fix: Refactor of LightGBM wrapper to prepare for streaming #1557
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svotaw
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Codecov Report
@@ Coverage Diff @@
## master #1557 +/- ##
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- Coverage 83.76% 83.55% -0.21%
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Files 301 305 +4
Lines 15376 15776 +400
Branches 698 732 +34
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+ Hits 12879 13181 +302
- Misses 2497 2595 +98
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/BasePartitionTask.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/BasePartitionTask.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/BulkPartitionTask.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMBase.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMBase.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMBase.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMBase.scala
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lightgbm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMPerformance.scala
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...bm/src/main/scala/com/microsoft/azure/synapse/ml/lightgbm/params/ClassifierTrainParams.scala
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mhamilton723
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Jul 12, 2022
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mhamilton723
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Jul 13, 2022
mhamilton723
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Approved to the best of my knowledge, @imatiach-msft @eisber please feel free to take a look and provide any comments!
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mhamilton723
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eisber
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Summary
In preparation for adding a "streaming" mode to LightGBM functionality (mostly to improve memory usage), this PR refactors the existing wrapper code. Followup PRs will actually add the streaming components, but this initial PR makes the following major interrelated changes to improve the organization of LightGBM code:
LightGBMBaseis now driver-only methods, and all worker code is inBasePartitionTaskand derived classes (onlyBulkPartitionTaskfor now).NetworkManager, a class that encapsulates all Networking functionality, both driver/worker and Spark/LightGBM.TrainingContextobject to help pass around configuration and initialization information easily, without passing lots of method parameters. This applies at the driver level for all of training, but there are also similar newPartitionTaskContextandPartitionTaskTrainingStateobjects that encapsulate read-only and variable properties respectively for individual tasks.InstrumentationMeasures, a class that holds timing perf for various stages, both for all of training and individual tasks. This class is returned along with the Booster, so is even exposed to the user.I also cleaned up all warnings about file/method length, use of "while" loops, excessive code branching, etc. There's more official tail recursion and less use of vars.
Notable new functionality:
NOTE: The actual streaming components are not huge, but were omitted for now to help shorten the long PR, and also since this PR can be checked in without any new native LightGBM library components.
Tests
Since this is a refactor, the existing LightGBM test suite should be sufficient, and for now runs in "bulk" mode only. The next PR will add "streaming" mode and reconcile the tests.
Dependency changes
If you needed to make any changes to dependencies of this project, please describe them here.
AB#1866292