To clarify clarify, Ted's got the right formula. You would use
-Phadoop-2.4 to set up the build configuration, and then customize
-Dhadoop.version= further to the 2.4+ version you want.
On Sat, Dec 20, 2014 at 12:35 AM, Denny Lee denny.g@gmail.com wrote:
To clarify, there isn't a Hadoop 2.6
Hi DB,
I cherry-picked the commit into branch-1.2 and it solved the problem. It
solves the problem but has some bits and pieces around which was not
finalized thus reverted beeing late in release process.
Jakub
--
Just out of my curiosity. Do you manually apply this patch and see if
I have a Spark job running on about 300 GB of log files, on Amazon EC2,
with 10 x Large instances (each with 600 GB disk). The job hasn't yet
completed.
So far, 18 stages have completed (2 of which have retries) and 3 stages
have failed. In each failed stage there are ~160 successful tasks, but
First, thanks for the efforts and contribution to such a useful software
stack! Spark is great!
I have been using the git tags for v1.2.0-rc1 and v1.2.0-rc2 built as
follows:
./make-distribution.sh -Dhadoop.version=2.5.0-cdh5.2.0
-Dyarn.version=2.5.0-cdh5.2.0 -Phadoop-2.4 -Phive -Pyarn
This makes no sense. There is no difference between v1.2.0-rc2 and v1.2.0:
https://github.com/apache/spark/compare/v1.2.0-rc2...v1.2.0
On Sat, Dec 20, 2014 at 12:44 PM, Matt Mead m...@matthewcmead.com wrote:
First, thanks for the efforts and contribution to such a useful software
stack!
Bizarre. I originally cloned from and have been pulling from
https://github.com/apache/spark, and my repo shows the following:
user@host:~/development/spark$ git diff v1.2.0-rc2..v1.2.0 | wc -l
1898
If I pull a fresh clone, I get this:
user@host:~$ git clone https://github.com/apache/spark
That seemed to correct the issue. Thanks for pointing out the lack of
diffs between v1.2.0-rc2 and v1.2.0 -- I'm not sure how my git repo ended
up not matching its origin.
-matt
On Sat, Dec 20, 2014 at 4:25 PM, Matt Mead m...@matthewcmead.com wrote:
Bizarre. I originally cloned from and
What version of the script are you running? What did you see in the EC2 web
console when this happened?
Sometimes instances just don't come up in a reasonable amount of time and
you have to kill and restart the process.
Does this always happen, or was it just once?
Nick
On Thu, Dec 18, 2014 at
Is the operation slow every time or does it run normally if you repeat the
operation within the same app?
Nick
On Thu, Dec 18, 2014 at 8:56 AM, Jon Chase jon.ch...@gmail.com wrote:
I'm running a very simple Spark application that downloads files from S3,
does a bit of mapping, then uploads
I would suggest checking out disk IO on the nodes in your cluster and then
reading up on the limiting behaviors that accompany different kinds of EC2
storage. Depending on how things are configured for your nodes, you may
have a local storage configuration that provides bursty IOPS where you
get
Hi ,
Can someone help me , Any pointers would help.
Thanks
Subacini
On Fri, Dec 19, 2014 at 10:47 PM, Subacini B subac...@gmail.com wrote:
Hi All,
Is there any API that can be used directly to write schemaRDD to HBase??
If not, what is the best way to write schemaRDD to HBase.
Thanks
I'm using JDBCRDD
https://spark.apache.org/docs/1.2.0/api/scala/index.html#org.apache.spark.rdd.JdbcRDD
+ Hbase JDBC driver http://phoenix.apache.org/+ schemaRDD
https://spark.apache.org/docs/1.2.0/api/scala/index.html#org.apache.spark.sql.SchemaRDD
make sure to use spark 1.2
On Sat, Dec 20,
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!
Everything else is there except spark-repl. Can someone check that out this
weekend?
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IMHO: cache doesn't provide redundancy, and its in the same jvm, so its much
faster.
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