概述

lookup join通常是查询外部系统的数据来充实FlinkSQL的主表
例如：事实表关联维度表，维度表在外部系统（如MySQL）
要求：
1个表具有处理时间属性（基于Processing Time Temporal Join语法）
语法上，和一般JOIN比较，多了FOR SYSTEM_TIME AS OF
另1个表由连接器（a lookup source connector）支持
Lookup Cache
默认情况下，不启用Lookup Cache
可设置lookup.cache.max-rows和lookup.cache.ttl参数来启用
启用Lookup Cache后，Flink会先查询缓存，缓存未命中才查询外部数据库
启用缓存可加快查询速，但缓存中的记录未必是最新的

SQL参数	说明
`connector`	连接器，可以是`jdbc`、`kafka`、`filesystem`…
`driver`	数据库驱动
`lookup.cache.ttl`	Lookup Cache中每行数据的最大存活时间
`lookup.cache.max-rows`	Lookup Cache中的最大行数

当缓存的行数>lookup.cache.max-rows 时，将清除存活时间最久的记录
缓存中的行的存货时间超过lookup.cache.ttl 也会被清除

pom.xml

环境：WIN10+IDEA+JDK1.8+Flink1.13+MySQL8

<properties>
    <maven.compiler.source>8</maven.compiler.source>
    <maven.compiler.target>8</maven.compiler.target>
    <flink.version>1.13.6</flink.version>
    <scala.binary.version>2.12</scala.binary.version>
    <slf4j.version>2.0.3</slf4j.version>
    <log4j.version>2.17.2</log4j.version>
    <fastjson.version>2.0.19</fastjson.version>
    <lombok.version>1.18.24</lombok.version>
    <mysql.version>8.0.31</mysql.version>
</properties>
<!-- https://mvnrepository.com/ -->
<dependencies>
    <!-- Flink -->
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-java</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-clients_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-runtime-web_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <!-- FlinkSQL -->
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-table-planner-blink_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <!-- 'format'='csv' -->
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-csv</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <!-- 'format'='json' -->
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-json</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <!-- 'connector' = 'jdbc' -->
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-connector-jdbc_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
    </dependency>
    <!-- 'driver' = 'com.mysql.cj.jdbc.Driver' -->
    <dependency>
        <groupId>mysql</groupId>
        <artifactId>mysql-connector-java</artifactId>
        <version>${mysql.version}</version>
    </dependency>
    <!-- 日志 -->
    <dependency>
        <groupId>org.slf4j</groupId>
        <artifactId>slf4j-api</artifactId>
        <version>${slf4j.version}</version>
    </dependency>
    <dependency>
        <groupId>org.slf4j</groupId>
        <artifactId>slf4j-log4j12</artifactId>
        <version>${slf4j.version}</version>
    </dependency>
    <dependency>
        <groupId>org.apache.logging.log4j</groupId>
        <artifactId>log4j-to-slf4j</artifactId>
        <version>${log4j.version}</version>
    </dependency>
    <!-- JSON解析 -->
    <dependency>
        <groupId>com.alibaba</groupId>
        <artifactId>fastjson</artifactId>
        <version>${fastjson.version}</version>
    </dependency>
    <!-- 简化JavaBean书写 -->
    <dependency>
        <groupId>org.projectlombok</groupId>
        <artifactId>lombok</artifactId>
        <version>${lombok.version}</version>
    </dependency>
</dependencies>

MySQL建表

DROP DATABASE IF EXISTS db0;
CREATE DATABASE db0;

CREATE TABLE db0.tb0 (
  a VARCHAR(255) PRIMARY KEY,
  b INT(3),
  c BIGINT(5),
  d FLOAT(3,2),
  e DOUBLE(4,2),
  f DATE DEFAULT '2022-10-24',
  g TIMESTAMP DEFAULT CURRENT_TIMESTAMP);

INSERT db0.tb0 (a,b,c,d,e) VALUES
('aa',1,11,1.11,11.11),
('bb',2,22,2.22,22.22),
('cc',3,33,3.33,33.33);
SELECT * FROM db0.tb0;

对应Flink的建表SQL

SQL

CREATE TEMPORARY TABLE temp_tb0 (
  a STRING,
  b INT,
  c BIGINT,
  d FLOAT,
  e DOUBLE,
  f DATE,
  g TIMESTAMP,
  PRIMARY KEY(a) NOT ENFORCED)
WITH (
  'lookup.cache.max-rows' = '2',
  'lookup.cache.ttl' = '30 second',
  'connector' = 'jdbc',
  'driver' = 'com.mysql.cj.jdbc.Driver',
  'url' = 'jdbc:mysql://localhost:3306/db0',
  'username' = 'root',
  'password' = '123456',
  'table-name' = 'tb0'
)

测试代码

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

public class Hello {
    
    
    public static void main(String[] args) {
    
    
        //创建流和表的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment().setParallelism(1);
        StreamTableEnvironment tbEnv = StreamTableEnvironment.create(env);
        //创建表，连接MySQL表
        tbEnv.executeSql("CREATE TEMPORARY TABLE temp_tb0 (\n" +
                "  a STRING,\n" +
                "  b INT,\n" +
                "  c BIGINT,\n" +
                "  d FLOAT,\n" +
                "  e DOUBLE,\n" +
                "  f DATE,\n" +
                "  g TIMESTAMP,\n" +
                "  PRIMARY KEY(a) NOT ENFORCED)\n" +
                "WITH (\n" +
                "  'lookup.cache.max-rows' = '2',\n" +
                "  'lookup.cache.ttl' = '30 second',\n" +
                "  'connector' = 'jdbc',\n" +
                "  'driver' = 'com.mysql.cj.jdbc.Driver',\n" +
                "  'url' = 'jdbc:mysql://localhost:3306/db0',\n" +
                "  'username' = 'root',\n" +
                "  'password' = '123456',\n" +
                "  'table-name' = 'tb0'\n" +
                ")");
        //执行查询，打印
        tbEnv.sqlQuery("SELECT * FROM temp_tb0").execute().print();
    }
}

测试结果打印

+----+----+---+----+------+-------+------------+----------------------------+
| op |  a | b |  c |    d |     e |          f |                          g |
+----+----+---+----+------+-------+------------+----------------------------+
| +I | aa | 1 | 11 | 1.11 | 11.11 | 2022-10-24 | 2022-11-29 14:57:50.000000 |
| +I | bb | 2 | 22 | 2.22 | 22.22 | 2022-10-24 | 2022-11-29 14:57:50.000000 |
| +I | cc | 3 | 33 | 3.33 | 33.33 | 2022-10-24 | 2022-11-29 14:57:50.000000 |
+----+----+---+----+------+-------+------------+----------------------------+

Lookup Join

FlinkSQL

SELECT * FROM v
JOIN t
  FOR SYSTEM_TIME AS OF v.y
  ON v.x=t.a

完整Java代码

import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

import java.util.Scanner;

import static org.apache.flink.table.api.Expressions.$;

public class Hi {
    
    
    public static void main(String[] args) {
    
    
        //创建流和表的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment().setParallelism(1);
        StreamTableEnvironment tbEnv = StreamTableEnvironment.create(env);
        //创建左表
        DataStreamSource<String> d = env.addSource(new ManualSource());
        Table tb = tbEnv.fromDataStream(d, $("x"), $("y").proctime());
        tbEnv.createTemporaryView("v", tb);
        //创建右表（维度表）
        tbEnv.executeSql("CREATE TEMPORARY TABLE t ( " +
                "  a STRING, " +
                "  b INT, " +
                "  c BIGINT, " +
                "  d FLOAT, " +
                "  e DOUBLE, " +
                "  f DATE, " +
                "  g TIMESTAMP, " +
                "  PRIMARY KEY(a) NOT ENFORCED) " +
                "WITH ( " +
                "  'lookup.cache.max-rows' = '2', " +
                "  'lookup.cache.ttl' = '30 second', " +
                "  'connector' = 'jdbc', " +
                "  'driver' = 'com.mysql.cj.jdbc.Driver', " +
                "  'url' = 'jdbc:mysql://localhost:3306/db0', " +
                "  'username' = 'root', " +
                "  'password' = '123456', " +
                "  'table-name' = 'tb0' " +
                ")");
        //执行查询，打印
        tbEnv.sqlQuery("SELECT * FROM v " +
                "JOIN t " +
                "  FOR SYSTEM_TIME AS OF v.y " +
                "  ON v.x=t.a").execute().print();
    }

    /** 手动输入的数据源 */
    public static class ManualSource implements SourceFunction<String> {
    
    
        public ManualSource() {
    
    }

        @Override
        public void run(SourceFunction.SourceContext<String> sc) {
    
    
            Scanner scanner = new Scanner(System.in);
            while (true) {
    
    
                String str = scanner.nextLine().trim();
                if (str.equals("STOP")) {
    
    break;}
                if (!str.equals("")) {
    
    sc.collect(str);}
            }
            scanner.close();
        }

        @Override
        public void cancel() {
    
    }
    }
}

测试结果

大数据（9h）FlinkSQL之Lookup Join

文章目录

概述

pom.xml

MySQL建表

对应Flink的建表SQL

Lookup Join

FlinkSQL

完整Java代码

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