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2025-01-19 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Development >
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This article focuses on "Elasticsearch mapping field data types and management methods", interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Next let the editor to take you to learn "Elasticsearch mapping field data types and management methods" it!
Elasticsearch mapping management
Indexes created in Elasticsearch 6.0.0 or later contain only one mapping type. Indexes created with multiple mapping types in 5.x will continue to run in Elasticsearch 6.x as before. Mapping types will be completely deleted in Elasticsearch 7.0.0
An introduction to mapping
When you create an index, you can pre-define the type and related properties of the field
Es guesses the fields you want to map based on the underlying type of the Json data source, turning the input data into index items that can be searched.
Mapping is a field data type that we define ourselves, while telling es how to index the data and whether it can be searched.
Function: it will make the establishment of the index more detailed and perfect.
1.1 Field data types
String type: text,keyword
Number type: long,integer,short,byte,double,float
Date type: data
Boolean type: boolean
Binary type: binary
Complex types: object (entities, objects), nested (list)
Geo Type: geo-point,geo-shape (Geographic location)
Type of major: ip,competion (search suggestions)
The mapping parameter attribute description is suitable for the type store value: yes for storage, no for no storage, default for noallindexyes for analysis, no for no analysis, default for truetextnull_value if the field is empty, you can set a default value, such as "NA" (pass empty, cannot search, na can search) allanalyzer can set the index and search when using the parser, the default is the standard parser, you can also use whitespace,simple. All English parsers allinclude_in_all default es defines a special field _ all for each document, its function is to let each field be searched. If you want a field not to be searched, you can set it to falseallformat time format string mode date2 to create an index.
Text type will take out words for inverted index, keyword will not be participle, stored as is, matching as is
Once the mapping type is determined, it cannot be modified in the future
# 6.x version no problem PUT books {"mappings": {"book": {"properties": {"title": {"type": "text", "analyzer": "ik_max_word"}, "price": {"type": "integer"} "addr": {"type": "keyword"}, "company": {"properties": {"name": {"type": "text"}, "company_addr": {"type": "text"}, "employee_count": {"type": "integer"} "publish_date": {"type": "date", "format": "yyy-MM-dd"}
After 7.x version
PUT books {"mappings": {"properties": {"title": {"type": "text", "analyzer": "ik_max_word"}, "price": {"type": "integer"}, "addr": {"type": "keyword"} "company": {"properties": {"type": "text"}, "company_addr": {"type": "text"}, "employee_count": {"type": "integer"}, "publish_date": {"type": "date", "format": "yyy-MM-dd"}
Insert data test:
PUT books/_doc/1 {"title": "Big head son thief father", "price": 100," addr ":" Beijing Tiananmen Square "," company ": {" name ":" I love Beijing Tiananmen Square "," company_addr ":" my home is in the Northeast Songhua River silly girl "," employee_count ": 10} "publish_date": "2019-08-19"} # Test data 2PUT books/_doc/2 {"title": "Snow White and the Ten Dwarfs", "price": "99", # string will automatically convert "addr": "Dark Senli", "company": {"name": "my hometown is in Shanghai", "company_addr": "Friends walk together for Life", "employee_count": 10} "publish_date": "2018-05-19"} three View Index # View the mappingGET books/_mapping# of the books index to get all the mappingGET _ all/_mapping here I believe that you have a deeper understanding of "Elasticsearch mapping field data types and management methods". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!
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