[
https://issues.apache.org/jira/browse/BEAM-13734?focusedWorklogId=715969&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-715969
]
ASF GitHub Bot logged work on BEAM-13734:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Jan/22 20:21
Start Date: 26/Jan/22 20:21
Worklog Time Spent: 10m
Work Description: VictorPlusC commented on a change in pull request
#16601:
URL: https://github.com/apache/beam/pull/16601#discussion_r793016733
##########
File path:
sdks/python/apache_beam/runners/interactive/interactive_environment.py
##########
@@ -675,3 +683,25 @@ def get_sql_chain(self, pipeline, set_user_pipeline=False):
pipeline)
chain.user_pipeline = pipeline
return chain
+
+ def check_bucket_exists(self, bucket_name):
+ try:
+ from apitools.base.py.exceptions import HttpError
+ except:
+ raise ImportError('Could not import HttpError from apitools.')
+
+ try:
+ storage_client = storage.StorageV1(
+ credentials=auth.get_service_credentials(),
+ get_credentials=False,
+ http=get_new_http(),
+ response_encoding='utf8')
+ request = storage.StorageBucketsGetRequest(bucket=bucket_name)
+ storage_client.buckets.Get(request)
+ except HttpError as e:
+ if e.status_code == 404:
+ _LOGGER.error("{} bucket does not exist!".format(bucket_name))
+ else:
+ _LOGGER.warning(
+ "HttpError - unable to verify whether bucket {} exists.\
+ ".format(bucket_name))
Review comment:
Noted, this should be resolved. Thanks!
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Issue Time Tracking
-------------------
Worklog Id: (was: 715969)
Time Spent: 3h 50m (was: 3h 40m)
> Support cache directories that use GCS buckets
> ----------------------------------------------
>
> Key: BEAM-13734
> URL: https://issues.apache.org/jira/browse/BEAM-13734
> Project: Beam
> Issue Type: New Feature
> Components: runner-py-interactive
> Reporter: Victor Chen
> Assignee: Victor Chen
> Priority: P2
> Time Spent: 3h 50m
> Remaining Estimate: 0h
>
> * Builds off of the work accomplished under BEAM-13685
> * Modified interactive_environment.py to support caching to a bucket on GCS
> for batch processing pipelines
> * If a specified bucket does not exist, the pipeline will terminate and
> return an error specifying that the bucket does not exist
> * Added cleanup() functionality to cache_manager.py, to enable the
> FileBasedCacheManager class to automatically delete cached values on GCS when
> a bucket path is specified
> * Added docstring to interactive_beam.py with an example of GCS path
> assignment
> * Cached files on GCS will be stored under a directory represented by the
> value of id(pipeline).
> ** Example cached path: gs://my-gcs-bucket/cache/dir/id(pipeline)
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