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From obaidul karim <obaidc...@gmail.com>
Subject Re: Data Ingestion forLarge Source Files and Masking
Date Thu, 14 Jan 2016 04:32:49 GMT
Hi Joe,

Please find attached jstat & iostat output.

So far it seems to me that it is CPU bound. However, your eyes are better
tan mine :).

-Obaid

On Thu, Jan 14, 2016 at 11:51 AM, Joe Witt <joe.witt@gmail.com> wrote:

> Hello
>
> Let's narrow in on potential issues.  So while this process is running
> and appears sluggish in nature please run the following on the command
> line
>
> 'jps'
>
> This command will tell you the process id of NiFi.  You'll want the
> pid associated with the Java process other than what is called 'jps'
> presuming there aren't other things running than NiFi at the time.
>
> Lets say the result is a pid of '12345'
>
> Then run this command
>
> 'jstat -gcutil 12345 1000'
>
> This will generate garbage collection information every one second
> until you decide to stop it with cntl-c.  So let that run for a while
> say 30 seconds or so then hit cntl-c.  Can you please paste that
> output in response.  That will show us how the general health of GC
> is.
>
> Another really important/powerful set of output can be gleaned by
> running 'iostat' which gives you statistics about input/output to
> things like the underlying storage system.  That is part of the
> 'sysstat' package in case you need to install that.  But then you can
> run
>
> ''iostat xmh 1"
>
> Or something even as simple as 'iostat 1'.  Your specific command
> string may vary.  Please let that run for say 10-20 seconds and paste
> those results as well.  That will give a sense of io utilization while
> the operation is running.
>
> Between these two outputs (Garbage Collection/IO) we should have a
> pretty good idea of where to focus the effort to find why it is slow.
>
> Thanks
> Joe
>
>
> On Wed, Jan 13, 2016 at 9:23 PM, obaidul karim <obaidcuet@gmail.com>
> wrote:
> > Hi Joe & Others,
> >
> > Thanks for all of your suggestions.
> >
> > Now I am using below code:
> > 1. Buffered reader (I tried to use NLKBufferedReader, but it requires too
> > many libs & Nifi failed to start. I was lost.)
> > 2. Buffered writer
> > 3. Using appending line end instead to concat new line
> >
> > Still no performance gain. Am I doing something wrong, anything else I
> can
> > change here.
> >
> > flowfile = session.write(flowfile, new StreamCallback() {
> > @Override
> > public void process(InputStream in, OutputStream out) throws IOException
> {
> >     try (BufferedReader reader = new BufferedReader(new
> > InputStreamReader(in, charset), maxBufferSize);
> >         BufferedWriter writer = new BufferedWriter(new
> > OutputStreamWriter(out, charset));) {
> >
> > if(skipHeader == true && headerExists==true) { // to skip header, do an
> > additional line fetch before going to next step
> > if(reader.ready())   reader.readLine();
> > } else if( skipHeader == false && headerExists == true) { // if header is
> > not skipped then no need to mask, just pass through
> > if(reader.ready())  {
> > writer.write(reader.readLine());
> > writer.write(lineEndingBuilder.toString());
> > }
> > }
> > // decide about empty line earlier
> > String line;
> > while ((line = reader.readLine()) != null) {
> > writer.write(parseLine(line, seperator, quote, escape, maskColumns));
> > writer.write(lineEndingBuilder.toString());
> > };
> > writer.flush();
> >         }
> > }
> >
> > });
> >
> >
> > -Obaid
> >
> > On Wed, Jan 13, 2016 at 1:38 PM, Joe Witt <joe.witt@gmail.com> wrote:
> >>
> >> Hello
> >>
> >> So the performance went from what sounded pretty good to what sounds
> >> pretty problematic.  The rate now sounds like it is around 5MB/s which
> >> is indeed quite poor.  Building on what Bryan said there does appear
> >> to be some good opportunities to improve the performance.  The link he
> >> provided just expanded to cover the full range to look at is here [1].
> >>
> >> Couple key points to note:
> >> 1) Use of a buffered line oriented reader than preserves the new lines
> >> 2) write to a buffered writer that accepts strings and understands
> >> which charset you intend to write out
> >> 3) avoid strong concat with newline
> >>
> >> Also keep in mind you how large any single line could be because if
> >> they can be quite large you may need to consider the GC pressure that
> >> can be caused.  But let's take a look at how things are after these
> >> easier steps first.
> >>
> >> [1]
> >>
> https://github.com/apache/nifi/blob/ee14d8f9dd0c3f18920d910fcddd6d79b8b9f9cf/nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/ReplaceText.java#L334-L361
> >>
> >> Thanks
> >> Joe
> >>
> >> On Tue, Jan 12, 2016 at 10:35 PM, Juan Sequeiros <hellojuan@gmail.com>
> >> wrote:
> >> > Obaid,
> >> >
> >> > Since you mention that you will have dedicated ETL servers and assume
> >> > they
> >> > will also have a decent amount of ram on them, then I would not shy
> away
> >> > from increasing your threads.
> >> >
> >> > Also in your staging directory if you do not need to keep originals,
> >> > then
> >> > might consider GetFile and on that one use one thread.
> >> >
> >> > Hi Joe,
> >> >
> >> > Yes, I took consideration of existinh RAID and HW settings. We have
> 10G
> >> > NIC
> >> > for all hadoop intra-connectivity and the server in question is an
> edge
> >> > node
> >> > of our hadoop cluster.
> >> > In production scenario we will use dedicated ETL servers having high
> >> > performance(>500MB/s) local disks.
> >> >
> >> > Sharing a good news, I have successfully mask & load to HDFS 110 GB
> data
> >> > using below flow:
> >> >
> >> > ExecuteProcess(touch and mv to input dir) > ListFile (1 thread) >
> >> > FetchFile
> >> > (1 thread) > maskColumn(4 threads) > PutHDFS (1 threads).
> >> >
> >> > * used 4 threads for masking and 1 for other because I found it is the
> >> > slowest component.
> >> >
> >> > However, It seems to be too slow. It was processing 2GB files in  6
> >> > minutes.
> >> > It may be because of my masking algorithm(although masking algorithm
> is
> >> > pretty simple FPE with some simple twist).
> >> > However I want to be sure that the way I have written custom processor
> >> > is
> >> > the most efficient way. Please below code chunk and let me know
> whether
> >> > it
> >> > is the fastest way to process flowfiles (csv source files) which needs
> >> > modifications on specific columns:
> >> >
> >> > * parseLine method contains logic for masking.
> >> >
> >> >        flowfile = session.write(flowfile, new StreamCallback() {
> >> >         @Override
> >> >            public void process(InputStream in, OutputStream out)
> throws
> >> > IOException {
> >> >
> >> >         BufferedReader reader = new BufferedReader(new
> >> > InputStreamReader(in));
> >> >         String line;
> >> >         if(skipHeader == true && headerExists==true) { // to skip
> >> > header, do
> >> > an additional line fetch before going to next step
> >> >         if(reader.ready())   reader.readLine();
> >> >         } else if( skipHeader == false && headerExists == true)
{ //
> if
> >> > header is not skipped then no need to mask, just pass through
> >> >         if(reader.ready())
> >> > out.write((reader.readLine()+"\n").getBytes());
> >> >         }
> >> >
> >> >         // decide about empty line earlier
> >> >         while ((line = reader.readLine()) != null) {
> >> >         if(line.trim().length() > 0 ) {
> >> >         out.write( parseLine(line, seperator, quote, escape,
> >> > maskColumns).getBytes() );
> >> >         }
> >> > };
> >> > out.flush();
> >> >            }
> >> >        });
> >> >
> >> >
> >> >
> >> >
> >> > Thanks in advance.
> >> > -Obaid
> >> >
> >> >
> >> > On Tue, Jan 5, 2016 at 12:36 PM, Joe Witt <joe.witt@gmail.com> wrote:
> >> >>
> >> >> Obaid,
> >> >>
> >> >> Really happy you're seeing the performance you need.  That works out
> >> >> to about 110MB/s on average over that period.  Any chance you have
a
> >> >> 1GB NIC?  If you really want to have fun with performance tuning you
> >> >> can use things like iostat and other commands to observe disk,
> >> >> network, cpu.  Something else to consider too is the potential
> >> >> throughput gains of multiple RAID-1 containers rather than RAID-5
> >> >> since NiFi can use both in parallel.  Depends on your goals/workload
> >> >> so just an FYI.
> >> >>
> >> >> A good reference for how to build a processor which does altering of
> >> >> the data (transformation) is here [1].  It is a good idea to do a
> >> >> quick read through that document.  Also, one of the great things you
> >> >> can do as well is look at existing processors.  Some good examples
> >> >> relevant to transformation are [2], [3], and [4] which are quite
> >> >> simple stream transform types. Or take a look at [5] which is a more
> >> >> complicated example.  You might also be excited to know that there
is
> >> >> some really cool work done to bring various languages into NiFi which
> >> >> looks on track to be available in the upcoming 0.5.0 release which
is
> >> >> NIFI-210 [6].  That will provide a really great option to quickly
> >> >> build transforms using languages like Groovy, JRuby, Javascript,
> >> >> Scala, Lua, Javascript, and Jython.
> >> >>
> >> >> [1]
> >> >>
> >> >>
> https://nifi.apache.org/docs/nifi-docs/html/developer-guide.html#enrich-modify-content
> >> >>
> >> >> [2]
> >> >>
> >> >>
> https://github.com/apache/nifi/blob/master/nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/Base64EncodeContent.java
> >> >>
> >> >> [3]
> >> >>
> >> >>
> https://github.com/apache/nifi/blob/master/nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/TransformXml.java
> >> >>
> >> >> [4]
> >> >>
> >> >>
> https://github.com/apache/nifi/blob/master/nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/ModifyBytes.java
> >> >>
> >> >> [5]
> >> >>
> >> >>
> https://github.com/apache/nifi/blob/master/nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/ReplaceText.java
> >> >>
> >> >> [6] https://issues.apache.org/jira/browse/NIFI-210
> >> >>
> >> >> Thanks
> >> >> Joe
> >> >>
> >> >> On Mon, Jan 4, 2016 at 9:32 PM, obaidul karim <obaidcuet@gmail.com>
> >> >> wrote:
> >> >> > Hi Joe,
> >> >> >
> >> >> > Just completed by test with 100GB data (on a local RAID 5 disk
on a
> >> >> > single
> >> >> > server).
> >> >> >
> >> >> > I was able to load 100GB data within 15 minutes(awesome!!) using
> >> >> > below
> >> >> > flow.
> >> >> > This throughput is enough to load 10TB data in a day with a single
> >> >> > and
> >> >> > simple machine.
> >> >> > During the test, server disk I/O went up to 200MB/s.
> >> >> >
> >> >> >     ExecuteProcess(touch and mv to input dir) > ListFile >
> FetchFile
> >> >> > (4
> >> >> > threads) > PutHDFS (4 threads)
> >> >> >
> >> >> > My Next action is to incorporate my java code for column masking
> with
> >> >> > a
> >> >> > custom processor.
> >> >> > I am now exploring on that. However, if you have any good reference
> >> >> > on
> >> >> > custom processor(altering actual data) please let  me know.
> >> >> >
> >> >> > Thanks,
> >> >> > Obaid
> >> >> >
> >> >> >
> >> >> >
> >> >> > On Mon, Jan 4, 2016 at 9:11 AM, obaidul karim <obaidcuet@gmail.com
> >
> >> >> > wrote:
> >> >> >>
> >> >> >> Hi Joe,
> >> >> >>
> >> >> >> Yes, symlink is another option I was thinking when I was trying
to
> >> >> >> use
> >> >> >> getfile.
> >> >> >> Thanks for your insights, I will update you on this mail chain
> when
> >> >> >> my
> >> >> >> entire workflow completes. So that thus could be an reference
for
> >> >> >> other
> >> >> >> :).
> >> >> >>
> >> >> >> -Obaid
> >> >> >>
> >> >> >> On Monday, January 4, 2016, Joe Witt <joe.witt@gmail.com>
wrote:
> >> >> >>>
> >> >> >>> Obaid,
> >> >> >>>
> >> >> >>> You make a great point.
> >> >> >>>
> >> >> >>> I agree we will ultimately need to do more to make that
very
> valid
> >> >> >>> approach work easily.  The downside is that puts the onus
on NiFi
> >> >> >>> to
> >> >> >>> keep track of a variety of potentially quite large state
about
> the
> >> >> >>> directory.  One way to avoid that expense is if NiFi can
pull a
> >> >> >>> copy
> >> >> >>> of then delete the source file.  If you'd like to keep
a copy
> >> >> >>> around I
> >> >> >>> wonder if a good approach is to simply create a symlink
to the
> >> >> >>> original file you want NiFi to pull but have the symlink
in the
> >> >> >>> NiFi
> >> >> >>> pickup directory.  NiFi is then free to read and delete
which
> means
> >> >> >>> it
> >> >> >>> simply pulls whatever shows up in that directory and doesn't
have
> >> >> >>> to
> >> >> >>> keep state about filenames and checksums.
> >> >> >>>
> >> >> >>> I realize we still need to do what you're suggesting as
well but
> >> >> >>> thought I'd run this by you.
> >> >> >>>
> >> >> >>> Joe
> >> >> >>>
> >> >> >>> On Sun, Jan 3, 2016 at 6:43 PM, obaidul karim <
> obaidcuet@gmail.com>
> >> >> >>> wrote:
> >> >> >>> > Hi Joe,
> >> >> >>> >
> >> >> >>> > Condider a scenerio, where we need to feed some older
files and
> >> >> >>> > we
> >> >> >>> > are
> >> >> >>> > using
> >> >> >>> > "mv" to feed files to input directory( to reduce
IO we may use
> >> >> >>> > "mv").
> >> >> >>> > If we
> >> >> >>> > use "mv", last modified date will not changed. And
this is very
> >> >> >>> > common
> >> >> >>> > on a
> >> >> >>> > busy file collection system.
> >> >> >>> >
> >> >> >>> > However, I think I can still manage it by adding
additional
> >> >> >>> > "touch"
> >> >> >>> > before
> >> >> >>> > moving fole in the target directory.
> >> >> >>> >
> >> >> >>> > So, my suggestion is to add file selection criteria
as an
> >> >> >>> > configurable
> >> >> >>> > option in listfile process on workflow. Options could
be last
> >> >> >>> > modified
> >> >> >>> > date(as current one) unique file names, checksum
etc.
> >> >> >>> >
> >> >> >>> > Thanks again man.
> >> >> >>> > -Obaid
> >> >> >>> >
> >> >> >>> >
> >> >> >>> > On Monday, January 4, 2016, Joe Witt <joe.witt@gmail.com>
> wrote:
> >> >> >>> >>
> >> >> >>> >> Hello Obaid,
> >> >> >>> >>
> >> >> >>> >> The default behavior of the ListFile processor
is to keep
> track
> >> >> >>> >> of
> >> >> >>> >> the
> >> >> >>> >> last modified time of the files it lists.  When
you changed
> the
> >> >> >>> >> name
> >> >> >>> >> of the file that doesn't change the last modified
time as
> >> >> >>> >> tracked
> >> >> >>> >> by
> >> >> >>> >> the OS but when you altered content it does.
 Simply 'touch'
> on
> >> >> >>> >> the
> >> >> >>> >> file would do it too.
> >> >> >>> >>
> >> >> >>> >> I believe we could observe the last modified
time of the
> >> >> >>> >> directory
> >> >> >>> >> in
> >> >> >>> >> which the file lives to detect something like
a rename.
> >> >> >>> >> However,
> >> >> >>> >> we'd
> >> >> >>> >> not know which file was renamed just that something
was
> changed.
> >> >> >>> >> So
> >> >> >>> >> it require keeping some potentially problematic
state to
> >> >> >>> >> deconflict
> >> >> >>> >> or
> >> >> >>> >> requiring the user to have a duplicate detection
process
> >> >> >>> >> afterwards.
> >> >> >>> >>
> >> >> >>> >> So with that in mind is the current behavior
sufficient for
> your
> >> >> >>> >> case?
> >> >> >>> >>
> >> >> >>> >> Thanks
> >> >> >>> >> Joe
> >> >> >>> >>
> >> >> >>> >> On Sun, Jan 3, 2016 at 6:17 AM, obaidul karim
> >> >> >>> >> <obaidcuet@gmail.com>
> >> >> >>> >> wrote:
> >> >> >>> >> > Hi Joe,
> >> >> >>> >> >
> >> >> >>> >> > I am now exploring your solution.
> >> >> >>> >> > Starting with below flow:
> >> >> >>> >> >
> >> >> >>> >> > ListFIle > FetchFile > CompressContent
> PutFile.
> >> >> >>> >> >
> >> >> >>> >> > Seems all fine. Except some confusion with
how ListFile
> >> >> >>> >> > identifies
> >> >> >>> >> > new
> >> >> >>> >> > files.
> >> >> >>> >> > In order to test, I renamed a already processed
file and put
> >> >> >>> >> > in
> >> >> >>> >> > in
> >> >> >>> >> > input
> >> >> >>> >> > folder and found that the file is not processing.
> >> >> >>> >> > Then I randomly changed the content of the
file and it was
> >> >> >>> >> > immediately
> >> >> >>> >> > processed.
> >> >> >>> >> >
> >> >> >>> >> > My question is what is the new file selection
criteria for
> >> >> >>> >> > "ListFile" ?
> >> >> >>> >> > Can
> >> >> >>> >> > I change it only to file name ?
> >> >> >>> >> >
> >> >> >>> >> > Thanks in advance.
> >> >> >>> >> >
> >> >> >>> >> > -Obaid
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >>> >> > On Fri, Jan 1, 2016 at 10:43 PM, Joe Witt
<
> joe.witt@gmail.com>
> >> >> >>> >> > wrote:
> >> >> >>> >> >>
> >> >> >>> >> >> Hello Obaid,
> >> >> >>> >> >>
> >> >> >>> >> >> At 6 TB/day and average size of 2-3GB
per dataset you're
> >> >> >>> >> >> looking
> >> >> >>> >> >> at
> >> >> >>> >> >> a
> >> >> >>> >> >> sustained rate of 70+MB/s and a pretty
low transaction
> rate.
> >> >> >>> >> >> So
> >> >> >>> >> >> well
> >> >> >>> >> >> within a good range to work with on
a single system.
> >> >> >>> >> >>
> >> >> >>> >> >> 'I's there any way to by pass writing
flow files on disk or
> >> >> >>> >> >> directly
> >> >> >>> >> >> pass those files to HDFS as it is ?"
> >> >> >>> >> >>
> >> >> >>> >> >>   There is no way to bypass NiFi taking
a copy of that data
> >> >> >>> >> >> by
> >> >> >>> >> >> design.
> >> >> >>> >> >> NiFi is helping you formulate a graph
of dataflow
> >> >> >>> >> >> requirements
> >> >> >>> >> >> from
> >> >> >>> >> >> a
> >> >> >>> >> >> given source(s) through given processing
steps and ultimate
> >> >> >>> >> >> driving
> >> >> >>> >> >> data into given destination systems.
 As a result it takes
> on
> >> >> >>> >> >> the
> >> >> >>> >> >> challenge of handling transactionality
of each interaction
> >> >> >>> >> >> and
> >> >> >>> >> >> the
> >> >> >>> >> >> buffering and backpressure to deal with
the realities of
> >> >> >>> >> >> different
> >> >> >>> >> >> production/consumption patterns.
> >> >> >>> >> >>
> >> >> >>> >> >> "If the files on the spool directory
are
> >> >> >>> >> >> compressed(zip/gzip),
> >> >> >>> >> >> can
> >> >> >>> >> >> we
> >> >> >>> >> >> store files on HDFS as uncompressed
?"
> >> >> >>> >> >>
> >> >> >>> >> >>   Certainly.  Both of those formats
(zip/gzip) are
> supported
> >> >> >>> >> >> in
> >> >> >>> >> >> NiFi
> >> >> >>> >> >> out of the box.  You simply run the
data through the proper
> >> >> >>> >> >> process
> >> >> >>> >> >> prior to the PutHDFS process to unpack
(zip) or decompress
> >> >> >>> >> >> (gzip)
> >> >> >>> >> >> as
> >> >> >>> >> >> needed.
> >> >> >>> >> >>
> >> >> >>> >> >> "2.a Can we use our existing java code
for masking ? if yes
> >> >> >>> >> >> then
> >> >> >>> >> >> how ?
> >> >> >>> >> >> 2.b For this Scenario we also want to
bypass storing flow
> >> >> >>> >> >> files
> >> >> >>> >> >> on
> >> >> >>> >> >> disk. Can we do it on the fly, masking
and storing on HDFS
> ?
> >> >> >>> >> >> 2.c If the source files are compressed
(zip/gzip), is there
> >> >> >>> >> >> any
> >> >> >>> >> >> issue
> >> >> >>> >> >> for masking here ?"
> >> >> >>> >> >>
> >> >> >>> >> >>   You would build a custom NiFi processor
that leverages
> your
> >> >> >>> >> >> existing
> >> >> >>> >> >> code.  If your code is able to operate
on an InputStream
> and
> >> >> >>> >> >> writes
> >> >> >>> >> >> to
> >> >> >>> >> >> an OutputStream then it is very likely
you'll be able to
> >> >> >>> >> >> handle
> >> >> >>> >> >> arbitrarily large objects with zero
negative impact to the
> >> >> >>> >> >> JVM
> >> >> >>> >> >> Heap
> >> >> >>> >> >> as
> >> >> >>> >> >> well.  This is thanks to the fact that
the data is present
> in
> >> >> >>> >> >> NiFi's
> >> >> >>> >> >> repository with copy-on-write/pass-by-reference
semantics
> and
> >> >> >>> >> >> that
> >> >> >>> >> >> the
> >> >> >>> >> >> API is exposing those streams to your
code in a
> transactional
> >> >> >>> >> >> manner.
> >> >> >>> >> >>
> >> >> >>> >> >>   If you want the process of writing
to HDFS to also do
> >> >> >>> >> >> decompression
> >> >> >>> >> >> and masking in one pass you'll need
to extend/alter the
> >> >> >>> >> >> PutHDFS
> >> >> >>> >> >> process to do that.  It is probably
best to implement the
> >> >> >>> >> >> flow
> >> >> >>> >> >> using
> >> >> >>> >> >> cohesive processors (grab files, decompress
files, mask
> >> >> >>> >> >> files,
> >> >> >>> >> >> write
> >> >> >>> >> >> to hdfs).  Given how the repository
construct in NiFi works
> >> >> >>> >> >> and
> >> >> >>> >> >> given
> >> >> >>> >> >> how caching in Linux works it is very
possible you'll be
> >> >> >>> >> >> quite
> >> >> >>> >> >> surprised by the throughput you'll see.
 Even then you can
> >> >> >>> >> >> optimize
> >> >> >>> >> >> once you're sure you need to.  The other
thing to keep in
> >> >> >>> >> >> mind
> >> >> >>> >> >> here
> >> >> >>> >> >> is
> >> >> >>> >> >> that often a flow that starts out as
specific as this turns
> >> >> >>> >> >> into
> >> >> >>> >> >> a
> >> >> >>> >> >> great place to tap the stream of data
to feed some new
> system
> >> >> >>> >> >> or
> >> >> >>> >> >> new
> >> >> >>> >> >> algorithm with a different format or
protocol.  At that
> >> >> >>> >> >> moment
> >> >> >>> >> >> the
> >> >> >>> >> >> benefits become even more obvious.
> >> >> >>> >> >>
> >> >> >>> >> >> Regarding the Flume processes in NiFi
and their memory
> usage.
> >> >> >>> >> >> NiFi
> >> >> >>> >> >> offers a nice hosting mechanism for
the Flume processes and
> >> >> >>> >> >> brings
> >> >> >>> >> >> some of the benefits of NiFi's UI, provenance,
repository
> >> >> >>> >> >> concept.
> >> >> >>> >> >> However, we're still largely limited
to the design
> >> >> >>> >> >> assumptions
> >> >> >>> >> >> one
> >> >> >>> >> >> gets when building a Flume process and
that can be quite
> >> >> >>> >> >> memory
> >> >> >>> >> >> limiting.  We see what we have today
as a great way to help
> >> >> >>> >> >> people
> >> >> >>> >> >> transition their existing Flume flows
into NiFi by
> leveraging
> >> >> >>> >> >> their
> >> >> >>> >> >> existing code but would recommend working
to phase the use
> of
> >> >> >>> >> >> those
> >> >> >>> >> >> out in time so that you can take full
benefit of what NiFi
> >> >> >>> >> >> brings
> >> >> >>> >> >> over
> >> >> >>> >> >> Flume.
> >> >> >>> >> >>
> >> >> >>> >> >> Thanks
> >> >> >>> >> >> Joe
> >> >> >>> >> >>
> >> >> >>> >> >>
> >> >> >>> >> >> On Fri, Jan 1, 2016 at 4:18 AM, obaidul
karim
> >> >> >>> >> >> <obaidcuet@gmail.com>
> >> >> >>> >> >> wrote:
> >> >> >>> >> >> > Hi,
> >> >> >>> >> >> >
> >> >> >>> >> >> > I am new in Nifi and exploring
it as open source ETL
> tool.
> >> >> >>> >> >> >
> >> >> >>> >> >> > As per my understanding, flow files
are stored on local
> >> >> >>> >> >> > disk
> >> >> >>> >> >> > and
> >> >> >>> >> >> > it
> >> >> >>> >> >> > contains
> >> >> >>> >> >> > actual data.
> >> >> >>> >> >> > If above is true, lets consider
a below scenario:
> >> >> >>> >> >> >
> >> >> >>> >> >> > Scenario 1:
> >> >> >>> >> >> > - In a spool directory we have
terabytes(5-6TB/day) of
> >> >> >>> >> >> > files
> >> >> >>> >> >> > coming
> >> >> >>> >> >> > from
> >> >> >>> >> >> > external sources
> >> >> >>> >> >> > - I want to push those files to
HDFS as it is without any
> >> >> >>> >> >> > changes
> >> >> >>> >> >> >
> >> >> >>> >> >> > Scenario 2:
> >> >> >>> >> >> > - In a spool directory we have
terabytes(5-6TB/day) of
> >> >> >>> >> >> > files
> >> >> >>> >> >> > coming
> >> >> >>> >> >> > from
> >> >> >>> >> >> > external sources
> >> >> >>> >> >> > - I want to mask some of the sensitive
columns
> >> >> >>> >> >> > - Then send one copy to HDFS and
another copy to Kafka
> >> >> >>> >> >> >
> >> >> >>> >> >> > Question for Scenario 1:
> >> >> >>> >> >> > 1.a In that case those 5-6TB data
will be again written
> on
> >> >> >>> >> >> > local
> >> >> >>> >> >> > disk
> >> >> >>> >> >> > as
> >> >> >>> >> >> > flow files and will cause double
I/O. Which eventually
> may
> >> >> >>> >> >> > cause
> >> >> >>> >> >> > slower
> >> >> >>> >> >> > performance due to I/O bottleneck.
> >> >> >>> >> >> > Is there any way to by pass writing
flow files on disk or
> >> >> >>> >> >> > directly
> >> >> >>> >> >> > pass
> >> >> >>> >> >> > those files to HDFS as it is ?
> >> >> >>> >> >> > 1.b If the files on the spool directory
are
> >> >> >>> >> >> > compressed(zip/gzip),
> >> >> >>> >> >> > can
> >> >> >>> >> >> > we
> >> >> >>> >> >> > store files on HDFS as uncompressed
?
> >> >> >>> >> >> >
> >> >> >>> >> >> > Question for Scenario 2:
> >> >> >>> >> >> > 2.a Can we use our existing java
code for masking ? if
> yes
> >> >> >>> >> >> > then
> >> >> >>> >> >> > how ?
> >> >> >>> >> >> > 2.b For this Scenario we also want
to bypass storing flow
> >> >> >>> >> >> > files
> >> >> >>> >> >> > on
> >> >> >>> >> >> > disk.
> >> >> >>> >> >> > Can
> >> >> >>> >> >> > we do it on the fly, masking and
storing on HDFS ?
> >> >> >>> >> >> > 2.c If the source files are compressed
(zip/gzip), is
> there
> >> >> >>> >> >> > any
> >> >> >>> >> >> > issue
> >> >> >>> >> >> > for
> >> >> >>> >> >> > masking here ?
> >> >> >>> >> >> >
> >> >> >>> >> >> >
> >> >> >>> >> >> > In fact, I tried above using flume+flume
interceptors.
> >> >> >>> >> >> > Everything
> >> >> >>> >> >> > working
> >> >> >>> >> >> > fine with smaller files. But when
source files greater
> that
> >> >> >>> >> >> > 50MB
> >> >> >>> >> >> > flume
> >> >> >>> >> >> > chocks :(.
> >> >> >>> >> >> > So, I am exploring options in NiFi.
Hope I will get some
> >> >> >>> >> >> > guideline
> >> >> >>> >> >> > from
> >> >> >>> >> >> > you
> >> >> >>> >> >> > guys.
> >> >> >>> >> >> >
> >> >> >>> >> >> >
> >> >> >>> >> >> > Thanks in advance.
> >> >> >>> >> >> > -Obaid
> >> >> >>> >> >
> >> >> >>> >> >
> >> >> >
> >> >> >
> >> >
> >> >
> >
> >
>

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