Is there a way to force update spark accumulators?
I wanted to do asynchronous job in the workers, but the accumulators don't apply for the driver side as the updateAccumulators method was already called.
The problem is that updateAccumulators is private so my question is : is there a way to force it to be used or another way to accomplish what i need>
val partiotionsDone =rdd.sparkContext.longAccumulator("partiotionsDone")
rdd.foreachPartitionAsync { rows =>
Future {
val ingestion = ingestRows(rows)
ingestion onSuccess{
case _=> {
partiotionsDone.add(1)
}
}
}
runTaskEvery(5 seconds,
func= ()=> println("partitionsFinished:${partiotionsDone.value}"),
whenDone=doFinalWork)
the runTaskEvery prints only 0 values - although debugger shows that partiotionsDone.add(1) was done successfully. Of course if i'm waiting on the future it all works - but the whole point here was not to do that
scala apache-spark asynchronous
add a comment |
I wanted to do asynchronous job in the workers, but the accumulators don't apply for the driver side as the updateAccumulators method was already called.
The problem is that updateAccumulators is private so my question is : is there a way to force it to be used or another way to accomplish what i need>
val partiotionsDone =rdd.sparkContext.longAccumulator("partiotionsDone")
rdd.foreachPartitionAsync { rows =>
Future {
val ingestion = ingestRows(rows)
ingestion onSuccess{
case _=> {
partiotionsDone.add(1)
}
}
}
runTaskEvery(5 seconds,
func= ()=> println("partitionsFinished:${partiotionsDone.value}"),
whenDone=doFinalWork)
the runTaskEvery prints only 0 values - although debugger shows that partiotionsDone.add(1) was done successfully. Of course if i'm waiting on the future it all works - but the whole point here was not to do that
scala apache-spark asynchronous
add a comment |
I wanted to do asynchronous job in the workers, but the accumulators don't apply for the driver side as the updateAccumulators method was already called.
The problem is that updateAccumulators is private so my question is : is there a way to force it to be used or another way to accomplish what i need>
val partiotionsDone =rdd.sparkContext.longAccumulator("partiotionsDone")
rdd.foreachPartitionAsync { rows =>
Future {
val ingestion = ingestRows(rows)
ingestion onSuccess{
case _=> {
partiotionsDone.add(1)
}
}
}
runTaskEvery(5 seconds,
func= ()=> println("partitionsFinished:${partiotionsDone.value}"),
whenDone=doFinalWork)
the runTaskEvery prints only 0 values - although debugger shows that partiotionsDone.add(1) was done successfully. Of course if i'm waiting on the future it all works - but the whole point here was not to do that
scala apache-spark asynchronous
I wanted to do asynchronous job in the workers, but the accumulators don't apply for the driver side as the updateAccumulators method was already called.
The problem is that updateAccumulators is private so my question is : is there a way to force it to be used or another way to accomplish what i need>
val partiotionsDone =rdd.sparkContext.longAccumulator("partiotionsDone")
rdd.foreachPartitionAsync { rows =>
Future {
val ingestion = ingestRows(rows)
ingestion onSuccess{
case _=> {
partiotionsDone.add(1)
}
}
}
runTaskEvery(5 seconds,
func= ()=> println("partitionsFinished:${partiotionsDone.value}"),
whenDone=doFinalWork)
the runTaskEvery prints only 0 values - although debugger shows that partiotionsDone.add(1) was done successfully. Of course if i'm waiting on the future it all works - but the whole point here was not to do that
scala apache-spark asynchronous
scala apache-spark asynchronous
edited Jan 2 at 14:56
Driss Nejjar
18210
18210
asked Jan 2 at 11:23
Ohad BittonOhad Bitton
858
858
add a comment |
add a comment |
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