Flink流批一体计算（23）：Flink SQL之多流kafka写入多个mysql sink

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目录

1. 准备工作

生成数据

创建数据表

2. 创建数据表

创建数据源表

创建数据目标表

3. 计算

WITH子句

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1. 准备工作

生成数据

source kafka json 数据格式 ：

topic  case_kafka_mysql：

{"ts": "20201011","id": 8,"price_amt":211}

topic  flink_test_2：

{"id": 8,"coupon_price_amt":100}

注意：针对双流中的每条记录都发触发

topic: case_kafka_mysql

docker exec -it 192d1369463a bashbash-5.1# cd /opt/kafka_2.12-2.5.0/binbash-5.1# ./kafka-console-producer.sh --broker-list localhost:9092 --topic case_kafka_mysql>{"ts": "20201011","id": 8,"price_amt":211}

topic: flink_test_2

docker exec -it 192d1369463a bashbash-5.1# cd /opt/kafka_2.12-2.5.0/binbash-5.1# ./kafka-console-producer.sh --broker-list localhost:9092 --topic flink_test_2>{"id": 8,"coupon_price_amt":100}

创建数据表

mysql 建表语句

CREATE TABLE `sync_test_2` (`id` bigint(11) NOT NULL AUTO_INCREMENT,`ts` varchar(64) DEFAULT NULL,`total_gmv` bigint(11) DEFAULT NULL,PRIMARY KEY (`id`),UNIQUE KEY `uidx` (`ts`) USING BTREE) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8mb4;CREATE TABLE `sync_test_22` (`id` bigint(11) NOT NULL AUTO_INCREMENT,`ts` varchar(64) DEFAULT NULL,`coupon_ratio` double DEFAULT NULL,PRIMARY KEY (`id`),UNIQUE KEY `uidx` (`ts`) USING BTREE) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8mb4;

2. 创建数据表

创建数据源表

create table flink_test_2_1 (id BIGINT,ts VARCHAR,price_amt BIGINT,proctime AS PROCTIME ()
)with ('connector' = 'kafka','topic' = 'case_kafka_mysql','properties.bootstrap.servers' = '127.0.0.1:9092','properties.group.id' = 'flink_gp_test2-1','scan.startup.mode' = 'earliest-offset','format' = 'json','json.fail-on-missing-field' = 'false','json.ignore-parse-errors' = 'true','properties.zookeeper.connect' = '127.0.0.1:2181/kafka');create table flink_test_2_2 (id BIGINT,coupon_price_amt BIGINT,proctime AS PROCTIME ()
)with ('connector' = 'kafka','topic' = 'flink_test_2','properties.bootstrap.servers' = '127.0.0.1:9092','properties.group.id' = 'flink_gp_test2-2','scan.startup.mode' = 'earliest-offset','format' = 'json','json.fail-on-missing-field' = 'false','json.ignore-parse-errors' = 'true','properties.zookeeper.connect' = '127.0.0.1:2181/kafka');

关键配置的说明：

json.fail-on-missing-field：在json缺失字段时是否报错

json.ignore-parse-errors：在解析json失败时是否报错

一般无法保证json格式，所以以上两个配置是比较重要的。

创建数据目标表

CREATE TABLE sync_test_2 (ts string,total_gmv bigint,PRIMARY KEY (ts) NOT ENFORCED) WITH ('connector' = 'jdbc','url' = 'jdbc:mysql://127.0.0.1:3306/db01?characterEncoding=UTF-8','table-name' = 'sync_test_2','username' = 'root','password' = 'Admin');CREATE TABLE sync_test_22 (ts string,coupon_ration bigint,PRIMARY KEY (ts) NOT ENFORCED) WITH ('connector' = 'jdbc','url' = 'jdbc:mysql://127.0.0.1:3306/db01?characterEncoding=UTF-8','table-name' = 'sync_test_2','username' = 'root','password' = 'Admin');

3. 计算

一个作业中写入一个Sink或多个Sink。

说明 写入多个Sink语句时，需要以BEGIN STATEMENT SET;开头，以END;结尾。

BEGIN STATEMENT SET;      --写入多个Sink时，必填。
INSERT INTO sync_test_2
SELECTts,SUM(price_amt - coupon_price_amt) AS total_gmv
FROM(SELECTa.ts as ts,a.price_amt as price_amt,b.coupon_price_amt as coupon_price_amtFROMflink_test_2_1 as aLEFT JOIN flink_test_2_2 b on b.id = a.id)
GROUP BY ts;INSERT INTO sync_test_22
SELECTts,sum(coupon_price_amt)/sum(amount) AS coupon_ration
FROM(SELECTa.ts as ts,a.price_amt as price_amt,b.coupon_price_amt as coupon_price_amtFROMflink_test_2_1 as aLEFT JOIN flink_test_2_2 b on b.id = a.id)
GROUP BY ts;;
END;      --写入多个Sink时，必填。

WITH子句

WITH提供了一种编写辅助语句以用于更大的查询的方法。这些语句通常被称为公共表表达式（CTE），可以被视为定义仅针对一个查询存在的临时视图。

改写上述查询：

BEGIN STATEMENT SET;      --写入多个Sink时，必填。
with orders_with_coupon AS (SELECTa.ts as ts,a.price_amt as price_amt,b.coupon_price_amt as coupon_price_amtFROMflink_test_2_1 as aLEFT JOIN flink_test_2_2 b on b.id = a.id
)INSERT INTO sync_test_2
SELECTts,SUM(price_amt - coupon_price_amt) AS total_gmv
FROM orders_with_coupon
GROUP BY ts;INSERT INTO sync_test_22
SELECTts,coupon_price_amt/price_amt AS coupon_ration
FROM orders_with_coupon
GROUP BY ts;;
END;      --写入多个Sink时，必填。

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