欢迎来到拽度站长资源网!

MySQL

当前位置:首页 > 数据库 > MySQL > 正文内容

MLSQL Stack如何让流调试更加简单详解

时间:2019-10-28|栏目:MySQL|点击:

前言

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

以上就是这篇文章的全部内容了,希望本文的内容对大家的学习或者工作具有一定的参考学习价值,谢谢大家对拽度站长教程网的支持。

上一篇:简单了解mysql mycat 中间件

栏    目:MySQL

下一篇:简单了解添加mysql索引的3条原则

本文标题:MLSQL Stack如何让流调试更加简单详解

本文地址:http://www.xiaochi100.com/web/MySQL/2573.html

广告投放 | 联系我们 | 版权申明

重要申明:本站所有的文章、图片、评论等,均由网友发表或上传并维护或收集自网络,属个人行为,与本站立场无关。

如果侵犯了您的权利,请与我们联系,我们将在24小时内进行处理、任何非本站因素导致的法律后果,本站均不负任何责任。

联系QQ:2587799600 | 邮箱:2587799600#qq.com(#换成@)

Copyright © 2015-2020 ZhuaiDU.COM. 拽度站长 版权所有 湘ICP备19014690号