Bucket aggregations (terms, histogram) in Elasticsearch - Mini Project: Build & Apply

Bucket aggregations with terms and histogram in Elasticsearch

📖 Scenario: You have a collection of sales data stored in Elasticsearch. Each sale has a product name and a price. You want to analyze this data by grouping sales by product and by price ranges.

🎯 Goal: Build an Elasticsearch query that uses bucket aggregations to group sales by product names using a terms aggregation, and also group sales by price ranges using a histogram aggregation.

📋 What You'll Learn

Create a terms aggregation named products on the product field

Create a histogram aggregation named price_ranges on the price field with interval 50

Nest the histogram aggregation inside the terms aggregation

Print the final JSON query

💡 Why This Matters

🌍 Real World

Bucket aggregations help analyze large datasets by grouping data into meaningful categories or ranges, such as grouping sales by product or price ranges.

💼 Career

Understanding bucket aggregations is essential for data analysts and backend developers working with Elasticsearch to build reports and dashboards.

1

Create the base Elasticsearch query with empty aggregations

Create a variable called query and assign it a dictionary with a key aggs set to an empty dictionary {}.

Elasticsearch

query = {
    "aggs": {}
}
# Your code here

Need a hint?

Start by creating a dictionary named query with an aggs key set to an empty dictionary.

2

Add a terms aggregation named products on the product field

Add a terms aggregation named products inside query["aggs"] that groups by the product field.

Elasticsearch

query = {
    "aggs": {
        # Add terms aggregation named 'products' on 'product' field here
    }
}
# Your code here

Need a hint?

Inside aggs, add a products key with a terms aggregation on the product field.

3

Add a histogram aggregation named price_ranges on the price field inside products

Inside the products aggregation, add a nested histogram aggregation named price_ranges on the price field with an interval of 50.

Elasticsearch

query = {
    "aggs": {
        "products": {
            "terms": {
                "field": "product"
            },
            # Add histogram aggregation named 'price_ranges' on 'price' field with interval 50 here
        }
    }
}
# Your code here

Need a hint?

Inside products, add an aggs key with a price_ranges histogram aggregation on price with interval 50.

4

Print the final Elasticsearch query

Write a print(query) statement to display the complete Elasticsearch query dictionary.

Elasticsearch

query = {
    "aggs": {
        "products": {
            "terms": {
                "field": "product"
            },
            "aggs": {
                "price_ranges": {
                    "histogram": {
                        "field": "price",
                        "interval": 50
                    }
                }
            }
        }
    }
}
# Print the query below
# Your code here

Need a hint?

Use print(query) to show the full query dictionary.