thanks guys.
just to clarify let us assume i am doing spark-submit as below:
${SPARK_HOME}/bin/spark-submit \
--packages ${PACKAGES} \
--driver-memory 2G \
--num-executors 2 \
--executor-memory 2G \
--executor-cores 2 \
--master yarn \
--deploy-mode client \
--conf "${SCHEDULER}" \
--conf "${EXTRAJAVAOPTIONS}" \
--jars ${JARS} \
--class "${FILE_NAME}" \
--conf "${SPARKUIPORT}" \
--conf "${SPARKDRIVERPORT}" \
--conf "${SPARKFILESERVERPORT}" \
--conf "${SPARKBLOCKMANAGERPORT}" \
--conf "${SPARKKRYOSERIALIZERBUFFERMAX}" \
*${JAR_FILE}*
The* ${JAR_FILE}* is the one. As I understand Spark should distribute that
${JAR_FILE} to each container?
Also --jars ${JARS} are the list of normal jar files that need to exist in
the same directory on each executor node?
cheers,
Dr Mich Talebzadeh
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On 17 July 2017 at 18:18, ayan guha <guha.a...@gmail.com> wrote:
> Hi Mitch
>
> your jar file can be anywhere in the file system, including hdfs.
>
> If using yarn, preferably use cluster mode in terms of deployment.
>
> Yarn will distribute the jar to each container.
>
> Best
> Ayan
>
> On Tue, 18 Jul 2017 at 2:17 am, Marcelo Vanzin <van...@cloudera.com>
> wrote:
>
>> Spark distributes your application jar for you.
>>
>> On Mon, Jul 17, 2017 at 8:41 AM, Mich Talebzadeh
>> <mich.talebza...@gmail.com> wrote:
>> > hi guys,
>> >
>> >
>> > an uber/fat jar file has been created to run with spark in CDH yarc
>> client
>> > mode.
>> >
>> > As usual job is submitted to the edge node.
>> >
>> > does the jar file has to be placed in the same directory ewith spark is
>> > running in the cluster to make it work?
>> >
>> > Also what will happen if say out of 9 nodes running spark, 3 have not
>> got
>> > the jar file. will that job fail or it will carry on on the fremaing 6
>> nodes
>> > that have that jar file?
>> >
>> > thanks
>> >
>> > Dr Mich Talebzadeh
>> >
>> >
>> >
>> > LinkedIn
>> > https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCd
>> OABUrV8Pw
>> >
>> >
>> >
>> > http://talebzadehmich.wordpress.com
>> >
>> >
>> > Disclaimer: Use it at your own risk. Any and all responsibility for any
>> > loss, damage or destruction of data or any other property which may
>> arise
>> > from relying on this email's technical content is explicitly
>> disclaimed. The
>> > author will in no case be liable for any monetary damages arising from
>> such
>> > loss, damage or destruction.
>> >
>> >
>>
>>
>>
>> --
>> Marcelo
>>
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>>
>> --
> Best Regards,
> Ayan Guha
>
