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From Jinal Shah <jinalshah2...@gmail.com>
Subject Re: Execution Control
Date Fri, 14 Feb 2014 19:47:14 GMT
Hi Chao,

Thanks for the reply. By Sequential I mean the run jobs in Sequence rather
than in Parallel. Is there a way in Crunch to bulk load data to HBase
directly?

Thanks
Jinal





On Thu, Feb 13, 2014 at 9:36 PM, Chao Shi <stepinto@live.com> wrote:

> Hi Jinal,
>
> > So how do I tell the planner in this
> case to run in Sequential format. Here is how the code looks like
> I didn't get your question. Did you mean "sequence file" format? HBase
> cannot load sequence file natively. You have to transform it into HFile via
> MR, then bulk load it into HBase.
>
> The code piece you show looks good to me. One potential problem is that,
> running MR on the same cluster with HBase will damage the serving quality
> (i.e. causing greater latency).
>
> In our production deployment, we have two clusters: one running HBase and
> serving online requests and the other for offline MR jobs. So we run a
> pipeline to produce HFiles, distcp them to the online cluster (with limited
> #mappers), then perform HBase bulkload.
>
> > Is there a way to do it Crunch itself to do incremental reads from HFiles
> which are stored in hdfs?
>
> No, there is no way to incrementally read HFiles. I think you have options:
> 1) use FromHBase#table(String, Scan) and specify the timestamp range that
> you are interested. Note that this will issue read RPCs to Region Servers,
> which may produce huge traffic and damage your online serving quality.
> 2) copy HFiles to another location and use HFileUtils#scanHFiles(). You can
> also specify the timerange but it internally does a full scan.
>
>
>
>
>
> 2014-02-14 2:30 GMT+08:00 Jinal Shah <jinalshah2007@gmail.com>:
>
> > Is there a way to do it Crunch itself to do incremental reads from HFiles
> > which are stored in hdfs?
> >
> > Thanks
> >
> >
> > On Thu, Feb 13, 2014 at 11:50 AM, Josh Wills <jwills@cloudera.com>
> wrote:
> >
> > > The only option I have for you in that case is pipeline.run or
> > > pipeline.done; LoadIncrementalHFiles isn't Crunch code, so we can't
> > > incorporate it into the planner's decision making process. Does
> > > LoadIncrementalHFiles even run an MR job?
> > >
> > >
> > > On Thu, Feb 13, 2014 at 9:27 AM, Jinal Shah <jinalshah2007@gmail.com>
> > > wrote:
> > >
> > > > Hi Josh,
> > > > I tried the option you said and it worked perfectly fine where I'm
> > doing
> > > > parallelDo. But for HBase I'm using
> > > > HFileUtils.writeToHFilesForIncrementalLoad() to write and then
> Reading
> > > > using  LoadIncrementalHFiles class. So how do I tell the planner in
> > this
> > > > case to run in Sequential format. Here is how the code looks like
> > > >
> > > > HFileUtils.writeToHFilesForIncrementalLoad(PCollection<keyValue>,
> > table,
> > > > path)
> > > > pipeline.run()
> > > >
> > > > LoadIncrementalHFiles loadIncremental = new
> > > LoadIncrementalHFiles(config);
> > > >
> > > > loadIncremental.doBulkLoad(path, table);
> > > >
> > > > Thanks
> > > > Jinal
> > > >
> > > >
> > > > On Wed, Feb 12, 2014 at 11:27 AM, Josh Wills <jwills@cloudera.com>
> > > wrote:
> > > >
> > > > > I'm not sure what you want here-- there is a mechanism to force the
> > > > planner
> > > > > to run stages sequentially (even if the input to stage 2 does not
> > > > directly
> > > > > depend directly on the output from stage 1) by using
> > ParallelDoOptions
> > > to
> > > > > introduce such a dependency, as I indicated before:
> > > > >
> > > > > SourceTarget marker = ...;
> > > > > HBase.read()
> > > > > doSomeChangesOnData
> > > > > dummyDoFnToCreateMarker
> > > > > HBase.write()
> > > > > marker.write()
> > > > > HBase.read().parallelDo(DoFn, PType,
> > > > > ParallelDoOptions.builder().sourceTarget(marker).build());
> > > > >
> > > > > That's less of a hint to the planner and more of a command. Another
> > > > option
> > > > > would be to set the maximum number of simultaneously running jobs
> in
> > > > Crunch
> > > > > to 1 using the crunch.max.running.jobs configuration parameter,
> > which
> > > > > would
> > > > > run everything in the pipeline sequentially, one job at a time.
> > > > >
> > > > >
> > > > >
> > > > > On Wed, Feb 12, 2014 at 9:15 AM, Jinal Shah <
> jinalshah2007@gmail.com
> > >
> > > > > wrote:
> > > > >
> > > > > > Can I get some comment on this?
> > > > > >
> > > > > >
> > > > > > On Thu, Feb 6, 2014 at 11:00 AM, Jinal Shah <
> > jinalshah2007@gmail.com
> > > >
> > > > > > wrote:
> > > > > >
> > > > > > > Hi Josh and Micah,
> > > > > > >
> > > > > > > In both the scenerios I can easily do a Pipeline.run()
and get
> > > going
> > > > > from
> > > > > > > there. But my main question would be why should I do a
> > > pipeline.run()
> > > > > in
> > > > > > > between just to make the planner run something in a sequential
> > > format
> > > > > > > rather than the way it would have planned otherwise. What
I'm
> > > getting
> > > > > at
> > > > > > is
> > > > > > > that there should some mechanism that will tell the Planner
to
> do
> > > > > > something
> > > > > > > in a certain way to some extend like you can take example
of
> > Apache
> > > > > Hive,
> > > > > > > till 0.7 release Hive use to provide a mechanism called
HINT
> > which
> > > > > would
> > > > > > > tell the query planner to run something as indicated in
the
> HINT
> > > > rather
> > > > > > > than the way it would have been otherwise. I know that
you
> might
> > > say
> > > > it
> > > > > > > might not create optimized plan but at this point the consumer
> is
> > > > more
> > > > > > > focused on the way it should be planned rather than the
> > > optimization.
> > > > > > >
> > > > > > > May be there might be option already there in Crunch that
I
> might
> > > > have
> > > > > > not
> > > > > > > explored but just wanted to put my point out there. If
there is
> > an
> > > > > > option I
> > > > > > > would love to learn about it.
> > > > > > >
> > > > > > >
> > > > > > > On Thu, Feb 6, 2014 at 10:44 AM, Josh Wills <
> > josh.wills@gmail.com>
> > > > > > wrote:
> > > > > > >
> > > > > > >> Hey Jinal,
> > > > > > >>
> > > > > > >> On scenario 2, the easiest way to do this is to force
a run()
> > > > between
> > > > > > the
> > > > > > >> write and the second read, ala:
> > > > > > >>
> > > > > > >> HBase.read()
> > > > > > >> doSomeChangesOnData
> > > > > > >> HBase.write()
> > > > > > >> Pipeline.run()
> > > > > > >> HBase.read()
> > > > > > >>
> > > > > > >> If that isn't possible for some reason, you'll need
to add an
> > > output
> > > > > > file
> > > > > > >> to the first phase that can be used to indicate that
the
> > > HBase.write
> > > > > is
> > > > > > >> complete, and then have the second read depend on that
file
> > > existing
> > > > > > >> before
> > > > > > >> it can run, which can be done via ParallelDoOptions,
e.g.,
> > > > > > >>
> > > > > > >> SourceTarget marker = ...;
> > > > > > >> HBase.read()
> > > > > > >> doSomeChangesOnData
> > > > > > >> dummyDoFnToCreateMarker
> > > > > > >> HBase.write()
> > > > > > >> marker.write()
> > > > > > >> HBase.read().parallelDo(DoFn, PType,
> > > > > > >> ParallelDoOptions.builder().sourceTarget(marker).build());
> > > > > > >>
> > > > > > >> but that's obviously uglier and more complicated.
> > > > > > >>
> > > > > > >> J
> > > > > > >>
> > > > > > >>
> > > > > > >> On Wed, Feb 5, 2014 at 7:14 PM, Jinal Shah <
> > > jinalshah2007@gmail.com
> > > > >
> > > > > > >> wrote:
> > > > > > >>
> > > > > > >> > Hi Josh,
> > > > > > >> >
> > > > > > >> > Here is a small example of what I am looking for.
So here is
> > > what
> > > > > I'm
> > > > > > >> doing
> > > > > > >> >
> > > > > > >> > Scenario 1:
> > > > > > >> >
> > > > > > >> > PCollection<Something> s = FunctionDoingSomething();
> > > > > > >> > pipeline.write(s, path);
> > > > > > >> > doSomeFilteringOn(s);
> > > > > > >> >
> > > > > > >> > I want that when I do some filtering this should
be done in
> > the
> > > > map
> > > > > > >> phase
> > > > > > >> > instead it is doing it in the Reduce phase due
to which I
> have
> > > to
> > > > > > >> introduce
> > > > > > >> > a pipeline.run() and now this is what the code
looks like
> > > > > > >> >
> > > > > > >> > PCollection<Something> s = FunctionDoingSomething();
> > > > > > >> > pipeline.write(s, path);
> > > > > > >> > pipeline.run()
> > > > > > >> > doSomeFilteringOn(s);
> > > > > > >> >
> > > > > > >> > Scenerio 2:
> > > > > > >> >
> > > > > > >> > I'm doing an operation on HBase and here is how
it looks.
> > > > > > >> >
> > > > > > >> > Hbase.read()
> > > > > > >> > doSomeChangesOnData
> > > > > > >> > HBase.write()
> > > > > > >> > HBase.read()
> > > > > > >> >
> > > > > > >> > Now Crunch at this points considers both the reads
as
> separate
> > > and
> > > > > > >> tries to
> > > > > > >> > run it in parallel so now before I even write
my changes it
> > > reads
> > > > > > those
> > > > > > >> > changes so I have to again put a pipeline.run()
in order to
> > > break
> > > > it
> > > > > > >> into 2
> > > > > > >> > separate flow and execute them in sequence.
> > > > > > >> >
> > > > > > >> > So I'm asking is there any way to send an HINT
to the
> Planner
> > > that
> > > > > how
> > > > > > >> it
> > > > > > >> > create the Plan instead of it deciding by itself
or someway
> to
> > > > have
> > > > > > more
> > > > > > >> > control how to make a planner understand in certain
> > situations.
> > > > > > >> >
> > > > > > >> > Thanks
> > > > > > >> > Jinal
> > > > > > >> >
> > > > > > >> >
> > > > > > >> > On Thu, Jan 30, 2014 at 11:10 AM, Josh Wills <
> > > jwills@cloudera.com
> > > > >
> > > > > > >> wrote:
> > > > > > >> >
> > > > > > >> > > On Thu, Jan 30, 2014 at 7:09 AM, Jinal Shah
<
> > > > > > jinalshah2007@gmail.com>
> > > > > > >> > > wrote:
> > > > > > >> > >
> > > > > > >> > > > Hi everyone,
> > > > > > >> > > >
> > > > > > >> > > > This is Jinal Shah, I'm new to the group.
I had a
> question
> > > > about
> > > > > > >> > > Execution
> > > > > > >> > > > Control in Crunch. Is there any way
we can force Crunch
> to
> > > do
> > > > > > >> certain
> > > > > > >> > > > operations in parallel or certain operations
in
> sequential
> > > > ways.
> > > > > > For
> > > > > > >> > > > example, let's say if we want the pipeline
to executed a
> > > > > > particular
> > > > > > >> > DoFn
> > > > > > >> > > > function in the Map phase instead of
the Reduce phase or
> > > > > > >> vice-versa. Or
> > > > > > >> > > > Execute a particular Flow only after
a particular flow
> is
> > > > > > completed
> > > > > > >> as
> > > > > > >> > > > oppose to running it in parallel.
> > > > > > >> > > >
> > > > > > >> > >
> > > > > > >> > > Forcing a DoFn to operate in a map or reduce
phase is
> tough
> > > for
> > > > > the
> > > > > > >> > planner
> > > > > > >> > > to do right now; we sort of rely on the developer
to have
> a
> > > > mental
> > > > > > >> model
> > > > > > >> > of
> > > > > > >> > > how the jobs will proceed. The place where
you usually
> want
> > to
> > > > > > force a
> > > > > > >> > DoFn
> > > > > > >> > > to execute in the reduce vs. the map phase
is when you
> have
> > > > > > dependent
> > > > > > >> > > groupByKey operations, and you can use cache()
or
> > > materialize()
> > > > on
> > > > > > the
> > > > > > >> > > intermediate output that you want to split
on, and the
> > planner
> > > > > will
> > > > > > >> > respect
> > > > > > >> > > that.
> > > > > > >> > >
> > > > > > >> > > On the latter question, the thing to look
for is
> > > > > > >> > > org.apache.crunch.ParallelDoOptions, which
isn't something
> > > I've
> > > > > > doc'd
> > > > > > >> in
> > > > > > >> > > the user guide yet (it's on the todo list,
I promise.) You
> > can
> > > > > give
> > > > > > a
> > > > > > >> > > parallelDo call an additional argument that
specifies one
> or
> > > > more
> > > > > > >> > > SourceTargets that have to exist before a
particular DoFn
> is
> > > > > allowed
> > > > > > >> to
> > > > > > >> > > run. In this way, you can force aspects of
the pipeline to
> > be
> > > > > > >> sequential
> > > > > > >> > > instead of parallel. We make use of ParallelDoOptions
> inside
> > > of
> > > > > the
> > > > > > >> > > MapsideJoinStrategy code, to ensure that
the data set that
> > > we'll
> > > > > be
> > > > > > >> > loading
> > > > > > >> > > in-memory actually exists in the file system
before we run
> > the
> > > > > code
> > > > > > >> that
> > > > > > >> > > reads it into memory.
> > > > > > >> > >
> > > > > > >> > >
> > > > > > >> > > >
> > > > > > >> > > > Maybe this might be asked before so
sorry if it came
> > again.
> > > If
> > > > > you
> > > > > > >> guys
> > > > > > >> > > > have further question on the details
do let me know
> > > > > > >> > > >
> > > > > > >> > > >
> > > > > > >> > > > Thanks everyone and Have a great day.
> > > > > > >> > > >
> > > > > > >> > > > Thanks
> > > > > > >> > > > Jinal
> > > > > > >> > > >
> > > > > > >> > >
> > > > > > >> > >
> > > > > > >> > >
> > > > > > >> > > --
> > > > > > >> > > Director of Data Science
> > > > > > >> > > Cloudera <http://www.cloudera.com>
> > > > > > >> > > Twitter: @josh_wills <http://twitter.com/josh_wills>
> > > > > > >> > >
> > > > > > >> >
> > > > > > >>
> > > > > > >
> > > > > > >
> > > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > Director of Data Science
> > > > > Cloudera <http://www.cloudera.com>
> > > > > Twitter: @josh_wills <http://twitter.com/josh_wills>
> > > > >
> > > >
> > >
> > >
> > >
> > > --
> > > Director of Data Science
> > > Cloudera <http://www.cloudera.com>
> > > Twitter: @josh_wills <http://twitter.com/josh_wills>
> > >
> >
>

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