Hi, Guys,
I have some code which runs will using Spark-Submit command.
$SPARK_HOME/bin/spark-submit --class com.myorg.service.SparkService ./Search.jar
How can I deploy it to Tomcat? If I simply deploy the jar file, I
will get ClassNotFound error.
Thanks!
Hi, Guys,
Where can I find the console log file of CoarseGrainedExecutorBackend
process?
Thanks!
Tao
Hi, Guys,
Is it possible that RDD created by driver A be used driver B?
Thanks!
Yes. Ayan, you approach will work.
Or alternatively, use Spark, and write a Scala/Java function which
implements similar logic in your Pig UDF.
Both approaches look similar.
Personally, I would go with Spark solution, it will be slightly faster, and
easier if you already have Spark cluster
Otherwise you pay
> more money for maintenance and development.
>
> Le jeu. 3 sept. 2015 à 17:16, Tao Lu <taolu2...@gmail.com> a écrit :
>
>> Yes. Ayan, you approach will work.
>>
>> Or alternatively, use Spark, and write a Scala/Java function which
>> implemen
Your requirements conflict with each other.
1. You want to dump all your messages somewhere
2. You want to be able to update/delete individual message
3. You don't want to introduce anther NOSQL database(like HBASE) since you
already have all messages stored in MongoDB
My suggestion is:
1. Don't
You situation is special. It seems to me Spark may not fit well in your
case.
You want to process the individual files (500M~2G) as a whole, you want
good performance.
You may want to write our own Scala/Java programs and distribute it along
with those files across your cluster, and run them in
You may consider storing it in one big HDFS file, and to keep appending new
messages to it.
For instance,
one message -> zip it -> append it to the HDFS as one line
On Wed, Sep 2, 2015 at 12:43 PM, wrote:
> Hi,
> I already store them in MongoDB in parralel for operational
Basically they need NOSQL like random update access.
On Fri, Sep 4, 2015 at 9:56 AM, Ted Yu wrote:
> What about concurrent access (read / update) to the small file with same
> key ?
>
> That can get a bit tricky.
>
> On Thu, Sep 3, 2015 at 2:47 PM, Jörn Franke
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