首先插入几条数据,让es自动为我们建立一个索引
PUT /website/article/1
{
"post_date": "2017-01-01",
"title": "my first article",
"content": "this is my first article in this website",
"author_id": 11400
}
PUT /website/article/2
{
"post_date": "2017-01-02",
"title": "my second article",
"content": "this is my second article in this website",
"author_id": 11400
}
PUT /website/article/3
{
"post_date": "2017-01-03",
"title": "my third article",
"content": "this is my third article in this website",
"author_id": 11400
}
尝试各种搜索
GET /website/article/_search?q=2017
GET /website/article/_search?q=2017-01-01
GET /website/article/_search?q=post_date:2017-01-01
GET /website/article/_search?q=post_date:2017
1)
GET /website/article/_search?q=2017
响应结果 3条结果
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.28004453,
"hits": [
{
"_index": "website",
"_type": "article",
"_id": "2",
"_score": 0.28004453,
"_source": {
"post_date": "2017-01-02",
"title": "my second article",
"content": "this is my second article in this website",
"author_id": 11400
}
},
{
"_index": "website",
"_type": "article",
"_id": "1",
"_score": 0.28004453,
"_source": {
"post_date": "2017-01-01",
"title": "my first article",
"content": "this is my first article in this website",
"author_id": 11400
}
},
{
"_index": "website",
"_type": "article",
"_id": "3",
"_score": 0.28004453,
"_source": {
"post_date": "2017-01-03",
"title": "my third article",
"content": "this is my third article in this website",
"author_id": 11400
}
}
]
}
}
2)
GET /website/article/_search?q=2017-01-01
响应结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 1.0566096,
"hits": [
{
"_index": "website",
"_type": "article",
"_id": "1",
"_score": 1.0566096,
"_source": {
"post_date": "2017-01-01",
"title": "my first article",
"content": "this is my first article in this website",
"author_id": 11400
}
},
{
"_index": "website",
"_type": "article",
"_id": "2",
"_score": 0.84013355,
"_source": {
"post_date": "2017-01-02",
"title": "my second article",
"content": "this is my second article in this website",
"author_id": 11400
}
},
{
"_index": "website",
"_type": "article",
"_id": "3",
"_score": 0.84013355,
"_source": {
"post_date": "2017-01-03",
"title": "my third article",
"content": "this is my third article in this website",
"author_id": 11400
}
}
]
}
}
3)
GET /website/article/_search?q=post_date:2017-01-01
响应结果
{
"took": 84,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "website",
"_type": "article",
"_id": "1",
"_score": 1,
"_source": {
"post_date": "2017-01-01",
"title": "my first article",
"content": "this is my first article in this website",
"author_id": 11400
}
}
]
}
}
4)
GET /website/article/_search?q=post_date:2017
响应结果
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "website",
"_type": "article",
"_id": "1",
"_score": 1,
"_source": {
"post_date": "2017-01-01",
"title": "my first article",
"content": "this is my first article in this website",
"author_id": 11400
}
}
]
}
}
我们会奇怪在2)搜索2017-01-01为什么会出现3条数据、在4)搜索2017为什么只出现1条数据
这是为什么呢?
查看es自动建立的mapping,带出什么是mapping的知识点自动或手动为index中的type建立的一种数据结构和相关配置,简称为mapping dynamic mapping:自动为我们建立index,创建type,以及type对应的mapping,mapping中包含了每个field对应的数据类型,以及如何分词等设置 dynamic mapping这个后边会了解的,我们当然也可以手动建立mapping,在创建数据之前,先创建index和type,以及type对应的mapping
查看自动创建的mappingGET /website/_mapping/article
响应结果
{
"website": {
"mappings": {
"article": {
"properties": {
"author_id": {
"type": "long"
},
"content": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"post_date": {
"type": "date"
},
"title": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
}
自动创建的mapping中设置了fileds的类型
author_id:long
content:text
post_date:date
title:text
因为es自动建立mapping的时候,设置了不同的field不同的data type。不同的data type的分词、搜索等行为是不一样的。
比如
GET /website/article/_search?q=2017-01-01
GET /website/article/_search?q=post_date:2017-01-01
q=2017-01-01 应该使用的是text的分词、搜索,
q=post_date:2017-01-01 使用的是date的分词、搜索
所以出现了_all field和post_date field的搜索表现完全不一样。