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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2020/05/27 22:18:00 UTC
[jira] [Work logged] (BEAM-10111) Create methods in fileio to read
from / write to archive files
[ https://issues.apache.org/jira/browse/BEAM-10111?focusedWorklogId=438055&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-438055 ]
ASF GitHub Bot logged work on BEAM-10111:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 27/May/20 22:17
Start Date: 27/May/20 22:17
Worklog Time Spent: 10m
Work Description: epicfaace opened a new pull request #11840:
URL: https://github.com/apache/beam/pull/11840
[still a draft]
The general idea here is that we use mixins (subclasses of `ArchiveFileSystemMixin`) for each archive type (tar, zip, etc.). Each mixin "wraps" the I/O operations of its corresponding FileSystem (GCSFileSystem, LocalFileSystem, etc.) so that it behaves like an archive that is mounted on its corresponding FileSystem.
```python
(
p
| MatchFiles("*.log", archive_path="s3://ashwin-bucket123/logs.zip")
| Map(print)
)
```
------------------------
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Issue Time Tracking
-------------------
Worklog Id: (was: 438055)
Remaining Estimate: 0h
Time Spent: 10m
> 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: 10m
> Remaining Estimate: 0h
>
> 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)
> | textio.WriteToText("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)
> | textio.WriteToText("output.tar.gz")
> )
> {code}
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