Apache Spark is an open source distributed general-purpose cluster-computing framework. It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?
On more advanced versions of LakeFS (probably > = v1.0.0), we would like to remove the logic that tries to fill the generation field in DB when loading old dumps. It means we will no longer support loading dump that made with a version lower than v0.61.0.
Describe the bug
When the finalizer is called for CLR JvmObjectId objects, it calls the rm DotnetBackend method and this calls goes through the JvmBridge class. Because the rm call goes through [JvmBridge.CallJavaMethod](https://github.com/do
Created by Matei Zaharia
Released May 26, 2014
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