Indexing Best Practices - (CosmosDB Performance Optimization)

Azure Cosmos DB is a popular NoSQL database platform that allows for global distribution, fast performance, and high availability. One of the key features of Cosmos DB is its indexing capabilities, which allow for fast querying and efficient data retrieval. In this tutorial, we'll discuss some indexing best practices for optimizing performance in Cosmos DB.

Syntax

There is no specific syntax for indexing best practices in Cosmos DB.

Example

Suppose you have a Cosmos DB collection that contains the following documents:

{
    "id": "1",
    "firstName": "John",
    "lastName": "Doe",
    "address": {
        "city": "New York",
        "state": "NY",
        "zip": "10001"
    }
}

To improve performance when querying by the firstName and lastName properties, you can create a composite index as follows using the Azure Portal:

1. Navigate to your Cosmos DB account in the Azure Portal.
2. Click on the "Data Explorer" tab.
3. Navigate to the collection and click on its name.
4. Click on the "Settings" tab.
5. Under "Indexes", click on the "Add Composite Index" button.
6. Create an index with the path ["firstName", "lastName"] and mark it as the default index for the collection.

This composite index helps to optimize queries that filter by both the firstName and lastName properties.

Explanation

Indexing in Cosmos DB is essential for efficient query processing and data retrieval. By optimizing your indexes, you can improve query performance and reduce the number of RU/s (request units per second) consumed by queries.

There are several best practices that you can follow when indexing Cosmos DB collections, including creating composite indexes for queries that filter on multiple properties, indexing large arrays and nested objects, and disabling indexing for rarely queried properties.

Use

Optimizing your indexes in Cosmos DB is an essential part of performance tuning. By following best practices for index creation and maintenance, you can ensure that your queries are processed quickly and efficiently.

Important Points

Here are some important points to keep in mind when indexing Cosmos DB collections:

• Create composite indexes for frequently queried properties.
• Use sparse indexes for rarely queried properties.
• Monitor the RU/s consumption of your queries to identify index performance bottlenecks.
• Use dedicated throughput for large collections to ensure consistent query performance.
• Use range-based partitioning to evenly distribute data and minimize query latencies.

Summary

In this tutorial, we discussed indexing best practices for optimizing performance in Cosmos DB. We covered the syntax, example, explanation, use, and important points of indexing in Cosmos DB. By following these best practices, you can ensure that your queries are processed efficiently and effectively, resulting in faster query times and lower RU/s consumption.