spark-instrumented-optimizer/python/pyspark/resource/resourceprofilebuilder.py
Thomas Graves 95aec091e4 [SPARK-29641][PYTHON][CORE] Stage Level Sched: Add python api's and tests
### What changes were proposed in this pull request?

As part of the Stage level scheduling features, add the Python api's to set resource profiles.
This also adds the functionality to properly apply the pyspark memory configuration when specified in the ResourceProfile. The pyspark memory configuration is being passed in the task local properties. This was an easy way to get it to the PythonRunner that needs it. I modeled this off how the barrier task scheduling is passing the addresses. As part of this I added in the JavaRDD api's because those are needed by python.

### Why are the changes needed?

python api for this feature

### Does this PR introduce any user-facing change?

Yes adds the java and python apis for user to specify a ResourceProfile to use stage level scheduling.

### How was this patch tested?

unit tests and manually tested on yarn. Tests also run to verify it errors properly on standalone and local mode where its not yet supported.

Closes #28085 from tgravescs/SPARK-29641-pr-base.

Lead-authored-by: Thomas Graves <tgraves@nvidia.com>
Co-authored-by: Thomas Graves <tgraves@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-04-23 10:20:39 +09:00

118 lines
5 KiB
Python

#
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# 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
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from pyspark.resource.executorrequests import ExecutorResourceRequest,\
ExecutorResourceRequests
from pyspark.resource.resourceprofile import ResourceProfile
from pyspark.resource.taskrequests import TaskResourceRequest, TaskResourceRequests
class ResourceProfileBuilder(object):
"""
.. note:: Evolving
Resource profile Builder to build a resource profile to associate with an RDD.
A ResourceProfile allows the user to specify executor and task requirements for
an RDD that will get applied during a stage. This allows the user to change the
resource requirements between stages.
.. versionadded:: 3.1.0
"""
def __init__(self):
from pyspark.context import SparkContext
_jvm = SparkContext._jvm
if _jvm is not None:
self._jvm = _jvm
self._java_resource_profile_builder = \
_jvm.org.apache.spark.resource.ResourceProfileBuilder()
else:
self._jvm = None
self._java_resource_profile_builder = None
self._executor_resource_requests = {}
self._task_resource_requests = {}
def require(self, resourceRequest):
if isinstance(resourceRequest, TaskResourceRequests):
if self._java_resource_profile_builder is not None:
if resourceRequest._java_task_resource_requests is not None:
self._java_resource_profile_builder.require(
resourceRequest._java_task_resource_requests)
else:
taskReqs = TaskResourceRequests(self._jvm, resourceRequest.requests)
self._java_resource_profile_builder.require(
taskReqs._java_task_resource_requests)
else:
self._task_resource_requests.update(resourceRequest.requests)
else:
if self._java_resource_profile_builder is not None:
if resourceRequest._java_executor_resource_requests is not None:
self._java_resource_profile_builder.require(
resourceRequest._java_executor_resource_requests)
else:
execReqs = ExecutorResourceRequests(self._jvm, resourceRequest.requests)
self._java_resource_profile_builder.require(
execReqs._java_executor_resource_requests)
else:
self._executor_resource_requests.update(resourceRequest.requests)
return self
def clearExecutorResourceRequests(self):
if self._java_resource_profile_builder is not None:
self._java_resource_profile_builder.clearExecutorResourceRequests()
else:
self._executor_resource_requests = {}
def clearTaskResourceRequests(self):
if self._java_resource_profile_builder is not None:
self._java_resource_profile_builder.clearTaskResourceRequests()
else:
self._task_resource_requests = {}
@property
def taskResources(self):
if self._java_resource_profile_builder is not None:
taskRes = self._java_resource_profile_builder.taskResourcesJMap()
result = {}
for k, v in taskRes.items():
result[k] = TaskResourceRequest(v.resourceName(), v.amount())
return result
else:
return self._task_resource_requests
@property
def executorResources(self):
if self._java_resource_profile_builder is not None:
result = {}
execRes = self._java_resource_profile_builder.executorResourcesJMap()
for k, v in execRes.items():
result[k] = ExecutorResourceRequest(v.resourceName(), v.amount(),
v.discoveryScript(), v.vendor())
return result
else:
return self._executor_resource_requests
@property
def build(self):
if self._java_resource_profile_builder is not None:
jresourceProfile = self._java_resource_profile_builder.build()
return ResourceProfile(_java_resource_profile=jresourceProfile)
else:
return ResourceProfile(_exec_req=self._executor_resource_requests,
_task_req=self._task_resource_requests)