Elasticsearch聚合查询案例分享
1.案例介绍
统计特定时间范围内每个应用的总访问量、访问成功数、访问失败数,每个应用请求响应时间分段统计(1秒内,1-3秒,3-5秒,5秒以上
2.准备工作
参考文档《 高性能elasticsearch ORM开发库使用介绍》中的第1章节和第2章节,在自己的工程中导入bboss es依赖包和配置es参数
3.定义统计dsl
在源码目录下新建文件esmapper/estrace/ESTracesMapper.xml,内容如下
4.编写统计dao及统计方法
5.执行测试用例
6.获取元数据信息的测试方法
7.相关资料
高性能elasticsearch ORM开发库使用介绍
https://my.oschina.net/bboss/blog/1556866
bboss elasticsearch交流群:166471282
1.案例介绍
统计特定时间范围内每个应用的总访问量、访问成功数、访问失败数,每个应用请求响应时间分段统计(1秒内,1-3秒,3-5秒,5秒以上
2.准备工作
参考文档《 高性能elasticsearch ORM开发库使用介绍》中的第1章节和第2章节,在自己的工程中导入bboss es依赖包和配置es参数
3.定义统计dsl
在源码目录下新建文件esmapper/estrace/ESTracesMapper.xml,内容如下
<properties> <!-- 应用汇总统计:总访问量,成功数,失败数 bboss es dao通过名称applicationSumStatic引用脚本 --> <property name="applicationSumStatic"> <![CDATA[ { "query": { "bool": { "filter": [ #if($channelApplications && $channelApplications.size() > 0) { "terms": { "applicationName.keyword": [ #foreach($application in $channelApplications) #if($velocityCount > 0),#end $application.applicationName #end ] } }, #end {"range": { "startTime": { "gte": #[startTime],##统计开始时间 "lt": #[endTime] ##统计截止时间 } } } ] } }, "size":0, "aggs": { "applicationsums": { "terms": { "field": "applicationName.keyword",##按应用名称进行统计计数 "size":10000 }, "aggs":{ "successsums" : { "terms" : { "field" : "err" ##按err标识统计每个应用的成功数和失败数,0标识成功,1标识失败 } }, "elapsed_ranges" : { "range" : { "field" : "elapsed", ##按响应时间分段统计 "keyed" : true, "ranges" : [ { "key" : "1秒", "to" : 1000 }, { "key" : "3秒", "from" : 1000, "to" : 3000 }, { "key" : "5秒", "from" : 3000, "to" : 5000 }, { "key" : "5秒以上", "from" : 5000 } ] } } } } } } ]]> </property> </properties>
4.编写统计dao及统计方法
public class TraceESDao { public List<ApplicationStatic> getApplicationSumStatic(TraceExtraCriteria traceExtraCriteria){ init(); //返回json统计报文,调试用,一遍根据json报文组装统计结果列表 // String response = clientUtil.executeRequest("trace-*/_search", // "applicationSumStatic",traceExtraCriteria); //根据条件进行统计,在对象traceExtraCriteria中指定开始时间和结束时间 MapRestResponse restResponse = clientUtil.search("trace-*/_search", "applicationSumStatic",traceExtraCriteria); //组装统计结果 //获取应用统计列表,包含每个应用的名称、总访问量以及成功数和失败数 List<Map<String,Object>> appstatics = (List<Map<String,Object>>)restResponse.getAggBuckets("applicationsums"); if(appstatics != null && appstatics.size() > 0) { List<ApplicationStatic> applicationStatics = new ArrayList<ApplicationStatic>(appstatics.size()); ApplicationStatic applicationStatic = null; for (int i = 0; i < appstatics.size(); i++) { applicationStatic = new ApplicationStatic(); Map<String, Object> map = appstatics.get(i); //应用名称 String appName = (String) map.get("key"); applicationStatic.setApplicationName(appName); //应用总访问量 Long totalsize = ResultUtil.longValue( map.get("doc_count"),0l); applicationStatic.setTotalSize(totalsize); //获取成功数和失败数 List<Map<String, Object>> appstatic = (List<Map<String, Object>>)ResultUtil.getAggBuckets(map, "successsums"); /** "buckets": [ { "key": 0, "doc_count": 30 } ] */ //key 0 Long success = 0l;//成功数 Long failed = 0l;//失败数 for (int j = 0; j < appstatic.size(); j++) { Map<String, Object> stats = appstatic.get(j); Integer key = (Integer) stats.get("key");//成功和错误标识 if (key == 0)//成功 success = ResultUtil.longValue( stats.get("doc_count"),0l); else if (key == 1)//失败 failed = ResultUtil.longValue( stats.get("doc_count"),0l); } applicationStatic.setSuccessCount(success); applicationStatic.setFailCount(failed); List<ApplicationPeriodStatic> applicationPeriodStatics = new ArrayList<ApplicationPeriodStatic>(4); ApplicationPeriodStatic applicationPeriodStatic = null; //获取响应时间分段统计信息 Map<String, Map<String, Object>> appPeriodstatic = (Map<String, Map<String, Object>>)ResultUtil.getAggBuckets(map, "elapsed_ranges"); //1秒 Map<String, Object> period = appPeriodstatic.get("1秒"); applicationPeriodStatic = new ApplicationPeriodStatic(); applicationPeriodStatic.setPeriod("1秒"); applicationPeriodStatic.setDocCount(ResultUtil.longValue(period.get("doc_count"),0l)); applicationPeriodStatic.setTo(ResultUtil.intValue(period.get("to"),1000)); applicationPeriodStatics.add(applicationPeriodStatic); //3秒 period = appPeriodstatic.get("3秒"); applicationPeriodStatic = new ApplicationPeriodStatic(); applicationPeriodStatic.setPeriod("3秒"); applicationPeriodStatic.setDocCount(ResultUtil.longValue(period.get("doc_count"),0l)); applicationPeriodStatic.setFrom(ResultUtil.intValue(period.get("from"),1000)); applicationPeriodStatic.setTo(ResultUtil.intValue(period.get("to"),3000)); applicationPeriodStatics.add(applicationPeriodStatic); //5秒 period = appPeriodstatic.get("5秒"); applicationPeriodStatic = new ApplicationPeriodStatic(); applicationPeriodStatic.setPeriod("5秒"); applicationPeriodStatic.setDocCount(ResultUtil.longValue(period.get("doc_count"),0l)); applicationPeriodStatic.setFrom(ResultUtil.intValue(period.get("from"),3000)); applicationPeriodStatic.setTo(ResultUtil.intValue(period.get("to"),5000)); applicationPeriodStatics.add(applicationPeriodStatic); //5秒以上 period = appPeriodstatic.get("5秒以上"); applicationPeriodStatic = new ApplicationPeriodStatic(); applicationPeriodStatic.setPeriod("5秒以上"); applicationPeriodStatic.setDocCount(ResultUtil.longValue(period.get("doc_count"),0l)); applicationPeriodStatic.setFrom(ResultUtil.intValue(period.get("from"),5000)); applicationPeriodStatics.add(applicationPeriodStatic); applicationStatic.setApplicationPeriodStatics(applicationPeriodStatics); applicationStatics.add(applicationStatic); } //返回统计结果 return applicationStatics; } return null; } }
5.执行测试用例
@Test public void testAppliationstaticList(){ TraceExtraCriteria traceExtraCriteria = new TraceExtraCriteria(); traceExtraCriteria.setStartTime(1516304868072l);//以long方式设置统计开始时间,Date的getTime方法获取 traceExtraCriteria.setEndTime(1516349516377l);//以long方式设置统计截止时间,Date的getTime方法获取 TraceESDao traceESDao = new TraceESDao();//定义dao组件 List<ApplicationStatic> applicationStatics = traceESDao.getApplicationSumStatic(traceExtraCriteria); System.out.println(applicationStatics.size()); }
6.获取元数据信息的测试方法
@Test public void testAppStatic(){ TraceExtraCriteria traceExtraCriteria = new TraceExtraCriteria(); traceExtraCriteria.setStartTime(1516304868072l); traceExtraCriteria.setEndTime(1516349516377l); ClientInterface clientUtil = ElasticSearchHelper.getConfigRestClientUtil("esmapper/estrace/ESTracesMapper.xml"); //通过下面的方法先得到查询的json报文,然后再通过MapRestResponse查询遍历结果,调试的时候打开String response的注释 //String response = clientUtil.executeRequest("trace-*/_search","applicationSumStatic",traceExtraCriteria); //System.out.println(response); MapRestResponse restResponse = clientUtil.search("trace-*/_search","applicationSumStatic",traceExtraCriteria); List<Map<String,Object>> appstatics = restResponse.getAggBuckets("applicationsums",new ESTypeReference<List<Map<String,Object>>>(){}); int doc_count_error_upper_bound = restResponse.getAggAttribute("applicationsums","doc_count_error_upper_bound",int.class); int sum_other_doc_count = restResponse.getAggAttribute("applicationsums","sum_other_doc_count",int.class); System.out.println("doc_count_error_upper_bound:"+doc_count_error_upper_bound); System.out.println("sum_other_doc_count:"+sum_other_doc_count); for(int i = 0; i < appstatics.size(); i ++){ Map<String,Object> map = appstatics.get(i); //应用名称 String appName = (String)map.get("key"); //应用总访问量 int totalsize = (int)map.get("doc_count"); //获取成功数和失败数 List<Map<String,Object>> appstatic = ResultUtil.getAggBuckets(map ,"successsums",new ESTypeReference<List<Map<String,Object>>>(){}); doc_count_error_upper_bound = ResultUtil.getAggAttribute(map ,"successsums","doc_count_error_upper_bound",int.class); sum_other_doc_count = ResultUtil.getAggAttribute(map ,"successsums","sum_other_doc_count",int.class); System.out.println("doc_count_error_upper_bound:"+doc_count_error_upper_bound); System.out.println("sum_other_doc_count:"+sum_other_doc_count); /** "buckets": [ { "key": 0, "doc_count": 30 } ] */ //key 0 int success = 0;//成功数 int failed = 0;//失败数 for(int j = 0; j < appstatic.size(); i ++){ Map<String,Object> stats = appstatic.get(i); int key = (int) stats.get("key");//成功和错误标识 if(key == 0) success = (int)stats.get("doc_count"); else if(key == 1) failed = (int)stats.get("doc_count"); } } }
7.相关资料
高性能elasticsearch ORM开发库使用介绍
https://my.oschina.net/bboss/blog/1556866
bboss elasticsearch交流群:166471282