SQL to Java code for Elasticsearch
Elasticsearch虽然定位为Search Engine,但是因其可以持久化数据,很多时候,我们把Elasticsearch当成Database用,但是Elasticsearch不支持SQL,就需要把SQL逻辑转换成代码实现对应的功能。
以下列举了一些常用的SQL转换成对应的Java代码。
1.按某个field group by查询count
SELECT
fieldA, COUNT(fieldA)
from table
WHERE fieldC = "hoge"
AND fieldD = "huga"
AND fieldB > 10
AND fieldB < 100
group by fieldA;
对应的java code:
SearchRequestBuilder searchReq = client.prepareSearch("sample_index");
searchReq.setTypes("sample_types");
TermsBuilder termsb = AggregationBuilders.terms("my_fieldA").field("fieldA").size(100); BoolFilterBuilder bf = FilterBuilders.boolFilter();
TermFilterBuilder tf_fieldC = FilterBuilders.termFilter("fieldC","hoge");
TermFilterBuilder tf_fieldD = FilterBuilders.termFilter("fieldD","huga");
bf.must(tf_fieldC);
bf.must(tf_fieldD); RangeFilterBuilder rangefieldBFilter = FilterBuilders.rangeFilter("fieldB")
.gt(10)
.lt(100); searchReq.setQuery(QueryBuilders.filteredQuery(QueryBuilders.matchAllQuery(),
FilterBuilders.andFilter(bf, rangefieldBFilter))).addAggregation(
termsb);
SearchResponse searchRes = searchReq.execute().actionGet(); Terms fieldATerms = searchRes.getAggregations().get("my_fieldA");
for (Terms.Bucket filedABucket : fieldATerms.getBuckets()) {
//fieldA
String fieldAValue = filedABucket.getKey(); //COUNT(fieldA)
long fieldACount = filedABucket.getDocCount();
}
2. 按某个field 和 date group by 并查询另一个filed的sum,时间统计图,时间间隔是1天。
SELECT
DATE(create_at), fieldA, SUM(fieldB)
from table
group by DATE(create_at), fieldA;
对应的java code:
SearchRequestBuilder searchReq = client.prepareSearch("sample_index");
searchReq.setTypes("sample_types");
DateHistogramBuilder dhb = AggregationBuilders.dateHistogram("my_datehistogram").field("create_at").interval(DateHistogram.Interval.days(1));
TermsBuilder termsb_fa = AggregationBuilders.terms("my_fieldA").field("fieldA").size(100);
termsb_fa.subAggregation(AggregationBuilders.sum("my_sum_fieldB").field("fieldB"));
dhb.subAggregation(termsb_fa) searchReq.setQuery(QueryBuilders.matchAllQuery()).addAggregation(dhb);
SearchResponse searchRes = searchReq.execute().actionGet(); DateHistogram dateHist = searchRes.getAggregations().get("my_datehistogram");
for (DateHistogram.Bucket dateBucket : dateHist.getBuckets()) {
//DATE(create_at)
String create_at = dateentry.getKey();
Terms fieldATerms = dateBucket.getAggregations().get("my_fieldA");
for (Terms.Bucket filedABucket : fieldATerms.getBuckets()) {
//fieldA
String fieldAValue = filedABucket.getKey(); //SUM(fieldB)
Sum sumagg = filedABucket.getAggregations().get("my_sum_fieldB");
long sumFieldB = (long)sumagg.getValues();
}
}
3. 按两个field group by并查询第三个filed的sum
SELECT
fieldA, fieldC, SUM(fieldB)
from table
group by fieldA, fieldC;
对应的java code:
SearchRequestBuilder searchReq = client.prepareSearch("sample_index");
searchReq.setTypes("sample_types"); TermsBuilder termsb_fa = AggregationBuilders.terms("my_fieldA").field("fieldA").size(100);
TermsBuilder termsb_fc = AggregationBuilders.terms("my_fieldC").field("fieldC").size(50); termsb_fc.subAggregation(AggregationBuilders.sum("my_sum_fieldB").field("fieldB"));
termsb_fa.subAggregation(termsb_fc) searchReq.setQuery(QueryBuilders.matchAllQuery()).addAggregation(termsb_fa);
SearchResponse searchRes = searchReq.execute().actionGet(); Terms fieldATerms = searchRes.getAggregations().get("my_fieldA");
for (Terms.Bucket filedABucket : fieldATerms.getBuckets()) {
//fieldA
String fieldAValue = filedABucket.getKey();
Terms fieldCTerms = filedABucket.getAggregations().get("my_fieldC");
for (Terms.Bucket filedCBucket : fieldCTerms.getBuckets()) {
//fieldC
String fieldCValue = filedCBucket.getKey(); //SUM(fieldB)
Sum sumagg = filedCBucket.getAggregations().get("my_sum_fieldB");
long sumFieldB = (long)sumagg.getValues();
}
}
4. 按某个filed group by 并查询count、sum 和 average
SELECT
fieldA, COUNT(fieldA), SUM(fieldB), AVG(fieldB)
from table
group by fieldA;
对应的java code:
SearchRequestBuilder searchReq = client.prepareSearch("sample_index");
searchReq.setTypes("sample_types"); TermsBuilder termsb = AggregationBuilders.terms("my_fieldA").field("fieldA").size(100);
termsb.subAggregation(AggregationBuilders.sum("my_sum_fieldB").field("fieldB"));
termsb.subAggregation(AggregationBuilders.avg("my_avg_fieldB").field("fieldB")); searchReq.setQuery(QueryBuilders.matchAllQuery()).addAggregation(termsb);
SearchResponse searchRes = searchReq.execute().actionGet();
Terms fieldATerms = searchRes.getAggregations().get("my_fieldA");
for (Terms.Bucket filedABucket : fieldATerms.getBuckets()) {
//fieldA
String fieldAValue = filedABucket.getKey(); //COUNT(fieldA)
long fieldACount = filedABucket.getDocCount(); //SUM(fieldB)
Sum sumagg = filedABucket.getAggregations().get("my_sum_fieldB");
long sumFieldB = (long)sumagg.getValues(); //AVG(fieldB)
Avg avgagg = filedABucket.getAggregations().get("my_avg_fieldB");
double avgFieldB = avgagg.getValues();
}
5. 按某个field group by 并按另一个filed的Sum排序,获取前10
SELECT
fieldA, SUM(fieldB)
from table
WHERE fieldC = "hoge"
group by fieldA
order by SUM(fieldB) DESC
limit 10;
对应的java code:
QueryBuilder termsc = QueryBuilders.termQuery("fieldC","hoge");
QueryBuilder queryBuilder = QueryBuilders.boolQuery().must(termsc);
TermsAggregationBuilder aggregationBuilder = AggregationBuilders.terms("my_fieldA").field("fieldA").size(10);
aggregationBuilder.subAggregation(AggregationBuilders.sum("my_sum_fieldB").field("fieldB"));
aggregationBuilder.order(Order.aggregation("my_sum_fieldB", false));
SearchResponse searchResponse = client.prepareSearch("sample_index").setQuery(queryBuilder).addAggregation(aggregationBuilder).execute().actionGet();
Terms terms = searchResponse.getAggregations().get("my_fieldA");
for (Terms.Bucket entry : terms.getBuckets()) {
String fieldAValue = entry.getKey().toString(); Sum sumagg = entry.getAggregations().get("my_sum_fieldB");
double fieldValue = sumagg.getValue();
}
代码在GitHub上:https://github.com/luxiaoxun/Code4Java
SQL to Java code for Elasticsearch的更多相关文章
- Java中使用elasticsearch搜索引擎实现简单查询、修改等操作-已在项目中实际应用
以下的操作环境为:jdk:1.8:elasticsearch:5.2.0 maven架包下载坐标为: <dependency> <groupId>org.elasticsear ...
- A java code
With the help of LiJun I got a piece of JAVA code. With this code, I can do below things like connec ...
- Elasticsearch入门系列~通过Java一系列操作Elasticsearch
Elasticsearch索引的创建.数据的增删该查操作 上一章节已经在Linux系统上安装Elasticsearch并且可以外网访问,这节主要通过Java代码操作Elasticsearch 1.创建 ...
- Java语言编码规范(Java Code Conventions)
Java语言编码规范(Java Code Conventions) 名称 Java语言编码规范(Java Code Conventions) 译者 晨光(Morning) 简介 本文档讲述了Java语 ...
- java code to byte code--partone--reference
Understanding how Java code is compiled into byte code and executed on a Java Virtual Machine (JVM) ...
- [转]Java Code Examples for android.util.JsonReader
[转]Java Code Examples for android.util.JsonReader The following are top voted examples for showing h ...
- JUnit单元测试教程(翻译自Java Code Geeks)
JUnit单元测试教程--终极指南 JUnit单元测试教程终极指南 说明 单元测试简介 1 什么是单元测试 2 测试覆盖 3 Java中的单元测试 JUnit简介 1 使用Eclipse实现简单JUn ...
- Java Code Style
近期困惑于团队成员代码风格迥异,代码质量不可控,作为一名老司机,忧患于后期服务的可维护性,多次一对一的代码Review,耗时耗力不说,效果也不明显.痛定思痛,多次反思之后得出结论:无规矩不成方圆,可靠 ...
- 使用Java客户端操作elasticsearch(二)
承接上文,使用Java客户端操作elasticsearch,本文主要介绍 常见的配置 和Sniffer(集群探测) 的使用. 常见的配置 前面已介绍过,RestClientBuilder支持同时提供一 ...
随机推荐
- 微信小程序学习笔记(阶段二)
二阶段学习过程: (一)看官方文档的框架.组件.API:https://mp.weixin.qq.com/debug/wxadoc/dev/ (二)看极客学院第3.4章视频:http://www.ph ...
- MYSQL数据库学习十二 使用MySQL运算符
12.1 算术运算符 + - * /(DIV) %(MOD) 12.2 比较运算符 > < = <=> != <> >= <= BETWEEN AND ...
- 【Python】 如何用pyinstaller打包python程序成exe
[pyinstaller] pyinstaller在他们的官方网站上下载:http://www.pyinstaller.org/ 下载完pyinstaller之后还要安装一个支持包pywin32. 这 ...
- 小程序之Tab切换
小程序越来越火了,作为一名,额 有理想的攻城狮,当然要紧跟互联网时代的步伐啦,于是我赶紧抽时间学习了一下小程序的开发,顺便把经验分享给大家. 对于申请账号以及安装开发工具等,大家可以看官网:http ...
- 基于FPGA的Cordic算法实现
CORDIC(Coordinate Rotation Digital Computer)算法即坐标旋转数字计算方法,是J.D.Volder1于1959年首次提出,主要用于三角函数.双曲线.指数.对数的 ...
- Property 'id' not found on type java.lang.String
改为 忘写了$符,取不出来,因此报错!
- 在Winform混合式框架中整合外部API接口的调用
在我们常规的业务处理中,一般内部处理的接口多数都是以数据库相关的,基于混合式开发的Winform开发框架,虽然在客户端调用的时候,一般选择也是基于Web API的调用,不过后端我们可能不仅仅是针对我们 ...
- Linux kernel 的 sendfile 是如何提高性能的
Linux kernel 的 sendfile 是如何提高性能的 现在流行的 web 服务器里面都提供 sendfile 选项用来提高服务器性能,那到底 sendfile 是什么,怎么影响性能的呢? ...
- 团队作业4——第一次项目冲刺(Alpha版本)11.14
a. 提供当天站立式会议照片一张 举行站立式会议,讨论项目安排: PM对整个项目的需求进行讲解: 全队对整个项目的细节进行沟通: 对整个项目的开发计划进行分析,分配每天的任务: 统一确定项目的开发环境 ...
- python之路--day15--常用模块之logging模块
常用模块 1 logging模块 日志级别:Noset (不设置) Debug---(调试信息)----也可用10表示 Info--(消息信息)----也可用20表示 Warning---(警告信息) ...