Cardinality Estimation is a crucial component of SQL
Server's query optimization process. It is the process by which the database
engine estimates the number of rows that will be returned by a query. The
accuracy of this estimation is important because it determines the execution
plan that the database engine will use to retrieve the data. If the estimation
is inaccurate, the database engine may choose an inefficient execution plan, resulting
in slow query performance.
In layman's terms, Cardinality Estimation is like a traffic
prediction system that estimates the number of cars that will be on a
particular road at a specific time. This information helps traffic management
systems plan the most efficient routes for commuters and reduce traffic
congestion.
Similarly, Cardinality Estimation in SQL Server helps
optimize the execution of queries by providing an estimate of the number of
rows that will be returned. This estimate is based on statistics gathered about
the data in the database. The accuracy of this estimation is important because
it determines the execution plan that the database engine will use to retrieve
the data. If the estimation is inaccurate, the database engine may choose an
inefficient execution plan, resulting in slow query performance.
For example, suppose you have a table of customer data and
you want to retrieve all customers who live in a certain state. The database
engine might use statistics on the number of customers in each state to
estimate the number of customers who live in the state you're interested in.
Based on this estimation, it will choose an execution plan that it believes
will be most efficient.
The accuracy of the Cardinality Estimation directly impacts
the performance of SQL Server. If the estimate is too low, SQL Server may
allocate more resources than necessary to execute the query, resulting in slow
performance. Conversely, if the estimate is too high, SQL Server may choose an
inefficient execution plan, leading to slower performance as well.
To improve the accuracy of Cardinality Estimation, SQL
Server uses statistical data about the data in the database, including the
number of distinct values, data distribution, and data correlation. It also considers
query predicates, joins, and filtering conditions to generate the most accurate
estimate.
In conclusion, Cardinality Estimation is an essential
process in SQL Server's query optimization. It estimates the number of rows
that will be returned by a query, allowing SQL Server to choose the most
efficient execution plan. By understanding Cardinality Estimation and its
importance, database administrators can improve the performance of their SQL
Server instances and ensure that queries run efficiently.