Range buckets in Elasticsearch - Mini Project: Build & Apply

Range Buckets

📖 Scenario: You work for an online store that wants to analyze sales data. You have a list of product prices and want to group them into price ranges to see how many products fall into each range.

🎯 Goal: Create an Elasticsearch query that uses range buckets to group products by price ranges: 0-50, 50-100, and 100-200.

📋 What You'll Learn

Create an Elasticsearch aggregation using range buckets on the price field.

Define three ranges: 0 to 50, 50 to 100, and 100 to 200.

Include a match_all query to select all products.

Print the final JSON query.

💡 Why This Matters

🌍 Real World

Range buckets help businesses understand how their products or sales are distributed across different value ranges, like price or age groups.

💼 Career

Knowing how to use range buckets in Elasticsearch is useful for data analysts and backend developers working with search and analytics platforms.

1

Create the base query

Create a JSON object called query with a match_all query to select all documents.

Elasticsearch

# Create the base query with match_all
# Your code here

Need a hint?

The match_all query selects all documents in the index.

2

Add the range aggregation configuration

Add an aggs key to query with a price_ranges aggregation of type range on the price field. Define the ranges: 0 to 50, 50 to 100, and 100 to 200.

Elasticsearch

query = {
  "query": {
    "match_all": {}
  }
}
# Add aggs with price_ranges range aggregation
# Your code here

Need a hint?

Use the range aggregation type and specify the field and ranges array.

3

Add the core logic to build the range buckets

Ensure the price_ranges aggregation correctly groups documents into the three price ranges using the range buckets on the price field.

Elasticsearch

query = {
  "query": {
    "match_all": {}
  },
  "aggs": {
    "price_ranges": {
      "range": {
        "field": "price",
        "ranges": [
          {"to": 50},
          {"from": 50, "to": 100},
          {"from": 100, "to": 200}
        ]
      }
    }
  }
}
# Confirm the range buckets are set correctly
# Your code here

Need a hint?

Check that the range aggregation has the correct field and ranges.

4

Print the final query

Print the query JSON object to display the complete Elasticsearch query with range buckets.

Elasticsearch

query = {
  "query": {
    "match_all": {}
  },
  "aggs": {
    "price_ranges": {
      "range": {
        "field": "price",
        "ranges": [
          {"to": 50},
          {"from": 50, "to": 100},
          {"from": 100, "to": 200}
        ]
      }
    }
  }
}
# Print the query
# Your code here

Need a hint?

Use print(json.dumps(query, indent=2)) to display the JSON nicely.