begin --> <dependencies> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-java</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-clients_2.12</artifactId> <version>1.14.3</version> </dependency> <!-- DataStream API maven settings end --> <!-- Table and SQL maven settings begin--> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-planner_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- 上面已经设置过了 --> <!--<dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-streaming-java_2.12</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency>--> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-common</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-csv</artifactId> <version>1.14.3</version> </dependency> <!-- Table and SQL maven settings end--> <!-- Hive Catalog maven settings begin --> <!-- Flink Dependency --> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-connector-hive_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-api-java-bridge_2.11</artifactId> <version>1.14.3</version> <scope>provided</scope> </dependency> <!-- Hive Dependency --> <dependency> <groupId>org.apache.hive</groupId> <artifactId>hive-exec</artifactId> <version>3.1.2</version> <scope>provided</scope> </dependency> <!-- Hive Catalog maven settings end --> <!--hadoop start--> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-core</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-common</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-common</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-mapreduce-client-jobclient</artifactId> <version>3.3.1</version> <scope>provided</scope> </dependency> <!--hadoop end--> </dependencies> </project>

【温馨提示】其实log4j2.xml和hive-site.xml不区分java和scala的,为了方便这里还是再复制一份。

2)log4j2.xml配置 <?xml version="1.0" encoding="UTF-8"?> <Configuration status="WARN"> <Appenders> <Console name="Console" target="SYSTEM_OUT"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> </Console> <RollingFile name="RollingFile" filename="log/test.log" filepattern="${logPath}/%d{YYYYMMddHHmmss}-fargo.log"> <PatternLayout pattern="%d{YYYY-MM-dd HH:mm:ss} [%t] %-5p %c{1}:%L - %msg%n" /> <Policies> <SizeBasedTriggeringPolicy size="10 MB" /> </Policies> <DefaultRolloverStrategy max="20" /> </RollingFile> </Appenders> <Loggers> <Root level="info"> <AppenderRef ref="Console" /> <AppenderRef ref="RollingFile" /> </Root> </Loggers> </Configuration> 3)hive-site.xml配置 <?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <!-- 所连接的 MySQL 数据库的地址,hive_remote2是数据库,程序会自动创建,自定义就行 --> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&amp;useSSL=false&amp;serverTimezone=Asia/Shanghai</value> </property> <!-- MySQL 驱动 --> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> <description>MySQL JDBC driver class</description> </property> <!-- mysql连接用户 --> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>root</value> <description>user name for connecting to mysql server</description> </property> <!-- mysql连接密码 --> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>123456</value> <description>password for connecting to mysql server</description> </property> <property> <name>hive.metastore.uris</name> <value>thrift://localhost:9083</value> <description>IP address (or fully-qualified domain name) and port of the metastore host</description> </property> <!-- host --> <property> <name>hive.server2.thrift.bind.host</name> <value>localhost</value> <description>Bind host on which to run the HiveServer2 Thrift service.</description> </property> <!-- hs2端口 默认是1000,为了区别,我这里不使用默认端口--> <property> <name>hive.server2.thrift.port</name> <value>10001</value> </property> <property> <name>hive.metastore.schema.verification</name> <value>true</value> </property> </configuration>

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