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java操作elasticsearch的案例解析

更新時(shí)間：2019年10月29日 15:00:50 作者：❤小蝦米❤

這篇文章主要介紹了java操作elasticsearch的案例解析,文中通過(guò)示例代碼介紹的非常詳細(xì)，對(duì)大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價(jià)值,需要的朋友可以參考下

到目前為止，我們一直都是使用RESTful風(fēng)格的 API操作elasticsearch服務(wù)，但是通過(guò)我們之前的學(xué)習(xí)知道，elasticsearch提供了很多語(yǔ)言的客戶端用于操作elasticsearch服務(wù)，例如：java、python、.net、JavaScript、PHP等。而我們此次就學(xué)習(xí)如何使用java語(yǔ)言來(lái)操作elasticsearch服務(wù)。在elasticsearch的官網(wǎng)上提供了兩種java語(yǔ)言的API，一種是Java Transport Client，一種是Java REST Client。

而Java REST Client又分為Java Low Level REST Client和Java High Level REST Client，Java High Level REST Client是在Java Low Level REST Client的基礎(chǔ)上做了封裝，使其以更加面向?qū)ο蠛筒僮鞲颖憷姆绞秸{(diào)用elasticsearch服務(wù)。

官方推薦使用Java High Level REST Client，因?yàn)樵趯?shí)際使用中，Java Transport Client在大并發(fā)的情況下會(huì)出現(xiàn)連接不穩(wěn)定的情況。

那接下來(lái)我們就來(lái)看看elasticsearch提供的Java High Level REST Client（以下簡(jiǎn)稱高級(jí)REST客戶端）的一些基礎(chǔ)的操作，跟多的操作大家自行閱讀elasticsearch的官方文檔：https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high.html在官網(wǎng)上已經(jīng)對(duì)高級(jí)REST客戶端的各種API做了很詳細(xì)的使用說(shuō)明，我們這篇文章主要還是翻譯官網(wǎng)上的內(nèi)容，先讓大家以更友好的中文文檔方式入門(mén)，等大家熟悉了這些API之后在查閱官網(wǎng)。

1.基本過(guò)濾查詢

long start = System.currentTimeMillis();
long end = start - 4 * 60 * 60 * 1000;
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("timestamp").from(end,true).to(start,true);
QueryBuilder s=QueryBuilders.boolQuery().must(rangeQueryBuilder);
QueryBuilder qb=new MatchAllQueryBuilder();
SearchResponse response= elasticsearchTemplate.getClient().prepareSearch("monitoring-cpu").setTypes("cloud-cpu").setQuery(s).setFrom(0)
　　.setSize(100).get();
SearchHits searchHits = response.getHits();
for(SearchHit hit:searchHits.getHits()){
　　System.out.println(hit.getSourceAsString());
}

2.條件過(guò)濾，進(jìn)然后行分組，對(duì)組內(nèi)數(shù)據(jù)求平均，然后排行查詢

//ES中查詢所有主機(jī)的監(jiān)控?cái)?shù)據(jù)
    BoolQueryBuilder uuidsBoolQuery = QueryBuilders.boolQuery();

    uuidsBoolQuery.must(QueryBuilders.matchQuery("uuid", uuidStr));

    //暫定向前推一天，計(jì)算平均
    long end = System.currentTimeMillis();
    long start = end - 24 * 60 * 60 * 1000;
    RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("timestamp").from(start,true).to(end,true);
    QueryBuilder timeFilter = QueryBuilders.boolQuery().must(rangeQueryBuilder);

    //開(kāi)始cputop查詢
    //分組字段是id，排序由多個(gè)字段排序組成
    TermsAggregationBuilder orderCpu = AggregationBuilders.terms("group-uuid").field("uuid.keyword").order(Terms.Order.compound(
        Terms.Order.aggregation("avg-cpuuse", true)
    ));

    //求和字段1
    AvgAggregationBuilder avgCpu = AggregationBuilders.avg("avg-cpuuse").field("usage_idle");

    orderCpu.subAggregation(avgCpu);//添加到分組聚合請(qǐng)求中
    orderCpu.size(10);//top10限制

    FilterAggregationBuilder cpuAggregationBuilder = AggregationBuilders.filter("uuidFilter", uuidsBoolQuery)
        .subAggregation(AggregationBuilders.filter("timeFilter",timeFilter).subAggregation(orderCpu));

    SearchResponse response = elasticsearchTemplate.getClient().prepareSearch("monitoring-cpu").setTypes("cloud-cpu")
        .addAggregation(cpuAggregationBuilder)
        .get();

    InternalFilter uuidFilterRe = response.getAggregations().get("uuidFilter");
    InternalFilter timeFilterRe = uuidFilterRe.getAggregations().get("timeFilter");

    Terms tms = timeFilterRe.getAggregations().get("group-uuid");
    //遍歷每一個(gè)分組的key
    for(Terms.Bucket tbb:tms.getBuckets()){
      //獲取count的和
      InternalAvg avg = tbb.getAggregations().get("avg-cpuuse");
      for (Map userResource : userResources) {
        Object uuid = userResource.get("uuid");
        if (uuid != null && !"".equals(uuid.toString())){
          if (uuid.equals(tbb.getKey())){
            userResource.put("cupPercent",numberFormat.format(100.0 - avg.getValue()));
            cpuSort.add(userResource);
          }
        }
      }
    }

3.過(guò)濾聚合求平均查詢

//ES中查詢所有主機(jī)的監(jiān)控?cái)?shù)據(jù)
    BoolQueryBuilder uuidsBoolQuery = QueryBuilders.boolQuery();

    uuidsBoolQuery.must(QueryBuilders.matchQuery("uuid", "1,2,4"));

    //暫定向前推一天，計(jì)算平均
    long end = System.currentTimeMillis();
    long start = end - 24 * 60 * 60 * 1000;
    RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("timestamp").from(start,true).to(end,true);
    QueryBuilder timeFilter = QueryBuilders.boolQuery().must(rangeQueryBuilder);

    //開(kāi)始查詢Cpu平均使用率
    FilterAggregationBuilder cpuAggregationBuilder = AggregationBuilders.filter("uuidFilter", uuidsBoolQuery)
        .subAggregation(AggregationBuilders.filter("timeFilter",timeFilter)
            .subAggregation(AggregationBuilders.avg("avgCpu").field("usage_idle")));


    SearchResponse response = elasticsearchTemplate.getClient().prepareSearch("monitoring-cpu").setTypes("cloud-cpu")
        .addAggregation(cpuAggregationBuilder)
        .get();

    InternalFilter uuidFilterRe = response.getAggregations().get("uuidFilter");
    InternalFilter timeFilterRe = uuidFilterRe.getAggregations().get("timeFilter");
    InternalAvg avgCpuRe = timeFilterRe.getAggregations().get("avgCpu");

    String cpupercent = "0.00";
    if (!"NaN".equals(avgCpuRe.getValue() + "")){
      cpupercent = numberFormat.format(100.0 - avgCpuRe.getValue());
    }

以上就是本文的全部?jī)?nèi)容，希望對(duì)大家的學(xué)習(xí)有所幫助，也希望大家多多支持腳本之家。

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