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https://issues.apache.org/jira/browse/BEAM-10111?focusedWorklogId=465558&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-465558
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ASF GitHub Bot logged work on BEAM-10111:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Aug/20 05:55
Start Date: 03/Aug/20 05:55
Worklog Time Spent: 10m
Work Description: stale[bot] closed pull request #11840:
URL: https://github.com/apache/beam/pull/11840
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Issue Time Tracking
-------------------
Worklog Id: (was: 465558)
Time Spent: 40m (was: 0.5h)
> Create methods in fileio to read from / write to archive files
> --------------------------------------------------------------
>
> Key: BEAM-10111
> URL: https://issues.apache.org/jira/browse/BEAM-10111
> Project: Beam
> Issue Type: Improvement
> Components: io-py-files
> Reporter: Ashwin Ramaswami
> Assignee: Ashwin Ramaswami
> Priority: P2
> Time Spent: 40m
> Remaining Estimate: 0h
>
> Discussion here:
> https://lists.apache.org/thread.html/r784701bda9edf9a52d5ee593f44a8870aab96b6df1dc8eedd2c8a249%40%3Cdev.beam.apache.org%3E
> It would be good to be able to read from / write to archive files (.zip,
> .tar) using fileio. The difference between this proposal and what we already
> have with CompressionTypes is that this would allow converting one file ->
> multiple files and vice versa. Here's how it might look like:
> *Reading all contents from archive files:*
> {code:python}
> files = (
> p
> | fileio.MatchFiles('hdfs://path/to/*.zip')
> | fileio.ExtractMatches()
> | fileio.MatchAll()
> | fileio.ReadMatches()
> | beam.Map(lambda x: (x.metadata.path,
> x.metadata._parent_archive_paths, x.read_utf8()))
> )
> {code}
> *Nested archive example:* (look for all inside of .tar inside of .zip)
> {code:python}
> files = (
> p
> | fileio.MatchFiles('hdfs://path/to/*.zip')
> | fileio.ExtractMatches()
> | fileio.MatchAll('*.tar')
> | fileio.Extract()
> | fileio.MatchAll() # gets all entries
> | fileio.ReadMatches()
> | beam.Map(lambda x: (x.metadata.path, x.read_utf8()))
> )
> {code}
> Note that in this case, this would involve modifying MatchAll() to take an
> argument, which would filter the files in the pcollection in the earlier
> stage of the pipeline.
> *Reading from archive files and explicitly specifying the archive type (when
> it can't be inferred by the file extension):*
> {code:python}
> files = (
> p
> | fileio.MatchFiles('hdfs://path/to/archive')
> | fileio.ExtractMatches(archivesystem=ArchiveSystem.TAR)
> | fileio.MatchAll(archive_path='*.txt')
> | fileio.ReadMatches()
> | beam.Map(lambda x: (x.metadata.path, x.read_utf8()))
> )
> {code}
> `ArchiveSystem` would be a generic class, just like `FileSystem`, which would
> allow for different implementations of methods such as `list()` and
> `extract()`. It would be implemented for .zip, .tar, etc.
> *Writing multiple files to an archive file:*
> {code:python}
> files = (
> p
> | fileio.MatchFiles('hdfs://path/to/files/*.txt')
> | fileio.CompressMatches(archivesystem=ArchiveSystem.ZIP)
> | fileio.WriteToArchive("output.zip")
> )
> {code}
> *Writing to a .tar.gz file:*
> {code:python}
> files = (
> p
> | fileio.MatchFiles('hdfs://path/to/files/*.txt')
> | fileio.CompressMatches(archivesystem=ArchiveSystem.TAR)
> | fileio.WriteToArchive("output.tar.gz")
> )
> {code}
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