Introduction

Want to supercharge query performance on your large SQL Server tables? Non-clustered columnstore indexes are a powerful tool for achieving blazing-fast analytics queries. But to get the most benefit, it’s crucial to choose the optimal column order when creating the index. In this post, you’ll learn the key principles for determining the best column order, with concrete examples to illustrate. Mastering this will enable you to build highly efficient columnstore indexes that greatly accelerate your queries.

Understanding Row Groups and Segments

At the core of a columnstore index are row groups and segments:

• A columnstore index organizes the data into groups of 1,048,576 rows called row groups
• Each column within a row group is stored as a separate column segment

When a query accesses the columnstore index, it scans the needed column segments. The query performance depends heavily on which column segments must be read. Therefore, the primary goal when choosing column order is to minimize the number of segments that need to be scanned for common queries.

Placing Commonly Filtered Columns First

One of the main principles is to place the most commonly filtered columns first in the index definition. This enables efficient segment elimination. For example, consider a table of product sales with these columns:

• SalesDate
• ProductCategory
• ProductSubcategory
• SalesAmount

If queries often filter by SalesDate and ProductCategory, an effective column order would be:

1. SalesDate
2. ProductCategory
3. ProductSubCategory
4. SalesAmount

With this order, queries filtering by SalesDate and ProductCategory can skip scanning the segments for ProductSubcategory and SalesAmount. This significantly reduces I/O and boosts query performance.

Ordering Low Cardinality Columns First

Another key principle is to place low cardinality columns earlier in the column order. Cardinality refers to the number of distinct values in a column. Columns with low cardinality, such as a ProductCategory column with a small number of distinct categories, are effective at enabling segment elimination when placed first. In contrast, placing a unique identifier column first would have little benefit as each value occurs only once.

Example of an Optimized Column Order

Let’s look at an example to tie these principles together. Assume we have a FactSales table with these columns:

• DateKey
• StoreKey
• ProductKey
• PromotionKey
• CurrencyKey
• SalesQuantity
• SalesAmount

An optimized column order for a non-clustered columnstore index might be:

1. DateKey – commonly filtered, low cardinality
2. StoreKey – commonly filtered, low cardinality
3. PromotionKey – low cardinality
4. CurrencyKey – low cardinality
5. ProductKey
6. SalesQuantity
7. SalesAmount

This order puts the most commonly filtered and low cardinality columns first, enabling efficient segment elimination for typical queries. The high cardinality ProductKey and metric columns are placed last as they are less likely to be filtered on.

Conclusion

Choosing the optimal column order is essential to getting the best performance from non-clustered columnstore indexes. By placing commonly filtered and low cardinality columns first, you can enable SQL Server to efficiently eliminate unnecessary column segments during query processing. I encourage you to apply these principles to your own columnstore indexes – the performance benefits can be substantial! To learn more, check out the in-depth columnstore index guide on Microsoft’s website. Happy optimizing!