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Posted to user@spark.apache.org by "Rao, Abhishek (Nokia - IN/Bangalore)" <ab...@nokia.com> on 2020/08/24 11:50:27 UTC
Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi All,
We're doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I'm attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We're not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we're missing?
Thanks and Regards,
Abhishek
RE: Spark 3.0 using S3 taking long time for some set of TPC DS
Queries
Posted by "Rao, Abhishek (Nokia - IN/Bangalore)" <ab...@nokia.com>.
Hi Luca,
Thanks for sharing the feedback. We'll include these recommendations in our tests. However, we feel the issue that we're seeing right now is due to the difference in size of data downloaded from storage by the executors. In case of S3, executors are downloading almost 50 GB of data whereas in case of HDFS, it is only 4.5 GB.
Any idea why this difference is there?
Thanks and Regards,
Abhishek
From: Luca Canali <Lu...@cern.ch>
Sent: Monday, August 24, 2020 7:18 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
Cc: user@spark.apache.org
Subject: RE: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi Abhishek,
Just a few ideas/comments on the topic:
When benchmarking/testing I find it useful to collect a more complete view of resources usage and Spark metrics, beyond just measuring query elapsed time. Something like this:
https://github.com/cerndb/spark-dashboard
I'd rather not use dynamic allocation when benchmarking if possible, as it adds a layer of complexity when examining results.
If you suspect that reading from S3 vs. HDFS may play an important role on the performance you observe, you may want to drill down on that with a simple micro-benchmark, for example something like this (for Spark 3.0):
val df=spark.read.parquet("/TPCDS/tpcds_1500/store_sales")
df.write.format("noop").mode("overwrite").save
Best,
Luca
From: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>>
Sent: Monday, August 24, 2020 13:50
To: user@spark.apache.org<ma...@spark.apache.org>
Subject: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi All,
We're doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I'm attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We're not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we're missing?
Thanks and Regards,
Abhishek
RE: Spark 3.0 using S3 taking long time for some set of TPC DS
Queries
Posted by Luca Canali <Lu...@cern.ch>.
Hi Abhishek,
Just a few ideas/comments on the topic:
When benchmarking/testing I find it useful to collect a more complete view of resources usage and Spark metrics, beyond just measuring query elapsed time. Something like this:
https://github.com/cerndb/spark-dashboard
I'd rather not use dynamic allocation when benchmarking if possible, as it adds a layer of complexity when examining results.
If you suspect that reading from S3 vs. HDFS may play an important role on the performance you observe, you may want to drill down on that with a simple micro-benchmark, for example something like this (for Spark 3.0):
val df=spark.read.parquet("/TPCDS/tpcds_1500/store_sales")
df.write.format("noop").mode("overwrite").save
Best,
Luca
From: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
Sent: Monday, August 24, 2020 13:50
To: user@spark.apache.org
Subject: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi All,
We're doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I'm attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We're not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we're missing?
Thanks and Regards,
Abhishek
RE: Spark 3.0 using S3 taking long time for some set of TPC DS
Queries
Posted by "Rao, Abhishek (Nokia - IN/Bangalore)" <ab...@nokia.com>.
Hi All,
We tried to regenerate the TPC DS data on S3 and after regeneration, we see that the queries are running faster and the execution time is now comparable with execution time on HDFS with Spark 3.0.0.
So may be there was some issue in generating the TPC DS data first time due to which we were seeing discrepancy in query execution time on S3 with Spark 3.0.0.
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>
Sent: Wednesday, August 26, 2020 5:49 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
Cc: user <us...@spark.apache.org>
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi
Can you try using emrfs?
Your study looks good best of luck.
Regards
Gourav
On Wed, 26 Aug 2020, 12:37 Rao, Abhishek (Nokia - IN/Bangalore), <ab...@nokia.com>> wrote:
Yeah… Not sure if I’m missing any configurations which is causing this issue. Any suggestions?
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>>
Sent: Wednesday, August 26, 2020 2:35 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>>
Cc: user@spark.apache.org<ma...@spark.apache.org>
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi,
So the results does not make sense.
Regards,
Gourav
On Wed, Aug 26, 2020 at 9:04 AM Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>> wrote:
Hi Gourav,
Yes. We’re using s3a.
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>>
Sent: Wednesday, August 26, 2020 1:18 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>>
Cc: user@spark.apache.org<ma...@spark.apache.org>
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi,
are you using s3a, which is not using EMRFS? In that case, these results does not make sense to me.
Regards,
Gourav Sengupta
On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>> wrote:
Hi All,
We’re doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I’m attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we’re missing?
Thanks and Regards,
Abhishek
---------------------------------------------------------------------
To unsubscribe e-mail: user-unsubscribe@spark.apache.org<ma...@spark.apache.org>
Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Posted by Gourav Sengupta <go...@gmail.com>.
Hi
Can you try using emrfs?
Your study looks good best of luck.
Regards
Gourav
On Wed, 26 Aug 2020, 12:37 Rao, Abhishek (Nokia - IN/Bangalore), <
abhishek.rao@nokia.com> wrote:
> Yeah… Not sure if I’m missing any configurations which is causing this
> issue. Any suggestions?
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
> *From:* Gourav Sengupta <go...@gmail.com>
> *Sent:* Wednesday, August 26, 2020 2:35 PM
> *To:* Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
> *Cc:* user@spark.apache.org
> *Subject:* Re: Spark 3.0 using S3 taking long time for some set of TPC DS
> Queries
>
>
>
> Hi,
>
>
>
> So the results does not make sense.
>
>
>
>
>
> Regards,
>
> Gourav
>
>
>
> On Wed, Aug 26, 2020 at 9:04 AM Rao, Abhishek (Nokia - IN/Bangalore) <
> abhishek.rao@nokia.com> wrote:
>
> Hi Gourav,
>
>
>
> Yes. We’re using s3a.
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
> *From:* Gourav Sengupta <go...@gmail.com>
> *Sent:* Wednesday, August 26, 2020 1:18 PM
> *To:* Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
> *Cc:* user@spark.apache.org
> *Subject:* Re: Spark 3.0 using S3 taking long time for some set of TPC DS
> Queries
>
>
>
> Hi,
>
>
>
> are you using s3a, which is not using EMRFS? In that case, these results
> does not make sense to me.
>
>
>
> Regards,
>
> Gourav Sengupta
>
>
>
> On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <
> abhishek.rao@nokia.com> wrote:
>
> Hi All,
>
>
>
> We’re doing some performance comparisons between Spark querying data on
> HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage)
> using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is
> consuming significantly larger duration for some set of queries when
> compared with HDFS.
>
> We also ran similar queries with Spark 2.4.5 querying data from S3 and we
> see that for these set of queries, time taken by Spark 2.4.5 is lesser
> compared to Spark 3.0 looks to be very strange.
>
> Below are the details of 9 queries where Spark 3.0 is taking >5 times the
> duration for running queries on S3 when compared to Hadoop.
>
>
>
> *Environment Details:*
>
> - *Spark running on Kubernetes*
> - *TPC DS Scale Factor*: *500 GB*
> - *Hadoop 3.x*
> - *Same CPU and memory used for all executions*
>
>
>
> *Query*
>
> *Spark 3.0 with S3 (Time in seconds)*
>
> *Spark 3.0 with Hadoop (Time in seconds)*
>
>
>
>
>
> *Spark 2.4.5 with S3 *
>
> *(Time in seconds)*
>
> *Spark 3.0 HDFS vs S3 (Factor)*
>
> *Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)*
>
> *Table involved*
>
> 9
>
> 880.129
>
> 106.109
>
> 147.65
>
> *8.294574*
>
> *5.960914*
>
> store_sales
>
> 44
>
> 129.618
>
> 23.747
>
> 103.916
>
> *5.458289*
>
> *1.247334*
>
> store_sales
>
> 58
>
> 142.113
>
> 20.996
>
> 33.936
>
> *6.768575*
>
> *4.187677*
>
> store_sales
>
> 62
>
> 32.519
>
> 5.425
>
> 14.809
>
> *5.994286*
>
> *2.195894*
>
> web_sales
>
> 76
>
> 138.765
>
> 20.73
>
> 49.892
>
> *6.693922*
>
> *2.781308*
>
> store_sales
>
> 88
>
> 475.824
>
> 48.2
>
> 94.382
>
> *9.871867*
>
> *5.04147*
>
> store_sales
>
> 90
>
> 53.896
>
> 6.804
>
> 18.11
>
> *7.921223*
>
> *2.976035*
>
> web_sales
>
> 94
>
> 241.172
>
> 43.49
>
> 81.181
>
> *5.545459*
>
> *2.970794*
>
> web_sales
>
> 96
>
> 67.059
>
> 10.396
>
> 15.993
>
> *6.450462*
>
> *4.193022*
>
> store_sales
>
>
>
> When we analysed it further, we see that all these queries are performing
> operations either on store_sales or web_sales tables and Spark 3 with S3
> seems to be downloading much more data from storage when compared to Spark
> 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for
> query completion. I’m attaching the screen shots of Driver UI for one such
> instance (Query 9) for reference.
>
> Also attached the spark configurations (Spark 3.0) used for these tests.
>
>
>
> We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on
> what we’re missing?
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: user-unsubscribe@spark.apache.org
>
>
RE: Spark 3.0 using S3 taking long time for some set of TPC DS
Queries
Posted by "Rao, Abhishek (Nokia - IN/Bangalore)" <ab...@nokia.com>.
Yeah… Not sure if I’m missing any configurations which is causing this issue. Any suggestions?
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>
Sent: Wednesday, August 26, 2020 2:35 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
Cc: user@spark.apache.org
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi,
So the results does not make sense.
Regards,
Gourav
On Wed, Aug 26, 2020 at 9:04 AM Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>> wrote:
Hi Gourav,
Yes. We’re using s3a.
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>>
Sent: Wednesday, August 26, 2020 1:18 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>>
Cc: user@spark.apache.org<ma...@spark.apache.org>
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi,
are you using s3a, which is not using EMRFS? In that case, these results does not make sense to me.
Regards,
Gourav Sengupta
On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>> wrote:
Hi All,
We’re doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I’m attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we’re missing?
Thanks and Regards,
Abhishek
---------------------------------------------------------------------
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Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Posted by Gourav Sengupta <go...@gmail.com>.
Hi,
So the results does not make sense.
Regards,
Gourav
On Wed, Aug 26, 2020 at 9:04 AM Rao, Abhishek (Nokia - IN/Bangalore) <
abhishek.rao@nokia.com> wrote:
> Hi Gourav,
>
>
>
> Yes. We’re using s3a.
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
> *From:* Gourav Sengupta <go...@gmail.com>
> *Sent:* Wednesday, August 26, 2020 1:18 PM
> *To:* Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
> *Cc:* user@spark.apache.org
> *Subject:* Re: Spark 3.0 using S3 taking long time for some set of TPC DS
> Queries
>
>
>
> Hi,
>
>
>
> are you using s3a, which is not using EMRFS? In that case, these results
> does not make sense to me.
>
>
>
> Regards,
>
> Gourav Sengupta
>
>
>
> On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <
> abhishek.rao@nokia.com> wrote:
>
> Hi All,
>
>
>
> We’re doing some performance comparisons between Spark querying data on
> HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage)
> using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is
> consuming significantly larger duration for some set of queries when
> compared with HDFS.
>
> We also ran similar queries with Spark 2.4.5 querying data from S3 and we
> see that for these set of queries, time taken by Spark 2.4.5 is lesser
> compared to Spark 3.0 looks to be very strange.
>
> Below are the details of 9 queries where Spark 3.0 is taking >5 times the
> duration for running queries on S3 when compared to Hadoop.
>
>
>
> *Environment Details:*
>
> - *Spark running on Kubernetes*
> - *TPC DS Scale Factor*: *500 GB*
> - *Hadoop 3.x*
> - *Same CPU and memory used for all executions*
>
>
>
> *Query*
>
> *Spark 3.0 with S3 (Time in seconds)*
>
> *Spark 3.0 with Hadoop (Time in seconds)*
>
>
>
>
>
> *Spark 2.4.5 with S3 *
>
> *(Time in seconds)*
>
> *Spark 3.0 HDFS vs S3 (Factor)*
>
> *Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)*
>
> *Table involved*
>
> 9
>
> 880.129
>
> 106.109
>
> 147.65
>
> *8.294574*
>
> *5.960914*
>
> store_sales
>
> 44
>
> 129.618
>
> 23.747
>
> 103.916
>
> *5.458289*
>
> *1.247334*
>
> store_sales
>
> 58
>
> 142.113
>
> 20.996
>
> 33.936
>
> *6.768575*
>
> *4.187677*
>
> store_sales
>
> 62
>
> 32.519
>
> 5.425
>
> 14.809
>
> *5.994286*
>
> *2.195894*
>
> web_sales
>
> 76
>
> 138.765
>
> 20.73
>
> 49.892
>
> *6.693922*
>
> *2.781308*
>
> store_sales
>
> 88
>
> 475.824
>
> 48.2
>
> 94.382
>
> *9.871867*
>
> *5.04147*
>
> store_sales
>
> 90
>
> 53.896
>
> 6.804
>
> 18.11
>
> *7.921223*
>
> *2.976035*
>
> web_sales
>
> 94
>
> 241.172
>
> 43.49
>
> 81.181
>
> *5.545459*
>
> *2.970794*
>
> web_sales
>
> 96
>
> 67.059
>
> 10.396
>
> 15.993
>
> *6.450462*
>
> *4.193022*
>
> store_sales
>
>
>
> When we analysed it further, we see that all these queries are performing
> operations either on store_sales or web_sales tables and Spark 3 with S3
> seems to be downloading much more data from storage when compared to Spark
> 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for
> query completion. I’m attaching the screen shots of Driver UI for one such
> instance (Query 9) for reference.
>
> Also attached the spark configurations (Spark 3.0) used for these tests.
>
>
>
> We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on
> what we’re missing?
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: user-unsubscribe@spark.apache.org
>
>
RE: Spark 3.0 using S3 taking long time for some set of TPC DS
Queries
Posted by "Rao, Abhishek (Nokia - IN/Bangalore)" <ab...@nokia.com>.
Hi Gourav,
Yes. We’re using s3a.
Thanks and Regards,
Abhishek
From: Gourav Sengupta <go...@gmail.com>
Sent: Wednesday, August 26, 2020 1:18 PM
To: Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>
Cc: user@spark.apache.org
Subject: Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Hi,
are you using s3a, which is not using EMRFS? In that case, these results does not make sense to me.
Regards,
Gourav Sengupta
On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <ab...@nokia.com>> wrote:
Hi All,
We’re doing some performance comparisons between Spark querying data on HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage) using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is consuming significantly larger duration for some set of queries when compared with HDFS.
We also ran similar queries with Spark 2.4.5 querying data from S3 and we see that for these set of queries, time taken by Spark 2.4.5 is lesser compared to Spark 3.0 looks to be very strange.
Below are the details of 9 queries where Spark 3.0 is taking >5 times the duration for running queries on S3 when compared to Hadoop.
Environment Details:
* Spark running on Kubernetes
* TPC DS Scale Factor: 500 GB
* Hadoop 3.x
* Same CPU and memory used for all executions
Query
Spark 3.0 with S3 (Time in seconds)
Spark 3.0 with Hadoop (Time in seconds)
Spark 2.4.5 with S3
(Time in seconds)
Spark 3.0 HDFS vs S3 (Factor)
Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)
Table involved
9
880.129
106.109
147.65
8.294574
5.960914
store_sales
44
129.618
23.747
103.916
5.458289
1.247334
store_sales
58
142.113
20.996
33.936
6.768575
4.187677
store_sales
62
32.519
5.425
14.809
5.994286
2.195894
web_sales
76
138.765
20.73
49.892
6.693922
2.781308
store_sales
88
475.824
48.2
94.382
9.871867
5.04147
store_sales
90
53.896
6.804
18.11
7.921223
2.976035
web_sales
94
241.172
43.49
81.181
5.545459
2.970794
web_sales
96
67.059
10.396
15.993
6.450462
4.193022
store_sales
When we analysed it further, we see that all these queries are performing operations either on store_sales or web_sales tables and Spark 3 with S3 seems to be downloading much more data from storage when compared to Spark 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for query completion. I’m attaching the screen shots of Driver UI for one such instance (Query 9) for reference.
Also attached the spark configurations (Spark 3.0) used for these tests.
We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on what we’re missing?
Thanks and Regards,
Abhishek
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To unsubscribe e-mail: user-unsubscribe@spark.apache.org<ma...@spark.apache.org>
Re: Spark 3.0 using S3 taking long time for some set of TPC DS Queries
Posted by Gourav Sengupta <go...@gmail.com>.
Hi,
are you using s3a, which is not using EMRFS? In that case, these results
does not make sense to me.
Regards,
Gourav Sengupta
On Mon, Aug 24, 2020 at 12:52 PM Rao, Abhishek (Nokia - IN/Bangalore) <
abhishek.rao@nokia.com> wrote:
> Hi All,
>
>
>
> We’re doing some performance comparisons between Spark querying data on
> HDFS vs Spark querying data on S3 (Ceph Object Store used for S3 storage)
> using standard TPC DS Queries. We are observing that Spark 3.0 with S3 is
> consuming significantly larger duration for some set of queries when
> compared with HDFS.
>
> We also ran similar queries with Spark 2.4.5 querying data from S3 and we
> see that for these set of queries, time taken by Spark 2.4.5 is lesser
> compared to Spark 3.0 looks to be very strange.
>
> Below are the details of 9 queries where Spark 3.0 is taking >5 times the
> duration for running queries on S3 when compared to Hadoop.
>
>
>
> *Environment Details:*
>
> - *Spark running on Kubernetes*
> - *TPC DS Scale Factor*: *500 GB*
> - *Hadoop 3.x*
> - *Same CPU and memory used for all executions*
>
>
>
> *Query*
>
> *Spark 3.0 with S3 (Time in seconds)*
>
> *Spark 3.0 with Hadoop (Time in seconds)*
>
>
>
>
>
> *Spark 2.4.5 with S3 *
>
> *(Time in seconds)*
>
> *Spark 3.0 HDFS vs S3 (Factor)*
>
> *Spark 2.4.5 S3 vs Spark 3.0 S3 (Factor)*
>
> *Table involved*
>
> 9
>
> 880.129
>
> 106.109
>
> 147.65
>
> *8.294574*
>
> *5.960914*
>
> store_sales
>
> 44
>
> 129.618
>
> 23.747
>
> 103.916
>
> *5.458289*
>
> *1.247334*
>
> store_sales
>
> 58
>
> 142.113
>
> 20.996
>
> 33.936
>
> *6.768575*
>
> *4.187677*
>
> store_sales
>
> 62
>
> 32.519
>
> 5.425
>
> 14.809
>
> *5.994286*
>
> *2.195894*
>
> web_sales
>
> 76
>
> 138.765
>
> 20.73
>
> 49.892
>
> *6.693922*
>
> *2.781308*
>
> store_sales
>
> 88
>
> 475.824
>
> 48.2
>
> 94.382
>
> *9.871867*
>
> *5.04147*
>
> store_sales
>
> 90
>
> 53.896
>
> 6.804
>
> 18.11
>
> *7.921223*
>
> *2.976035*
>
> web_sales
>
> 94
>
> 241.172
>
> 43.49
>
> 81.181
>
> *5.545459*
>
> *2.970794*
>
> web_sales
>
> 96
>
> 67.059
>
> 10.396
>
> 15.993
>
> *6.450462*
>
> *4.193022*
>
> store_sales
>
>
>
> When we analysed it further, we see that all these queries are performing
> operations either on store_sales or web_sales tables and Spark 3 with S3
> seems to be downloading much more data from storage when compared to Spark
> 3 with Hadoop or Spark 2.4.5 with S3 and this is resulting in more time for
> query completion. I’m attaching the screen shots of Driver UI for one such
> instance (Query 9) for reference.
>
> Also attached the spark configurations (Spark 3.0) used for these tests.
>
>
>
> We’re not sure why Spark 3.0 on S3 is having this behaviour. Any inputs on
> what we’re missing?
>
>
>
> Thanks and Regards,
>
> Abhishek
>
>
>
> ---------------------------------------------------------------------
> To unsubscribe e-mail: user-unsubscribe@spark.apache.org