大数据(9h)FlinkSQL之Lookup Join
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文章目录
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
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