ElasticHD SQL Features Support:Beyond SQL Features Support：SQL Usage

ElasticHD SQL Features Support:Beyond SQL Features Support：SQL Usage 介绍

ElasticHD 是一款 ElasticSearch的可视化应用。不依赖ES的插件安装，更便捷；导航栏直接填写对应的ES
IP和端口就可以操作Es了。目前支持如下功能：

ES Real time data search
ES Dashboard data visualization
ES Index Template (在线修改、查看、上传）
ES Indices Index deletion and search
sql Converts to Elasticsearch DSL
ES 基本查询文档

Installation

Precompiled binaries for
supported operating systems are available.

Basic Usage

linux and MacOs use ElasticHD
```
下载对应的elasticHD版本，unzip xxx_elasticHd_xxx.zip
```
修改权限 chmod 0777 ElasticHD
可指定ip端口运行elastichd ./ElasticHD -p 127.0.0.1:9800 默认 ip和端口也是这个

windows

直接下载对应windows版本,解压，双击运行。当然想指定端口的话同linux

Es version support

测试过elasticsearch 1.5版本到5.2.1的版本都能正常使用。关于 sql 转化成 dsl 马上会出elasticHD
1.1版本修复一些兼容性错误。

Contributing

Contributions are welcome! Open a pull request to fix a bug, or open an issue
to discuss a new feature or change.

ElasticHD sql Converts to ElasticSearch DSL Usage

sql Features Support:

[x] sql Select
[x] sql Where
[x] sql Order Bysql
[x] sql Group By
[x] sql AND & OR
[x] sql Like & NOT Like
[x] sql COUNT distinct
[x] sql In & Not In
[x] sql Between
[x] sql avg()、count(*), count(field), min(field), max(field)

Beyond sql Features Support：

[x] ES TopHits
[x] ES date_histogram
[x] ES STATS
[x] ES RANGE
[x] ES DATE_RANGE

Improvement : Now the query DSL is much more flat

sql Usage

Query

select * from test where a=1 and b="c" and create_time between '2015-01-01T00:00:00+0800' and '2016-01-01T00:00:00+0800' and process_id > 1 order by id desc limit 100,10

Aggregation

select avg(age),min(age),max(age),count(student),count(distinct student) from test group by grade,class limit 10

Beyond sql

range age group 20-25,25-30,30-35,35-40

 SELECT COUNT(age) FROM bank GROUP BY range(age, 20,25,30,35,40)

range date group by your config

 SELECT online FROM online GROUP BY date_range(field="insert_time",format="yyyy-MM-dd" ,"2014-08-18","2014-08-17","Now-8d","Now-7d","Now-6d","Now")

range date group by day

select * from test group by date_histogram(field="changeTime",interval="1h",format="yyyy-MM-dd HH