es的普通查询是通过某些条件来查询满足的文档,percolator则不同,先是注册一些条件,然后查询一条文档是否满足其中的某些条件。
es的percolator特性在数据分类、数据路由、事件监控和预警方面都有很好的应用。
第一步是建立名为percolate的索引,包含一个字段message
curl -XPUT ‘localhost:9200/percolate‘ -d‘{ "mappings":{ "my_type":{ "properties":{ "message":{ "type":"string" } } } } }‘
第二步,注册一个percolator查询
第三步,构建查询
第四步,查看是否有匹配的条件
第二步到第四步的代码如下,代码基于es 2.1版本:
QueryBuilder qb = QueryBuilders.termQuery("message", "bonsai"); try { //Index the query = register it in the percolator //把查询条件添加到索引中,myDesignatedQueryName为定义的查询名 client.prepareIndex("percolate", ".percolator", "myDesignatedQueryName") .setSource( XContentFactory.jsonBuilder() .startObject() // Register the query,添加查询记录 .field("query", qb) .endObject()) .setRefresh(true) // Needed when the query shall be available immediately .execute().actionGet(); //上面的term查询定义名为:myDesignatedQueryName XContentBuilder docBuilder = XContentFactory.jsonBuilder().startObject(); //This is needed to designate the document docBuilder.field("doc").startObject(); docBuilder.field("message", "A new bonsai tree in the office"); docBuilder.endObject(); docBuilder.endObject(); //Percolate查询 PercolateResponse response = client.preparePercolate() .setIndices("percolate") .setDocumentType("message") .setSource(docBuilder).execute().actionGet(); //获取查询query后处理逻辑 for(PercolateResponse.Match match : response) { //创建percolate时指定的ID,根据查询ID在做相应的操作 System.out.println("percolate ID: "+match.getId()); System.out.println("percolate Index Name: " +match.getIndex()); } } catch (ElasticsearchException e) { e.printStackTrace(); } catch (IOException e) { e.printStackTrace(); }
输出结果为:
percolate ID: myDesignatedQueryName
percolate Index Name: percolate
时间: 2024-10-30 00:40:47