第1章 简介
在此佳节之际，首先祝福所有读者国庆中秋双节快乐！
经过前几篇文章的介绍，相信大家已经了解Flink在生产环境上的部署和使用。那么问题随之而来：难道每一个Flink开发人员都要部署安装一套集群才能做开发吗？答案当然是否定的，如果每一个开发人员都要一套集群那开发成本就太高了。本篇文章以Flink Table API/SQL为例，以Kafka为数据源、Mysql为数据汇，采用容器的方式，为大家介绍Flink开发环境的搭建及使用。（注：笔者以windows为例，mac系统类似）
第2章 安装组件
2.1 官网安装docker
这里就不详细介绍了，大家自行到官网（https://www.docker.com）下载安装。
2.2 设置国内镜像仓库地址
2.3 查询docker版本
C:\Users\zihao>docker --version
Docker version 19.03.12, build 48a66213fe2.4 安装kafka
安装前可先查询kafka相关镜像docker search kafka拉取kafka镜像
C:\Users\zihao>docker pull wurstmeister/kafka:2.12-2.5.0
2.12-2.5.0: Pulling from wurstmeister/kafka
Image docker.io/wurstmeister/kafka:2.12-2.5.0 uses outdated schema1 manifest format. Please upgrade to a schema2 image for better future compatibility. More information at https://docs.docker.com/registry/spec/deprecated-schema-v1/
e7c96db7181b: Retrying in 1 second f910a506b6cb: Retrying in 1 second b6abafe80f63: Downloading 2e9c2caa5758: Waiting 1b29071c565f: Waiting c81626d038e3: Waiting 2.12-2.5.0: Pulling from wurstmeister/kafka
e7c96db7181b: Pull complete f910a506b6cb: Pull complete b6abafe80f63: Pull complete 2e9c2caa5758: Pull complete 1b29071c565f: Pull complete c81626d038e3: Pull complete Digest: sha256:71aa89afe97d3f699752b6d80ddc2024a057ae56407f6ab53a16e9e4bedec04c
Status: Downloaded newer image for wurstmeister/kafka:2.12-2.5.0
docker.io/wurstmeister/kafka:2.12-2.5.02.5 安装zookeeper
拉取zookeeper镜像
C:\Users\zihao>docker pull zookeeper:3.5.7
3.5.7: Pulling from library/zookeeper
afb6ec6fdc1c: Pulling fs layer ee19e84e8bd1: Pulling fs layer 6ac787417531: Pulling fs layer f3f781d4d83e: Waiting 424c9e43d19a: Waiting f0929561e8a7: Waiting f1cf0c087cb3: Waiting 2f47bb4dd07a: Waiting 3.5.7: Pulling from library/zookeeper
afb6ec6fdc1c: Pulling fs layer ee19e84e8bd1: Pulling fs layer 6ac787417531: Pulling fs layer f3f781d4d83e: Waiting 424c9e43d19a: Waiting f0929561e8a7: Waiting f1cf0c087cb3: Waiting 2f47bb4dd07a: Waiting 3.5.7: Pulling from library/zookeeper
afb6ec6fdc1c: Pull complete ee19e84e8bd1: Pull complete 6ac787417531: Pull complete f3f781d4d83e: Pull complete 424c9e43d19a: Pull complete f0929561e8a7: Pull complete f1cf0c087cb3: Pull complete 2f47bb4dd07a: Pull complete Digest: sha256:883b014b6535574503bda8fc6a7430ba009c0273242f86d401095689652e5731
Status: Downloaded newer image for zookeeper:3.5.7
docker.io/library/zookeeper:3.5.72.6 安装Mysql
C:\Users\zihao>docker pull mysql:5.7
5.7: Pulling from library/mysql
Image docker.io/library/mysql:5.7 uses outdated schema1 manifest format. Please upgrade to a schema2 image for better future compatibility. More information at https://docs.docker.com/registry/spec/deprecated-schema-v1/
d121f8d1c412: Downloading f3cebc0b4691: Downloading 1862755a0b37: Downloading 489b44f3dbb4: Downloading 690874f836db: Downloading baa8be383ffb: Downloading 55356608b4ac: Downloading 277d8f888368: Downloading 21f2da6feb67: Downloading 2c98f818bcb9: Downloading 031b0a770162: Downloading 5.7: Pulling from library/mysql
d121f8d1c412: Pull complete f3cebc0b4691: Pull complete 1862755a0b37: Pull complete 489b44f3dbb4: Pull complete 690874f836db: Pull complete baa8be383ffb: Pull complete 55356608b4ac: Pull complete 277d8f888368: Pull complete 21f2da6feb67: Pull complete 2c98f818bcb9: Pull complete 031b0a770162: Pull complete Digest: sha256:14fd47ec8724954b63d1a236d2299b8da25c9bbb8eacc739bb88038d82da4919
Status: Downloaded newer image for mysql:5.7
docker.io/library/mysql:5.72.7 查看已安装的镜像images
C:\Users\zihao>docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
mysql 5.7 ef08065b0a30 3 days ago 448MB
wurstmeister/kafka 2.12-2.5.0 caa449bd6c28 3 weeks ago 431MB
zookeeper 3.5.7 6bd990489b09 4 months ago 245MB第3章 启动容器
3.1 启动zookeeper
C:\Users\zihao>docker run -d --name zookeeper -p 2181:2181 -t zookeeper:3.5.7
5a29cfcb77c1bbd33eedf41add46da89b91468d09702acde5caa3086b6cc467e3.2 启动kafka
C:\Users\zihao>docker run -d --name kafka --publish 9092:9092 --link zookeeper --env KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 --env KAFKA_ADVERTISED_HOST_NAME=127.0.0.1 --env KAFKA_ADVERTISED_PORT=9092 wurstmeister/kafka:2.12-2.5.0
e45499f971d1efd59227031f41631d1cf6e9e13b7950872efbf96dcbb5f998fb3.3 启动Mysql
C:\Users\zihao>docker run -p 3306:3306 --name mysql -v D:/21docker/mysql/conf:/etc/mysql/conf.d -v D:/21docker/mysql/logs:/logs -v D:/21docker/mysql/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=123456 -d mysql:5.7
2bea9be2ccdbea6f41c9a4dedc7d3bf8efa5538b39e19dea43eb66f4df100bb7注意用-v参数挂载路径
3.4 查看启动的容器
C:\Users\zihao>docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
5f4d03dee765 mysql:5.7 "docker-entrypoint.s…" 4 seconds ago Up 3 seconds 0.0.0.0:3306->3306/tcp, 33060/tcp mysql
e45499f971d1 wurstmeister/kafka:2.12-2.5.0 "start-kafka.sh" 47 minutes ago Up 47 minutes 0.0.0.0:9092->9092/tcp kafka
5a29cfcb77c1 zookeeper:3.5.7 "/docker-entrypoint.…" 52 minutes ago Up 52 minutes 2888/tcp, 3888/tcp, 0.0.0.0:2181->2181/tcp, 8080/tcp zookeeper3.5 检查kafka运行情况
进入kafka容器
C:\Users\zihao>docker exec -it kafka /bin/bash到kafka目录
bash-4.4# cd opt/kafka新建topic
bash-4.4# bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --topic test
Created topic test.命令启动生产者
bash-4.4# bin/kafka-console-producer.sh --topic=test --broker-list localhost:9092
>启动一个消费者
bash-4.4# bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 -from-beginning --topic test
发送数据，查看消费是否正常
生产者发送数据
bash-4.4# bin/kafka-console-producer.sh --topic=test --broker-list localhost:9092
>hello
>flink
>消费者消费数据情况
bash-4.4# bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 -from-beginning --topic test
hello
flink可以看到kafka的消息生成和消费正常，证明kafka安装已经正常。
3.6 检查mysql运行情况
C:\Users\zihao>docker exec -it mysql bash
root@5f4d03dee765:/# mysql -h localhost -u root -p
Enter password:
Welcome to the MySQL monitor. Commands end with ; or \g.
Your MySQL connection id is 2
Server version: 5.7.31 MySQL Community Server (GPL)
Copyright (c) 2000, 2020, Oracle and/or its affiliates. All rights reserved.
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
mysql> show databases;
+--------------------+
| Database |
+--------------------+
| information_schema |
| mysql |
| performance_schema |
| sys |
+--------------------+
4 rows in set (0.02 sec)可以看到mysql中的数据库，证明mysql也安装运行正常。
第4章 运行flink
4.1 建立kafka topic
bash-4.4# bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --topic country-log
Created topic country-log.4.2 建立Mysql表
建库
mysql> create database flinkdb;建表
mysql> create table country_log(country_id bigint,country_msg varchar(100));4.3 启动kafka生产者
bash-4.4# bin/kafka-console-producer.sh --topic=country-log --broker-list localhost:90924.4 Idea编写作业
package sql;
import org.apache.flink.api.common.restartstrategy.RestartStrategies;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.runtime.state.filesystem.FsStateBackend;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import java.util.concurrent.TimeUnit;
/**
* Kafka生产的数据：
* {"country_id":"1","country_msg":"hello flink!"}
* MySql建表语句:
* create table country(country_id bigint,country_msg varchar(100));
*/
public class Kafka2Mysql {
public static void main(String[] args) throws Exception {
// Kafka source
String sourceSQL="CREATE TABLE demo_source (country_id BIGINT,country_msg STRING)\n" +
" WITH (\n" +
" 'connector' = 'kafka-0.11',\n" +
" 'topic'='country-log',\n" +
" 'properties.bootstrap.servers'='localhost:9092',\n" +
" 'format' = 'json',\n" +
" 'scan.startup.mode' = 'latest-offset'\n" +
")";
//Mysql sink
String sinkSQL="CREATE TABLE demo_sink (country_id BIGINT,country_msg STRING)\n" +
" WITH (" +
" 'connector' = 'jdbc',\n" +
" 'url' = 'jdbc:mysql://localhost:3306/flinkdb?characterEncoding=utf-8&useSSL=false',\n" +
" 'table-name' = 'country_log',\n" +
" 'username' = 'root',\n" +
" 'password' = '123456',\n" +
" 'sink.buffer-flush.max-rows' = '1',\n" +
" 'sink.buffer-flush.interval' = '1s'\n" +
")";
// 创建执行环境
EnvironmentSettings settings=EnvironmentSettings
.newInstance()
.useBlinkPlanner()
.inStreamingMode()
.build();
//TableEnvironment tEnv = TableEnvironment.create(settings);
StreamExecutionEnvironment sEnv = StreamExecutionEnvironment.getExecutionEnvironment();
sEnv.setRestartStrategy(RestartStrategies.fixedDelayRestart(3, Time.of(1, TimeUnit.SECONDS)));
//sEnv.enableCheckpointing(1000);
//sEnv.setStateBackend(new FsStateBackend("file:///tmp/chkdir",false));
StreamTableEnvironment tEnv= StreamTableEnvironment.create(sEnv,settings);
//注册souuce
tEnv.executeSql(sourceSQL);
//注册sink
tEnv.executeSql(sinkSQL);
//数据提取
Table sourceTable=tEnv.from("demo_source");
//发送数据
sourceTable.executeInsert("demo_sink");
//执行作业
tEnv.execute("Hello Flink");
}
}
在Idea里直接运行上面的程序。
至此，Kafka、Mysql、Flink作业程序已经全部Running，接下来我们开始生成数据，查看数据情况。
4.5 命令行生产数据
到kafka命令行手动生产消息
bash-4.4# bin/kafka-console-producer.sh --topic=country-log --broker-list localhost:9092
>{"country_id":"1","country_msg":"hello flink!"}
>{"country_id":"2","country_msg":"hello flink!"}
>4.6 查看Mysql中的数据
数据经过Kafka-Flink到达Mysql，查看Mysql中的数据
mysql> select * from country_log;
+------------+--------------+
| country_id | country_msg |
+------------+--------------+
| 1 | hello flink! |
| 2 | hello flink! |
+------------+--------------+
2 rows in set (0.01 sec)至此，我们已经通过Flink成功从Kafka迁移至下游的Mysql，完成了Flink在本地开发环境搭建及使用。但是本篇文章只是简单的将数据从Flink中流过，也没有完整的端到端的业务。下篇文章将为大家介绍一个完整的端到端涵盖Flink计算的案例。期待您的持续关注！