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PySQL Connector split into core and non core part #444

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@jprakash-db jprakash-db commented Sep 24, 2024

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databricks_sqlalchemy split is present in this PR - https://github.com/databricks/databricks-sqlalchemy/pull/1

Description

databricks-sql-python library is split so that package size can be reduced for the end user based on their requirements
Particularly pyarrow is the heavy component that is planned to be kept optional.

Users View

So for end users, who just want to use the core functionality can use the databricks_sql_connector_core, which does not have pyarrow and thus will be much smaller in size. These users will primarily be interested in dealing with small sizes of data.
For the remaining users can continue using the package as it is
existing library split into

  • databricks-sql-connector ( This is kept, so that the existing users import flow does not change )
  • databricks-sql-connector-core ( This is the lightweight library that separates the core part )

Tasks Completed

  • Refractored the code into its respective folders based on the proposed design doc
  • pyproject.toml file has been changed to reflect the proper dependencies for the split
  • Made sure that all the existing e2e and units tests are working pre and post spit, ensuring parity
  • Added benchmarking queries to test the performance of pre and post split and a dashboard has been created for visualization
  • Dependency tests are also added to check how the library behaves when certain libraries are not available and the user requests their functions

How to Test

Testing pipeline remains the same as it is before the split.
pytest can be used to directly run both the integration as well as unit tests, by pytest [directory_name or file_name]

Performance Comparison - Benchmarking

The pre-split and post-split preformance comparison has been made using the large and small queries to make sure their is no regression of performance
Dashboard has been created so that everytime the benchmarking is run the result are stored in the benchfood, and comparisons can be made easily
Screenshot 2024-09-03 at 2 48 19 PM

…ore part (#417)

* Implemented ColumnQueue to test the fetchall without pyarrow

Removed token

removed token

* order of fields in row corrected

* Changed the folder structure and tested the basic setup to work

* Refractored the code to make connector to work

* Basic Setup of connector, core and sqlalchemy is working

* Basic integration of core, connect and sqlalchemy is working

* Setup working dynamic change from ColumnQueue to ArrowQueue

* Refractored the test code and moved to respective folders

* Added the unit test for column_queue

Fixed __version__

Fix

* venv_main added to git ignore

* Added code for merging columnar table

* Merging code for columnar

* Fixed the retry_close sesssion test issue with logging

* Fixed the databricks_sqlalchemy tests and introduced pytest.ini for the sqla_testing

* Added pyarrow_test mark on pytest

* Fixed databricks.sqlalchemy to databricks_sqlalchemy imports

* Added poetry.lock

* Added dist folder

* Changed the pyproject.toml

* Minor Fix

* Added the pyarrow skip tag on unit tests and tested their working

* Fixed the Decimal and timestamp conversion issue in non arrow pipeline

* Removed not required files and reformatted

* Fixed test_retry error

* Changed the folder structure to src / databricks

* Removed the columnar non arrow flow to another PR

* Moved the README to the root

* removed columnQueue instance

* Revmoved databricks_sqlalchemy dependency in core

* Changed the pysql_supports_arrow predicate, introduced changes in the pyproject.toml

* Ran the black formatter with the original version

* Extra .py removed from all the __init__.py files names

* Undo formatting check

* Check

* Check

* Check

* Check

* Check

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* BIG UPDATE

* Refeactor code

* Refractor

* Fixed versioning

* Minor refractoring

* Minor refractoring
Print warning message if pyarrow is not installed

Signed-off-by: Jacky Hu <[email protected]>
Remove sqlalchemy and update README.md

Signed-off-by: Jacky Hu <[email protected]>
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