Implement over() function for window aggregations#42
Open
Conversation
Co-Authored-By: neema.raphael@gs.com <Neema.Raphael@gs.com>
…mentation Co-Authored-By: neema.raphael@gs.com <Neema.Raphael@gs.com>
Co-Authored-By: neema.raphael@gs.com <Neema.Raphael@gs.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Implement over() function for window aggregationsThis PR implements the
over()function in LegendQL, which is used within theextend()method to perform window aggregations.Changes include:- Implemented the_parse_overfunction inparser.pyto handle window aggregations- Addedvisit_over_functionmethod to the ExecutionVisitor interface inmetamodel.py- Implemented conversion of OverFunction to Legend code indialect.py- Enabled the previously skipped test intest/parser/parser_test.py- Added comprehensive unit tests intest/parser/over_function_test.pycovering: - Basic over function usage - Multiple partition columns - Multiple aggregation functions - Sort specifications - Rows and range frames - Qualify filtersAll tests are now passing, confirming that the implementation works correctly.Link to Devin run: https://app.devin.ai/sessions/6a4229792d9f439d9a81e501119a24dcRequested by: Neema Raphael