Learn Window Functions on Snowflake. Become a cloud data warehouse superhero.
In a recent post we compared Window Function Features by Database Vendors. In this post we will give you an overview on the support for various window function features on Snowflake. Window functions are essential for data warehousing Window functions are the base of data warehousing workloads for many reasons. First of all they are ...
Read MoreComparing Window Function Features by Database Vendors
We will round off the series on window functions with comparison of what database vendors offer. There are various mutations of window functions and every vendor supports a different subset or feature. Some also add extra window functions or features beyond standard ANSI SQL. One of the most powerful features is user-defined aggregate functions (UDAF), ...
Read MoreWindow Function ROWS and RANGE on Redshift and BigQuery
Frames in window functions allow us to operate on subsets of the partitions by breaking the partition into even smaller sequences of rows. SQL provides syntax to express very flexible definitions of a frame. We described the syntax in the first post on Window functions and demonstrated some basic use cases in the post on ...
Read MoreRedshift Window Functions Advanced Use Cases
Merging time-based events into periods Thanks to our previous posts about the window functions, Introduction to Window functions on Redshift and Data exploration with Window functions on Redshift, you should now be familiar with the most common functions that can be used in the OVER clause and how to apply them to your data. Today, ...
Read More