druid.io sql支持
来源:互联网 发布:windows界面开发主流 编辑:程序博客网 时间:2024/06/18 01:38
参考地址:http://druidwithsql.tumblr.com/post/98578718282/a-first-look-at-druid-with-sql
download: git clone git@git.corp.yahoo.com:srikalyan/Sql4D.git
make install:
mvn clean install -DskipTests=true
start:
java -jar Sql4DClient/target/Sql4DClient-4.1.0.jar -bh 10.13.4.45 -bp 8092 ch 10.13.4.45 -cp 8091 -oh 10.13.4.45 -op 8061 -mh 10.210.136.64 -mp 3306 -mid druid -mpw diurd -
mdb druid -i 50
-bh: broke node host
-bp: broke node port
-ch: coordinator node host
-cp: coordinator node port
-oh: overlord node host
-op: overlord node port
-mh: mysql host
-mp: mysql port
-mid: mysql username
-mpw: mysql password
-mdb: mysql db
help:
1. select/crud statements (GroupBy, TimeSeries, TopN, Select, Search, Insert). See wiki for examples: https://github.com/srikalyc/Sql4D/wiki/Sql4DCompiler
2. generatebean=BeanName (This command must be preceding a SQL, it generates a java source file BeanName.java which extends DruidBaseBean.
3. trace=[true|false] (When enabled prints out compiled JSON query)
4. querymode=[sql|json] (Default is sql, when mode is json it is fired directly)
5. show tables (Displays all the datasources)
6. describe TableName (Displays the given datasource's schema)
7. quit (Exits client)
query语法:
query支持sql及json两种方式,默认为sql
sql:
支持基本的show tables,
desc table—> describe TableName
注:druid table列的类型一共三种
1: Implicit_Dimension (一般为timestamp列)
2: Dimension (查询条件,只能通过groupby来查询)
3: Metric (指标项,一般为数值,可直接查询)
select Metric
SELECT LONG_SUM(count) as num FROM weibovolence where interval between '2015-09-17T14:01:00.000Z' AND '2015-09-17T14:15:05.832Z' LIMIT 100;
select groupBy and order by
SELECT uid, LONG_SUM(count) AS count FROM weibovolence WHERE interval BETWEEN '2015-09-17T14:01:00.000Z' AND '2015-09-17T14:15:05.832Z' BREAK BY 'all' GROUP BY uid order by count desc limit 10;
BREAK BY 表示聚合粒度,一般有以下几种值(day\hour\all\none等)group by order by 都能正常支持。
HINT(‘')为查询类型,可为GroupBy, TimeSeries, TopN等
select Timeseries
SELECT LONG_SUM(count) AS count FROM weibovolence WHERE interval BETWEEN '2015-09-17T14:01:00.000Z' AND '2015-09-17T14:15:05.832Z' BREAK BY 'all' HINT('timeseries');
select Timeseries BREAK BY ‘minute’ and limit
SELECT LONG_SUM(count) AS count FROM weibovolence WHERE interval BETWEEN '2015-09-17T14:01:00.000Z' AND '2015-09-17T14:15:05.832Z' BREAK BY 'minute' HINT('timeseries') limit10;
注意:druid 查询的核心是聚合,基本上所有的查询都需要通过LONG_SUM、DOUNLE_SUM函数以及group by来聚合
总结:druid sql 与比较类似,但与列的类型区分不一样。在druid中,大体划分为三种类型,Implicit_Dimension、Dimension、Metric
之所以Dimension类型不能直接查询,是跟druid底层存储有关,Implicit_Dimension\Metric一般是采用lz4压缩算法直接压缩,而Dimension是采用位图的方式存储,因此Dimension中的列能高效的支持and和or操作。
0 0
- druid.io sql支持
- druid.io中文版文档
- druid.io分享PPT
- Druid.io系列
- druid.io可视化调研
- Druid:Druid.io 部署&使用文档
- 第二章:druid.io组成部分
- logoOLAP 数据存储系统 Druid-IO
- Druid用于sql解析
- Druid.io系列(三): Druid集群节点
- druid打印error的sql
- big data for realtime (druid.io)
- 第三章:初体验druid.io引擎
- 第四章:druid.io的功能
- 第五章:druid.io的应用场景
- druid.io中国社区群信息
- Linux_Shell druid.io 集群启动脚本
- Druid.io系列(一):简介
- Opencv实现曼水填充算法-floodFill函数
- [转]腾讯计费平台部分布式MySQL数据库TDSQL架构分析
- 杭电1010-Tempter of the Bone(BFS)
- Leetcode: Product of Array Except Self (60ms) analysis and solution
- vm虚拟机本地连接已连接上 但为什么上不去网
- druid.io sql支持
- Linux2.6.32驱动笔记(3)分析应用程序read访问驱动过程
- 关于阅读那些大神的开源库的一些感想
- UI树
- python面向对象
- Android学习——Frame动画、Shape动画
- 微信支付之认识微信支付开发
- C#方便操作数据总结
- SQL Server中的三种物理连接图文解析:Loop Join,Merge Join,Hash Join