ElasticSearch实战系列三: ElasticSearch的JAVA …

2019-10-12 08:22:23来源:博客园 阅读 ()

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ElasticSearch实战系列三: ElasticSearch的JAVA API使用教程

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<String, Object> 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<String, Object> 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<String, Object> keyword = new HashMap<>();
    //设置类型
    keyword.put("type", "keyword");
    Map<String, Object> lon = new HashMap<>();
    //设置类型
    lon.put("type", "long");
    Map<String, Object> date = new HashMap<>();
    //设置类型
    date.put("type", "date");
    date.put("format", "yyyy-MM-dd HH:mm:ss");

    Map<String, Object> jsonMap2 = new HashMap<>();
    Map<String, Object> 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<String, Object> 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<String, Object> 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<String, Object> 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<String, Object> 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<String, Object> 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<String, Object> 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

参考ES官方文档:
https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high.html

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

ElasticSearch实战系列:
ElasticSearch实战系列一: ElasticSearch集群+Kinaba安装教程
ElasticSearch实战系列二: ElasticSearch的DSL语句使用教程---图文详解

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原文链接:https://www.cnblogs.com/xuwujing/p/11645630.html
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