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Elasticsearch 2.2.0 JAVA开发篇:搜索操作

时间:2016-02-20 10:34:59      阅读:285      评论:0      收藏:0      [点我收藏+]

标签:elasticsearch 赛克蓝德 日志分析 secilog

普通查询

    Elasticsearch java API同时提供了强大的搜索功能,不过这也是很正常的因为所有的http接口到后面都要转换成java代码才可以执行。索引名和type名称都可以是多个,用逗号分开。

SearchRequestBuilder  sbuilder = client.prepareSearch("secilog") //index name

        .setTypes( "type") //type name

        .setSearchType(SearchType.DFS_QUERY_THEN_FETCH)

        .setQuery(QueryBuilders.termQuery("message", "insert")) // Query         

        .setPostFilter(QueryBuilders.rangeQuery("eventCount").from(1).to(18))// Filter

        .setFrom(0).setSize(60).setExplain(true);

System.out.println(sbuilder.toString());

SearchResponse response = sbuilder.execute().actionGet();

System.out.println(response.toString());

    SearchRequestBuilder就是请求的json字符串的解析后的对象,如果想看json数据非常简单,主要把这个对象打印出来就可以,例如上面例子中的System.out.println(sbuilder.toString());


比如我这里打印出的结果见下面,是不是很强大:

{

  "from" : 0,

  "size" : 60,

  "query" : {

    "term" : {

      "message" : "insert"

    }

  },

  "post_filter" : {

    "range" : {

      "eventCount" : {

        "from" : 1,

        "to" : 18,

        "include_lower" : true,

        "include_upper" : true

      }

    }

  },

  "explain" : true

}

    SearchResponse是搜索出来的结果,同样可以把这个对象打印出来看一下搜索的结果。下面是我搜索的部分内容:

{

  "took" : 1,

  "timed_out" : false,

  "_shards" : {

    "total" : 1,

    "successful" : 1,

    "failed" : 0

  },

  "hits" : {

    "total" : 1,

    "max_score" : 0.15342641,

    "hits" : [ {

      "_shard" : 0,

      "_node" : "jevOQqVQT_a_pAGqKA0p7w",

      "_index" : "secilog",

      "_type" : "log",

      "_id" : "1",

      "_score" : 0.15342641,

      "_source" : {

        "type" : "syslog",

        "eventCount" : 1,

        "eventDate" : "2016-02-18T06:13:10.818Z",

        "message" : "secilog insert doc test"

      },

      "_explanation" : {

      .......

      }

    } ]

  }

}

需要注意的是,上面例子中的参数都可以忽略,例如可以查询全部:

SearchResponse response = client.prepareSearch().execute().actionGet();


查询总数

    查询总数和普通查询语法一样,唯一的就是把size设置为0。

SearchRequestBuilder  sbuilder = client.prepareSearch("secilog") //index name

        .setTypes( "type") //type name

        .setSearchType(SearchType.DFS_QUERY_THEN_FETCH)

        .setQuery(QueryBuilders.termQuery("message", "insert"))        // Query

        .setPostFilter(QueryBuilders.rangeQuery("eventCount").from(1).to(18)) // Filter

        .setFrom(0).setSize(0).setExplain(true);

System.out.println(sbuilder.toString());

SearchResponse response = sbuilder.execute().actionGet();

System.out.println(response.toString());

System.out.println(response.getHits().getTotalHits());

返回的内容:

{

  "took" : 1,

  "timed_out" : false,

  "_shards" : {

    "total" : 1,

    "successful" : 1,

    "failed" : 0

  },

  "hits" : {

    "total" : 2,

    "max_score" : 0.0,

    "hits" : [ ]

  }

}

滚动查询scroll

    具体说明详见文章Elasticsearch 2.20 滚动查询请求,通过java也是比较方便的得到此信息。

QueryBuilder qb = QueryBuilders.termQuery("message", "insert");

SearchRequestBuilder  sbuilder = client.prepareSearch(indexName)

        .setSearchType(SearchType.SCAN)

        .setScroll(new TimeValue(60000))

        .setQuery(qb)

        .setSize(100);

System.out.println(sbuilder);

//100 hits per shard will be returned for each scroll

SearchResponse scrollResp = sbuilder.execute().actionGet(); 

while (true) {

    for (SearchHit hit : scrollResp.getHits().getHits()) {

        System.out.println(hit.getSource());

    }

    

    scrollResp = client.prepareSearchScroll(scrollResp.getScrollId())

    .setScroll(new TimeValue(60000)).execute().actionGet();

    System.out.println(scrollResp);

    //Break condition: No hits are returned

    if (scrollResp.getHits().getHits().length == 0) {

        break;

    }

}

我们同样可以打印一下请求的记录和返回的内容。

{

  "size" : 100,

  "query" : {

    "term" : {

      "message" : "insert"

    }

  }

}

{

  "_scroll_id" : "c2NhbjswOzE7dG90YWxfaGl0czoyOw==",

  "took" : 3,

  "timed_out" : false,

  "_shards" : {

    "total" : 1,

    "successful" : 1,

    "failed" : 0

  },

  "hits" : {

    "total" : 2,

    "max_score" : 0.0,

    "hits" : [ {

      "_index" : "secilog",

      "_type" : "log",

      "_id" : "1",

      "_score" : 0.0,

      "_source" : {

        "type" : "file",

        "eventCount" : 1,

        "eventDate" : "2016-02-18T06:13:10.818Z",

        "message" : "secilog insert doc test"

      }

    }, {

      "_index" : "secilog",

      "_type" : "log",

      "_id" : "3",

      "_score" : 0.0,

      "_source" : {

        "type" : "syslog",

        "eventCount" : 2,

        "eventDate" : "2016-02-18T06:19:59.015Z",

        "message" : "secilog insert doc test"

      }

    } ]

  }

}

本文由赛克 蓝德(secisland)原创,转载请标明作者和出处。


简单的汇聚查询

SearchRequestBuilder  sbuilder = client

        .prepareSearch(indexName)

        .setQuery(QueryBuilders.matchAllQuery())

        .addAggregation(AggregationBuilders.terms("type").field("type"))

        .addAggregation(

            AggregationBuilders.dateHistogram("eventDate").field("eventDate")

            .interval(DateHistogramInterval.YEAR));

System.out.println(sbuilder);

 

SearchResponse sr = sbuilder.execute().actionGet();

System.out.println(sr);

// Get your facet results

StringTerms agg1 = sr.getAggregations().get("type");

System.out.println(agg1.getBuckets().get(0).getKeyAsString()+":"

+agg1.getBuckets().get(0).getDocCount());

InternalHistogram<?> agg2 = sr.getAggregations().get("eventDate");

List<? extends Histogram.Bucket> bucketList = ((Histogram) agg2).getBuckets();

System.out.println(bucketList.get(0).getKeyAsString()+":"

+bucketList.get(0).getDocCount());

然后我们看一下请求的参数:

{

  "query" : {

    "match_all" : { }

  },

  "aggregations" : {

    "type" : {

      "terms" : {

        "field" : "type"

      }

    },

    "eventDate" : {

      "date_histogram" : {

        "field" : "eventDate",

        "interval" : "1y"

      }

    }

  }

}

返回的结果:

{

  "took" : 16,

  "timed_out" : false,

  "_shards" : {

    "total" : 1,

    "successful" : 1,

    "failed" : 0

  },

  "hits" : {

    "total" : 2,

    "max_score" : 1.0,

    "hits" : [ {

      "_index" : "secilog",

      "_type" : "log",

      "_id" : "1",

      "_score" : 1.0,

      "_source" : {

        "type" : "file",

        "eventCount" : 1,

        "eventDate" : "2016-02-18T06:13:10.818Z",

        "message" : "secilog insert doc test"

      }

    }, {

      "_index" : "secilog",

      "_type" : "log",

      "_id" : "3",

      "_score" : 1.0,

      "_source" : {

        "type" : "syslog",

        "eventCount" : 2,

        "eventDate" : "2016-02-18T06:19:59.015Z",

        "message" : "secilog insert doc test"

      }

    } ]

  },

  "aggregations" : {

    "eventDate" : {

      "buckets" : [ {

        "key_as_string" : "2016-01-01T00:00:00.000Z",

        "key" : 1451606400000,

        "doc_count" : 2

      } ]

    },

    "type" : {

      "doc_count_error_upper_bound" : 0,

      "sum_other_doc_count" : 0,

      "buckets" : [ {

        "key" : "file",

        "doc_count" : 1

      }, {

        "key" : "syslog",

        "doc_count" : 1

      } ]

    }

  }

}

从上面可以看出,java接口的功能是非常强大的。

    赛克蓝德(secisland)后续会逐步对Elasticsearch的最新版本的各项功能进行分析,近请期待。也欢迎加入secisland公众号进行关注。


Elasticsearch 2.2.0 JAVA开发篇:搜索操作

标签:elasticsearch 赛克蓝德 日志分析 secilog

原文地址:http://zhulinu.blog.51cto.com/539189/1743550

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