[
https://issues.apache.org/jira/browse/BEAM-13812?focusedWorklogId=729174&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-729174
]
ASF GitHub Bot logged work on BEAM-13812:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 17/Feb/22 19:09
Start Date: 17/Feb/22 19:09
Worklog Time Spent: 10m
Work Description: VictorPlusC commented on a change in pull request
#16741:
URL: https://github.com/apache/beam/pull/16741#discussion_r809379319
##########
File path:
sdks/python/apache_beam/runners/interactive/dataproc/dataproc_cluster_manager.py
##########
@@ -18,60 +18,71 @@
# pytype: skip-file
import logging
+from dataclasses import dataclass
from typing import Optional
-try:
- from google.cloud import dataproc_v1
-except ImportError:
- raise ImportError(
- 'Google Cloud Dataproc not supported for this execution environment.')
+from apache_beam.runners.interactive import interactive_environment as ie
_LOGGER = logging.getLogger(__name__)
+@dataclass
+class MasterURLIdentifier:
+ project_id: Optional[str] = None
+ region: Optional[str] = None
+ cluster_name: Optional[str] = None
+
+ def __key(self):
+ return (self.project_id, self.region, self.cluster_name)
+
+ def __hash__(self):
+ return hash(self.__key())
+
+ def __eq__(self, other):
+ if isinstance(other, MasterURLIdentifier):
+ return self.__key() == other.__key()
+ raise NotImplementedError(
+ 'Comparisons are only supported between '
+ 'instances of MasterURLIdentifier.')
+
+
class DataprocClusterManager:
"""The DataprocClusterManager object simplifies the operations
required for creating and deleting Dataproc clusters for use
under Interactive Beam.
"""
- DEFAULT_NAME = 'interactive-beam-cluster'
-
- def __init__(
- self,
- project_id: Optional[str] = None,
- region: Optional[str] = None,
- cluster_name: Optional[str] = None) -> None:
+ def __init__(self, cluster_metadata: MasterURLIdentifier) -> None:
"""Initializes the DataprocClusterManager with properties required
to interface with the Dataproc ClusterControllerClient.
"""
-
- self._project_id = project_id
- if region == 'global':
+ self.cluster_metadata = cluster_metadata
+ if self.cluster_metadata.region == 'global':
# The global region is unsupported as it will be eventually deprecated.
raise ValueError('Clusters in the global region are not supported.')
- elif region:
- self._region = region
- else:
+ elif not self.cluster_metadata.region:
_LOGGER.warning(
'No region information was detected, defaulting Dataproc cluster '
'region to: us-central1.')
- self._region = 'us-central1'
+ self.cluster_metadata.region = 'us-central1'
- if cluster_name:
- _LOGGER.warning(
- 'A user-specified cluster_name has been detected. '
- 'Please note that you will have to manually delete the Dataproc '
- 'cluster that will be created under the name: %s',
- cluster_name)
- self._cluster_name = cluster_name
- else:
- self._cluster_name = self.DEFAULT_NAME
+ if not self.cluster_metadata.cluster_name:
+ self.cluster_metadata.cluster_name = ie.current_env(
+ ).clusters.default_cluster_name
+ from google.cloud import dataproc_v1
self._cluster_client = dataproc_v1.ClusterControllerClient(
client_options={
- 'api_endpoint': f'{self._region}-dataproc.googleapis.com:443'
+ 'api_endpoint':
f'{self.cluster_metadata.region}-dataproc.googleapis.com:443'
})
+ if self.cluster_metadata in ie.current_env().clusters.master_urls.inverse:
+ self.master_url = self.get_master_url(self.cluster_metadata)
Review comment:
Sounds good, I've updated the code now. Thanks!
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Issue Time Tracking
-------------------
Worklog Id: (was: 729174)
Time Spent: 19h 50m (was: 19h 40m)
> Integrate DataprocClusterManager into Interactive Environment
> -------------------------------------------------------------
>
> Key: BEAM-13812
> URL: https://issues.apache.org/jira/browse/BEAM-13812
> Project: Beam
> Issue Type: New Feature
> Components: runner-py-interactive
> Reporter: Victor Chen
> Assignee: Victor Chen
> Priority: P2
> Time Spent: 19h 50m
> Remaining Estimate: 0h
>
> * Adds code to automatically create a Dataproc cluster configured with Docker
> and Flink if a user instantiates an InteractiveRunner using
> underlying_runner='FlinkRunner'
> * By default, the created Dataproc cluster will be called
> 'interactive-beam-cluster' and will be cleaned up when the Interactive
> Environment is interrupted
> * Users will be able to toggle an automatic deletion of the cluster with the
> default name, 'interactive-beam-cluster' when the kernel is interrupted
> * Introduces the Clusters class in interactive_beam.py, which acts as a user
> interface that provides the user with the following capabilities:
> ** Changing the default name of the clusters created by Interactive Beam
> ** Cleaning up a cluster by providing a corresponding pipeline, an option to
> force the deletion is provided, in the case where more than one pipeline use
> the same cluster
> ** Getting all pipelines that use the provided master_url
> ** Receiving a description back for either the cluster corresponding to a
> specific pipeline, or the descriptions of all pipelines
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