On Wed, Aug 2, 2017 at 7:49 AM, Chris Hebert <
[email protected]> wrote:
> Thanks for the feedback!
>
> Aggregated thoughts:
>
> 1. Warn users about large files (like 5GB large)
>
I would set the threshold smaller. Also remember, that while you may warn,
some runners might simply fail to process the record causing pipelines to
either get stuck or fail all together.
> 2. Filenames can stick with contents via PCollection<KV<filename,
> contents>>
> 3. InputStreams can't be encoded directly, but could be referenced in a
> FileWrapper object
> 4. Be mindful of sink race conditions with multiple workers; make sure
> failed workers cleanup incompletely written files
> 5. File systems often do better with few large files than many small
> ones
> 6. Most/all of this can be done in the context of a DoFn
>
> # Regarding point 1 and point 2
> Yes!
>
> # Regarding point 3:
>
> ## Approach A:
> When the FileWrapper is encoded, it must somehow encode a reference to the
> InputStream it is associated with, so that when the FileWrapper is decoded
> it can pick up that InputStream again. My Java knowledge isn't deep enough
> to know how one would do that with hashcodes and object lookup and such,
> but I could sidestep that entirely by simply encoding the filepath with the
> FileWrapper, then open up a new InputStream on that file path every time
> the FileWrapper is decoded.
>
> ## Approach B:
> An alternative to the above technique is to simply pass a byte[] array,
> like so:
> PCollection<KV<String, byte[]>> fileNamesAndBytes = p.apply("Read",
> WholeFileIO.read().from("/path/to/input/dir/*"));
>
> That would solve the encoding problem, allow users to get whatever they
> want out of it with a ByteArrayInputStream, AND put a hard limit on the
> size of incoming files at just below 2 GB (if my math is right). (This is
> large enough for my use case, at present.)
>
>
> # Regarding point 4:
>
> Any examples or guidance I could pull from to protect against this
> properly?
>
>
> # Regarding point 5:
>
> TextIO can read and write with different compressions. Would it be feasible
> for this WholeFileIO to read and write these many files to compressed zip
> files also? (I envision this as a stretch feature that would be added after
> the initial iteration anyway.)
>
>
> # Regarding point 6:
>
> The only prebuilt IO thing I've found find in Beam that uses DoFn is
> WriteFiles. Do you have any examples to point towards to enlighten me on
> the use of DoFn in this context? Unfortunately, we all know the "Authoring
> I/O Transforms" documentation is sparse.
>
>
> Keep it coming,
> Chris
>
> On Tue, Aug 1, 2017 at 3:55 PM, Robert Bradshaw
> <[email protected]
> > wrote:
>
> > On Tue, Aug 1, 2017 at 1:42 PM, Eugene Kirpichov <
> > [email protected]> wrote:
> >
> > > Hi,
> > > As mentioned on the PR - I support the creation of such an IO (both
> read
> > > and write) with the caveats that Reuven mentioned; we can refine the
> > naming
> > > during code review.
> > > Note that you won't be able to create a PCollection<InputStream>
> because
> > > elements of a PCollection must have a coder and it's not possible to
> > > provide a coder for InputStream.
> >
> >
> > Well, it's possible, but the fact that InputStream is mutable may cause
> > issues (e.g. if there's fusion, or when estimating its size).
> >
> > I would probably let the API consume/produce a PCollection<KV<filename,
> > contents>>. Alternatively, a FileWrapper object of some kind could
> provide
> > accessors to InputStream (or otherwise facilitate lazy reading).
> >
> > Note for the sink one must take care there's no race in case multiple
> > workers are attempting to process the same bundle (and ideally cleanup in
> > the face of failure). Other than that, these could be entirely done in
> the
> > context of a DoFn.
> >
> > Also not that most filesystems, especially distributed ones, do better
> > reading and writing fewer larger files than many, many small ones.
> >
> >
> > > On Tue, Aug 1, 2017 at 1:33 PM Reuven Lax <[email protected]>
> > > wrote:
> > >
> > > > One thing to keep in mind is that many runners might have issues with
> > > huge
> > > > elements. If you have a 5gb file, encoding it as a single element
> might
> > > > give you pain or might simply not work on some runners.
> > > >
> > > > Reuven
> > > >
> > > > On Tue, Aug 1, 2017 at 1:22 PM, Chris Hebert <
> > > > [email protected]> wrote:
> > > >
> > > > > Hi,
> > > > >
> > > > > I'd like to:
> > > > >
> > > > > 1. Read whole files as one input each. (If my input files are
> > > hi.txt,
> > > > > what.txt, and yes.txt, then the whole contents of hi.txt are an
> > > > element
> > > > > of
> > > > > the returned PCollection, the whole contents of what.txt are the
> > > next
> > > > > element, etc.)
> > > > > 2. Write elements as individual files. (Rather than smashing
> > > thousands
> > > > > of outputs into a handful of files as TextIO does:
> > > > > output-00000-of-00005,
> > > > > output-00001-of-00005,..., I want to output each thing
> > individually.
> > > > So
> > > > > if
> > > > > I'm given hi.txt, what.txt, yes.txt then I'd like to read those
> in
> > > as
> > > > > whole
> > > > > files individually, then write out my processed results as
> > > > > hi.txt-modified,
> > > > > what.txt-modified, yes.txt-modified.).
> > > > >
> > > > > Before reading on, if you have easier ways to do these things, then
> > I'd
> > > > > love to hear them!
> > > > >
> > > > > # Part 1
> > > > >
> > > > > I attempted Part 1 with this PR:
> > > > > https://github.com/apache/beam/pull/3543
> > > > >
> > > > > But I overgeneralized.
> > > > >
> > > > > Specifically, I want:
> > > > >
> > > > > Pipeline p = Pipeline.create(options);
> > > > > PCollection<Strings> wholeFilesAsStrings = p.apply("Read Whole
> Files
> > > from
> > > > > Input Directory", WholeFileIO.read().from("/
> path/to/input/dir/*"));
> > > > >
> > > > > or
> > > > >
> > > > > Pipeline p = Pipeline.create(options);
> > > > > PCollection<InputStream> wholeFileStreams = p.apply("Read Whole
> Files
> > > > from
> > > > > Input Directory", WholeFileIO.read().from("/
> path/to/input/dir/*"));
> > > > >
> > > > > Bonus points would include:
> > > > >
> > > > > - Keeping the filename somehow
> > > > >
> > > > >
> > > > > # Part 2
> > > > >
> > > > > Currently, if you output hundreds of thousands of elements
> > (batch-mode)
> > > > > with TextIO in Beam on Flink with, say, 45 TaskManagers, then you
> get
> > > > > output-00000-of-00045, output-00001-of-00045, etc., and each one of
> > > those
> > > > > files contain tens of thousands of outputs back to back. I want
> them
> > to
> > > > be
> > > > > output as individual files.
> > > > >
> > > > > If appended after code snippets from Part 1, it would look like:
> > > > >
> > > > > ...
> > > > > p.apply("Write Whole File Outputs",
> > > > > WholeFileIO.write().to("/path/to/output/dir/"));
> > > > >
> > > > > Bonus points would include:
> > > > >
> > > > > - Writing each element of the given PCollection to the filename
> > > they'd
> > > > > like to go to.
> > > > > - Parallelizable. (This might already be done, I just noticed
> that
> > > my
> > > > > Beam+Flink+YARN pipeline with TextIO.write() only had one
> > > TaskManager
> > > > > writing the DataSink output even though all other components of
> my
> > > > > pipeline
> > > > > had many TaskManagers working on them simultaneously. I haven't
> > > found
> > > > > the
> > > > > way to fix that yet. The current arrangement added 15 minutes to
> > the
> > > > > end of
> > > > > my pipeline as the lonely TaskManager did all the output.)
> > > > >
> > > > >
> > > > > I'm available to put the dev work into this. (Actually, I'm putting
> > dev
> > > > > time into some kind of solution whether this is agreed upon or not
> > :).
> > > > >
> > > > > Feedback, please,
> > > > > Chris
> > > > >
> > > >
> > >
> >
>
