大家好，我是考100分的小小码 ，祝大家学习进步，加薪顺利呀。今天说一说flink hadoop3_flink开发环境搭建,希望您对编程的造诣更进一步.
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）HiveCatalog
- 1、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
IDEA2020.2.3版本：https://www.cnblogs.com/liugp/p/13868346.html
最新版本安装详情请参考：https://www.jb51.net/article/196349.htm
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）
当然也可以部署在linux系统上，远程连接，可以参考以下两篇文章：
大数据Hadoop原理介绍+安装+实战操作（HDFS+YARN+MapReduce）
大数据Hadoop之——数据仓库Hive
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&useSSL=false&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%sharehadoopcommonlibguava-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 (
user_id BIGINT,
item_id BIGINT,
category_id BIGINT,
behavior STRING,
ts TIMESTAMP(3)
) WITH (
"connector" = "kafka",
"topic" = "user_behavior",
"properties.bootstrap.servers" = "hadoop-node1:9092",
"properties.group.id" = "testGroup",
"format" = "json",
"json.fail-on-missing-field" = "false",
"json.ignore-parse-errors" = "true"
)")
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&useSSL=false&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&useSSL=false&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>
关于更多大数据的内容，请耐心等待~
原文地址：https://www.cnblogs.com/liugp/archive/2022/05/08/16245546.html
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