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- Secret To Optimizing SQL Queries - Understand The SQL Execution Order
Secret To Optimizing SQL Queries - Understand The SQL Execution Order
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Video Transcript
In this video, we're going to deep dive into SQL query execution.
We'll cover query processing, optimization techniques, and best practices.
Let's get started.
Here's the example query we'll use throughout this video.
In this query, we find the top 10 customers with at least a $1,000 spend on orders since
January 1, 2023 by joining the Customers and Orders table and grouping by customer ID.
We display their total orders and amount spent sorted in descending order
by the total spent.
Now before we dive into the query,
let's discuss query execution plans.
Database systems create these plans
to optimize queries and minimize resource usage.
Understanding the plan can help us
optimize our query for better performance.
Execution plans provide information
like estimated costs, chosen,
joint algorithms, and a sequence of operations.
Now first let's start with the from and join causes.
This is where we choose the tables we want to work with and specify how to join them.
In our query, we are using the Customers table and joining it with the Orders table using
the common ID and Custom ID columns.
Using indexes on join columns can significantly improve the performance of the join operation.
Make sure we have appropriate indexes in place for faster query execution.
Now, index types, such as B-tree and bitmap indexes, can impact performance based on data
distribution and query types.
Now we move to the WHERE clause.
This filters the combined data by applying a condition.
In our case, we are considering orders placed on or after January 1, 2023.
It's important to write a soluble query to leverage indexes effectively.
A soluble means search argument able, and
it refers to queries that can use indexes for faster execution.
Now let's dive deeper into the concept of soluble queries.
When we say a query is soluble, it means that the query can efficiently use
indexes to speed up the execution process.
Writing soluble queries is essential for optimizing database performance.
Here is an example to help illustrate soluble vs. non-soluble queries.
In a soluble query, we directly compare the two variables.
the Order Date column to a specific date. This allows the database engine to use an
index on the Order Date column to quickly filter out the records that meet the condition.
In contrast, the non-sargible query uses the year function on the Order Date column.
This prevents the database engine from using an index on Order Date because the function
must be applied to every row in the table, even if the index exists. The non-sargible
query will be slower because there are a lot more records to scan.
To write sargible queries, 1. Avoid using functions or calculations on index columns
in the WHERE clause. 2. Use direct comparisons when possible. Do not wrap columns in a function.
3. If we need to use a function on a column, create a computer column or a function-based
index if the database system supports it.
Next up are the Group By and Having causes. In our query, we are grouping the records
by customer ID and filtering the groups based on the condition, total spend greater than
or equal to $1000. This query finds those who have spent a significant amount on orders.
