MLSQLStack如何让流调试更加简单详解
前言
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有一位同学正在调研MLSQL Stack对流的支持。然后说了流调试其实挺困难的。经过实践,希望实现如下三点:
- 能随时查看最新固定条数的Kafka数据
- 调试结果(sink)能打印在web控制台
- 流程序能自动推测json schema(现在spark是不行的)
实现这三个点之后,我发现调试确实就变得简单很多了。
流程
首先我新建了一个kaf_write.mlsql,里面方便我往Kafka里写数据:
set abc=''' { "x": 100, "y": 200, "z": 200 ,"dataType":"A group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} { "x": 120, "y": 100, "z": 260 ,"dataType":"B group"} '''; load jsonStr.`abc` as table1; select to_json(struct(*)) as value from table1 as table2; save append table2 as kafka.`wow` where kafka.bootstrap.servers="127.0.0.1:9092";
这样我每次运行,数据就能写入到Kafka.
接着,我写完后,需要看看数据是不是真的都写进去了,写成了什么样子:
!kafkaTool sampleData 10 records from "127.0.0.1:9092" wow;
这句话表示,我要采样Kafka 10条Kafka数据,该Kafka的地址为127.0.0.1:9092,主题为wow.运行结果如下:
没有什么问题。接着我写一个非常简单的流式程序:
-- the stream name, should be uniq. set streamName="streamExample"; -- use kafkaTool to infer schema from kafka !kafkaTool registerSchema 2 records from "127.0.0.1:9092" wow; load kafka.`wow` options kafka.bootstrap.servers="127.0.0.1:9092" as newkafkatable1; select * from newkafkatable1 as table21; -- print in webConsole instead of terminal console. save append table21 as webConsole.`` options mode="Append" and duration="15" and checkpointLocation="/tmp/s-cpl4";
运行结果如下:
在终端我们也可以看到实时效果了。
补充
当然,MLSQL Stack 还有对流还有两个特别好地方,第一个是你可以对流的事件设置http协议的callback,以及对流的处理结果再使用批SQL进行处理,最后入库。参看如下脚本:
-- the stream name, should be uniq. set streamName="streamExample"; -- mock some data. set data=''' {"key":"yes","value":"no","topic":"test","partition":0,"offset":0,"timestamp":"2008-01-24 18:01:01.001","timestampType":0} {"key":"yes","value":"no","topic":"test","partition":0,"offset":1,"timestamp":"2008-01-24 18:01:01.002","timestampType":0} {"key":"yes","value":"no","topic":"test","partition":0,"offset":2,"timestamp":"2008-01-24 18:01:01.003","timestampType":0} {"key":"yes","value":"no","topic":"test","partition":0,"offset":3,"timestamp":"2008-01-24 18:01:01.003","timestampType":0} {"key":"yes","value":"no","topic":"test","partition":0,"offset":4,"timestamp":"2008-01-24 18:01:01.003","timestampType":0} {"key":"yes","value":"no","topic":"test","partition":0,"offset":5,"timestamp":"2008-01-24 18:01:01.003","timestampType":0} '''; -- load data as table load jsonStr.`data` as datasource; -- convert table as stream source load mockStream.`datasource` options stepSizeRange="0-3" as newkafkatable1; -- aggregation select cast(value as string) as k from newkafkatable1 as table21; !callback post "http://127.0.0.1:9002/api_v1/test" when "started,progress,terminated"; -- output the the result to console. save append table21 as custom.`` options mode="append" and duration="15" and sourceTable="jack" and code=''' select count(*) as c from jack as newjack; save append newjack as parquet.`/tmp/jack`; ''' and checkpointLocation="/tmp/cpl15";
总结
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