Opensearch Index Mapping. Patterns for updating Amazon OpenSearch Service index settings and mappings AWS Big Data Blog OpenSearch Service indexes have two types of settings that periodically need adjustments as the profile of your workload changes: You can specify the data type for each field (for example, year as date) to make storage and querying more efficient
How to Index OpenSearch from dattell.com
If you need to index a large and unpredictable number of keyword fields on inner objects then you can use the flattened field type which maps all the object content into a single field and allows you to run basic query operations This approach seems supported by the Opensearch docs, which state (emphasis mine): If you want to create or add mappings and fields to an index, you can use the put mapping API operation
How to Index OpenSearch
Data producers can add new fields with data types to an index Mappings tell OpenSearch how to store and index your documents and their fields The better option is to always have one document type per index
Indexes OpenSearch Documentation. So it is recommended to save one mapping type into one index Mapping parameters are used to configure the behavior of index fields
Control access to Amazon OpenSearch Service Dashboards with attributebased role mappings AWS. Parameter Description; analyzer: Specifies the analyzer used to analyze string fields. You can make the document structure match the structure of the index mapping by setting the dynamic request body field to strict, as seen in the following example: {"dynamic": "strict", "properties