In Sparkflows, we can use the ‘Windows Analytics’ processor to perform Windows Analytics on a dataset. It facilitates partitioning the dataset based on a selected column and applies windows functions such as first_value, last_value, lag and lead to compute value.
To use the ‘Windows Analytics’ Processor:
Select a set of columns to partition the dataset in the ‘Partition By’ field.
Select a set of columns to Order dataset in the ‘Order By’ field.
Select ‘Windows Function’ to be used to perform analysis.
Select a column in ‘Analytics Columns’. Windows function selected would be applied to the selected column. It would be added as a new column to the output dataset.
Enter a value for ‘Window Offset’. It would be used when a function is selected as ‘Lead’ or ‘Lag’. It would determine how many backward or forward rows data would be used.
For more information read the Sparkflows Documentation here:
Hey Nagisa,
In Sparkflows, we can use the ‘Windows Analytics’ processor to perform Windows Analytics on a dataset. It facilitates partitioning the dataset based on a selected column and applies windows functions such as first_value, last_value, lag and lead to compute value.
To use the ‘Windows Analytics’ Processor:
Select a set of columns to partition the dataset in the ‘Partition By’ field.
Select a set of columns to Order dataset in the ‘Order By’ field.
Select ‘Windows Function’ to be used to perform analysis.
Select a column in ‘Analytics Columns’. Windows function selected would be applied to the selected column. It would be added as a new column to the output dataset.
Enter a value for ‘Window Offset’. It would be used when a function is selected as ‘Lead’ or ‘Lag’. It would determine how many backward or forward rows data would be used.
For more information read the Sparkflows Documentation here:
https://docs.sparkflows.io/en/latest/user-guide/data-preparation/others.html?highlight=windows%20analytics#windows-analytics