Quick observation for now off latest data:
- GC looks pretty good though it is surprising there were any full GCs
during that short test
- cpu has low utilization
- disk has low utilization
Can you share your sample input data, processor code, flow as a
template? Attaching to a JIRA for example could be a good way. We
can use this as a good example of how someone can
troubleshoot/optimize.
Thanks
Joe
On Thu, Jan 14, 2016 at 1:00 AM, obaidul karim <obaidc...@gmail.com> wrote:
> 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
>> >> >> >> >>> >> >
>> >> >> >> >>> >> >
>> >> >> >> >
>> >> >> >> >
>> >> >> >
>> >> >> >
>> >> >
>> >> >
>> >
>> >
>
>
