The purpose for which the hardware of this elasticsearch project is optimized. Also known as the Elasticsearch project subtype.
The general_purpose option is suitable for most search use cases. For example, it is the right profile for full-text search, sparse vectors, and dense vectors that use compression such as BBQ. It is used by default when you create projects from the UI.
The vector option is recommended only for uncompressed dense vectors (dense_vector fields with int4 or int8 quantization strategies) and high dimensionality. Refer to documentation about billing dimensions for the impact to virtual compute unit (VCU) consumption.
Controls how fast searches are against your project data. When ingested, a certain amount of data is loaded into a cache that makes it super fast to query. You can either increase the performance of searches on cached data by adding replicas, or reduce the quantity of cached data by a static factor to save on costs.
Minimum value is 28, maximum value is 3000.
boost_window
integer
Determines how much data can benefit from faster search. When ingested, a certain amount of data is loaded into a cache that makes it super fast to query. The system dynamically adjusts the cache allocated to your project based on how much data you ingest during the period defined by your Search Boost Window.
Minimum value is 1, maximum value is 180.
endpoints
objectRequired
The endpoints to access the different apps of the project.