這裏Elasticsearch是單節點,版本爲5.2.2。
【1】獲取PreBuiltTransportClient
實例代碼
@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);
}
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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】創建索引
實例代碼:
@Test
public void createIndex(){
CreateIndexResponse blog = client.admin().indices().prepareCreate("my-blog").get();
System.out.println(blog);
client.close();
}
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查看當前ES中索引
http://192.168.18.128:9200/_cat/indices
查看my-blog詳細
http://192.168.18.128:9200/my-blog?pretty
如果不加pretty參數則如下所示:
Elasticsearch索引結束時將得到5個分片及其各自1個副本。簡單來說,操作結束時,將有10個Lucene索引分佈在集羣中。
【3】刪除索引
實例代碼
@Test
public void deleteIndex(){
// 1 刪除索引
DeleteIndexResponse deleteIndexResponse = client.admin().indices().prepareDelete("my-blog").get();
System.out.println(deleteIndexResponse);
// 2 關閉連接
client.close();
}
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查詢索引確認索引已經刪除
【4】創建文檔
① 以json串方式新建文檔
當直接在ElasticSearch建立文檔對象時,如果索引不存在的,默認會自動創建,映射採用默認方式。
實例代碼:
@Test
public void createIndexByJson() {
// 1 文檔數據準備
String json = "{" + "\"id\":\"1\"," + "\"title\":\"基於Lucene的搜索服務器\","
+ "\"content\":\"它提供了一個分佈式多用戶能力的全文搜索引擎,基於RESTful web接口\"" + "}";
// 2 創建文檔
IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "1").setSource(json).execute().actionGet();
// 3 打印返回的結果
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 關閉連接
client.close();
}
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瀏覽器查看http://192.168.18.128:9200/my-blog?pretty
:
② 源數據map方式添加json創建文檔
實例代碼:
@Test
public void createIndexByMap() {
// 1 文檔數據準備
Map<String, Object> json = new HashMap<String, Object>();
json.put("id", "2");
json.put("title", "基於Lucene的搜索服務器");
json.put("content", "它提供了一個分佈式多用戶能力的全文搜索引擎,基於RESTful web接口");
// 2 創建文檔
IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "2").setSource(json).execute().actionGet();
// 3 打印返回的結果
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 關閉連接
client.close();
}
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瀏覽器確認該索引文檔http://192.168.18.128:9200/my-blog/_search?pretty
瀏覽器查詢ES所有信息http://192.168.18.128:9200/_all/_search?pretty
③ 源數據es構建器添加json創建文檔
實例代碼:
@Test
public void createIndex() throws Exception {
// 1 通過es自帶的幫助類,構建json數據
XContentBuilder builder = XContentFactory.jsonBuilder().startObject().field("id", 3)
.field("title", "基於Lucene的搜索服務器").field("content", "它提供了一個分佈式多用戶能力的全文搜索引擎,基於RESTful web接口。")
.endObject();
// 2 創建文檔
IndexResponse indexResponse = client.prepareIndex("my-blog", "article", "3").setSource(builder).get();
// 3 打印返回的結果
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 關閉連接
client.close();
}
控制檯打印:
瀏覽器查詢確認http://192.168.18.128:9200/my-blog/_search?pretty
【5】查詢索引中文檔數據
① 根據索引ID查詢單條數據
實例代碼:
@Test
public void getData() throws Exception {
// 1 查詢文檔
GetResponse response = client.prepareGet("my-blog", "article", "1").get();
// 2 打印搜索的結果
System.out.println(response.getSourceAsString());
// 3 關閉連接
client.close();
}
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② 根據索引ID查詢多條數據
實例代碼:
@Test
public void getMultiData() {
// 1 查詢多個文檔
MultiGetResponse response = client.prepareMultiGet().add("my-blog", "article", "1").add("my-blog", "article", "2", "3")
.add("my-blog", "article", "2").get();
// 2 遍歷返回的結果
for(MultiGetItemResponse itemResponse:response){
GetResponse getResponse = itemResponse.getResponse();
// 如果獲取到查詢結果
if (getResponse.isExists()) {
String sourceAsString = getResponse.getSourceAsString();
System.out.println(sourceAsString);
}
}
// 3 關閉資源
client.close();
}
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【6】更新索引文檔數據
① update-更新文檔數據
實例代碼:
@Test
public void updateData() throws Throwable {
// 1 創建更新數據的請求對象
UpdateRequest updateRequest = new UpdateRequest();
updateRequest.index("my-blog");
updateRequest.type("article");
updateRequest.id("3");
updateRequest.doc(XContentFactory.jsonBuilder().startObject()
// 對沒有的字段添加, 對已有的字段替換
.field("title", "基於Lucene的搜索服務器")
.field("content",
"它提供了一個分佈式多用戶能力的全文搜索引擎,基於RESTful web接口。大數據前景無限")
.field("createDate", "2019-12-22").endObject());
// 2 獲取更新後的值
UpdateResponse indexResponse = client.update(updateRequest).get();
// 3 打印返回的結果
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 關閉連接
client.close();
}
控制檯打印:
瀏覽器查詢確認http://192.168.18.128:9200/my-blog/_search?pretty
② upsert-更新文檔數據
設置查詢條件, 查找不到則添加IndexRequest內容,查找到則按照UpdateRequest更新。
實例代碼:
@Test
public void testUpsert() throws Exception {
// 設置查詢條件, 查找不到則添加
IndexRequest indexRequest = new IndexRequest("my-blog", "article", "5")
.source(XContentFactory.jsonBuilder().startObject().field("title", "搜索服務器").field("content","它提供了一個分佈式多用戶能力的全文搜索引擎,基於RESTful web接口。Elasticsearch是用Java開發的,並作爲Apache許可條款下的開放源碼發佈,是當前流行的企業級搜索引擎。設計用於雲計算中,能夠達到實時搜索,穩定,可靠,快速,安裝使用方便。").endObject());
// 設置更新, 查找到更新下面的設置
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();
}
瀏覽器查詢確認http://192.168.18.128:9200/my-blog/_search?pretty
【7】刪除文檔數據
實例代碼:
@Test
public void deleteData() {
// 1 刪除文檔數據
DeleteResponse indexResponse = client.prepareDelete("blog", "article", "5").get();
// 2 打印返回的結果
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 關閉連接
client.close();
}
控制檯打印:
瀏覽器查詢確認http://192.168.18.128:9200/my-blog/_search?pretty
【8】條件查詢
① 查詢索引所有文檔數據(matchAllQuery)
實例代碼:
@Test
public void matchAllQuery() {
// 1 執行查詢
SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
.setQuery(QueryBuilders.matchAllQuery()).get();
// 2 打印查詢結果
SearchHits hits = searchResponse.getHits(); // 獲取命中次數,查詢結果有多少對象
System.out.println("查詢結果有:" + hits.getTotalHits() + "條");
Iterator<SearchHit> iterator = hits.iterator();
while (iterator.hasNext()) {
SearchHit searchHit = iterator.next(); // 每個查詢對象
System.out.println(searchHit.getSourceAsString()); // 獲取字符串格式打印
}
// 3 關閉連接
client.close();
}
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② 對所有字段分詞查詢(queryStringQuery)
實例代碼:
@Test
public void query() {
// 1 條件查詢
SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
.setQuery(QueryBuilders.queryStringQuery("全文")).get();
// 2 打印查詢結果
SearchHits hits = searchResponse.getHits(); // 獲取命中次數,查詢結果有多少對象
System.out.println("查詢結果有:" + hits.getTotalHits() + "條");
Iterator<SearchHit> iterator = hits.iterator();
while (iterator.hasNext()) {
SearchHit searchHit = iterator.next(); // 每個查詢對象
System.out.println(searchHit.getSourceAsString()); // 獲取字符串格式打印
}
// 3 關閉連接
client.close();
}
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③ 通配符查詢(wildcardQuery)
*:表示多個字符(任意的字符)
?:表示單個字符
實例代碼:
@Test
public void wildcardQuery() {
// 1 通配符查詢
SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
.setQuery(QueryBuilders.wildcardQuery("content", "*全*")).get();
// 2 打印查詢結果
SearchHits hits = searchResponse.getHits(); // 獲取命中次數,查詢結果有多少對象
System.out.println("查詢結果有:" + hits.getTotalHits() + "條");
Iterator<SearchHit> iterator = hits.iterator();
while (iterator.hasNext()) {
SearchHit searchHit = iterator.next(); // 每個查詢對象
System.out.println(searchHit.getSourceAsString()); // 獲取字符串格式打印
}
// 3 關閉連接
client.close();
}
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④ 詞條查詢(TermQuery)
實例代碼;
@Test
public void termQuery() {
// 1 第一field查詢
// SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
// .setQuery(QueryBuilders.termQuery("content", "全文")).get();//0條
SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
.setQuery(QueryBuilders.termQuery("content", "全")).get();//3條
// 2 打印查詢結果
SearchHits hits = searchResponse.getHits(); // 獲取命中次數,查詢結果有多少對象
System.out.println("查詢結果有:" + hits.getTotalHits() + "條");
Iterator<SearchHit> iterator = hits.iterator();
while (iterator.hasNext()) {
SearchHit searchHit = iterator.next(); // 每個查詢對象
System.out.println(searchHit.getSourceAsString()); // 獲取字符串格式打印
}
// 3 關閉連接
client.close();
}
這裏需要說明,默認詞條查詢是將每個字作爲索引進行查找,使用詞(比如全文)進行查找是找不到的。單一使用有點雞肋,需要藉助分詞器組合使用。
⑤ 模糊查詢(fuzzy)
實例代碼:
@Test
public void fuzzy() {
// 1 模糊查詢
SearchResponse searchResponse = client.prepareSearch("my-blog").setTypes("article")
.setQuery(QueryBuilders.fuzzyQuery("content", "大")).get();
// 2 打印查詢結果
SearchHits hits = searchResponse.getHits(); // 獲取命中次數,查詢結果有多少對象
System.out.println("查詢結果有:" + hits.getTotalHits() + "條");
Iterator<SearchHit> iterator = hits.iterator();
while (iterator.hasNext()) {
SearchHit searchHit = iterator.next(); // 每個查詢對象
System.out.println(searchHit.getSourceAsString()); // 獲取字符串格式打印
}
// 3 關閉連接
client.close();
}
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【9】映射mappings
上面創建的索引默認映射信息http://192.168.18.128:9200/my-blog?pretty
:
添加mapping的索引必須存在且該索引不能存在mapping,否則添加不成功。
實例代碼:
@Test
public void createMapping() throws Exception {
//1.添加mapping的索引必須存在;2.該索引不能存在mapping,否則添加不成功
CreateIndexResponse blog = client.admin().indices().prepareCreate("my-blog2").get();
System.out.println(blog);
// 2設置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 關閉資源
client.close();
}
瀏覽器查詢確認http://192.168.18.128:9200/_cat/indices
:
查詢索引明細http://192.168.18.128:9200/my-blog2?pretty
:
總結,用java原生操作es十分麻煩,建議使用SpringData Elasticsearch官網。