computation slows down 10x because of cached RDDs

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computation slows down 10x because of cached RDDs

Koert Kuipers
hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?
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Re: computation slows down 10x because of cached RDDs

Matei Zaharia
Administrator
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?

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Re: computation slows down 10x because of cached RDDs

Koert Kuipers
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?


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Re: computation slows down 10x because of cached RDDs

Koert Kuipers
hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?



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Re: computation slows down 10x because of cached RDDs

Matei Zaharia
Administrator
Right, that’s it. I think what happened is the following: all the nodes generated some garbage that put them very close to the threshold for a full GC in the first few runs of the program (when you cached the RDDs), but on the subsequent queries, only a few nodes are hitting full GC per query, so every query sees a slowdown but the problem persists for a whille. You can try manually forcing a GC on the nodes like this after you do your loading:

sc.parallelize(1 to numNodes, numNodes).foreach(x => System.gc())

Where numNodes is your number of nodes. (Actually it’s also okay to just make this higher, System.gc() returns fast when there’s no GC to run.)

Matei

On Mar 11, 2014, at 7:12 AM, Koert Kuipers <[hidden email]> wrote:

hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?




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Re: computation slows down 10x because of cached RDDs

Andrew Ash
Note that calling System.gc() is just a suggestion to the JVM that it should run a garbage collection and doesn't force it right then 100% of the time.



On Tue, Mar 11, 2014 at 12:17 PM, Matei Zaharia <[hidden email]> wrote:
Right, that’s it. I think what happened is the following: all the nodes generated some garbage that put them very close to the threshold for a full GC in the first few runs of the program (when you cached the RDDs), but on the subsequent queries, only a few nodes are hitting full GC per query, so every query sees a slowdown but the problem persists for a whille. You can try manually forcing a GC on the nodes like this after you do your loading:

sc.parallelize(1 to numNodes, numNodes).foreach(x => System.gc())

Where numNodes is your number of nodes. (Actually it’s also okay to just make this higher, System.gc() returns fast when there’s no GC to run.)

Matei

On Mar 11, 2014, at 7:12 AM, Koert Kuipers <[hidden email]> wrote:

hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?





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Re: computation slows down 10x because of cached RDDs

Koert Kuipers
In reply to this post by Matei Zaharia
hey matei,
ha i will definitely that one! looks like a total hack... i might just schedule it after the precaching of rdds defensively.

also trying java 7 with g1


On Tue, Mar 11, 2014 at 3:17 PM, Matei Zaharia <[hidden email]> wrote:
Right, that’s it. I think what happened is the following: all the nodes generated some garbage that put them very close to the threshold for a full GC in the first few runs of the program (when you cached the RDDs), but on the subsequent queries, only a few nodes are hitting full GC per query, so every query sees a slowdown but the problem persists for a whille. You can try manually forcing a GC on the nodes like this after you do your loading:

sc.parallelize(1 to numNodes, numNodes).foreach(x => System.gc())

Where numNodes is your number of nodes. (Actually it’s also okay to just make this higher, System.gc() returns fast when there’s no GC to run.)

Matei

On Mar 11, 2014, at 7:12 AM, Koert Kuipers <[hidden email]> wrote:

hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?





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Re: computation slows down 10x because of cached RDDs

Matei Zaharia
Administrator
Yeah, System.gc() is a suggestion but in practice it does invoke full GCs on the Sun JVM.

Matei

On Mar 11, 2014, at 12:35 PM, Koert Kuipers <[hidden email]> wrote:

hey matei,
ha i will definitely that one! looks like a total hack... i might just schedule it after the precaching of rdds defensively.

also trying java 7 with g1


On Tue, Mar 11, 2014 at 3:17 PM, Matei Zaharia <[hidden email]> wrote:
Right, that’s it. I think what happened is the following: all the nodes generated some garbage that put them very close to the threshold for a full GC in the first few runs of the program (when you cached the RDDs), but on the subsequent queries, only a few nodes are hitting full GC per query, so every query sees a slowdown but the problem persists for a whille. You can try manually forcing a GC on the nodes like this after you do your loading:

sc.parallelize(1 to numNodes, numNodes).foreach(x => System.gc())

Where numNodes is your number of nodes. (Actually it’s also okay to just make this higher, System.gc() returns fast when there’s no GC to run.)

Matei

On Mar 11, 2014, at 7:12 AM, Koert Kuipers <[hidden email]> wrote:

hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?






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Re: computation slows down 10x because of cached RDDs

Koert Kuipers
hey matei,
ok when i switch to java 7 with G1 the GC time for all the "quick" tasks goes from 150ms to 10ms, but the slow ones stay just as slow. all i did was add -XX:+UseG1GC so maybe thats wrong, i still have to read up on G1.

an example of GC in a slow task is below.
best, koert


[GC pause (young), 0.0100070 secs]
   [Parallel Time: 7.3 ms, GC Workers: 18]
      [GC Worker Start (ms): Min: 2889329.4, Avg: 2889329.8, Max: 2889330.0, Diff: 0.6]
      [Ext Root Scanning (ms): Min: 2.0, Avg: 2.5, Max: 3.2, Diff: 1.2, Sum: 44.2]
      [Update RS (ms): Min: 0.0, Avg: 0.3, Max: 3.5, Diff: 3.5, Sum: 5.8]
         [Processed Buffers: Min: 0, Avg: 3.3, Max: 14, Diff: 14, Sum: 59]
      [Scan RS (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.1]
      [Object Copy (ms): Min: 0.2, Avg: 0.7, Max: 1.0, Diff: 0.8, Sum: 12.0]
      [Termination (ms): Min: 0.0, Avg: 2.4, Max: 2.6, Diff: 2.6, Sum: 43.8]
      [GC Worker Other (ms): Min: 0.0, Avg: 0.0, Max: 0.1, Diff: 0.0, Sum: 0.5]
      [GC Worker Total (ms): Min: 5.7, Avg: 5.9, Max: 6.3, Diff: 0.6, Sum: 106.4]
      [GC Worker End (ms): Min: 2889335.7, Avg: 2889335.7, Max: 2889335.7, Diff: 0.0]
   [Code Root Fixup: 0.0 ms]
   [Clear CT: 1.1 ms]
   [Other: 1.6 ms]
      [Choose CSet: 0.0 ms]
      [Ref Proc: 1.0 ms]
      [Ref Enq: 0.0 ms]
      [Free CSet: 0.3 ms]
   [Eden: 20.0M(752.0M)->0.0B(304.0M) Survivors: 2048.0K->2048.0K Heap: 5917.7M(6144.0M)->5898.8M(6144.0M)]
 [Times: user=0.12 sys=0.00, real=0.01 secs]
[Full GC 5898M->2057M(6144M), 5.7978580 secs]
   [Eden: 2048.0K(304.0M)->0.0B(1064.0M) Survivors: 2048.0K->0.0B Heap: 5898.9M(6144.0M)->2057.5M(6144.0M)]
 [Times: user=9.24 sys=0.00, real=5.80 secs]



On Tue, Mar 11, 2014 at 4:35 PM, Matei Zaharia <[hidden email]> wrote:
Yeah, System.gc() is a suggestion but in practice it does invoke full GCs on the Sun JVM.

Matei

On Mar 11, 2014, at 12:35 PM, Koert Kuipers <[hidden email]> wrote:

hey matei,
ha i will definitely that one! looks like a total hack... i might just schedule it after the precaching of rdds defensively.

also trying java 7 with g1


On Tue, Mar 11, 2014 at 3:17 PM, Matei Zaharia <[hidden email]> wrote:
Right, that’s it. I think what happened is the following: all the nodes generated some garbage that put them very close to the threshold for a full GC in the first few runs of the program (when you cached the RDDs), but on the subsequent queries, only a few nodes are hitting full GC per query, so every query sees a slowdown but the problem persists for a whille. You can try manually forcing a GC on the nodes like this after you do your loading:

sc.parallelize(1 to numNodes, numNodes).foreach(x => System.gc())

Where numNodes is your number of nodes. (Actually it’s also okay to just make this higher, System.gc() returns fast when there’s no GC to run.)

Matei

On Mar 11, 2014, at 7:12 AM, Koert Kuipers <[hidden email]> wrote:

hey matei,
most tasks have GC times of 200ms or less, and then a few tasks take many seconds. example GC activity for a slow one:

[GC [PSYoungGen: 1051814K->262624K(1398144K)] 3789259K->3524429K(5592448K), 0.0986800 secs] [Times: user=1.53 sys=0.01, real=0.10 secs]
[GC [PSYoungGen: 786935K->524512K(1398144K)] 4048741K->4048762K(5592448K), 0.1132490 secs] [Times: user=1.70 sys=0.01, real=0.11 secs]
[Full GC [PSYoungGen: 524512K->0K(1398144K)] [PSOldGen: 3524250K->2207344K(4194304K)] 4048762K->2207344K(5592448K) [PSPermGen: 56545K->54639K(83968K)], 7.7059350 secs] [Times:\
 user=7.71 sys=0.00, real=7.70 secs]


so looks like i am hit by stop-the-world gc?


On Mon, Mar 10, 2014 at 7:00 PM, Koert Kuipers <[hidden email]> wrote:
hey matei,
it happens repeatedly.

we are currently runnning on java 6 with spark 0.9.

i will add -XX:+PrintGCDetails and collect details, and also look into java 7 G1. thanks






On Mon, Mar 10, 2014 at 6:27 PM, Matei Zaharia <[hidden email]> wrote:
Does this happen repeatedly if you keep running the computation, or just the first time? It may take time to move these Java objects to the old generation the first time you run queries, which could lead to a GC pause that also slows down the small queries.

If you can run with -XX:+PrintGCDetails in your Java options, it would also be good to see what percent of each GC generation is used.

The concurrent mark-and-sweep GC -XX:+UseConcMarkSweepGC or the G1 GC in Java 7 (-XX:+UseG1GC) might also avoid these pauses by GCing concurrently with your application threads.

Matei

On Mar 10, 2014, at 3:18 PM, Koert Kuipers <[hidden email]> wrote:

hello all,
i am observing a strange result. i have a computation that i run on a cached RDD in spark-standalone. it typically takes about 4 seconds.

but when other RDDs that are not relevant to the computation at hand are cached in memory (in same spark context), the computation takes 40 seconds or more.

the problem seems to be GC time, which goes from milliseconds to tens of seconds.

note that my issue is not that memory is full. i have cached about 14G in RDDs with 66G available across workers for the application. also my computation did not push any cached RDD out of memory.

any ideas?