flink一定要和hadoop flink hadoop 詳情 - flink一定要和hadoop,大數據,hadoop,flink,Hadoop,大數據 mob64ca1404ed65 博客

文章目錄

一、下載安裝IDEA

二、搭建本地hadoop環境（window10）

三、安裝Maven

四、新建項目和模塊

1）新建maven項目

2）新建flink模塊

五、配置IDEA環境（scala）

1）下載安裝scala插件

2）配置scala插件到模塊或者全局環境

3）創建scala項目

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與Hive Guava衝突問題

3、示例演示

7）下載flink並本地啓動集羣（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環境（java）

1）maven配置

2）log4j2.xml配置

3）hive-site.xml配置

一、下載安裝IDEA

二、搭建本地hadoop環境（window10）

可以看我之前的文章：大數據Hadoop之——部署hadoop+hive環境（window10環境）

三、安裝Maven

可以看我之前的文章：Java-Maven詳解

四、新建項目和模塊

flink一定要和hadoop flink hadoop_hadoop

因為之前我創建過了，所以會標紅

flink一定要和hadoop flink hadoop_flink一定要和hadoop_02

把自動生成的src刪掉，以後是通過模塊來管理項目，因為一個項目一般會包含很多模塊。

2）新建flink模塊

flink一定要和hadoop flink hadoop_flink一定要和hadoop_03

flink一定要和hadoop flink hadoop_flink一定要和hadoop_04

flink一定要和hadoop flink hadoop_flink_05

設置目錄屬性

flink一定要和hadoop flink hadoop_大數據_06

因為之前創建過項目，所以這裏創建一個新項目來演示：bigdata-test2023

flink一定要和hadoop flink hadoop_hadoop_07

五、配置IDEA環境（scala）

1）下載安裝scala插件

File-》Settings

intellij IDEA本來是不能開發Scala程序的,但是通過配置是可以的，我之前已經裝過了，沒裝過的小夥伴，點擊這裏安裝即可。

flink一定要和hadoop flink hadoop_flink_08

2）配置scala插件到模塊或者全局環境

flink一定要和hadoop flink hadoop_flink一定要和hadoop_09

flink一定要和hadoop flink hadoop_flink_10

flink一定要和hadoop flink hadoop_hadoop_11

flink一定要和hadoop flink hadoop_flink_12

添加完scala插件之後就可以創建scala項目了

3）創建scala項目

flink一定要和hadoop flink hadoop_flink_13

創建Object類

flink一定要和hadoop flink hadoop_大數據_14

flink一定要和hadoop flink hadoop_hadoop_15

【温馨提示】類只會被編譯，不能直接被執行。

4）DataStream API配置

1、Maven配置

在flink模塊目錄下pom.xml配置如下內容：

【温馨提示】這裏的scala版本要與上面插件版本一致

<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>
AI寫代碼
xml

【問題】IDEA 在使用Maven項目時，未加載 provided 範圍的依賴包，導致啓動時報錯

【原因】就是 Run Application時，IDEA未加載 provided 範圍的依賴包，導致啓動時報錯，這是IDEA的bug

【解決】在IDEA中設置

flink一定要和hadoop flink hadoop_flink_16

flink一定要和hadoop flink hadoop_flink一定要和hadoop_17

2、示例演示

（官網示例）

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")
  }
}

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java

運行

在命令行起一個9999端口的服務

$ nc -lk 9999
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bash
1

flink一定要和hadoop flink hadoop_flink_18

運行測試

flink一定要和hadoop flink hadoop_大數據_19

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>
AI寫代碼
xml

2、示例演示

這裏使用filesystem，不需要引用相應得maven配置，像kafka，ES等連接器是需要引入相應的maven配置，但是這裏使用到了format csv，所以得引入相應得配置，配置如下：

更多連接器的介紹，你看官方文檔

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

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xml

源碼

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())

    // 創建一個查詢語句
    val sourceTable = tableEnv.sqlQuery("SELECT * FROM CsvSourceTable limit 2")

    // 將查詢到的數據轉到下游存儲
    sourceTable.executeInsert("CsvSinkTable")
  }
}

AI寫代碼bash

flink一定要和hadoop flink hadoop_flink_20

6）HiveCatalog

1、Maven配置

基礎配置

<!-- 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>
AI寫代碼
xml

【温馨提示】在IDEA中scope設置provided的時候，必須對應的運行文件設置加載provided的依賴到classpath

flink一定要和hadoop flink hadoop_flink一定要和hadoop_21

flink一定要和hadoop flink hadoop_flink_22

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>

flink一定要和hadoop flink hadoop_hadoop_23

配置hive-site.xml

配置hive-site.xml
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>

    <!-- 所連接的 MySQL 數據庫的地址，hive_remote2是數據庫，程序會自動創建，自定義就行 -->
    <property>
        <name>javax.jdo.option.ConnectionURL</name>
        <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&useSSL=false&serverTimezone=Asia/Shanghai</value>
    </property>

    <!-- MySQL 驅動 -->
    <property>
        <name>javax.jdo.option.ConnectionDriverName</name>
        <value>com.mysql.jdbc.Driver</value>
        <description>MySQL JDBC driver class</description>
    </property>

    <!-- mysql連接用户 -->
    <property>
        <name>javax.jdo.option.ConnectionUserName</name>
        <value>root</value>
        <description>user name for connecting to mysql server</description>
    </property>

    <!-- mysql連接密碼 -->
    <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 默認是1000，為了區別，我這裏不使用默認端口-->
    <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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【温馨提示】必須啓動metastore和hiveserver2服務，不清楚的小夥拍可以參考我之前的文章：大數據Hadoop之——部署hadoop+hive環境（window10環境）

$ hive --service metastore
$ hive --service hiveserver2
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bash
1
2

2、Hadoop與Hive Guava衝突問題

【問題】Hadoop和hive-exec-3.1.2的Guava的版本衝突導致Flink任務啓動異常

【解決】刪掉%HIVE_HOME%\lib目錄下的guava-19.0.jar，再把%HADOOP_HOME%\share\hadoop\common\lib\guava-27.0-jre.jar複製到%HIVE_HOME%\lib目錄下。

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)
    // 註冊catalog，會話結束自動消失
    tableEnv.registerCatalog("myhive", hive)
    // 顯示有多少個catalog
    tableEnv.executeSql("show catalogs").print()
    // 切換到myhive 的catalog
    tableEnv.useCatalog("myhive")
    // 創建庫，已經持久化到hive了，會話結束依然存在
    tableEnv.executeSql("CREATE DATABASE IF NOT EXISTS mydatabase")
    // 顯示有多少個database
    tableEnv.executeSql("show databases").print()
    // 切換數據庫
    tableEnv.useDatabase("mydatabase")
    // 切換表
    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()

  }
}

flink一定要和hadoop flink hadoop_flink一定要和hadoop_24

看下面通過hive客户端連接查看上面程序創建的庫和表，依然是存在的

flink一定要和hadoop flink hadoop_hadoop_25

從上面驗證顯示，一切ok，記得開發的時候引入連接器的時候需要引入對應的maven配置

7）下載flink並本地啓動集羣（window）

下載地址：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已經找不到了，但是可以從以前的版本中複製過來。下載下面的老版本

flink-1.9.1：https://archive.apache.org/dist/flink/flink-1.9.1/flink-1.9.1-bin-scala_2.11.tgz

其實主要從flink-1.9.1中copy以下兩個文件到新版本中

flink一定要和hadoop flink hadoop_flink_26

下載比較慢，所以我這裏還是提供一下這兩個文件

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

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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

啓動flink集羣很簡單，只要雙擊start-cluster.bat

flink一定要和hadoop flink hadoop_hadoop_27

通過sql客户端驗證一下

$ SELECT 'Hello World';

AI寫代碼

bash

【錯誤】NoResourceAvailableException: Could not acquire the minimum required resources

【解決】是因為資源太小，不足以跑任務，擴大配置，修改如下配置：

jobmanager.memory.process.size: 3200m

taskmanager.memory.process.size: 2728m

taskmanager.memory.flink.size: 2280m

flink一定要和hadoop flink hadoop_flink_28

但是我這裏調大了還是太小了，自己電腦配置有限，如果有小夥伴的配置高，可以再調大驗證一下。

flink一定要和hadoop flink hadoop_flink一定要和hadoop_29

flink一定要和hadoop flink hadoop_flink_30

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>
        <!-- 上面已經設置過了 -->
        <!--<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>

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xml

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>

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xml

3、hive-site.xml配置

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>

    <!-- 所連接的 MySQL 數據庫的地址，hive_remote2是數據庫，程序會自動創建，自定義就行 -->
    <property>
        <name>javax.jdo.option.ConnectionURL</name>
        <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&useSSL=false&serverTimezone=Asia/Shanghai</value>
    </property>

    <!-- MySQL 驅動 -->
    <property>
        <name>javax.jdo.option.ConnectionDriverName</name>
        <value>com.mysql.jdbc.Driver</value>
        <description>MySQL JDBC driver class</description>
    </property>

    <!-- mysql連接用户 -->
    <property>
        <name>javax.jdo.option.ConnectionUserName</name>
        <value>root</value>
        <description>user name for connecting to mysql server</description>
    </property>

    <!-- mysql連接密碼 -->
    <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 默認是1000，為了區別，我這裏不使用默認端口-->
    <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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xml

六、配置IDEA環境（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>
        <!-- 上面已經設置過了 -->
        <!--<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>

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【温馨提示】其實log4j2.xml和hive-site.xml不區分java和scala的，為了方便這裏還是再複製一份。

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>
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xml

3）hive-site.xml配置

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>

    <!-- 所連接的 MySQL 數據庫的地址，hive_remote2是數據庫，程序會自動創建，自定義就行 -->
    <property>
        <name>javax.jdo.option.ConnectionURL</name>
        <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&useSSL=false&serverTimezone=Asia/Shanghai</value>
    </property>

    <!-- MySQL 驅動 -->
    <property>
        <name>javax.jdo.option.ConnectionDriverName</name>
        <value>com.mysql.jdbc.Driver</value>
        <description>MySQL JDBC driver class</description>
    </property>

    <!-- mysql連接用户 -->
    <property>
        <name>javax.jdo.option.ConnectionUserName</name>
        <value>root</value>
        <description>user name for connecting to mysql server</description>
    </property>

    <!-- mysql連接密碼 -->
    <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 默認是1000，為了區別，我這裏不使用默認端口-->
    <property>
        <name>hive.server2.thrift.port</name>
        <value>10001</value>
    </property>

    <property>
        <name>hive.metastore.schema.verification</name>
        <value>true</value>
    </property>

</configuration>

AI寫代碼

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