The existing ContinuousFileMonitoringFunction and
ContinuousFileReaderOperator already take care of that.
Unless you aren't re-implementing them from scratch you shouldn't have
to do anything.
On 10/22/2020 1:47 PM, Satyaa Dixit wrote:
Hi Chesnay,
Thanks for your support.It helped a lot. I need one more help on how to do
checkpointing as part of the s3 reader source in case if some failure
happens due to OutOfMemoryError exception or it could be any other failure,
and want to recover the data from last reader splitted offset during
restart the job in continuation of the previous job in order to avoid
duplicate data.
Thanks,
Satya
On Thu, Oct 15, 2020 at 3:29 PM Chesnay Schepler <ches...@apache.org> wrote:
hmm...I don't see an easy way.
You may have to replicated StreamExecutionEnvironment#createFileInput and
create a custom ContinuousFileMonitoringFunction that ignores missing
files in it's run() method.
Alternatively, use some library to check the existence of the S3
directories before creating the sources.
On 10/15/2020 11:49 AM, Satyaa Dixit wrote:
Hi Chesnay/Team,
Thanks, we got the fix for our problem but got stuck with the below
issue,
request your support.
How to catch FileNotFoundException during runtime,if any directory is
missing in s3 as part of the below source code to avoid job failure.
s3PathList.stream().map(directory ->
S3Service.createInputStream(environment, directory, readerParallelism))
.reduce(DataStream::union).map(joinedStream ->
joinedStream.addSink(kafkaProducer));
Regards,
Satya
On Wed, Oct 14, 2020 at 8:57 PM Satyaa Dixit <satyaadi...@gmail.com>
wrote:
Hi Chesnay/Team
Thank you so much.I have tried with the solution but it is not working
as
expected showing compilation issues and tried all the ways .Please find
below code snippet :
s3PathList.stream()
.map(directory -> S3Service.customCreateInputStream(environment,
directory, readerParallelism))
.reduce(DataStream::union).map(joinedStream -> stream.flatMap(new
IntermidiateOperator()).map(joinedStream ->
joinedStream.addSink(kafkaProducer).name("Publish to " +
kafkaTopicName));
public static class IntermidiateOperator implements
FlatMapFunction<String, String> {
private static final ObjectMapper objectMapper1 = new ObjectMapper();
@Override
public void flatMap(String value, Collector<String> out) throws
Exception {
Test m = objectMapper1.readValue(value, Test.class);
System.out.println("Json string:: ------" + m);
// logger.info("Json string:: ------"+m);
out.collect(value);
}
}
Also just to clarify one doubt , How to handle *FileNotFoundException*
as
part of flink reader during runtime if in case directory is not
available
in s3. How to avoid job failure in that use case.
Regards,
Satya
On Tue, Oct 13, 2020 at 11:15 AM Satyaa Dixit <satyaadi...@gmail.com>
wrote:
Thanks, I'll check it out.
On Mon, Oct 12, 2020 at 1:29 PM Chesnay Schepler <ches...@apache.org>
wrote:
1) There's no mechanism in the API to restrict the number of number
of
readers across several sources. I can't quite think of a way to
achieve
this; maybe Kostas has an idea.
2) You're mixing up the Java Streams and Finks DataStream API.
Try this:
s3PathList.stream()
.map(...)
.reduce(...)
.map(joinedStream -> stream.map(new FlatMapFunction...))
.map(joinedStream-> joinedStream.addSink...)
On 10/12/2020 6:05 AM, Satyaa Dixit wrote:
Hi Team,
Could you please help me here. I’m sorry for asking on such short
notice
but my work has stopped due to this.
Regards,
Satya
On Fri, 9 Oct 2020 at 8:53 PM, Satyaa Dixit <satyaadi...@gmail.com>
wrote:
Hi Shesnay/Team,
Thank you so much for the reply.In the continuation of the previous
email, below is the block diagram where I am reading the file from
s3 and
pushing it to kafka.Now with the current setup, I have total 4
directory
based on the readfile method from flink environment ,we are
creating 4
readers parallely to process the data from s3 .
Below are my Questions:
1. Can we restrict the no. of readers to process the data parallely.
e.g let's say if we have a thousand of directory , in that case i
want to
restrict the no. of readers to 10 and ten parallel threads will
continue
with 100 sequential reading of the directory per thread to consume
the data
.
2.In between the two flink operators i.e s3 reader and kafka sink , i
just want to implement one more operator in order to transform the
data
which i am reading from s3 bucket and then want to push into the
kafka
sink. Below is my working code.Here i am finding difficulties to
implement map operator in order to transform the union of
datastreams by
applying union method over each directory's reader before pushing to
kafka.
List<String> s3PathList =
S3Service.getListOfS3Paths(finalParameters);
s3PathList.stream()
.map(directory -> S3Service.customInputStream(environment, directory,
readerParallelism))
.reduce(DataStream::union)
.map(joinedStream ->
joinedStream.addSink(kafkaProducer).name("Publish
to " + kafkaTopicName));
*Something like this I'm trying to do in order to achieve the above
use
case by applying FlatMap, it could be map as well:*
s3PathList.stream()
.map(directory -> S3Service.customInputStream(environment, directory,
readerParallelism))
.reduce(DataStream::union).flatMap(new FlatMapFunction<DataStream,
String>() {
@Override
public void flatMap(String value, Collector<String> out) throws
Exception {
FinalJsonMessage m=objectMapper.readValue(value,
FinalJsonMessage.class);
System.out.println("Json string:: ------"+m);
//transformation logic
out.collect(value);
}
})
.map(joinedStream ->
joinedStream.addSink(kafkaProducer).name("Publish
to " + kafkaTopicName));
[image: image.png]
Request your support on the same.
Regards,
Satya
On Mon, Oct 5, 2020 at 12:16 PM Satyaa Dixit <satyaadi...@gmail.com>
wrote:
Hi @ches...@apache.org <ches...@apache.org> ,
Thanks for your support, it was really helpful.
Do you know the list of directories when you submit the job? [Yes we
do have]
The impletemation is progress and will get back to you if any
further
challenges we may face.
Appreciate your support in this regard.
Regards,
Satya
On Thu, Oct 1, 2020 at 7:46 PM Satyaa Dixit <satyaadi...@gmail.com>
wrote:
Thank you @Chesnay let me try this change .
On Thu, Oct 1, 2020 at 1:21 PM Chesnay Schepler <
ches...@apache.org>
wrote:
You could also try using streams to make it a little more concise:
directories.stream()
.map(directory -> createInputStream(environment, directory))
.reduce(DataStream::union)
.map(joinedStream -> joinedStream.addSink(kafka));
On 10/1/2020 9:48 AM, Chesnay Schepler wrote:
Do you know the list of directories when you submit the job?
If so, then you can iterate over them, create a source for each
directory, union them, and apply the sink to the union.
private static
DataStream<String>createInputStream(StreamExecutionEnvironment
environment,
String directory) {
TextInputFormat format =new TextInputFormat(new
org.apache.flink.core.fs.Path(directory));
format.setNestedFileEnumeration(true); return
environment.readFile(format,
directory, FileProcessingMode.PROCESS_ONCE, -1,
FilePathFilter.createDefaultFilter()); }
public static void runJob()throws Exception {
StreamExecutionEnvironment environment =
StreamExecutionEnvironment.getExecutionEnvironment(); List<String>
directories =getDirectories(); DataStream<String> joinedStreams
=null; for
(String directory : directories) {
DataStream<String> inputStream
=createInputStream(environment,
directory); if (joinedStreams ==null) {
joinedStreams = inputStream; }else {
joinedStreams.union(inputStream); }
}
// add a sanity check that there was at least 1 directory
joinedStreams.addSink(kafka); }
On 10/1/2020 9:08 AM, Satyaa Dixit wrote:
Hi Guys,
Got stuck with it please help me here
Regards,
Satya
On Wed, 30 Sep 2020 at 11:09 AM, Satyaa Dixit
<satyaadi...@gmail.com> <satyaadi...@gmail.com> wrote:
Hi Guys,
Sorry to bother you again, but someone could help me here? Any
help
in
this regard will be much appreciated.
Regards,
Satya
On Tue, Sep 29, 2020 at 2:57 PM Satyaa Dixit <
satyaadi...@gmail.com>
<satyaadi...@gmail.com>
wrote:
Hi Guys,
I need one help, any leads will be highly appreciated.I have
written
a
flink streaming job to read the data from s3 bucket and push to
kafka.
Below is the working source that deal with single s3 path:
TextInputFormat format = new TextInputFormat(new
org.apache.flink.core.fs.Path("s3a://directory/2020-09-03/"));
format.setNestedFileEnumeration(true);
DataStream<String> inputStream = environment.readFile(format,
"s3a://directory/2020-09-03/", FileProcessingMode.PROCESS_ONCE,
-1,
FilePathFilter.createDefaultFilter());
inputStream.addSink(kafka);
But my requirement is get the list of paths and pass them one by
one
to
this environment.readFile() method.How we can achieve this.
Thanks,
Satya
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
--
--------------------------
Best Regards
Satya Prakash
(M)+91-9845111913
