What is Indexing?

Indexing is a technique to optimize the selection and sorting of data in a database. An index is a data structure that stores a subset of columns from a table or a view, along with pointers to the corresponding rows. The database can use an index to quickly locate and retrieve the rows that match a given condition or order.

There are two main types of indexes in SQL Server: clustered and non-clustered. A clustered index defines the physical order of the rows in the table or view. There can be only one clustered index per table or view. A non-clustered index is a separate data structure from the table or view that stores a copy of some columns and pointers to the rows. There can be multiple non-clustered indexes per table or view.

Indexes can improve the performance of queries by reducing the amount of data that needs to be scanned or sorted at runtime. However, indexes also have some drawbacks, such as:

  • They consume disk space and memory.
  • They must be maintained when the data changes, which can cause overhead and fragmentation.
  • The query optimizer may not use them if they are unsuitable for the query or outdated or inaccurate.

Therefore, it is vital to design and implement indexes carefully based on the characteristics of the data and the queries.

Indexing for Group By

The GROUP BY clause is used to aggregate data into groups based on some common values. For example, if you want to calculate the total sales amount for each product category, you can use a query like this:

SELECT ProductCategory, SUM(SalesAmount) AS TotalSales
FROM Sales
GROUP BY ProductCategory

The query will scan all the rows in the Sales table and group them by ProductCategory. Then, it will apply the SUM function to each group and return the result.

To improve the performance of this query, you can create an index on the ProductCategory column. This index will allow the database to scan only the index instead of the whole table and use the sorted order of the index to group the rows by ProductCategory. For example:

CREATE INDEX IX_Sales_ProductCategory ON Sales(ProductCategory)

This index will cover both the grouping and selecting columns of the query so that it will be very efficient.

However, not all queries that use GROUP BY can benefit from indexing. Some factors can affect whether an index will be used or not by the query optimizer, such as:

  • The selectivity of the index: If the index covers only a small percentage of rows in the table, it is more likely to be used than an index that covers most or all rows.
  • The cardinality of the index: If the index has many distinct values, it is more likely to be used than an index with few or repeated values.
  • The index size: If the index is too large or has too many columns, it may not fit in memory or cause more I/O than scanning the table.
  • The statistics of the index: If the statistics of the index are outdated or inaccurate, they may not reflect the actual data distribution in the table or index and lead to suboptimal query plans.
  • The query hints: If you use query hints to force or prevent using an index, you may override the query optimizer’s decision.

Therefore, you should always test your queries and indexes on realistic data and workload and monitor their performance and execution plans.

Indexing for Order By

The ORDER BY clause is used to sort data in a specified order. For example, if you want to list the products by their list price in descending order, you can use a query like this:

SELECT Name, ListPrice
FROM Production.Product
ORDER BY ListPrice DESC

The query will scan all the rows in the Product table and sort them by ListPrice column in descending order. Then, it will return the result.

To improve the performance of this query, you can create an index on the ListPrice column. This index will allow the database to scan only the index instead of the whole table and return the rows without sorting them. For example:

CREATE INDEX IX_Product_ListPrice 
ON Production.Product(ListPrice DESC)

This index will cover both the selecting and sorting columns of the query so that it will be very efficient.

However, not all queries that use ORDER BY can benefit from indexing. There are some factors that can affect whether an index will be used or not by the query optimizer, such as:

  • The direction of the index: If the index is in a different order than the ORDER BY clause, it may not be used, or it may require an additional sort operation. For example, if you have an index on the ListPrice column in ascending order but want to order by ListPrice column in descending order, the index may not be helpful.
  • The columns of the index: If the index has more columns than the ORDER BY clause, it may not be used, or it may require an additional sort operation. For example, if you have an index on ListPrice and Name columns but only want to order by ListPrice column, the index may not be helpful.
  • The selectivity of the index: If the index covers only a small percentage of rows in the table, it is more likely to be used than an index that covers most or all rows.
  • The cardinality of the index: If the index has many distinct values, it is more likely to be used than an index with few or repeated values.
  • The index size: If the index is too large or has too many columns, it may not fit in memory or cause more I/O than scanning the table.
  • The statistics of the index: If the statistics of the index are outdated or inaccurate, they may not reflect the actual distribution of data in the table or index and lead to suboptimal query plans.
  • The query hints: If you use query hints to force or prevent using an index, you may override the query optimizer’s decision.

Therefore, you should always test your queries and indexes on realistic data and workload and monitor their performance and execution plans.

In this blog, we learned how to use indexes to improve the performance of queries that use the GROUP BY and ORDER BY clauses in SQL Server. We saw some examples of how creating indexes on the grouping and sorting columns can reduce the amount of data that needs to be scanned or sorted by the database engine.

However, we also learned that indexing for GROUP BY and ORDER BY is not always beneficial and that some factors can affect whether an index will be used or not by the query optimizer. Therefore, we should always test our queries and indexes on realistic data and workload and monitor their performance and execution plans.

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