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https://issues.apache.org/jira/browse/BEAM-2572?focusedWorklogId=342817&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-342817
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ASF GitHub Bot logged work on BEAM-2572:
----------------------------------------
Author: ASF GitHub Bot
Created on: 13/Nov/19 19:30
Start Date: 13/Nov/19 19:30
Worklog Time Spent: 10m
Work Description: pabloem commented on pull request #9955: [BEAM-2572]
Python SDK S3 Filesystem
URL: https://github.com/apache/beam/pull/9955#discussion_r345936305
##########
File path: sdks/python/apache_beam/io/aws/s3filesystem.py
##########
@@ -0,0 +1,275 @@
+#
+# 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.
+#
+"""S3 file system implementation for accessing files on AWS S3."""
+
+from __future__ import absolute_import
+
+from future.utils import iteritems
+
+from apache_beam.io.aws import s3io
+from apache_beam.io.filesystem import BeamIOError
+from apache_beam.io.filesystem import CompressedFile
+from apache_beam.io.filesystem import CompressionTypes
+from apache_beam.io.filesystem import FileMetadata
+from apache_beam.io.filesystem import FileSystem
+
+__all__ = ['S3FileSystem']
+
+
+class S3FileSystem(FileSystem):
+ """An S3 `FileSystem` implementation for accessing files on AWS S3
+ """
+
+ CHUNK_SIZE = s3io.MAX_BATCH_OPERATION_SIZE
+ S3_PREFIX = 's3://'
+
+ @classmethod
+ def scheme(cls):
+ """URI scheme for the FileSystem
+ """
+ return 's3'
+
+ def join(self, basepath, *paths):
+ """Join two or more pathname components for the filesystem
+
+ Args:
+ basepath: string path of the first component of the path
+ paths: path components to be added
+
+ Returns: full path after combining all of the return nulled components
+ """
+ if not basepath.startswith(S3FileSystem.S3_PREFIX):
+ raise ValueError('Basepath %r must be S3 path.' % basepath)
+
+ path = basepath
+ for p in paths:
+ path = path.rstrip('/') + '/' + p.lstrip('/')
+ return path
+
+ def split(self, path):
+ """Splits the given path into two parts.
+
+ Splits the path into a pair (head, tail) such that tail contains the last
+ component of the path and head contains everything up to that.
+
+ Head will include the S3 prefix ('s3://').
+
+ Args:
+ path: path as a string
+ Returns:
+ a pair of path components as strings.
+ """
+ path = path.strip()
+ if not path.startswith(S3FileSystem.S3_PREFIX):
+ raise ValueError('Path %r must be S3 path.' % path)
+
+ prefix_len = len(S3FileSystem.S3_PREFIX)
+ last_sep = path[prefix_len:].rfind('/')
Review comment:
a lot of this code is duplicated, so it would be nice to deduplicate between
the filesystems.... but you don't need to worry about it for now : P
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Issue Time Tracking
-------------------
Worklog Id: (was: 342817)
Time Spent: 1.5h (was: 1h 20m)
> Implement an S3 filesystem for Python SDK
> -----------------------------------------
>
> Key: BEAM-2572
> URL: https://issues.apache.org/jira/browse/BEAM-2572
> Project: Beam
> Issue Type: Task
> Components: sdk-py-core
> Reporter: Dmitry Demeshchuk
> Priority: Minor
> Labels: GSoC2019, gsoc, gsoc2019, mentor, outreachy19dec
> Time Spent: 1.5h
> Remaining Estimate: 0h
>
> There are two paths worth exploring, to my understanding:
> 1. Sticking to the HDFS-based approach (like it's done in Java).
> 2. Using boto/boto3 for accessing S3 through its common API endpoints.
> I personally prefer the second approach, for a few reasons:
> 1. In real life, HDFS and S3 have different consistency guarantees, therefore
> their behaviors may contradict each other in some edge cases (say, we write
> something to S3, but it's not immediately accessible for reading from another
> end).
> 2. There are other AWS-based sources and sinks we may want to create in the
> future: DynamoDB, Kinesis, SQS, etc.
> 3. boto3 already provides somewhat good logic for basic things like
> reattempting.
> Whatever path we choose, there's another problem related to this: we
> currently cannot pass any global settings (say, pipeline options, or just an
> arbitrary kwarg) to a filesystem. Because of that, we'd have to setup the
> runner nodes to have AWS keys set up in the environment, which is not trivial
> to achieve and doesn't look too clean either (I'd rather see one single place
> for configuring the runner options).
> Also, it's worth mentioning that I already have a janky S3 filesystem
> implementation that only supports DirectRunner at the moment (because of the
> previous paragraph). I'm perfectly fine finishing it myself, with some
> guidance from the maintainers.
> Where should I move on from here, and whose input should I be looking for?
> Thanks!
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