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?

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

Description

PyArrow Filesystems don't expect paths to be provided as URIs with a scheme prefix (e.g. s3://). The only reason that DeltaTable.to_pyarrow_dataset() works (if you don't pass a filesystem) is that our DeltaStorageHandler accepts URIs.

We need to change so that:

1. DeltaStorageHandler rejects scheme prefixes
2. We always pass file paths to PyArrow functions *withou

Follow-up work for #1460

• expose name-to-id mapping for warehouses & clusters

Example syntax could be as below

data "databricks_sql_warehouses" "all_shared" {
  warehouse_name_contains = "shared"
}

output "warehouses_mapping" {
  value = data.databricks_sql_warehouses.all_shared.mappings <- this returns { "shared" = "11", "shared_1" = [12, 13]}
}

• add lookup of cluster