Keyword Mapping Elasticsearch

You use full text search to discover relevant text in documents while you would use keyword identifiers for sorting aggregating and filtering the documents.

Keyword mapping elasticsearch. One as a text type for full text search and another as keyword type which in most cases is a waste of space. The dynamic mapping rules can be configured to customise the mapping that is used for new fields. What was new in elasticsearch 5 0 for mapping. There are more but these are the most common core datatypes.

The keyword and text datatypes haven t always been part of elasticsearch. Here is a list of elasticsearch s core datatypes for reference. However they are often retrieved using term level queries. If i wanted multiple keywords associated with a json document how would i create the mapping for the index s field.

Elasticsearch supports a number of different datatypes for the fields in a. I use node js elasticsearch module to create mapping indices and insert documents to elasticsearch. However keyword fields are better for term and other term level queries. You know more about your data than elasticsearch can guess so while dynamic mapping can be useful to get started at some point you will want to specify your own explicit mappings.

Originally elasticsearch provided just a single string datatype and users could set an option called index to either analyzed or not analyzed in their mapping to specify whether they wanted a string to be broken down into its individual terms upon indexing or simply indexed as is. Now map each field to an elasticsearch data type by the data it will store. Mapping is the outline of the documents stored in an index. Elasticsearch automatically creates an all field inside the mapping and copies values of each field of a document inside the all field.

Elasticsearch optimizes numeric fields such as integer or long for range queries. For example if the field stored a date then the elasticsearch date datatype would be used. Identifiers such as an isbn or a product id are rarely used in range queries. I checked in kibana that types of all fields correspond to types i set in mapping for each field but fields with a keyword type sometimes every 1 3 days may be changed and have extra field field keyword or vise versa field keyword may disappear and original field became aggregatable.

It defines the data type like geo point or string and format of the fields present in the documents and rules to control the mapping of dynamically added fields. Not all numeric data should be mapped as a numeric field data type.