This document explains about the terms used in the Handbook.
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An alias is a virtual index name that can point to one or more indices.
Aggregations let you tap into OpenSearch’s powerful analytics engine to analyze your data and extract statistics from it.
Note: OpenSearch doesn’t support aggregations on a
There are three main types of aggregations:
- Metric aggregations - Calculate metrics such as sum, min, max, and avg on numeric fields.
- Bucket aggregations - Sort query results into groups based on some criteria.
- Pipeline aggregations - Pipe the output of one aggregation as an input to another.
A set of documents in Kibiter that have certain characteristics in common. For example, matching documents might be bucketed by name, type, or date range.
A collection of visualizations that provide insights into your data.
The data sources are the platforms and tools from where BAP can pull data to analyze.
A JSON object containing data stored and indexed in OpenSearch.
A key-value pair in a document.
Hatstall is a web interface for SortingHat databases developed mainly with Django.
It is available in
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A collection of JSON documents.
A string containing a wildcard (*) pattern that can match multiple indices or aliases.
The process of collecting data from various data sources and sending it to OpenSearch.
Request for information about your data. You can think of a query as a question, written in a way OpenSearch understands.
Unstructured content, such as a product description or log message which can be used for better analysis.
A graphical representation of query results in Kibiter.