HyukjinKwon commented on a change in pull request #28085: [SPARK-29641][PYTHON][CORE] Stage Level Sched: Add python api's and tests URL: https://github.com/apache/spark/pull/28085#discussion_r408521978
########## File path: python/pyspark/resource/taskresourcerequests.py ########## @@ -0,0 +1,52 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +from pyspark.resource.taskresourcerequest import TaskResourceRequest + + +class TaskResourceRequests(object): + + """ + .. note:: Evolving + + A set of task resource requests. This is used in conjuntion with the + ResourceProfileBuilder to programmatically specify the resources needed for + an RDD that will be applied at the stage level. + """ + + def __init__(self): + """Create a new TaskResourceRequests that wraps the underlying JVM object.""" + from pyspark import SparkContext + self._javaTaskResourceRequests \ + = SparkContext._jvm.org.apache.spark.resource.TaskResourceRequests() Review comment: There's no policy for it. It's just logically best to avoid JVM access whenever it's possible because it's flaky in general and expensive, and it makes users possible to create resource files before users launch `SparkContext`. Otherwise, users should always create `SparkContext` instances first in some cases such as when using a regular Python shell. PySpark types and UDF don't have such restrictions. Do you plan to expose `ResourceProfile.id` in PySpark side as an API? From my cursory look, it might not be very difficult to switch because the classes in Python side look simple; however, I could miss something. Is there any instance dependent on JVM side? If so, we'll have no choice but depending on JVM. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
