Yeah, then the easiest would be to fork spark and run using the forked
version, and in case of YARN it should be pretty easy to do.
git clone https://github.com/apache/spark.git
cd spark
export MAVEN_OPTS="-Xmx4g -XX:ReservedCodeCacheSize=512m"
./build/mvn -DskipTests clean package
./dev/make-distribution.sh --name custom-spark --tgz -Phadoop-2.7 -Phive
-Pyarn
ls -la spark-2.4.0-SNAPSHOT-bin-custom-spark.tgz
scp spark-2.4.0-SNAPSHOT-bin-custom-spark.tgz cluster:/tmp
export SPARK_HOME="/tmp/spark-2.3.0-SNAPSHOT-bin-custom-spark"
cd $SPARK_HOME
mv conf conf.new
ln -s /etc/spark/conf conf
echo $SPARK_HOME
spark-submit --version
On Tue, Feb 12, 2019 at 6:40 AM Serega Sheypak <serega.sheypak@gmail.com>
wrote:
>
> I tried a similar approach, it works well for user functions. but I need
to crash tasks or executor when spark application runs "repartition". I
didn't any away to inject "poison pill" into repartition call :(
>
> пн, 11 февр. 2019 г. в 21:19, Vadim Semenov <vadim@datadoghq.com>:
>>
>> something like this
>>
>> import org.apache.spark.TaskContext
>> ds.map(r => {
>> val taskContext = TaskContext.get()
>> if (taskContext.partitionId == 1000) {
>> throw new RuntimeException
>> }
>> r
>> })
>>
>> On Mon, Feb 11, 2019 at 8:41 AM Serega Sheypak <serega.sheypak@gmail.com>
wrote:
>> >
>> > I need to crash task which does repartition.
>> >
>> > пн, 11 февр. 2019 г. в 10:37, Gabor Somogyi <gabor.g.somogyi@gmail.com
>:
>> >>
>> >> What blocks you to put if conditions inside the mentioned map
function?
>> >>
>> >> On Mon, Feb 11, 2019 at 10:31 AM Serega Sheypak <
serega.sheypak@gmail.com> wrote:
>> >>>
>> >>> Yeah, but I don't need to crash entire app, I want to fail several
tasks or executors and then wait for completion.
>> >>>
>> >>> вс, 10 февр. 2019 г. в 21:49, Gabor Somogyi <
gabor.g.somogyi@gmail.com>:
>> >>>>
>> >>>> Another approach is adding artificial exception into the
application's source code like this:
>> >>>>
>> >>>> val query = input.toDS.map(_ /
0).writeStream.format("console").start()
>> >>>>
>> >>>> G
>> >>>>
>> >>>>
>> >>>> On Sun, Feb 10, 2019 at 9:36 PM Serega Sheypak <
serega.sheypak@gmail.com> wrote:
>> >>>>>
>> >>>>> Hi BR,
>> >>>>> thanks for your reply. I want to mimic the issue and kill tasks
at
a certain stage. Killing executor is also an option for me.
>> >>>>> I'm curious how do core spark contributors test spark fault
tolerance?
>> >>>>>
>> >>>>>
>> >>>>> вс, 10 февр. 2019 г. в 16:57, Gabor Somogyi <
gabor.g.somogyi@gmail.com>:
>> >>>>>>
>> >>>>>> Hi Serega,
>> >>>>>>
>> >>>>>> If I understand your problem correctly you would like to
kill one
executor only and the rest of the app has to be untouched.
>> >>>>>> If that's true yarn -kill is not what you want because it
stops
the whole application.
>> >>>>>>
>> >>>>>> I've done similar thing when tested/testing Spark's HA features.
>> >>>>>> - jps -vlm | grep
"org.apache.spark.executor.CoarseGrainedExecutorBackend.*applicationid"
>> >>>>>> - kill -9 pidofoneexecutor
>> >>>>>>
>> >>>>>> Be aware if it's a multi-node cluster check whether at least
one
process runs on a specific node(it's not required).
>> >>>>>> Happy killing...
>> >>>>>>
>> >>>>>> BR,
>> >>>>>> G
>> >>>>>>
>> >>>>>>
>> >>>>>> On Sun, Feb 10, 2019 at 4:19 PM Jörn Franke <jornfranke@gmail.com>
wrote:
>> >>>>>>>
>> >>>>>>> yarn application -kill applicationid ?
>> >>>>>>>
>> >>>>>>> > Am 10.02.2019 um 13:30 schrieb Serega Sheypak <
serega.sheypak@gmail.com>:
>> >>>>>>> >
>> >>>>>>> > Hi there!
>> >>>>>>> > I have weird issue that appears only when tasks
fail at
specific stage. I would like to imitate failure on my own.
>> >>>>>>> > The plan is to run problematic app and then kill
entire
executor or some tasks when execution reaches certain stage.
>> >>>>>>> >
>> >>>>>>> > Is it do-able?
>> >>>>>>>
>> >>>>>>>
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>> >>>>>>> To unsubscribe e-mail: user-unsubscribe@spark.apache.org
>> >>>>>>>
>>
>>
>> --
>> Sent from my iPhone
--
Sent from my iPhone
|