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The essentials of data management and analytics lie in how efficiently you can execute queries. And when it comes to SQL, query execution makes all the difference. So, how do we tune our SQL performance in Databricks? This blog post walks you through SQL performance tuning, focusing on optimising your query execution.
Understanding SQL Query Execution
At the core, SQL executes queries by scanning the entire table to search for the result, which can be time-consuming. Performance tuning involves using strategies to prevent the complete table scan and efficiently execute these queries.
Now, let’s have a look at the step-by-step guide to enhance SQL Query performance with Databricks:
Step 1: Using Indexes
The principle is simple, just like using a textbook index instead of flipping through each page, Indexes offer a shortcut to data retrieval. They reduce the amount of data that needs to be examined and speed up the retrieval times.
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CREATE INDEX idx_customer_name ON Customers (CustomerName); |
Note:
Indexes do come with the trade-off of disk space as they need to be stored, and also require maintenance when data is updated.
Step 2: Optimizing Joins
Joins can be a major reason for slowing down the performance as SQL needs to work hard to find the matching data columns between two tables. Be cautious while joining. Try to only join tables that have indexed columns and this can improve performance significantly.
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SELECT Orders.OrderID, Customers.CustomerName, Shippers.ShipperName FROM ((Orders INNER JOIN Customers ON Orders.CustomerID = Customers.CustomerID) INNER JOIN Shippers ON Orders.ShipperID = Shippers.ShipperID); |
Step 3: Using the Optimal Data Types
Using optimal data types can also significantly improve Databricks SQL performance. Try to avoid large data types if possible.
For instance, use integer (int) rather than big integer (bigint) whenever possible as int is smaller in size than bigint and it saves storage, ultimately speeding up execution.
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CREATE TABLE Customers ( CustomerID int, CustomerName varchar(255), ContactName varchar(255), Country varchar(255), Phone varchar(255), ); |
Wrap up:
These are some of the basic yet powerful techniques to enhance the performance of your SQL queries with Databricks. Remember that the key to optimisation is being aware of what is going on under the hood with each query. Happy tuning!