Understanding Bucket Aggregations
Bucket aggregations are used to group documents into “buckets” based on certain criteria. Here are some commonly used bucket aggregations:
- Terms Aggregation: Groups documents by the unique values of a field.
- Date Histogram Aggregation: Groups documents into time intervals.
- Range Aggregation: Groups documents into ranges based on numeric values.
- Histogram Aggregation: Groups documents into intervals based on numeric values.
Example: Grouping Products by Category
Suppose we want to group products by their category. We can use the term aggregation to achieve this.
GET /products/_search
{
"aggs": {
"categories": {
"terms": {
"field": "category.keyword"
}
}
}
}
Output:
{
"aggregations": {
"categories": {
"buckets": [
{
"key": "electronics",
"doc_count": 5
},
{
"key": "clothing",
"doc_count": 3
},
{
"key": "books",
"doc_count": 2
}
]
}
}
}
In this example, products are grouped into categories, and the number of products in each category is counted.
Elasticsearch Aggregations
Elasticsearch is not just a search engine; it’s a powerful analytics tool that allows you to gain valuable insights from your data. One of the key features that make Elasticsearch so powerful is its ability to perform aggregations.
In this article, we’ll explore Elasticsearch aggregations in detail, explaining what they are, how they work, and providing examples with outputs to help you understand them better.
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