ES高级查询，高亮显示
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package xxx.xxx.xxx.xxx;import org.elasticsearch.action.search.SearchType;import org.elasticsearch.action.search.SearchResponse;import org.elasticsearch.common.text.Text;import org.elasticsearch.search.aggregations.AggregationBuilders;import org.elasticsearch.search.aggregations.Aggregation;import org.elasticsearch.search.aggregations.metrics.avg.InternalAvg;import org.elasticsearch.client.transport.TransportClient;import org.elasticsearch.common.settings.Settings;import org.elasticsearch.common.transport.InetSocketTransportAddress;import org.elasticsearch.common.transport.TransportAddress;import org.elasticsearch.index.query.QueryBuilder;import org.elasticsearch.index.query.QueryBuilders;import org.elasticsearch.search.SearchHit;import org.elasticsearch.search.SearchHits;import org.elasticsearch.search.aggregations.AbstractAggregationBuilder;import org.elasticsearch.search.aggregations.Aggregations;import org.elasticsearch.search.highlight.HighlightField;import org.elasticsearch.search.sort.SortOrder;import org.junit.After;import org.junit.Before;import org.junit.Test;import java.net.InetAddress;import java.net.UnknownHostException;import java.util.Map;/** * ElasticSearch高级查询基本操作 * * 操作的入口TransportClient */public class ElasticSearchQuery { private TransportClient tc; private int port = 9300; private String clusterName = "bigdata"; private String node_1 = "hadoop01"; private String node_2 = "hadoop02"; private String node_3 = "hadoop03"; private String[] indices = {"bigdata","bank"}; @Before public void setUp() throws UnknownHostException { Settings setting = Settings.builder() .put("cluster.name",clusterName) .put("analyzer","ik") .build(); tc = TransportClient.builder().settings(setting).build(); TransportAddress hadoop = new InetSocketTransportAddress(InetAddress.getByName(node_1),port); TransportAddress spark = new InetSocketTransportAddress(InetAddress.getByName(node_2),port); TransportAddress storm = new InetSocketTransportAddress(InetAddress.getByName(node_3),port); tc.addTransportAddresses(hadoop,spark,storm); } /** * 查找包涵Apache的数据信息 */ @Test public void testSearch(){// tc.prepareSearch(indices)// .setSearchType(SearchType.DEFAULT)// .setQuery(QueryBuilders.matchQuery("author", "Apache"))// .get(); SearchResponse response = tc.prepareSearch(indices)//设置要进行查询的方式，有4中查询方式：QUERY_AND_FETCH、QUERY_THEN_FETCH、DFS_QUERY_AND_FETCH、DFS_QUERY_THEN_FETCH .setSearchType(SearchType.DEFAULT)//设置查询的内容，和在哪些字段中进行查询,要通过QueryBuilders来进行设置 .setQuery(QueryBuilders.matchQuery("author", "Apache")) .get(); SearchHits hits = response.getHits(); long totalHits = hits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); for(SearchHit searchHit:hits){ printSearchHit(searchHit); } } @Test public void testSearch_02(){ SearchResponse searchResponse = tc.prepareSearch(indices) .setSearchType(SearchType.DEFAULT) .setQuery(QueryBuilders.prefixQuery("name", "h")) .addSort("name", SortOrder.DESC) .setFrom(0) .setSize(10) .get(); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); for(SearchHit searchHit: hits){ printSearchHit(searchHit); } } /** * 查询年龄在35到40之间的成员信息 */ @Test public void testSearch_03(){ SearchResponse searchResponse = tc.prepareSearch(indices) .setSearchType(SearchType.DEFAULT) .setQuery(QueryBuilders.rangeQuery("age").gte(35).lte(40)) .addSort("balance", SortOrder.DESC) .setFrom(0) .setSize(2) .get(); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); for(SearchHit searchHit:hits){ printSearchHit(searchHit); } } /** * 执行聚合操作 * 查询年龄在35到40之间的平均年龄 */ @Test public void testSearch_04(){ SearchResponse searchResponse = tc.prepareSearch(indices) .setSearchType(SearchType.DEFAULT) .setQuery(QueryBuilders.rangeQuery("age").gte(35).lte(40)) .addAggregation(AggregationBuilders.avg("avg_age").field("age")) .get(); SearchHits hits = searchResponse.getHits(); long totalHits = hits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); Aggregations aggregations = searchResponse.getAggregations(); Map<String, Aggregation> aggregationMap = aggregations.asMap(); for(Map.Entry<String, Aggregation> map:aggregationMap.entrySet()){ String key = map.getKey(); //由Aggregations---->强转为InternalAvg,才拿到平均值 InternalAvg aggregation = (InternalAvg)map.getValue(); System.out.println("key = " + key); System.out.println("aggregation = " + aggregation.getValue()); } } /** * 代码的高亮显示 * HighLight * <font color='red'>keyword</font> * 对于这种高亮显示，就是在查询关键字之前和之后分别追加前缀和后缀 * 前缀：pre * 后缀：post * * 设置高亮注意的地方： * 1、设置高亮字段：addHighlightedField * 2、设置高亮的前缀和后缀： * setHighlighterPreTags("<font color='red'>") * setHighlighterPostTags("</font>") * 3、获取高亮数据 * searchHit.getHighlightFields()中的fragment获取 */ @Test public void testSearch_05(){ SearchResponse response = tc.prepareSearch(indices) .setSearchType(SearchType.DEFAULT) .setQuery(QueryBuilders.matchQuery("name", "hadoop02")) .addHighlightedField("name") .setHighlighterPreTags("<font color='red'>") .setHighlighterPostTags("</font>") .get(); SearchHits searchHits = response.getHits(); long totalHits = searchHits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); for(SearchHit searchHit : searchHits){ System.out.println(" ================== " ); Map<String, HighlightField> highlightFields = searchHit.getHighlightFields(); for(Map.Entry<String, HighlightField> me : highlightFields.entrySet()){ String key = me.getKey(); System.out.println("key = " + key); HighlightField highlightField = me.getValue(); String name = highlightField.getName(); System.out.println("name = " + name); Text[] fragments = highlightField.getFragments(); String hightStr = ""; for(Text text : fragments){ hightStr += text.toString(); } System.out.println("hightStr = " + hightStr); } } } /** * 查询中文 * * 分词： * 我们发现设置Query为termQuery，QueryBuilders.termQuery("author", "孙")有结果 * 而Query为termQuery，QueryBuilders.termQuery("author", "孙鹏")没有结果 * 这是因为中文分词的原因，英文分词非常简单：就是通过一个个的空格进行拆分，而汉字的拆分默认情况下就是一个字一个字的拆 * * 我们要想查询孙鹏 或者鹏飞这些词组的时候，默认的拆分方式就提供不了数据了，为了满足用户的需要，在软件发展过程中就有非常多的 * 各种各样的分词法(庖丁解牛分词法,IK分词法) * * 如果使用了IK等分词法，对索引库中已经存在的数据不执行相应的分词，只有对新增的数据才会执行相应的分词！！！ */ @Test public void testSearch_Chinese(){ indices = new String[]{"bigdata"}; SearchResponse response = tc.prepareSearch(indices) .setSearchType(SearchType.DEFAULT) //奥利猫(ik之前) 法拉狗 .setQuery(QueryBuilders.termQuery("author", "奥利")) .get(); SearchHits hits = response.getHits(); long totalHits = hits.getTotalHits(); System.out.println("老王为您找到相关结果约 " + totalHits); for(SearchHit searchHit : hits){ printSearchHit(searchHit); } } private void printSearchHit(SearchHit searchHit){ String index = searchHit.getIndex(); String type = searchHit.getType(); String id = searchHit.getId(); long version = searchHit.getVersion(); float score = searchHit.getScore(); Map<String, Object> source = searchHit.getSource(); System.out.println("index "+index); System.out.println("type "+type); System.out.println("id "+id); System.out.println("version "+version); System.out.println("score "+score); System.out.println("source "+source); } @After public void cleanUp(){ if(tc != null){ tc.close(); } }}阅读全文
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