Re: Spark runs into an Infinite loop even if the tasks are completed successfully
Yep, and it works fine for operations which does not involve any shuffle
(like foreach,, count etc) and those which involves shuffle operations ends
up in an infinite loop. Spark should somehow indicate this instead of going
in an infinite loop.
Thanks
Best Regards
On Thu, Aug 13, 2015 at 11:37 PM, Imran Rashid iras...@cloudera.com wrote:
oh I see, you are defining your own RDD Partition types, and you had a
bug where partition.index did not line up with the partitions slot in
rdd.getPartitions. Is that correct?
On Thu, Aug 13, 2015 at 2:40 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
I figured that out, And these are my findings:
- It just enters in an infinite loop when there's a duplicate partition
id.
- It enters in an infinite loop when the partition id starts from 1
rather than 0
Something like this piece of code can reproduce it: (in getPartitions())
val total_partitions = 4
val partitionsArray: Array[Partition] =
Array.ofDim[Partition](total_partitions)
var i = 0
for(outer - 0 to 1){
for(partition - 1 to total_partitions){
partitionsArray(i) = new DeadLockPartitions(partition)
i = i + 1
}
}
partitionsArray
Thanks
Best Regards
On Wed, Aug 12, 2015 at 10:57 PM, Imran Rashid iras...@cloudera.com
wrote:
yikes.
Was this a one-time thing? Or does it happen consistently? can you
turn on debug logging for o.a.s.scheduler (dunno if it will help, but maybe
...)
On Tue, Aug 11, 2015 at 8:59 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Hi
My Spark job (running in local[*] with spark 1.4.1) reads data from a
thrift server(Created an RDD, it will compute the partitions in
getPartitions() call and in computes hasNext will return records from these
partitions), count(), foreach() is working fine it returns the correct
number of records. But whenever there is shuffleMap stage (like reduceByKey
etc.) then all the tasks are executing properly but it enters in an
infinite loop saying :
1. 15/08/11 13:05:54 INFO DAGScheduler: Resubmitting
ShuffleMapStage 1 (map at FilterMain.scala:59) because some of its
tasks had failed: 0, 3
Here's the complete stack-trace http://pastebin.com/hyK7cG8S
What could be the root cause of this problem? I looked up and bumped
into this closed JIRA https://issues.apache.org/jira/browse/SPARK-583
(which is very very old)
Thanks
Best Regards
Re: Spark runs into an Infinite loop even if the tasks are completed successfully
What I understood from Imran's mail (and what was referenced in his
mail) the RDD mentioned seems to be violating some basic contracts on
how partitions are used in spark [1].
They cannot be arbitrarily numbered,have duplicates, etc.
Extending RDD to add functionality is typically for niche cases; and
requires subclasses to adhere to the explicit (and implicit)
contracts/lifecycles for them.
Using existing RDD's as template would be a good idea for
customizations - one way to look at it is, using RDD is more in api
space but extending them is more in spi space.
Violations would actually not even be detectable by spark-core in general case.
Regards,
Mridul
[1] Ignoring the array out of bounds, etc - I am assuming the intent
is to show overlapping partitions, duplicates. index to partition
mismatch - that sort of thing.
On Thu, Aug 13, 2015 at 11:42 PM, Akhil Das ak...@sigmoidanalytics.com wrote:
Yep, and it works fine for operations which does not involve any shuffle
(like foreach,, count etc) and those which involves shuffle operations ends
up in an infinite loop. Spark should somehow indicate this instead of going
in an infinite loop.
Thanks
Best Regards
On Thu, Aug 13, 2015 at 11:37 PM, Imran Rashid iras...@cloudera.com wrote:
oh I see, you are defining your own RDD Partition types, and you had a
bug where partition.index did not line up with the partitions slot in
rdd.getPartitions. Is that correct?
On Thu, Aug 13, 2015 at 2:40 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
I figured that out, And these are my findings:
- It just enters in an infinite loop when there's a duplicate partition
id.
- It enters in an infinite loop when the partition id starts from 1
rather than 0
Something like this piece of code can reproduce it: (in getPartitions())
val total_partitions = 4
val partitionsArray: Array[Partition] =
Array.ofDim[Partition](total_partitions)
var i = 0
for(outer - 0 to 1){
for(partition - 1 to total_partitions){
partitionsArray(i) = new DeadLockPartitions(partition)
i = i + 1
}
}
partitionsArray
Thanks
Best Regards
On Wed, Aug 12, 2015 at 10:57 PM, Imran Rashid iras...@cloudera.com
wrote:
yikes.
Was this a one-time thing? Or does it happen consistently? can you
turn on debug logging for o.a.s.scheduler (dunno if it will help, but maybe
...)
On Tue, Aug 11, 2015 at 8:59 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Hi
My Spark job (running in local[*] with spark 1.4.1) reads data from a
thrift server(Created an RDD, it will compute the partitions in
getPartitions() call and in computes hasNext will return records from
these
partitions), count(), foreach() is working fine it returns the correct
number of records. But whenever there is shuffleMap stage (like
reduceByKey
etc.) then all the tasks are executing properly but it enters in an
infinite
loop saying :
15/08/11 13:05:54 INFO DAGScheduler: Resubmitting ShuffleMapStage 1
(map at FilterMain.scala:59) because some of its tasks had failed: 0, 3
Here's the complete stack-trace http://pastebin.com/hyK7cG8S
What could be the root cause of this problem? I looked up and bumped
into this closed JIRA (which is very very old)
Thanks
Best Regards
-
To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org
For additional commands, e-mail: dev-h...@spark.apache.org
Re: Spark runs into an Infinite loop even if the tasks are completed successfully
Thanks for the clarifications Mrithul.
Thanks
Best Regards
On Fri, Aug 14, 2015 at 1:04 PM, Mridul Muralidharan mri...@gmail.com
wrote:
What I understood from Imran's mail (and what was referenced in his
mail) the RDD mentioned seems to be violating some basic contracts on
how partitions are used in spark [1].
They cannot be arbitrarily numbered,have duplicates, etc.
Extending RDD to add functionality is typically for niche cases; and
requires subclasses to adhere to the explicit (and implicit)
contracts/lifecycles for them.
Using existing RDD's as template would be a good idea for
customizations - one way to look at it is, using RDD is more in api
space but extending them is more in spi space.
Violations would actually not even be detectable by spark-core in general
case.
Regards,
Mridul
[1] Ignoring the array out of bounds, etc - I am assuming the intent
is to show overlapping partitions, duplicates. index to partition
mismatch - that sort of thing.
On Thu, Aug 13, 2015 at 11:42 PM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Yep, and it works fine for operations which does not involve any shuffle
(like foreach,, count etc) and those which involves shuffle operations
ends
up in an infinite loop. Spark should somehow indicate this instead of
going
in an infinite loop.
Thanks
Best Regards
On Thu, Aug 13, 2015 at 11:37 PM, Imran Rashid iras...@cloudera.com
wrote:
oh I see, you are defining your own RDD Partition types, and you had a
bug where partition.index did not line up with the partitions slot in
rdd.getPartitions. Is that correct?
On Thu, Aug 13, 2015 at 2:40 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
I figured that out, And these are my findings:
- It just enters in an infinite loop when there's a duplicate
partition
id.
- It enters in an infinite loop when the partition id starts from 1
rather than 0
Something like this piece of code can reproduce it: (in
getPartitions())
val total_partitions = 4
val partitionsArray: Array[Partition] =
Array.ofDim[Partition](total_partitions)
var i = 0
for(outer - 0 to 1){
for(partition - 1 to total_partitions){
partitionsArray(i) = new DeadLockPartitions(partition)
i = i + 1
}
}
partitionsArray
Thanks
Best Regards
On Wed, Aug 12, 2015 at 10:57 PM, Imran Rashid iras...@cloudera.com
wrote:
yikes.
Was this a one-time thing? Or does it happen consistently? can you
turn on debug logging for o.a.s.scheduler (dunno if it will help, but
maybe
...)
On Tue, Aug 11, 2015 at 8:59 AM, Akhil Das
ak...@sigmoidanalytics.com
wrote:
Hi
My Spark job (running in local[*] with spark 1.4.1) reads data from a
thrift server(Created an RDD, it will compute the partitions in
getPartitions() call and in computes hasNext will return records
from these
partitions), count(), foreach() is working fine it returns the
correct
number of records. But whenever there is shuffleMap stage (like
reduceByKey
etc.) then all the tasks are executing properly but it enters in an
infinite
loop saying :
15/08/11 13:05:54 INFO DAGScheduler: Resubmitting ShuffleMapStage 1
(map at FilterMain.scala:59) because some of its tasks had failed:
0, 3
Here's the complete stack-trace http://pastebin.com/hyK7cG8S
What could be the root cause of this problem? I looked up and bumped
into this closed JIRA (which is very very old)
Thanks
Best Regards
Re: Spark runs into an Infinite loop even if the tasks are completed successfully
oh I see, you are defining your own RDD Partition types, and you had a
bug where partition.index did not line up with the partitions slot in
rdd.getPartitions. Is that correct?
On Thu, Aug 13, 2015 at 2:40 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
I figured that out, And these are my findings:
- It just enters in an infinite loop when there's a duplicate partition
id.
- It enters in an infinite loop when the partition id starts from 1
rather than 0
Something like this piece of code can reproduce it: (in getPartitions())
val total_partitions = 4
val partitionsArray: Array[Partition] =
Array.ofDim[Partition](total_partitions)
var i = 0
for(outer - 0 to 1){
for(partition - 1 to total_partitions){
partitionsArray(i) = new DeadLockPartitions(partition)
i = i + 1
}
}
partitionsArray
Thanks
Best Regards
On Wed, Aug 12, 2015 at 10:57 PM, Imran Rashid iras...@cloudera.com
wrote:
yikes.
Was this a one-time thing? Or does it happen consistently? can you turn
on debug logging for o.a.s.scheduler (dunno if it will help, but maybe ...)
On Tue, Aug 11, 2015 at 8:59 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Hi
My Spark job (running in local[*] with spark 1.4.1) reads data from a
thrift server(Created an RDD, it will compute the partitions in
getPartitions() call and in computes hasNext will return records from these
partitions), count(), foreach() is working fine it returns the correct
number of records. But whenever there is shuffleMap stage (like reduceByKey
etc.) then all the tasks are executing properly but it enters in an
infinite loop saying :
1. 15/08/11 13:05:54 INFO DAGScheduler: Resubmitting ShuffleMapStage
1 (map at FilterMain.scala:59) because some of its tasks had failed:
0, 3
Here's the complete stack-trace http://pastebin.com/hyK7cG8S
What could be the root cause of this problem? I looked up and bumped
into this closed JIRA https://issues.apache.org/jira/browse/SPARK-583
(which is very very old)
Thanks
Best Regards
Re: Spark runs into an Infinite loop even if the tasks are completed successfully
yikes. Was this a one-time thing? Or does it happen consistently? can you turn on debug logging for o.a.s.scheduler (dunno if it will help, but maybe ...) On Tue, Aug 11, 2015 at 8:59 AM, Akhil Das ak...@sigmoidanalytics.com wrote: Hi My Spark job (running in local[*] with spark 1.4.1) reads data from a thrift server(Created an RDD, it will compute the partitions in getPartitions() call and in computes hasNext will return records from these partitions), count(), foreach() is working fine it returns the correct number of records. But whenever there is shuffleMap stage (like reduceByKey etc.) then all the tasks are executing properly but it enters in an infinite loop saying : 1. 15/08/11 13:05:54 INFO DAGScheduler: Resubmitting ShuffleMapStage 1 (map at FilterMain.scala:59) because some of its tasks had failed: 0, 3 Here's the complete stack-trace http://pastebin.com/hyK7cG8S What could be the root cause of this problem? I looked up and bumped into this closed JIRA https://issues.apache.org/jira/browse/SPARK-583 (which is very very old) Thanks Best Regards
Spark runs into an Infinite loop even if the tasks are completed successfully
Hi My Spark job (running in local[*] with spark 1.4.1) reads data from a thrift server(Created an RDD, it will compute the partitions in getPartitions() call and in computes hasNext will return records from these partitions), count(), foreach() is working fine it returns the correct number of records. But whenever there is shuffleMap stage (like reduceByKey etc.) then all the tasks are executing properly but it enters in an infinite loop saying : 1. 15/08/11 13:05:54 INFO DAGScheduler: Resubmitting ShuffleMapStage 1 (map at FilterMain.scala:59) because some of its tasks had failed: 0, 3 Here's the complete stack-trace http://pastebin.com/hyK7cG8S What could be the root cause of this problem? I looked up and bumped into this closed JIRA https://issues.apache.org/jira/browse/SPARK-583 (which is very very old) Thanks Best Regards
