We're trying to filter out some records of the output that we have to
another table in ORC and the job takes twice as long. Not sure if there's a
better way to do this?
Here's the code
jsonRows.foreachRDD(r => {
val jsonDf = sqlSession.read.schema(sparrowSchema.schema).json(r)
val cnsDf =
amazonaws" % "aws-java-sdk-core" % "1.11.155"
Not sure if I need special configuration?
On Tue, 25 Jul 2017 at 04:17 周康 <zhoukang199...@gmail.com> wrote:
> Ensure com.amazonaws.services.s3.AmazonS3ClientBuilder in your classpath
> which include your appli
I have this spark job which is using S3 client in mapPartition. And I get
this error
Job aborted due to stage failure: Task 0 in stage 3.0 failed 4 times, most
recent failure: Lost task 0.3 in stage 3.0 (TID 74,
ip-10-90-78-177.ec2.internal, executor 11): java.lang.NoClassDefFoundError:
Could not
I'm super new to Spark and I'm writing this job to parse nginx log to ORC
file format so it can be read from Presto. We wrote LogLine2Json which
parse a line of nginx log to json. And that works fine.
val sqs = streamContext.receiverStream(new SQSReceiver("elb")
//.credentials("key",
