ElasticSearch入门


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介绍

The Elastic Stack, 包括 Elasticsearch、Kibana、Beats 和 Logstash（也称为 ELK Stack）。能够安全可靠地获取任何来源、任何格式的数据，然后实时地对数据进行搜索、分析和可视化。Elaticsearch，简称为ES， ES是一个开源的高扩展的分布式全文搜索引擎，是整个Elastic Stack技术栈的核心。它可以近乎实时的存储、检索数据；本身扩展性很好，可以扩展到上百台服务器，处理PB级别的数据。

目前市面上流行的搜索引擎软件，主流的就两款：Elasticsearch和Solr,这两款都是基于Lucene搭建的，可以独立部署启动的搜索引擎服务软件。由于内核相同，所以两者除了服务器安装、部署、管理、集群以外，对于数据的操作 修改、添加、保存、查询等等都十分类似。

image-20220109145455240

Http基本操作

1.索引

  1. 创建索引——对比关系型数据库，创建索引就等同于创建数据库

    向 ES 服务器发 PUT 请求 http://127.0.0.1:9200/shopping，自动创建shopping索引

  2. 查看所有索引——向 ES 服务器发 GET 请求 http://127.0.0.1:9200/_cat/indices?v

    image-20220109145832063

  3. 查看单个索引——向 ES 服务器发 GET 请求 http://127.0.0.1:9200/shopping

  4. 删除索引——向 ES 服务器发 DELETE 请求 http://127.0.0.1:9200/shopping

2.文档

  1. 创建文档——索引已经创建好了，接下来我们来创建文档，并添加数据。这里的文档可以类比为关系型数
    据库中的表数据，添加的数据格式为 JSON 格式

    向 ES 服务器发 POST 请求 http://127.0.0.1:9200/shopping/_doc，并在请求体中放入如下json字符

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    {
        "title":"小米手机",
        "category":"小米",
        "images":"http://www.gulixueyuan.com/xm.jpg",
        "price":3999.00
    }

    上面的数据创建后，由于没有指定数据唯一性标识（ID ），默认情况下 ES 服务器会随机生成一个 。
    如果想要自定义唯一性标识，需要在创建时指定http://127.0.0.1:9200/shopping/_doc/1001

  2. 查看文档——向 ES 服务器发 GET 请求 http://127.0.0.1:9200/shopping/_doc/1001

  3. 修改文档——和新增文档一样，输入相同的URL 地址请求，如果请求体变化，会将原有的数据内容覆盖

  4. 修改字段——修改数据时，也可以只修改某一给条数据的局部信息

    向 ES 服务器发 POST 请求 http://127.0.0.1:9200/shopping/_update/1001，请求体如下：

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    {
        "doc":{
             "price":3000.00
        }
    }

    根据唯一性标识，查询文档数据，文档数据已经更新

  5. 删除文档——删除一个文档不会立即从磁盘上移除，它只是被标记成已删除（逻辑删除）。向 ES 服务器发 DELETE 请求 http://127.0.0.1:9200/shopping/_doc/1001

  6. 条件删除文档——一般删除数据都是根据文档的唯一性标识进行删除，实际操作时，也可以根据条件对多条数据进行删除

    向ES 服务器发 POST 请求 http://127.0.0.1:9200/shopping/_delete_by_query，json请求体如下：

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    {
        "query":{
            "match":{
                "price":3999.00
            }
        }
    }

3.映射

有了索引库，等于有了数据库中的database。接下来就需要建索引库( 中的映射了，类似于数据库中的表结构 。创建数据库表需要设置字段名称，类型，长度，约束等；索引库也一样，需要知道这个类型下有哪些字段，每个字段有哪些约束信息，这就叫做映射。

  1. 创建映射——向 ES 服务器发 PUT 请求 http://127.0.0.1:9200/student/_mapping，请求体内容为：

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    {
        "properties": {
            "name": {
                "type": "text",
                "index": true
            },
            "sex": {
                "type" :"text",
                "index": false
            },
            "age": {
                "type":"1ong",
                "index": false
            }
        }
    }

    映射数据说明：

    • 字段名：任意填写，下面指定许多属性，例如： title 、 subtitle 、 images 、 price

    • type ：类型 Elasticsearch 中支持的数据类型非常丰富，说几个关键的：

      text：可分词

      keyword：不可分词，数据会作为完整字段进行匹配

      Date ：日期类型

      Array ：数组类型

    • index ：是否索引，默认为 true ，也就是说你不进行任何配置，所有字段都会被索引。

      true：字段会被索引，则可以用来进行搜索

      false：字段不会被索引，不能用来搜索

  2. 查看映射——向 ES 服务器发 GET 请求 http://127.0.0.1:9200/student/_mapping

JavaAPI

1.索引

连接客户端

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//连接es服务器
RestHighLevelClient esClient = new RestHighLevelClient(
    RestClient.builder(new HttpHost("localhost", 9200, "http"))
);
esClient.close();

创建索引

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CreateIndexRequest request = new CreateIndexRequest("user");
CreateIndexResponse response = esClient.indices().create(request, RequestOptions.DEFAULT);
System.out.println(response.isAcknowledged());

查询索引

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GetIndexRequest request = new GetIndexRequest("user");
GetIndexResponse response = esClient.indices().get(request, RequestOptions.DEFAULT);
System.out.println(response.getAliases());
System.out.println(response.getMappings());
System.out.println(response.getIndices());

删除索引

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// 删除索引 请求对象
DeleteIndexRequest request = new DeleteIndexRequest("user");
// 发送请求，获取响应
AcknowledgedResponse response = client.indices().delete(request,RequestOptions.DEFAULT);

2.文档

新增文档

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IndexRequest request = new IndexRequest();
request.index("user").id("1001");
User user = new User();
user.setAge(20);
user.setName("JY");
user.setSex("male");
//转化为JSON格式
ObjectMapper mapper = new ObjectMapper();
String s = mapper.writeValueAsString(user);
request.source(s, XContentType.JSON);
IndexResponse response = esClient.index(request, RequestOptions.DEFAULT);

System.out.println(response.getResult());

修改文档

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UpdateRequest request = new UpdateRequest();
request.index("user").id("1001");
request.doc(XContentType.JSON,"sex","female");
UpdateResponse response = esClient.update(request, RequestOptions.DEFAULT);
System.out.println(response.getResult());

查询文档

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GetRequest requset = new GetRequest();
requset.index("user").id("1001");
GetResponse response = esClient.get(requset, RequestOptions.DEFAULT);
System.out.println(response.getSourceAsString());

删除文档

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DeleteRequest request = new DeleteRequest().index("user").id("1");
DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
System.out.println(response.toString());

批量操作

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创建批量新增请求对象
BulkRequest requ est = new BulkRequest();
request.add(newIndexRequest().index("user").id("1001").source(XContentType.JSON, "name","JY"));
request.add(newIndexRequest().index("user").id("1002").source(XContentType.JSON, "name","LL"));
request.add(newIndexRequest().index("user").id("1003").source(XContentType.JSON, "name","KK"));
BulkResponse responses = client.bulk(request, RequestOptions.DEFAULT);

3.高级查询

3.1查询全部数据

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SearchRequest request = new SearchRequest();
request.indices("user");

request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()));

SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

SearchHits hits =  response.getHits();

System.out.println(hits.getTotalHits());
System.out.println(response.getTook());

for ( SearchHit hit : hits ) {
    System.out.println(hit.getSourceAsString());
}

3.2条件查询

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SearchRequest request = new SearchRequest();
request.indices("user");

request.source(new SearchSourceBuilder().query(QueryBuilders.termQuery("age", 30)));
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

SearchHits hits = response.getHits();

System.out.println(hits.getTotalHits());
System.out.println(response.getTook());

for ( SearchHit hit : hits ) {
    System.out.println(hit.getSourceAsString());
}

3.3分页查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
// (当前页码-1)*每页显示数据条数
builder.from(2);
builder.size(2);
request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.4查询排序

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
builder.sort("age", SortOrder.DESC);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.5过滤字段

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchAllQuery());
String[] excludes = {"age"};
String[] includes = {};
builder.fetchSource(includes, excludes);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.6组合查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();

//boolQueryBuilder.must(QueryBuilders.matchQuery("age", 30));
//boolQueryBuilder.must(QueryBuilders.matchQuery("sex", "男"));
//boolQueryBuilder.mustNot(QueryBuilders.matchQuery("sex", "男"));
boolQueryBuilder.should(QueryBuilders.matchQuery("age", 30));
boolQueryBuilder.should(QueryBuilders.matchQuery("age", 40));

builder.query(boolQueryBuilder);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.7范围查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();
RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("age");

rangeQuery.gte(30);
rangeQuery.lt(50);

builder.query(rangeQuery);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.8模糊查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();
builder.query(QueryBuilders.fuzzyQuery("name", "wangwu").fuzziness(Fuzziness.TWO));//误差在两个字符以内

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.9高亮查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();
TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("name", "zhangsan");

HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("<font color='red'>");
highlightBuilder.postTags("</font>");
highlightBuilder.field("name");

builder.highlighter(highlightBuilder);
builder.query(termsQueryBuilder);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.10聚合查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();

AggregationBuilder aggregationBuilder = AggregationBuilders.max("maxAge").field("age");//最大年龄
builder.aggregation(aggregationBuilder);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

3.11分组查询

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SearchRequest request = new SearchRequest();
request.indices("user");

SearchSourceBuilder builder = new SearchSourceBuilder();

AggregationBuilder aggregationBuilder = AggregationBuilders.terms("ageGroup").field("age");
builder.aggregation(aggregationBuilder);

request.source(builder);
SearchResponse response = esClient.search(request, RequestOptions.DEFAULT);

结语

这里只是总结了ElasticSearch的http操作和JavaAPI的使用，算是入门了。个人建议JavaAPI过一遍有个印象就行，用到直接百度搜。

进阶版的集群和优化现在打算不搞，以后碰到了再学吧😂我现在菜的很，专挑最拉的学一点。

赏

谢谢你请我吃糖果

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tag:

    缺失模块。
    1、请确保node版本大于6.2
    2、在博客根目录（注意不是yilia根目录）执行以下命令：
    npm i hexo-generator-json-content --save

    3、在根目录_config.yml里添加配置： 

      jsonContent:
    meta: false
    pages: false
    posts:
      title: true
      date: true
      path: true
      text: false
      raw: false
      content: false
      slug: false
      updated: false
      comments: false
      link: false
      permalink: false
      excerpt: false
      categories: false
      tags: true

很惭愧<br><br>只做了一点微小的工作<br>谢谢大家