1.7 release note. [skip ci] #8374
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trivialfis
changed the title
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@hcho3 @RAMitchell @WeichenXu123 @razdoburdin @wbo4958 @rongou Could you please take a look into the release note and check if it's a fair summary of your work? |
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looks fine |
NEWS.md
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| ### PySpark | ||
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| XGBoost 1.7 features initial support for PySpark integration. The new interface is adopted from the existing PySpark XGBoost interface developed by databricks with additional features like `QuantileDMatrix` and rapidsai plugin (GPU pipeline) support. The new Spark XGBoost Python estimators not only benefits from PySpark ml facilities for powerful distributed computing but also enjoys the rest of the Python ecosystem. Users can define a custom objective, callbacks, and metrics in Python and use them with this interface on distributed clusters. The support is labeled as experimental with more features to come in future releases. For a brief introduction please visit the tutorial on XGBoost's [document page](https://xgboost.readthedocs.io/en/latest/tutorials/spark_estimator.html). (#8355, #8344, #8335, #8284, #8271, #8283, #8250, #8231, #8219, #8245, #8217, #8200, #8173, #8172, #8145, #8117, #8131, #8088, #8082, #8085, #8066, #8068, #8067, #8020, #8385) |
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Q: When can we remove the experimental label ?
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@WeichenXu123 I think we will have at least one release for that. I will walk through the open issues for pyspark later on and revise a roadmap for improving it after 1.7.
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@WeichenXu123 I started a new github project for pyspark https://github.com/dmlc/xgboost/projects/5 .
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LGTM |
trivialfis
commented
Oct 27, 2022
rongou
approved these changes
Oct 27, 2022
hcho3
requested changes
Oct 28, 2022
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
RAMitchell
approved these changes
Oct 28, 2022
Co-authored-by: Rory Mitchell <r.a.mitchell.nz@gmail.com>
hcho3
approved these changes
Oct 28, 2022
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