kibana查询es数据记录

已经有一段时间没有更新博客信息了，最近刚从北京出差回来，老电脑已经被我放置了快一年的时间没有使用，现在要同步所有的信息到老电脑上去，还好自己对这一套东西也是比较熟悉了

1. 询index为test的数据信息

GET test/_search
{
  "size": 20, 
  "query": {
    "match_all": {}
  }
}

2. 查询名为pms,type为product的index的数据信息

GET pms/product/_search
{
  "size": 20, 
  "query": {
    "match_all": {}
  }
}

3. 删除名为test.type为文档类型的index

DELETE test/_doc/*

4. 清空test下的所有数据

POST test/_doc/_delete_by_query?refresh&slices=5&pretty 
{ "query": 
  { "match_all": {} }
}

5. 创建名为pms,type为product的index,注意使用的时候需要和我们代码中的实体类的属性类型对应起来，这里我贴出了我的实体类型中的属性

POST pms/product         
{
  "mappings": {
    "properties": {
      	"id": { 
      	  "type": "long"
      	 },
      	"productSn": {
      	  "type": "long" 
      	 },
      	"brandName": {
      	  "type": "Keyword" 
      	 },
      	"productCategoryId": {
      	  "type": "long"
      	 },
     		"productCategoryName":{
     		  "type": "Keyword" 
     		 },
     		 "pic":{
     		   "type": "Keyword" 
     		 },
     		 "name":{
     		    "type": "text" 
     		 },
     		 "subTitle": {
     		   "type": "text" 
     		 },
     		  "keywords": {
     		   "type": "text" 
     		 },
     		 "price": {
     		   "type": "text" 
     		 },
     		  "sale": {
     		   "type": "double" 
     		 },
     		  "newStatus": {
     		   "type": "integer" 
     		 },
     		  "recommandStatus": {
     		   "type": "integer" 
     		 },
     		  "stock": {
     		   "type": "integer" 
     		 },
     		  "promotionType": {
     		   "type": "integer" 
     		 },
     		 "sort": {
     		   "type": "integer" 
     		 },
     		 "attrValueList": {
     		   "type": "Nested" 
     		 },
     		 "crtTm": {
     		   "type": "date",
     		   "format": "YYYY-MM-dd HH-mm-ss"
     		 }
    }
  }
}


------------------------------------------------

/**
 * 搜索商品的信息
 * Created by macro on 2018/6/19.
 */
@Document(indexName = "pms", type = "product",shards = 1,replicas = 0)
public class EsProduct implements Serializable {
    private static final long serialVersionUID = -1L;
    @Id
    private Long id;
    @Field(type = FieldType.Keyword)
    private String productSn;
    private Long brandId;
    @Field(type = FieldType.Keyword)
    private String brandName;
    private Long productCategoryId;
    @Field(type = FieldType.Keyword)
    private String productCategoryName;
    private String pic;
    @Field(analyzer = "ik_max_word",type = FieldType.Text)
    private String name;
    @Field(analyzer = "ik_max_word",type = FieldType.Text)
    private String subTitle;
    @Field(analyzer = "ik_max_word",type = FieldType.Text)
    private String keywords;
    private BigDecimal price;
    private Integer sale;
    private Integer newStatus;
    private Integer recommandStatus;
    private Integer stock;
    private Integer promotionType;
    private Integer sort;
    @Field(type =FieldType.Nested)
    private List<EsProductAttributeValue> attrValueList;




public enum FieldType {
    Auto,
    Text,
    Keyword,
    Long,
    Integer,
    Short,
    Byte,
    Double,
    Float,
    Half_Float,
    Scaled_Float,
    Date,
    Date_Nanos,
    Boolean,
    Binary,
    Integer_Range,
    Float_Range,
    Long_Range,
    Double_Range,
    Date_Range,
    Ip_Range,
    Object,
    Nested,
    Ip,
    TokenCount,
    Percolator,
    Flattened,
    Search_As_You_Type;

    private FieldType() {
    }
}

6. 查询index中数据信息的数量

GET test/_count
{
  "query": {
    "match_all": {}
  }
}

7. 获取所有索引

GET _all

8. 快速创建一个test的index,type为文档类型_doc

PUT test/_doc/1
{
  "name": "乔哈哈",
  "age": 18,
  "birth": "2000-01-01"
}