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

程序员文章站 2022-06-29 13:47:36
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ElasticSea ......

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:

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项目中,若有兴趣,欢迎star、fork和issues。
项目地址:

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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