Windows系统安装Flink及实现MySQL之间数据同步_flink windows安装

        Apache Flink是一个框架和分布式处理引擎，用于对无界和有界数据流进行有状态计算。Flink的设计目标是在所有常见的集群环境中运行，并以内存执行速度和任意规模来执行计算。它支持高吞吐、低延迟、高性能的流处理，并且是一个面向流处理和批处理的分布式计算框架，将批处理看作一种特殊的有界流。

Flink的主要特点包括：

1. 事件驱动型：Flink是一个事件驱动型的应用，可以从一个或多个事件流提取数据，并根据到来的事件触发计算、状态更新或其他外部动作。
2. 支持有状态计算：Flink提供了Extactor-once语义及checkpoint机制，支持带有事件操作的流处理和窗口处理，以及灵活的窗口处理（如时间窗口、大小窗口等）。
3. 轻量级容错处理：Flink使用savepoint进行错误恢复，可以在出现故障时快速恢复任务。
4. 高吞吐、低延迟、高性能：Flink的设计目标是在保证数据处理稳定性的同时，实现高吞吐、低延迟、高性能的流处理。
5. 支持大规模集群模式：Flink支持在yarn、Mesos、k8s等大规模集群环境中运行。
6. 支持多种编程语言：Flink对java、scala、python都提供支持，但最适合使用java进行开发。

        Flink的应用场景非常广泛，可以用于实时流数据的分析计算、实时数据与维表数据关联计算、实时数仓建设、ETL（提取-转换-加载）多存储系统之间进行数据转化和迁移等场景。同时，Flink也适用于事件驱动型应用场景，如以kafka为代表的消息队列等。

1.Winows系统安装Flink

下载地址：Downloads | Apache Flink

选择 Apache Flink 1.16.0 - 2022-10-28 (Binaries）

下载 flink-1.16.0-bin-scala_2.12.tgz

在Flink安装路径/bin/目录下创建start-cluster.bat，代码如下：

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::  distributed under the License is distributed on an "AS IS" BASIS,
::  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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:: 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 /b java %JVM_ARGS% %log_setting_jm% -cp "%FLINK_CLASSPATH%"; org.apache.flink.runtime.entrypoint.StandaloneSessionClusterEntrypoint --configDir "%FLINK_CONF_DIR%" > "%out_jm%" 2>&1
start /b java %JVM_ARGS% %log_setting_tm% -cp "%FLINK_CLASSPATH%"; org.apache.flink.runtime.taskexecutor.TaskManagerRunner --configDir "%FLINK_CONF_DIR%" > "%out_tm%" 2>&1
 
endlocal
 

使用CMD窗口，在Flink安装路径/bin目录下启动start-cluster.bat

访问http://localhost:8081，界面如下：

2.使用Flink实现MySQL数据库之间数据同步（JAVA）

<flink.version>1.16.0</flink.version>
<flink-cdc.version>2.3.0</flink-cdc.version>

1.创建Flink流处理运行环境。

2.设置流处理并发数。

3.设置Flink存档间隔时间,单位为ms，当同步发生异常时会恢复最近的checkpoint继续同步。

4.在Flink中创建中间同步数据库。

5.在Flink中创建中间表flink_source，来源于MySQL表source，（注意connector为mysql-cdc）。

6.在Flink中创建中间表flink_sink，来源于MySQL表sink。

7.将Flink中间表来源表数据写入flink_sink表，Flink会根据MySQL binlog中source表变化，动态更新flink_sink表，同时会将flink_sink表数据写入MySQL sink表，实现MySQL数据持续同步。

package com.demo.flink;
 
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
 
public class FlinkCdcMySql {
    public static void main(String[] args) {
        System.out.println("==========start run FlinkCdcMySql#main.");
 
        // 创建Flink流处理运行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
 
//        StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment("127.0.0.1", 8081);
        // 设置流处理并发数
        env.setParallelism(3);
        // 设置Flink存档间隔时间,单位为ms，当同步发生异常时会恢复最近的checkpoint继续同步
        env.enableCheckpointing(5000);
 
        final StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);
 
        // 在Flink中创建中间同步数据库
        tEnv.executeSql("CREATE DATABASE IF NOT EXISTS flink_test");
 
        // 在Flink中创建中间表flink_source，来源于MySQL表source
        // 注意connector为mysql-cdc
        tEnv.executeSql("CREATE TABLE flink_test.flink_source (\n" +
                "    id int,\n" +
                "    name varchar(255),\n" +
                "    create_time TIMESTAMP\n," + // Flink不支持datetime格式
                "    PRIMARY KEY (id) NOT ENFORCED" + //主键必须标明NOT ENFORCED
                ") WITH (\n" +
                "  'connector'  = 'mysql-cdc',\n" +
                "  'hostname'   = '127.0.0.1',\n" +
                "  'database-name'   = 'flink-source',\n" +
                "  'table-name' = 'source',\n" +
                "  'username'   = 'root',\n" +
                "  'password'   = 'root'\n" +
                ")");
 
        // 在Flink中创建中间表flink_sink，来源于MySQL表sink
        tEnv.executeSql("CREATE TABLE flink_test.flink_sink (\n" +
                "    id int,\n" +
                "    name varchar(255),\n" +
                "    create_time TIMESTAMP\n," +
                "    PRIMARY KEY (id) NOT ENFORCED" +
                ") WITH (\n" +
                "  'connector'  = 'jdbc',\n" +
                "  'url'        = 'jdbc:mysql://127.0.0.1:3306/flink-sink',\n" +
                "  'table-name' = 'sink',\n" +
                "  'driver'     = 'com.mysql.jdbc.Driver',\n" +
                "  'username'   = 'root',\n" +
                "  'password'   = 'root'\n" +
                ")");
 
//        Table transactions = tEnv.from("flink_source");
//        transactions.executeInsert("flink_sink");
 
        System.out.println("==========begin Mysql data cdc.");
 
        // 将Flink中间表来源表数据写入flink_sink表
        // Flink会根据MySQL binlog中source表变化，动态更新flink_sink表，同时会将flink_sink表数据写入MySQL sink表，实现MySQL数据持续同步
        tEnv.executeSql("INSERT INTO flink_test.flink_sink(id, name, create_time)\n" +
                "select id, name, create_time\n" +
                "from flink_test.flink_source\n");
 
        System.out.println("==========continue Mysql data cdc.");
    }
 
}

git代码地址：

flink-cdc-MySQL: FlinkCDC实现MySQL之间数据同步