Types of Bucket Aggregations
Elasticsearch provides several types of bucket aggregations, each suited for different grouping scenarios:
- Terms Aggregation: Groups documents based on unique values in a field.
- Histogram Aggregation: Groups numeric data into buckets of a fixed size.
- Date Histogram Aggregation: Groups date values into buckets of a fixed time interval.
- Range Aggregation: Groups numeric data into custom ranges.
- Date Range Aggregation: Groups date values into custom date ranges.
- Filter Aggregation: Groups documents that match a specific filter.
- Filters Aggregation: Groups documents based on multiple filters.
- Significant Terms Aggregation: Finds unusual terms in a set of documents.
- Geohash Grid Aggregation: Groups geo-point data into geohash cells.
Example Dataset
To illustrate bucket aggregations, let’s consider an Elasticsearch index called products with documents like this:
{
"product_id": 1,
"name": "Laptop",
"category": "electronics",
"price": 1000,
"quantity_sold": 5,
"rating": 4.5,
"sold_date": "2023-01-15"
}
Bucket Aggregation in Elasticsearch
Elasticsearch is a robust tool not only for full-text search but also for data analytics. One of the core features that make Elasticsearch powerful is its aggregation framework, particularly bucket aggregations. Bucket aggregations allow you to group documents into buckets based on certain criteria, making it easier to analyze and summarize your data.
This article will explain what bucket aggregations are, how they work, and provide detailed examples to help you understand their usage.
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