插件名称：flink-connector-redis

插件地址：https://github.com/jeff-zou/flink-connector-redis.git

无法翻墙：https://gitee.com/jeff-zou/flink-connector-redis.git

项目介绍

基于bahir-flink二次开发，相对bahir调整的内容有：删除过期Flink API、增加Table/SQL API、 增加维表查询支持、增加写入与查询缓存、统一使用过期策略、写入并发数等。

因bahir使用的flink接口版本较老，所以改动较大，开发过程中参考了腾讯云与阿里云两家产商的流计算产品，取两家之长，并增加了更丰富的功能，包括更多的redis操作命令和更多的redis服务类型，如：simple sentinel cluster。

支持功能对应redis的操作命令有：

使用方法:

命令行执行 mvn package -DskipTests打包后，将生成的包flink-connector-redis-1.0.2.jar引入flink lib中即可，无需其它设置。

开发环境工程直接引用：

<dependency>
    <groupId>io.github.jeff-zou</groupId>
    <artifactId>flink-connector-redis</artifactId>
    <version>1.0.3</version>
</dependency>

使用说明：

无需通过primary key来映射redis中的Key，直接由ddl中的字段顺序来决定Key,如：

create table sink_redis(username VARCHAR, passport VARCHAR)  with ('command'='set') 
其中username为key, passport为value.

create table sink_redis(name VARCHAR, subject VARCHAR, score VARCHAR)  with ('command'='hset') 
其中name为map结构的key, subject为field, score为value.

with参数说明：

集群类型为sentinel时额外连接参数:

使用示例:

• 维表查询：

create table sink_redis(name varchar, level varchar, age varchar) with ( 'connector'='redis', 'host'='10.11.80.147','port'='7001', 'redis-mode'='single','password'='******','command'='hset');

-- 先在redis中插入数据,相当于redis命令： hset 3 3 100 --
insert into sink_redis select * from (values ('3', '3', '100'));
                
create table dim_table (name varchar, level varchar, age varchar) with ('connector'='redis', 'host'='10.11.80.147','port'='7001', 'redis-mode'='single', 'password'='*****','command'='hget', 'maxIdle'='2', 'minIdle'='1', 'lookup.cache.max-rows'='10', 'lookup.cache.ttl'='10', 'lookup.max-retries'='3');
    
-- 随机生成10以内的数据作为数据源 --
-- 其中有一条数据会是： username = 3  level = 3, 会跟上面插入的数据关联 -- 
create table source_table (username varchar, level varchar, proctime as procTime()) with ('connector'='datagen',  'rows-per-second'='1',  'fields.username.kind'='sequence',  'fields.username.start'='1',  'fields.username.end'='10', 'fields.level.kind'='sequence',  'fields.level.start'='1',  'fields.level.end'='10');

create table sink_table(username varchar, level varchar,age varchar) with ('connector'='print');

insert into
    sink_table
select
    s.username,
    s.level,
    d.age
from
    source_table s
left join dim_table for system_time as of s.proctime as d on
    d.name = s.username
    and d.level = s.level;
-- username为3那一行会关联到redis内的值，输出为： 3,3,100   

• DataStream查询方式
• 示例代码路径: src/test/java/org.apache.flink.streaming.connectors.redis.datastream.DataStreamTest.java hset示例，相当于redis命令：hset tom math 150

Configuration configuration = new Configuration();
configuration.setString(REDIS_MODE, REDIS_CLUSTER);
configuration.setString(REDIS_COMMAND, RedisCommand.HSET.name());

RedisSinkMapper redisMapper = (RedisSinkMapper)RedisHandlerServices
.findRedisHandler(RedisMapperHandler.class, configuration.toMap())
.createRedisMapper(configuration);

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

GenericRowData genericRowData = new GenericRowData(3);
genericRowData.setField(0, "tom");
genericRowData.setField(1, "math");
genericRowData.setField(2, "152");
DataStream<GenericRowData> dataStream = env.fromElements(genericRowData, genericRowData);

RedisCacheOptions redisCacheOptions = new RedisCacheOptions.Builder().setCacheMaxSize(100).setCacheTTL(10L).build();
FlinkJedisConfigBase conf = getLocalRedisClusterConfig();
RedisSinkFunction redisSinkFunction = new RedisSinkFunction<>(conf, redisMapper, redisCacheOptions);

dataStream.addSink(redisSinkFunction).setParallelism(1);
env.execute("RedisSinkTest");

• redis-cluster写入示例
• 示例代码路径: src/test/java/org.apache.flink.streaming.connectors.redis.table.SQLTest.java set示例，相当于redis命令： set test test11

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
EnvironmentSettings environmentSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env, environmentSettings);

String ddl = "create table sink_redis(username VARCHAR, passport VARCHAR) with ( 'connector'='redis', " +
              "'cluster-nodes'='10.11.80.147:7000,10.11.80.147:7001','redis- mode'='cluster','password'='******','command'='set')" ;

tEnv.executeSql(ddl);
String sql = " insert into sink_redis select * from (values ('test', 'test11'))";
TableResult tableResult = tEnv.executeSql(sql);
tableResult.getJobClient().get()
.getJobExecutionResult()
.get();

开发与测试环境

ide: IntelliJ IDEA

code format: google-java-format + Save Actions

code check: CheckStyle