This method is doing very little. Line 2 constructs the CoGroupedRDD, which
will do all the real work. Note that while this cogroup function just
groups 2 RDDs together, CoGroupedRDD allows general n-way cogrouping, so it
takes a Seq[RDD(K, _)] rather than just 2 such key-value RDDs.
The rest of
I'm looking at adding spark / shark to our analytics pipeline and would
also like to use spark streaming for some incremental computations, but I
have some questions about the suitability of spark streaming.
Roughly, we have events that are generated by app servers based on user
interactions with
So i've been struggling with this now for a bit using SparkR.. I can't
even seem to write a basic mean/median function in R that works when
passing it into reduceByKey() for my very simple dataset. I can pass
in R's base function 'sum' and it works just fine. Looking in help
shows that the
Hi,
While running the Bagel’s Wikipedia Page Rank example
(org.apache.spark.examples.bagel.WikipediaPageRank), it is having this error at
the end:
org.apache.spark.SparkException: Job aborted: Task 3.0:4 failed 4 times (most
recent failure: Exception failure: java.lang.ClassNotFoundException:
On 4 Feb, 2014, at 10:08 am, Tsai Li Ming mailingl...@ltsai.com wrote:
Hi,
While running the Bagel’s Wikipedia Page Rank example
(org.apache.spark.examples.bagel.WikipediaPageRank), it is having this error
at the end:
org.apache.spark.SparkException: Job aborted: Task 3.0:4 failed 4
after googling around I realize how ridiculous my question is :(
being new to Spark, for some reason I thought all of the basic stats
function were implemented in a first class way out of the box over the
mapreduce framework... oops! sorry for the spam :)
On Monday, February 3, 2014, Justin
Hello,
I am experiencing the following problem with Spark.
My application runs properly for very small datasets (6 MB), but fails for
datasets beyond 12MB.
With those larger datasets, the main log shows the following errors for
all of my executors. The application (launched from sbt command)
