Learning ElasticSearch: additions and deletions to the document change search

• Here we are with index database index as an example, is still using the postman to send data to complete json
  

1, by

• 1 refers _id documents, not following id, id with the same general _id

{
	"id":1,
	"title":"我是一个标题1",
	"content":"我是内容1"
}

• Get results, success

{
    "_index": "index",
    "_type": "1",
    "_id": "AW6dhLRtj92VZTE9RyoB",
    "_version": 1,
    "result": "created",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "created": true
}

2, delete

• Return json

{
    "found": true,
    "_index": "index",
    "_type": "1",
    "_id": "AW6dhLRtj92VZTE9RyoB",
    "_version": 2,
    "result": "deleted",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    }
}

• Here are the figures behind the _id

3, change

• The principle here is: delete and add, where you can directly add operation, it will delete and add
• Before modifying
  
  
• Return json

{
    "_index": "index",
    "_type": "hello",
    "_id": "1",
    "_version": 2,
    "result": "updated",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "created": false
}

• View data
  

4, according to query id

• The request is to query changed to get
• Json data returned

{
	"_index": "index",
	"_type": "hello",
	"_id": "1",
	"_version": 2,
	"found": true,
	"_source": {
		"id": 1,
		"title": "修改之后的文档",
		"content": "修改之后的内容"
	}
}

5, according to the keyword query

• Here is a post request
  

{
	"query":{
		"term":{
			"title":"修"
		}
	}
}

• And in which the query term are keywords., Where queries can only enter a Chinese character
• Return json

{
	"took": 127,
	"timed_out": false,
	"_shards": {
		"total": 5,
		"successful": 5,
		"skipped": 0,
		"failed": 0
	},
	"hits": {
		"total": 2,
		"max_score": 0.28582606,
		"hits": [
			{
				"_index": "index",
				"_type": "hello",
				"_id": "1",
				"_score": 0.28582606,
				"_source": {
					"id": 1,
					"title": "修改之后的文档",
					"content": "修改之后的内容"
				}
			},
			{
				"_index": "index",
				"_type": "hello",
				"_id": "3",
				"_score": 0.25811607,
				"_source": {
					"id": 1,
					"title": "修改之后的文档as12d",
					"content": "修改之后的内12容"
				}
			}
		]
	}
}

6, queryString inquiry

• Using this word will be, with the word above query is the same.
  
• Returned json

{
	"took": 125,
	"timed_out": false,
	"_shards": {
		"total": 5,
		"successful": 5,
		"skipped": 0,
		"failed": 0
	},
	"hits": {
		"total": 2,
		"max_score": 0.5716521,
		"hits": [
			{
				"_index": "index",
				"_type": "hello",
				"_id": "1",
				"_score": 0.5716521,
				"_source": {
					"id": 1,
					"title": "修改之后的文档",
					"content": "修改之后的内容"
				}
			},
			{
				"_index": "index",
				"_type": "hello",
				"_id": "3",
				"_score": 0.51623213,
				"_source": {
					"id": 1,
					"title": "修改之后的文档as12d",
					"content": "修改之后的内12容"
				}
			}
		]
	}
}

7, extension

• Segmentation effect in view tokenizer
• Enter http://127.0.0.1:9200/_analyze?analyzer=standard&text=
• Rising behind text with English or Chinese

Support for English

{
    "tokens": [
        {
            "token": "i",
            "start_offset": 0,
            "end_offset": 1,
            "type": "<ALPHANUM>",
            "position": 0
        },
        {
            "token": "am",
            "start_offset": 2,
            "end_offset": 4,
            "type": "<ALPHANUM>",
            "position": 1
        },
        {
            "token": "a",
            "start_offset": 5,
            "end_offset": 6,
            "type": "<ALPHANUM>",
            "position": 2
        },
        {
            "token": "hbu",
            "start_offset": 7,
            "end_offset": 10,
            "type": "<ALPHANUM>",
            "position": 3
        },
        {
            "token": "student",
            "start_offset": 11,
            "end_offset": 18,
            "type": "<ALPHANUM>",
            "position": 4
        }
    ]
}

For support of Chinese

{
    "tokens": [
        {
            "token": "我",
            "start_offset": 0,
            "end_offset": 1,
            "type": "<IDEOGRAPHIC>",
            "position": 0
        },
        {
            "token": "是",
            "start_offset": 1,
            "end_offset": 2,
            "type": "<IDEOGRAPHIC>",
            "position": 1
        },
        {
            "token": "河",
            "start_offset": 2,
            "end_offset": 3,
            "type": "<IDEOGRAPHIC>",
            "position": 2
        },
        {
            "token": "北",
            "start_offset": 3,
            "end_offset": 4,
            "type": "<IDEOGRAPHIC>",
            "position": 3
        },
        {
            "token": "大",
            "start_offset": 4,
            "end_offset": 5,
            "type": "<IDEOGRAPHIC>",
            "position": 4
        },
        {
            "token": "学",
            "start_offset": 5,
            "end_offset": 6,
            "type": "<IDEOGRAPHIC>",
            "position": 5
        },
        {
            "token": "青",
            "start_offset": 6,
            "end_offset": 7,
            "type": "<IDEOGRAPHIC>",
            "position": 6
        },
        {
            "token": "年",
            "start_offset": 7,
            "end_offset": 8,
            "type": "<IDEOGRAPHIC>",
            "position": 7
        }
    ]
}

• In fact this is very bad for the Chinese, so the actual development we do not use a standard word breaker