Joe,
Last time it was below:
java.arg.2=-Xms512m
java.arg.3=-Xmx512m
Now I made as below:
java.arg.2=-Xms5120m
java.arg.3=-Xmx10240m
latest jstate & iostate output are attached.
To me it is still slow, no significant improvements.
-Obaid
On Thu, Jan 14, 2016 at 12:41 PM, Joe Witt <joe.w...@gmail.com> wrote:
> Obaid,
>
> Great so this is helpful info. Iostat output shows both CPU and disk
> are generally bored and ready for more work. Looking at the gc output
> though suggests trouble. We see there are 32 samples at 1 second
> spread each and in that time spent more than 6 seconds of it doing
> garbage collection including 5 full collections. That is usually a
> sign of inefficient heap usage and/or simply an undersized heap. What
> size do you have your heap settings at in the conf/bootstrap.conf
> file?
>
> Thanks
> Joe
>
> On Wed, Jan 13, 2016 at 11:32 PM, obaidul karim <obaidc...@gmail.com>
> wrote:
> > 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.w...@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 <obaidc...@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.w...@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 <
> helloj...@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.w...@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 <
> obaidc...@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
> >> >> >> > <obaidc...@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.w...@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
> >> >> >> >>> <obaidc...@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.w...@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
> >> >> >> >>> >> <obaidc...@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.w...@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
> >> >> >> >>> >> >> <obaidc...@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
> >> >> >> >>> >> >
> >> >> >> >>> >> >
> >> >> >> >
> >> >> >> >
> >> >> >
> >> >> >
> >> >
> >> >
> >
> >
>
[etl@sthdmgt1-pvt nifi]$ jps
41616 RunJar
54865 FsShell
55476 FsShell
48118 RunJar
41497 RunJar
55706 Jps
4733 RunNiFi
4862 NiFi
[etl@sthdmgt1-pvt nifi]$
[etl@sthdmgt1-pvt nifi]$ jstat -gcutil 4862 1000
S0 S1 E O M CCS YGC YGCT FGC FGCT GCT
28.12 0.00 73.42 38.76 95.44 90.23 6520 29.834 3 0.228
30.063
0.00 28.12 53.58 38.76 95.44 90.23 6523 29.849 3 0.228
30.077
43.75 0.00 29.34 38.76 95.44 90.23 6526 29.864 3 0.228
30.092
0.00 18.75 5.45 38.76 95.44 90.23 6529 29.879 3 0.228
30.108
0.00 43.75 85.98 38.77 95.44 90.23 6531 29.889 3 0.228
30.117
29.69 0.00 60.71 38.77 95.44 90.23 6534 29.904 3 0.228
30.132
0.00 18.75 35.86 38.78 95.44 90.23 6537 29.918 3 0.228
30.146
32.81 0.00 19.34 38.78 95.44 90.23 6540 29.933 3 0.228
30.161
0.00 37.50 5.96 38.78 95.44 90.23 6543 29.948 3 0.228
30.176
0.00 32.81 85.03 38.78 95.44 90.23 6545 29.959 3 0.228
30.187
37.50 0.00 62.76 38.79 95.44 90.23 6548 29.974 3 0.228
30.203
0.00 34.38 39.26 38.79 95.44 90.23 6551 29.990 3 0.228
30.218
46.88 0.00 19.40 38.79 95.44 90.23 6554 30.005 3 0.228
30.233
0.00 26.56 0.00 38.79 95.44 90.23 6557 30.019 3 0.228
30.247
0.00 10.94 68.94 38.80 95.44 90.23 6559 30.029 3 0.228
30.257
31.25 0.00 3.96 38.80 95.44 90.23 6560 30.034 3 0.228
30.262
0.00 29.69 89.64 38.80 95.44 90.23 6561 30.039 3 0.228
30.268
81.25 0.00 1.00 38.80 95.44 90.23 6562 30.045 3 0.228
30.273
0.00 34.38 55.85 38.80 95.44 90.23 6563 30.050 3 0.228
30.279
[etl@sthdmgt1-pvt nifi]$ iostat xmh 1
Linux 2.6.32-358.el6.x86_64 (sthdmgt1-pvt.aiu.axiata) 01/14/2016
_x86_64_ (24 CPU)
avg-cpu: %user %nice %system %iowait %steal %idle
6.52 0.00 0.81 0.04 0.00 92.62
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
22.08 0.00 3.02 12.76 0.00 62.13
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
24.09 0.00 4.66 7.26 0.00 63.99
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
24.71 0.00 3.54 4.46 0.00 67.30
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
20.46 0.00 1.98 1.22 0.00 76.34
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
20.15 0.00 2.06 1.01 0.00 76.78
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
20.63 0.00 2.23 1.05 0.00 76.09
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
19.53 0.00 1.05 1.01 0.00 78.42
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
19.10 0.00 1.17 0.17 0.00 79.56
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
19.71 0.00 1.43 0.21 0.00 78.66
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
18.96 0.00 1.34 0.59 0.00 79.11
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
20.60 0.00 1.72 1.34 0.00 76.34
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
avg-cpu: %user %nice %system %iowait %steal %idle
20.07 0.00 1.21 1.09 0.00 77.63
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
^C
[etl@sthdmgt1-pvt nifi]$
