java search 不能使用方法_ElasticSearch实战系列三: ElasticSearch的JAVA API使用教程

柔情只为你懂 2022-11-03 11:25 217阅读 0赞

前言

在上一篇中介绍了ElasticSearch实战系列二: ElasticSearch的DSL语句使用教程---图文详解，本篇文章就来讲解下 ElasticSearch 6.x官方Java API的使用。

ElasticSearch JAVA API

目前市面上有几种常见的ElasticSearch Java API架包，JestClient、SpringBoot整合的SpringData、Spring整合的ElasticsearchTemplate、Elasticsearch Bboss等一些开源架包，上述这些第三方整合的架包中，基本已经支持日常的使用，除了支持的ES版本会低一些而已。

本文介绍的是ElasticSearch官方的Java High Level REST Client的使用，Java High Level REST Client是ElasticSearch官方目前推荐使用的，适用于6.x以上的版本，要求JDK在1.8以上，可以很好的在大版本中进行兼容，并且该架包自身也包含Java Low Level REST Client中的方法，可以应对一些特需的情况进行特殊的处理， 它对于一些常用的方法封装Restful风格，可以直接对应操作名调用使用即可，支持同步和异步(Async)调用。

这里我们的使用也可以直接对应上一篇文章中的DSL语句使用，这样的话可以非常方便的对照和学习使用。

在对下述进行操作时，我们先来看下Elasticsearch Java High Level REST Client的初始化连接写法吧。

RestHighLevelClient client = new RestHighLevelClient(RestClient.builder(new HttpHost(elasticIp, elasticPort)));

是不是很简单呢，关闭也很简单，client不为空直接close即可！

一、新增数据

ElasticSearch可以直接新增数据，只要你指定了index(索引库名称)和type(类型)即可。在新增的时候你可以自己指定主键ID，也可以不指定，由 ElasticSearch自身生成。Elasticsearch Java High Level REST Client新增数据提供了三种方法，这里我们就来看一下这三种写法吧。

新增数据代码示例一，通过jsonString进行创建：

String index = "test1";

String type = "\_doc";

// 唯一编号

String id = "1";

IndexRequest request = new IndexRequest(index, type, id);

String jsonString = "\{" + "\\"uid\\":\\"1234\\","+ "\\"phone\\":\\"12345678909\\","+ "\\"msgcode\\":\\"1\\"," + "\\"sendtime\\":\\"2019-03-14 01:57:04\\","

\+ "\\"message\\":\\"xuwujing study Elasticsearch\\"" + "\}";

request.source(jsonString, XContentType.JSON);

IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);

新增数据代码示例二，通过map创建,会自动转换成json的数据:

String index = "test1";

String type = "\_doc";

// 唯一编号

String id = "1";

IndexRequest request = new IndexRequest(index, type, id);

Map jsonMap = new HashMap<>();

jsonMap.put("uid", 1234);

jsonMap.put("phone", 12345678909L);

jsonMap.put("msgcode", 1);

jsonMap.put("sendtime", "2019-03-14 01:57:04");

jsonMap.put("message", "xuwujing study Elasticsearch");

request.source(jsonMap);

IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);

新增数据代码示例三，通过XContentBuilder对象进行创建:

String index = "test1";

String type = "\_doc";

// 唯一编号

String id = "1";

IndexRequest request = new IndexRequest(index, type, id);

XContentBuilder builder = XContentFactory.jsonBuilder();

builder.startObject();

builder.field("uid", 1234);

builder.field("phone", 12345678909L);

builder.field("msgcode", 1);

builder.timeField("sendtime", "2019-03-14 01:57:04");

builder.field("message", "xuwujing study Elasticsearch");

builder.endObject();

request.source(builder);

IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);

上述三种方法中，个人推荐第二种，比较容易理解和使用。

二、创建索引库

在上述示例中，我们通过直接通过创建数据从而创建了索引库，但是没有创建索引库而通过ES自身生成的这种并不友好，因为它会使用默认的配置，字段结构都是text(text的数据会分词，在存储的时候也会额外的占用空间)，分片和索引副本采用默认值，默认是5和1，ES的分片数在创建之后就不能修改，除非reindex，所以这里我们还是指定数据模板进行创建。

使用JAVA API 创建索引库的方法和上述中新增数据的一样，有三种方式，不过这里就只介绍一种。

新增索引库的代码示例:

private static void createIndex() throws IOException \{

String type = "\_doc";

String index = "test1";

// setting 的值

Map setmapping = new HashMap<>();

// 分区数、副本数、缓存刷新时间

setmapping.put("number\_of\_shards", 10);

setmapping.put("number\_of\_replicas", 1);

setmapping.put("refresh\_interval", "5s");

Map keyword = new HashMap<>();

//设置类型

keyword.put("type", "keyword");

Map lon = new HashMap<>();

//设置类型

lon.put("type", "long");

Map date = new HashMap<>();

//设置类型

date.put("type", "date");

date.put("format", "yyyy-MM-dd HH:mm:ss");

Map jsonMap2 = new HashMap<>();

Map properties = new HashMap<>();

//设置字段message信息

properties.put("uid", lon);

properties.put("phone", lon);

properties.put("msgcode", lon);

properties.put("message", keyword);

properties.put("sendtime", date);

Map mapping = new HashMap<>();

mapping.put("properties", properties);

jsonMap2.put(type, mapping);

GetIndexRequest getRequest = new GetIndexRequest();

getRequest.indices(index);

getRequest.local(false);

getRequest.humanReadable(true);

boolean exists2 = client.indices().exists(getRequest, RequestOptions.DEFAULT);

//如果存在就不创建了

if(exists2) \{

System.out.println(index+"索引库已经存在!");

return;

// 开始创建库

CreateIndexRequest request = new CreateIndexRequest(index);

try \{

// 加载数据类型

request.settings(setmapping);

//设置mapping参数

request.mapping(type, jsonMap2);

//设置别名

request.alias(new Alias("pancm\_alias"));

CreateIndexResponse createIndexResponse = client.indices().create(request, RequestOptions.DEFAULT);

boolean falg = createIndexResponse.isAcknowledged();

if(falg)\{

System.out.println("创建索引库:"+index+"成功！" );

\} catch (IOException e) \{

e.printStackTrace();

注：创建索引库的时候，一定要先判断索引库是否存在！！！

这里创建索引库的时候顺便也指定了别名(alias)，这个别名是一个好东西，使用恰当可以提升查询性能，这里我们留着下次在讲。

三、修改数据

ES提供修改API的时候，有两种方式，一种是直接修改，但是若数据不存在会抛出异常，另一种则是存在更新，不存着就插入。相比第一种，第二种会更加好用一些，不过在写入速度上是不如第一种的。

ES修改的代码示例:

private static void update() throws IOException \{

String type = "\_doc";

String index = "test1";

// 唯一编号

String id = "1";

UpdateRequest upateRequest = new UpdateRequest();

upateRequest.id(id);

upateRequest.index(index);

upateRequest.type(type);

// 依旧可以使用Map这种集合作为更新条件

Map jsonMap = new HashMap<>();

jsonMap.put("uid", 12345);

jsonMap.put("phone", 123456789019L);

jsonMap.put("msgcode", 2);

jsonMap.put("sendtime", "2019-03-14 01:57:04");

jsonMap.put("message", "xuwujing study Elasticsearch");

upateRequest.doc(jsonMap);

// upsert 方法表示如果数据不存在，那么就新增一条

upateRequest.docAsUpsert(true);

client.update(upateRequest, RequestOptions.DEFAULT);

System.out.println("更新成功！");

注:upsert 方法表示如果数据不存在，那么就新增一条，默认是false。

四、删除数据

根据上述的几个操作，想必不用多说，已经知道了是DELETE方法了，那我们就直接开始吧。

ES根据ID删除代码示例:

private static void delete() throws IOException \{

String type = "\_doc";

String index = "test1";

// 唯一编号

String id = "1";

DeleteRequest deleteRequest = new DeleteRequest();

deleteRequest.id(id);

deleteRequest.index(index);

deleteRequest.type(type);

// 设置超时时间

deleteRequest.timeout(TimeValue.timeValueMinutes(2));

// 设置刷新策略"wait\_for"

// 保持此请求打开，直到刷新使此请求的内容可以搜索为止。此刷新策略与高索引和搜索吞吐量兼容，但它会导致请求等待响应，直到发生刷新

deleteRequest.setRefreshPolicy(WriteRequest.RefreshPolicy.WAIT\_UNTIL);

// 同步删除

DeleteResponse deleteResponse = client.delete(deleteRequest, RequestOptions.DEFAULT);

ES根据条件进行删除：

private static void deleteByQuery() throws IOException \{

String type = "\_doc";

String index = "test1";

DeleteByQueryRequest request = new DeleteByQueryRequest(index,type);

// 设置查询条件

request.setQuery(QueryBuilders.termsQuery("uid",1234));

// 同步执行

BulkByScrollResponse bulkResponse = client.deleteByQuery(request, RequestOptions.DEFAULT);

测试结果

示例图:

查询语句

几个常用的查询API这里就简单的介绍下用法，然后再直接给出所有的查询语句代码。

查询API

等值(term查询：QueryBuilders.termQuery(name,value);

多值(terms)查询:QueryBuilders.termsQuery(name,value,value2,value3...);

范围(range)查询：QueryBuilders.rangeQuery(name).gte(value).lte(value);

存在(exists)查询:QueryBuilders.existsQuery(name);

模糊(wildcard)查询:QueryBuilders.wildcardQuery(name,+value+);

组合(bool)查询: BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();

查询所有代码示例

private static void allSearch() throws IOException \{

SearchRequest searchRequestAll = new SearchRequest();

SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();

searchSourceBuilder.query(QueryBuilders.matchAllQuery());

searchRequestAll.source(searchSourceBuilder);

// 同步查询

SearchResponse searchResponseAll = client.search(searchRequestAll, RequestOptions.DEFAULT);

System.out.println("所有查询总数:" + searchResponseAll.getHits().getTotalHits());

一般查询代码示例

其实就是等值查询，只不过在里面加入了分页、排序、超时、路由等等设置，并且在查询结果里面增加了一些处理。

private static void genSearch() throws IOException \{

String type = "\_doc";

String index = "test1";

// 查询指定的索引库

SearchRequest searchRequest = new SearchRequest(index);

searchRequest.types(type);

SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

// 设置查询条件

sourceBuilder.query(QueryBuilders.termQuery("uid", "1234"));

// 设置起止和结束

sourceBuilder.from(0);

sourceBuilder.size(5);

sourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));

// 设置路由

//searchRequest.routing("routing");

// 设置索引库表达式

searchRequest.indicesOptions(IndicesOptions.lenientExpandOpen());

// 查询选择本地分片，默认是集群分片

searchRequest.preference("\_local");

// 排序

// 根据默认值进行降序排序

//sourceBuilder.sort(new ScoreSortBuilder().order(SortOrder.DESC));

// 根据字段进行升序排序

//sourceBuilder.sort(new FieldSortBuilder("id").order(SortOrder.ASC));

// 关闭suorce查询

//sourceBuilder.fetchSource(false);

String\[\] includeFields = new String\[\]\{"title", "user", "innerObject.\*"\};

String\[\] excludeFields = new String\[\]\{"\_type"\};

// 包含或排除字段

//sourceBuilder.fetchSource(includeFields, excludeFields);

searchRequest.source(sourceBuilder);

System.out.println("普通查询的DSL语句:"+sourceBuilder.toString());

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

// HTTP状态代码、执行时间或请求是否提前终止或超时

RestStatus status = searchResponse.status();

TimeValue took = searchResponse.getTook();

Boolean terminatedEarly = searchResponse.isTerminatedEarly();

boolean timedOut = searchResponse.isTimedOut();

// 供关于受搜索影响的切分总数的统计信息，以及成功和失败的切分

int totalShards = searchResponse.getTotalShards();

int successfulShards = searchResponse.getSuccessfulShards();

int failedShards = searchResponse.getFailedShards();

// 失败的原因

for (ShardSearchFailure failure : searchResponse.getShardFailures()) \{

// failures should be handled here

// 结果

searchResponse.getHits().forEach(hit -> \{

Map map = hit.getSourceAsMap();

System.out.println("普通查询的结果:" + map);

\});

System.out.println("\\n=================\\n");

或查询

其实这个或查询也是bool查询中的一种，这里的查询语句相当于SQL语句中的

SELECT \* FROM test1 where (uid = 1 or uid =2) and phone = 12345678919

代码示例:

private static void orSearch() throws IOException \{

SearchRequest searchRequest = new SearchRequest();

searchRequest.indices("test1");

searchRequest.types("\_doc");

SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();

BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();

BoolQueryBuilder boolQueryBuilder2 = new BoolQueryBuilder();

/\*\*

\* SELECT \* FROM test1 where (uid = 1234 or uid =12345) and phone = 12345678909

\* \*/

boolQueryBuilder2.should(QueryBuilders.termQuery("uid", 1234));

boolQueryBuilder2.should(QueryBuilders.termQuery("uid", 12345));

boolQueryBuilder.must(boolQueryBuilder2);

boolQueryBuilder.must(QueryBuilders.termQuery("phone", "12345678909"));

searchSourceBuilder.query(boolQueryBuilder);

System.out.println("或查询语句:" + searchSourceBuilder.toString());

searchRequest.source(searchSourceBuilder);

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

searchResponse.getHits().forEach(documentFields -> \{

System.out.println("查询结果:" + documentFields.getSourceAsMap());

\});

模糊查询

相当于SQL语句中的like查询。

private static void likeSearch() throws IOException \{

String type = "\_doc";

String index = "test1";

SearchRequest searchRequest = new SearchRequest();

searchRequest.indices(index);

searchRequest.types(type);

SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();

BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder();

/\*\*

\* SELECT \* FROM p\_test where message like '%xu%';

\* \*/

boolQueryBuilder.must(QueryBuilders.wildcardQuery("message", "\*xu\*"));

searchSourceBuilder.query(boolQueryBuilder);

System.out.println("模糊查询语句:" + searchSourceBuilder.toString());

searchRequest.source(searchSourceBuilder);

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

searchResponse.getHits().forEach(documentFields -> \{

System.out.println("模糊查询结果:" + documentFields.getSourceAsMap());

\});

System.out.println("\\n=================\\n");

多值查询

也就是相当于SQL语句中的in查询。

private static void inSearch() throws IOException \{

String type = "\_doc";

String index = "test1";

// 查询指定的索引库

SearchRequest searchRequest = new SearchRequest(index,type);

SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

/\*\*

\* SELECT \* FROM p\_test where uid in (1,2)

\* \*/

// 设置查询条件

sourceBuilder.query(QueryBuilders.termsQuery("uid", 1, 2));

searchRequest.source(sourceBuilder);

System.out.println("in查询的DSL语句:"+sourceBuilder.toString());

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

// 结果

searchResponse.getHits().forEach(hit -> \{

Map map = hit.getSourceAsMap();

String string = hit.getSourceAsString();

System.out.println("in查询的Map结果:" + map);

System.out.println("in查询的String结果:" + string);

\});

System.out.println("\\n=================\\n");

存在查询

判断是否存在该字段，用法和SQL语句中的exist类似。

private static void existSearch() throws IOException \{

String type = "\_doc";

String index = "test1";

// 查询指定的索引库

SearchRequest searchRequest = new SearchRequest(index);

searchRequest.types(type);

SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

// 设置查询条件

sourceBuilder.query(QueryBuilders.existsQuery("msgcode"));

searchRequest.source(sourceBuilder);

System.out.println("存在查询的DSL语句:"+sourceBuilder.toString());

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

// 结果

searchResponse.getHits().forEach(hit -> \{

Map map = hit.getSourceAsMap();

String string = hit.getSourceAsString();

System.out.println("存在查询的Map结果:" + map);

System.out.println("存在查询的String结果:" + string);

\});

System.out.println("\\n=================\\n");

范围查询

和SQL语句中<>使用方法一样,其中gt是大于，lt是小于，gte是大于等于，lte是小于等于。

private static void rangeSearch() throws IOException\{

String type = "\_doc";

String index = "test1";

SearchRequest searchRequest = new SearchRequest(index);

searchRequest.types(type);

SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

// 设置查询条件

sourceBuilder.query(QueryBuilders.rangeQuery("sendtime").gte("2019-01-01 00:00:00").lte("2019-12-31 23:59:59"));

searchRequest.source(sourceBuilder);

System.out.println("范围查询的DSL语句:"+sourceBuilder.toString());

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

// 结果

searchResponse.getHits().forEach(hit -> \{

String string = hit.getSourceAsString();

System.out.println("范围查询的String结果:" + string);

\});

System.out.println("\\n=================\\n");

正则查询

ES可以使用正则进行查询，查询方式也非常的简单，代码示例如下：

private static void regexpSearch() throws IOException\{

String type = "\_doc";

String index = "test1";

// 查询指定的索引库

SearchRequest searchRequest = new SearchRequest(index);

searchRequest.types(type);

SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();

// 设置查询条件

sourceBuilder.query(QueryBuilders.regexpQuery("message","xu\[0-9\]"));

searchRequest.source(sourceBuilder);

System.out.println("正则查询的DSL语句:"+sourceBuilder.toString());

// 同步查询

SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);

// 结果

searchResponse.getHits().forEach(hit -> \{

Map map = hit.getSourceAsMap();

String string = hit.getSourceAsString();

System.out.println("正则查询的Map结果:" + map);

System.out.println("正则查询的String结果:" + string);

\});

System.out.println("\\n=================\\n");

查询测试结果

所有查询总数:6

普通查询的DSL语句:\{"from":0,"size":5,"timeout":"60s","query":\{"term":\{"uid":\{"value":"1234","boost":1.0\}\}\}\}

=================

或查询语句:\{"query":\{"bool":\{"must":\[\{"bool":\{"should":\[\{"term":\{"uid":\{"value":1234,"boost":1.0\}\}\},\{"term":\{"uid":\{"value":12345,"boost":1.0\}\}\}\],"adjust\_pure\_negative":true,"boost":1.0\}\},\{"term":\{"phone":\{"value":"12345678909","boost":1.0\}\}\}\],"adjust\_pure\_negative":true,"boost":1.0\}\}\}

或查询结果:\{msgcode=1, uid=12345, phone=12345678909, message=qq, sendtime=2019-03-14 01:57:04\}

=================

模糊查询语句:\{"query":\{"bool":\{"must":\[\{"wildcard":\{"message":\{"wildcard":"xu","boost":1.0\}\}\}\],"adjust\_pure\_negative":true,"boost":1.0\}\}\}

模糊查询结果:\{msgcode=2, uid=12345, phone=123456789019, sendtime=2019-03-14 01:57:04, message=xuwujing study Elasticsearch\}

模糊查询结果:\{uid=123456, phone=12345678909, message=xu1, sendtime=2019-03-14 01:57:04\}

=================

存在查询的DSL语句:\{"query":\{"exists":\{"field":"msgcode","boost":1.0\}\}\}

存在查询的Map结果:\{msgcode=2, uid=12345, phone=123456789019, sendtime=2019-03-14 01:57:04, message=xuwujing study Elasticsearch\}

存在查询的String结果:\{"uid":12345,"phone":123456789019,"msgcode":2,"sendtime":"2019-03-14 01:57:04","message":"xuwujing study Elasticsearch"\}

存在查询的Map结果:\{msgcode=1, uid=12345, phone=12345678909, message=qq, sendtime=2019-03-14 01:57:04\}

存在查询的String结果:\{"uid":"12345","phone":"12345678909","message":"qq","msgcode":"1","sendtime":"2019-03-14 01:57:04"\}

=================

范围查询的DSL语句:\{"query":\{"range":\{"sendtime":\{"from":"2019-01-01 00:00:00","to":"2019-12-31 23:59:59","include\_lower":true,"include\_upper":true,"boost":1.0\}\}\}\}

范围查询的String结果:\{"uid":12345,"phone":123456789019,"msgcode":2,"sendtime":"2019-03-14 01:57:04","message":"xuwujing study Elasticsearch"\}

范围查询的String结果:\{"uid":"123456","phone":"12345678909","message":"xu1","sendtime":"2019-03-14 01:57:04"\}

范围查询的String结果:\{"uid":"12345","phone":"12345678909","message":"qq","msgcode":"1","sendtime":"2019-03-14 01:57:04"\}

=================

正则查询的DSL语句:\{"query":\{"regexp":\{"message":\{"value":"xu\[0-9\]","flags\_value":65535,"max\_determinized\_states":10000,"boost":1.0\}\}\}\}

正则查询的Map结果:\{uid=123456, phone=12345678909, message=xu1, sendtime=2019-03-14 01:57:04\}

正则查询的String结果:\{"uid":"123456","phone":"12345678909","message":"xu1","sendtime":"2019-03-14 01:57:04"\}

=================

组合查询的DSL语句:\{"query":\{"bool":\{"must":\[\{"term":\{"uid":\{"value":12345,"boost":1.0\}\}\},\{"term":\{"msgcode":\{"value":1,"boost":1.0\}\}\}\],"adjust\_pure\_negative":true,"boost":1.0\}\}\}

组合查询的String结果:\{"uid":"12345","phone":"12345678909","message":"qq","msgcode":"1","sendtime":"2019-03-14 01:57:04"\}

=================

其它

关于SpringBoot集成ElasticSearch和JestClient的使用可以查看这篇文章：SpringBoot整合ElasticSearch实现多版本的兼容

关于ElasticSearch Java API的选择，如果ElasticSearch版本在6.x以前的话，推荐使用JestClient。如果是6.x之后并且有意升级到7.x的话，那么直接使用ES官方的Java High Level REST Client，因为在7.x之后将直接会舍弃Transport client的连接方式，目前Spring和SpringBoot集成的ES就是使用该方式(不知后续是否会做调整)。

本篇文章的代码已收录在本人的java-study项目中，若有兴趣，欢迎star、fork和issues。

项目地址:https://github.com/xuwujing/java-study

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