Indexed views with columnstore indexes

 Indexed views with columnstore indexes in SQL Server combine the benefits of indexed views with the performance advantages of columnstore indexes. This combination is particularly useful for data warehousing and analytical workloads where you need to aggregate and query large volumes of data efficiently.

Understanding Columnstore Indexes

Columnstore Indexes are a type of index optimized for read-heavy operations, particularly for large-scale data warehouses and analytic queries. They store data in a columnar format rather than the traditional row-based format, which can significantly improve performance for certain types of queries.

Indexed Views with Columnstore Indexes

Here’s how you can use columnstore indexes with indexed views to enhance performance:

1. Create the Indexed View

First, you need to create an indexed view. The view must be defined with WITH SCHEMABINDING, and you must create a unique clustered index on the view.

Example of creating an indexed view:

CREATE VIEW dbo.SalesSummary
WITH SCHEMABINDING
AS
SELECT 
    SalesPersonID,
    SUM(SalesAmount) AS TotalSales
FROM 
    dbo.Sales
GROUP BY 
    SalesPersonID;

2. Create a Columnstore Index on the Indexed View

After creating the indexed view, you can create a columnstore index on it. Columnstore indexes are particularly effective for large datasets with many aggregate queries.

Example of creating a columnstore index on the indexed view:

CREATE NONCLUSTERED COLUMNSTORE INDEX IX_SalesSummary_Columnstore
ON dbo.SalesSummary;

Key Points

1. Data Storage: Columnstore indexes store data in a columnar format, which reduces I/O and can improve query performance for large datasets, especially for queries involving aggregations or scans.

2. Compression: Columnstore indexes use advanced compression techniques, which can reduce the amount of storage required and improve I/O performance.

3. Performance: Combining indexed views with columnstore indexes can significantly enhance performance for analytic queries by reducing the need for large-scale aggregations and scans.

4. Update Performance: Be aware that columnstore indexes are optimized for read operations. While they support updates, inserts, and deletes, the performance for these operations may not be as high as for traditional row-based indexes.

5. Use Cases: This approach is particularly useful in data warehousing scenarios where you need to aggregate and analyze large volumes of data efficiently.

Example Query

After creating the indexed view with a columnstore index, you can query it like any other view:

SELECT 
    SalesPersonID,
    TotalSales
FROM 
    dbo.SalesSummary
WHERE 
    TotalSales > 10000;

This query will benefit from the columnstore index, especially if the TotalSales column is involved in the filtering or aggregation.

Summary

Using columnstore indexes with indexed views can provide significant performance improvements for analytical queries by combining the benefits of both technologies. Indexed views offer precomputed results, while columnstore indexes optimize storage and retrieval for large datasets. This approach is highly effective in data warehousing and analytical environments where performance is crucial.