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Learn how to perform `Terms Aggregation` in Elasticsearch to count distinct terms across nested collections effectively.
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Distinct Terms Aggregation in Elasticsearch: Count Fruits Across Nested Collections

When working with nested documents in Elasticsearch, especially when it comes to aggregating data, you might run into challenges. One such problem arises when you want to count distinct terms from nested collections, such as fruits in your dataset. This guide will guide you through the process of achieving this desired outcome using Elasticsearch's aggregation framework.

Understanding the Problem

Suppose you have a structure of documents where each document contains nested elements. For instance, you could have documents structured like this:

[[See Video to Reveal this Text or Code Snippet]]

In this scenario, you aim to count how many distinct bars contain various fruit values. For example, you may want to recognize that:

banana appears in 2 different bars

apple also appears in 2 different bars

But orange appears in only 1 bar

The challenge is to modify your existing aggregation query to reflect this requirement accurately.

Existing Aggregation Query

Initially, you may have created an aggregation similar to this:

[[See Video to Reveal this Text or Code Snippet]]

This query accurately counts the total occurrences of each fruit, but it does not count how many distinct bars contain each fruit, leading to incorrect doc_count values.

The Solution

To achieve your goal of counting distinct bars for each fruit, you can utilize a combination of terms aggregation along with reverse_nested aggregation. Here’s how you can modify your query:

Updated Query Structure

[[See Video to Reveal this Text or Code Snippet]]

Expected Results

With the updated query, the results should now provide a better picture of your distinct counts, something like this:

[[See Video to Reveal this Text or Code Snippet]]

Breaking Down Results

Key: This is the fruit type.

Doc_count: Represents the total occurrences of that fruit across all bars.

Fruit_to_bears: This shows how many distinct bars contain that specific fruit.

Conclusion

By adjusting your Elasticsearch aggregation query to include reverse_nested functionality, you can effectively count distinct terms from nested collections. This method enhances your ability to analyze your data and derive valuable insights.

Feel free to experiment with this approach to better suit your specific use case. Happy querying!