【1】获取PreBuiltTransportClient
实例代码
@Test public void getClient() throws Exception { Settings settings= Settings.builder().put("cluster.name","my-application").build(); PreBuiltTransportClient client = new PreBuiltTransportClient(settings); byte[] addr = {(byte) 192, (byte) 168,18, (byte) 128}; client.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByAddress(addr),9300)); System.out.println(client); }
控制台打印
io.netty.channel.DefaultChannelId - -Dio.netty.machineId: 28:d2:44:ff:fe:f0:2f:30 (auto-detected) io.netty.util.internal.InternalThreadLocalMap - -Dio.netty.threadLocalMap.stringBuilder.initialSize: 1024 io.netty.util.internal.InternalThreadLocalMap - -Dio.netty.threadLocalMap.stringBuilder.maxSize: 4096 io.netty.util.ResourceLeakDetector - -Dio.netty.leakDetection.level: simple io.netty.util.ResourceLeakDetector - -Dio.netty.leakDetection.targetRecords: 4 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.numHeapArenas: 8 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.numDirectArenas: 8 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.pageSize: 8192 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.maxOrder: 11 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.chunkSize: 16777216 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.tinyCacheSize: 512 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.smallCacheSize: 256 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.normalCacheSize: 64 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.maxCachedBufferCapacity: 32768 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.cacheTrimInterval: 8192 io.netty.buffer.PooledByteBufAllocator - -Dio.netty.allocator.useCacheForAllThreads: true io.netty.buffer.ByteBufUtil - -Dio.netty.allocator.type: pooled io.netty.buffer.ByteBufUtil - -Dio.netty.threadLocalDirectBufferSize: 0 io.netty.buffer.ByteBufUtil - -Dio.netty.maxThreadLocalCharBufferSize: 16384 io.netty.buffer.AbstractByteBuf - -Dio.netty.buffer.bytebuf.checkAccessible: true io.netty.util.ResourceLeakDetectorFactory - Loaded default ResourceLeakDetector: io.netty.util.ResourceLeakDetector@5f5b5ca4 io.netty.util.Recycler - -Dio.netty.recycler.maxCapacityPerThread: 4096 io.netty.util.Recycler - -Dio.netty.recycler.maxSharedCapacityFactor: 2 io.netty.util.Recycler - -Dio.netty.recycler.linkCapacity: 16 io.netty.util.Recycler - -Dio.netty.recycler.ratio: 8 org.elasticsearch.transport.netty4.Netty4Transport - connected to node [{#transport#-1}{DX4Qcrb4QAaGAgDUb-XYxg}{192.168.18.128}{192.168.18.128:9300}] org.elasticsearch.transport.netty4.Netty4Transport - connected to node [{node-1}{rBJNxRw2RxisNp-uBs8o4g}{10h3v06bR4SI4x4ee0F1HQ}{192.168.18.128}{192.168.18.128:9300}] org.elasticsearch.transport.client.PreBuiltTransportClient@7af1cd63
【2】创建索引
实例代码:
@Test public void createIndex(){ CreateIndexResponse blog = client.admin().indices().prepareCreate("my-blog").get(); System.out.println(blog); client.close(); }
控制台打印
查看当前ES中索引
http://192.168.18.128:9200/_cat/indices
查看my-blog详细
http://192.168.18.128:9200/my-blog?pretty
如果不加pretty参数则如下所示:
Elasticsearch索引结束时将得到5个分片及其各自1个副本。简单来说,操作结束时,将有10个Lucene索引分布在集群中。
【3】删除索引
实例代码
@Test public void deleteIndex(){ // 1 删除索引 DeleteIndexResponse deleteIndexResponse = client.admin().indices().prepareDelete("my-blog").get(); System.out.println(deleteIndexResponse); // 2 关闭连接 client.close(); }
控制台打印
查询索引确认索引已经删除
【4】创建文档
① 以json串方式新建文档
当直接在ElasticSearch建立文档对象时,如果索引不存在的,默认会自动创建,映射采用默认方式。
实例代码:
@Test public void createIndexByJson() { // 1 文档数据准备 String json = "{" + "\"id\":\"1\"," + "\"title\":\"基于Lucene的搜索服务器\"," + "\"content\":\"它提供了一个分布式多用户能力的全文搜索引擎,基于RESTful web接口\"" + "}"; // 2 创建文档 IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "1").setSource(json).execute().actionGet(); // 3 打印返回的结果 System.out.println("index:" + indexResponse.getIndex()); System.out.println("type:" + indexResponse.getType()); System.out.println("id:" + indexResponse.getId()); System.out.println("version:" + indexResponse.getVersion()); System.out.println("result:" + indexResponse.getResult()); // 4 关闭连接 client.close(); }
控制台打印:
浏览器查看http://192.168.18.128:9200/my-blog?pretty
:
② 源数据map方式添加json创建文档
实例代码:
@Test public void createIndexByMap() { // 1 文档数据准备 Map<String, Object> json = new HashMap<String, Object>(); json.put("id", "2"); json.put("title", "基于Lucene的搜索服务器"); json.put("content", "它提供了一个分布式多用户能力的全文搜索引擎,基于RESTful web接口"); // 2 创建文档 IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "2").setSource(json).execute().actionGet(); // 3 打印返回的结果 System.out.println("index:" + indexResponse.getIndex()); System.out.println("type:" + indexResponse.getType()); System.out.println("id:" + indexResponse.getId()); System.out.println("version:" + indexResponse.getVersion()); System.out.println("result:" + indexResponse.getResult()); // 4 关闭连接 client.close(); }
控制台打印:
浏览器确认该索引文档http://192.168.18.128:9200/my-blog/_search?pretty
浏览器查询ES所有信息http://192.168.18.128:9200/_all/_search?pretty
③ 源数据es构建器添加json创建文档
实例代码:
@Test public void createIndex() throws Exception { // 1 通过es自带的帮助类,构建json数据 XContentBuilder builder = XContentFactory.jsonBuilder().startObject().field("id", 3) .field("title", "基于Lucene的搜索服务器").field("content", "它提供了一个分布式多用户能力的全文搜索引擎,基于RESTful web接口。") .endObject(); // 2 创建文档 IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "3").setSource(builder).get(); // 3 打印返回的结果 System.out.println("index:" + indexResponse.getIndex()); System.out.println("type:" + indexResponse.getType()); System.out.println("id:" + indexResponse.getId()); System.out.println("version:" + indexResponse.getVersion()); System.out.println("result:" + indexResponse.getResult()); // 4 关闭连接 client.close(); }
控制台打印:
浏览器查询确认http://192.168.18.128:9200/my-blog/_search?pretty
【5】查询索引中文档数据
① 根据索引ID查询单条数据
实例代码:
@Test public void getData() throws Exception { // 1 查询文档 GetResponse response = client.prepareGet("my-blog", "article", "1").get(); // 2 打印搜索的结果 System.out.println(response.getSourceAsString()); // 3 关闭连接 client.close(); }
控制台打印:
② 根据索引ID查询多条数据
实例代码:
@Test public void getMultiData() { // 1 查询多个文档 MultiGetResponse response = client.prepareMultiGet().add("my-blog", "article", "1").add("my-blog", "article", "2", "3") .add("my-blog", "article", "2").get(); // 2 遍历返回的结果 for(MultiGetItemResponse itemResponse:response){ GetResponse getResponse = itemResponse.getResponse(); // 如果获取到查询结果 if (getResponse.isExists()) { String sourceAsString = getResponse.getSourceAsString(); System.out.println(sourceAsString); } } // 3 关闭资源 client.close(); }
控制台打印:
【6】更新索引文档数据
① update-更新文档数据
实例代码:
@Test public void updateData() throws Throwable { // 1 创建更新数据的请求对象 UpdateRequest updateRequest = new UpdateRequest(); updateRequest.index("my-blog"); updateRequest.type("article"); updateRequest.id("3"); updateRequest.doc(XContentFactory.jsonBuilder().startObject() // 对没有的字段添加, 对已有的字段替换 .field("title", "基于Lucene的搜索服务器") .field("content", "它提供了一个分布式多用户能力的全文搜索引擎,基于RESTful web接口。大数据前景无限") .field("createDate", "2019-12-22").endObject()); // 2 获取更新后的值 UpdateResponse indexResponse = client.update(updateRequest).get(); // 3 打印返回的结果 System.out.println("index:" + indexResponse.getIndex()); System.out.println("type:" + indexResponse.getType()); System.out.println("id:" + indexResponse.getId()); System.out.println("version:" + indexResponse.getVersion()); System.out.println("create:" + indexResponse.getResult()); // 4 关闭连接 client.close(); }
控制台打印:
浏览器查询确认http://192.168.18.128:9200/my-blog/_search?pretty
② upsert-更新文档数据
设置查询条件, 查找不到则添加IndexRequest内容,查找到则按照UpdateRequest更新。
实例代码:
@Test public void testUpsert() throws Exception { // 设置查询条件, 查找不到则添加 IndexRequest indexRequest = new IndexRequest("my-blog", "article", "5") .source(XContentFactory.jsonBuilder().startObject().field("title", "搜索服务器").field("content","它提供了一个分布式多用户能力的全文搜索引擎,基于RESTful web接口。Elasticsearch是用Java开发的,并作为Apache许可条款下的开放源码发布,是当前流行的企业级搜索引擎。设计用于云计算中,能够达到实时搜索,稳定,可靠,快速,安装使用方便。").endObject()); // 设置更新, 查找到更新下面的设置 UpdateRequest upsert = new UpdateRequest("my-blog", "article", "5") .doc(XContentFactory.jsonBuilder().startObject().field("user", "李四").endObject()).upsert(indexRequest); client.update(upsert).get(); client.close(); }
浏览器查询确认http://192.168.18.128:9200/my-blog/_search?pretty
【7】删除文档数据
实例代码:
@Test public void deleteData() { // 1 删除文档数据 DeleteResponse indexResponse = client.prepareDelete("blog", "article", "5").get(); // 2 打印返回的结果 System.out.println("index:" + indexResponse.getIndex()); System.out.println("type:" + indexResponse.getType()); System.out.println("id:" + indexResponse.getId()); System.out.println("version:" + indexResponse.getVersion()); System.out.println("found:" + indexResponse.getResult()); // 3 关闭连接 client.close(); }
控制台打印:
浏览器查询确认http://192.168.18.128:9200/my-blog/_search?pretty
【8】条件查询
① 查询索引所有文档数据(matchAllQuery)
实例代码:
@Test public void matchAllQuery() { // 1 执行查询 SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") .setQuery(QueryBuilders.matchAllQuery()).get(); // 2 打印查询结果 SearchHits hits = searchResponse.getHits(); // 获取命中次数,查询结果有多少对象 System.out.println("查询结果有:" + hits.getTotalHits() + "条"); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); // 每个查询对象 System.out.println(searchHit.getSourceAsString()); // 获取字符串格式打印 } // 3 关闭连接 client.close(); }
控制台打印:
② 对所有字段分词查询(queryStringQuery)
实例代码:
@Test public void query() { // 1 条件查询 SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") .setQuery(QueryBuilders.queryStringQuery("全文")).get(); // 2 打印查询结果 SearchHits hits = searchResponse.getHits(); // 获取命中次数,查询结果有多少对象 System.out.println("查询结果有:" + hits.getTotalHits() + "条"); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); // 每个查询对象 System.out.println(searchHit.getSourceAsString()); // 获取字符串格式打印 } // 3 关闭连接 client.close(); }
控制台打印:
③ 通配符查询(wildcardQuery)
*:表示多个字符(任意的字符) ?:表示单个字符
实例代码:
@Test public void wildcardQuery() { // 1 通配符查询 SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") .setQuery(QueryBuilders.wildcardQuery("content", "*全*")).get(); // 2 打印查询结果 SearchHits hits = searchResponse.getHits(); // 获取命中次数,查询结果有多少对象 System.out.println("查询结果有:" + hits.getTotalHits() + "条"); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); // 每个查询对象 System.out.println(searchHit.getSourceAsString()); // 获取字符串格式打印 } // 3 关闭连接 client.close(); }
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④ 词条查询(TermQuery)
实例代码;
@Test public void termQuery() { // 1 第一field查询 // SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") // .setQuery(QueryBuilders.termQuery("content", "全文")).get();//0条 SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") .setQuery(QueryBuilders.termQuery("content", "全")).get();//3条 // 2 打印查询结果 SearchHits hits = searchResponse.getHits(); // 获取命中次数,查询结果有多少对象 System.out.println("查询结果有:" + hits.getTotalHits() + "条"); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); // 每个查询对象 System.out.println(searchHit.getSourceAsString()); // 获取字符串格式打印 } // 3 关闭连接 client.close(); }
这里需要说明,默认词条查询是将每个字作为索引进行查找,使用词(比如全文)进行查找是找不到的。单一使用有点鸡肋,需要借助分词器组合使用。
⑤ 模糊查询(fuzzy)
实例代码:
@Test public void fuzzy() { // 1 模糊查询 SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article") .setQuery(QueryBuilders.fuzzyQuery("content", "大")).get(); // 2 打印查询结果 SearchHits hits = searchResponse.getHits(); // 获取命中次数,查询结果有多少对象 System.out.println("查询结果有:" + hits.getTotalHits() + "条"); Iterator<SearchHit> iterator = hits.iterator(); while (iterator.hasNext()) { SearchHit searchHit = iterator.next(); // 每个查询对象 System.out.println(searchHit.getSourceAsString()); // 获取字符串格式打印 } // 3 关闭连接 client.close(); }
控制台打印:
【9】映射mappings
上面创建的索引默认映射信息http://192.168.18.128:9200/my-blog?pretty
:
添加mapping的索引必须存在且该索引不能存在mapping,否则添加不成功。
实例代码:
@Test public void createMapping() throws Exception { //1.添加mapping的索引必须存在;2.该索引不能存在mapping,否则添加不成功 CreateIndexResponse blog = client.admin().indices().prepareCreate("my-blog2").get(); System.out.println(blog); // 2设置mapping XContentBuilder builder = XContentFactory.jsonBuilder() .startObject() .startObject("article") .startObject("properties") .startObject("id1") .field("type", "string") .field("store", "yes") .endObject() .startObject("title2") .field("type", "string") .field("store", "no") .endObject() .startObject("content") .field("type", "string") .field("store", "yes") .endObject() .endObject() .endObject() .endObject(); // 3 添加mapping PutMappingRequest mapping = Requests.putMappingRequest("my-blog2").type("article").source(builder); client.admin().indices().putMapping(mapping).get(); // 4 关闭资源 client.close(); }
浏览器查询确认http://192.168.18.128:9200/_cat/indices:
查询索引明细http://192.168.18.128:9200/my-blog2?pretty:
总结,用java原生操作es十分麻烦,建议使用SpringData Elasticsearch官网。