[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16528379#comment-16528379
]
Dongjoon Hyun commented on SPARK-23309:
---
Thank you for updating, [~tgraves].
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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Thomas Graves commented on SPARK-23309:
---
We tried this on a newest 2.3.1 and haven't been able to reproduce this, so
closing.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16491233#comment-16491233
]
Xiao Li commented on SPARK-23309:
-
[~vanzin] https://issues.apache.org/jira/browse/SPARK-24373 is not related to
this JIRA. This JIRA uses a pure SQL and thus it will not hit the problem
caused by AnalysisBarrier.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16489391#comment-16489391
]
Marcelo Vanzin commented on SPARK-23309:
[~kiszk] SPARK-24373 has some code.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16482476#comment-16482476
]
Truong Duc Kien commented on SPARK-23309:
-
We're also having also a performance problem with cached query on Spark 2.3.
Once in a while, a query will take abnormally long time. We take a look at the
thead-dump and see the executor waiting to fetch remote cached blocks, which
progresses very slowly. It seems to be a run-time bug, because if we run the
same query again, the slow-down might go away.
This did not happen with 2.2.1.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Kazuaki Ishizaki commented on SPARK-23309:
--
When there is a repro, I am happy to investigate the reason.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Sameer Agarwal commented on SPARK-23309:
Thanks, I'll then go ahead and downgrade the priority for now to unblock RC3.
Please feel free to -1 the RC if there's a repro.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Thomas Graves commented on SPARK-23309:
---
sorry I haven't had time to make a query/dataset to reproduce that. I'm ok
with this not being a blocker for 2.3.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Sameer Agarwal commented on SPARK-23309:
[~tgraves] [~smilegator] [~cloud_fan] – any advice here? If we'd like this to
continue to block the release on this, it'd be good to have a repro.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Wenchen Fan commented on SPARK-23309:
-
is it possible to provide a concrete query(with table schema) to demonstrate
the performance regression? By looking at the code I can't find any potential
places that may contribute to this regression. We need to do some profile and
this issue may be caused by something else(e.g. aggregate), not the cache.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Thomas Graves commented on SPARK-23309:
---
I pulled in that patch ([https://github.com/apache/spark/pull/20513]) and
numbers got better but am still seeing 10% slower on 2.3. (this is down from
15%)
This is using the configs: --conf spark.sql.orc.impl=hive --conf
spark.sql.orc.filterPushdown=true --conf
spark.sql.hive.convertMetastoreOrc=false --conf
spark.sql.inMemoryColumnarStorage.enableVectorizedReader=false
has anyone else reproduced this or is it only me seeing it?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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Wenchen Fan commented on SPARK-23309:
-
By looking at the code, the only difference between 2.3 and 2.2 when disabling
the columnar cache reader is whole stage codegen. I've sent
[https://github.com/apache/spark/pull/20513] to totally keep the behavior same
as 2.2 if we disable columnar cache reader.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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Thomas Graves commented on SPARK-23309:
---
I should ask is there a log statement or query plan I can dump out just to make
sure spark.sql.inMemoryColumnarStorage.enableVectorizedReader=false was applied
properly?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16350900#comment-16350900
]
Thomas Graves commented on SPARK-23309:
---
So the last test I did was spark 2.3 with the old hive path and spark 2.2.
Spark 2.3 is slower then spark 2.2 reading the cached data.
[~smilegator] I already tried the patch, see the last config I tested with
where -conf spark.sql.inMemoryColumnarStorage.enableVectorizedReader=false
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16350857#comment-16350857
]
Xiao Li commented on SPARK-23309:
-
Based on my understanding about what [~tgraves]said above, the number of
partitions is different between our ORC reader and Hive-serde reader because we
do not respect Hive confs.
Now the performance regression is observed when we read cached data. This
should not be related to Hive. This
https://issues.apache.org/jira/browse/SPARK-23312 has been merged. Thus, maybe
[~tgraves]can try that patch and see whether the performance regression is gone
after setting {{spark.sql.inMemoryColumnarStorage.enableVectorizedReader}} to
{{false}}?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16350846#comment-16350846
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Dongjoon Hyun commented on SPARK-23309:
---
To sum up, the same Hive code (old Hive path) of Spark 2.3/Spark2.2 is used and
Spark 2.3 is slower than Spark 2.2.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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]
Thomas Graves commented on SPARK-23309:
---
I'm still seeing spark 2.3 slower by about 15% for the larger dataset. I tried
=> --conf spark.sql.orc.impl=hive --conf spark.sql.orc.filterPushdown=true
--conf spark.sql.hive.convertMetastoreOrc=false
and then also tried setting the vectoried reader to false
=> --conf spark.sql.orc.impl=hive --conf spark.sql.orc.filterPushdown=true
--conf spark.sql.hive.convertMetastoreOrc=false --conf
spark.sql.inMemoryColumnarStorage.enableVectorizedReader=false
Note the # of partitions its processing is now the same since turning off the
native orc impl.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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]
Thomas Graves commented on SPARK-23309:
---
Note the schema of "something" here is a "string".
I'll try with the changes in SPARK-23312 and turn off the vectorized cache
reader.
I'm also running 2.3 with the configs --conf spark.sql.orc.impl=hive --conf
spark.sql.orc.filterPushdown=true --conf
spark.sql.hive.convertMetastoreOrc=false which should be the same as 2.2 and it
gives me the same # of partitions
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Dongjoon Hyun commented on SPARK-23309:
---
We are still investigating this, but is this a regression due to SPARK-22392
(data source v2 columnar batch reader)?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Wenchen Fan commented on SPARK-23309:
-
I propose to add a config to turn off vectorized cache reader:
https://issues.apache.org/jira/browse/SPARK-23312
This is a workaround for the performance regression, so that 2.3 doesn't need
to be blocked by this. We should continue investigate the real problem.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Wenchen Fan commented on SPARK-23309:
-
We need to know the schema of your cached data to figure out what's going on
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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Dongjoon Hyun commented on SPARK-23309:
---
Yep. I'll make a PR for migration guide. For the conf
(hive.exec.orc.split.strategy), I think like you. Since I didn't try it before,
I want to make it sure.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Xiao Li commented on SPARK-23309:
-
[~dongjoon] We need to document it in the migration guide. Basically, we ignore
the conf specified by users, right?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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]
Xiao Li commented on SPARK-23309:
-
What is the data type of `something`?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
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Dongjoon Hyun commented on SPARK-23309:
---
Thank you for confirming for the non-cache case, [~tgraves]. For
`hive.exec.orc.split.strategy`, I'll check and reply on SPARK-23304.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16349576#comment-16349576
]
Xiao Li commented on SPARK-23309:
-
Just to confirm it. The cached data only has one column whose type is bigint.
How many rows do you have? Could you just try some simpler queries? {{SELECT
COUNT(something) from dailycached}}
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16349553#comment-16349553
]
Thomas Graves commented on SPARK-23309:
---
[~dongjoon] is there any native way with the native hive to control the # of
partitions? (like hive.exec.orc.split.strategy). Or do you have to do the
coalesce?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16349551#comment-16349551
]
Thomas Graves commented on SPARK-23309:
---
seeing the same time difference after adding in the
spark.table("dailyCached").count()
[~dongjoon] Correct this is only when read from cached data. Without caching
spark 2.3 is quite a bit faster (1.5-2x+) then spark 2.2 when reading from hive
using orc. (which is awesome, thanks for all the work!)
I'm running now with --conf spark.sql.orc.impl=hive --conf
spark.sql.hive.convertMetastoreOrc=false. For the smaller data set it did get
closer, only 1 second diff on average between spark 2.2 and spark 2.3. Trying
to run on the larger dataset now. I'm wondering if much of the difference is
the larger # of partitions you get with hive native in spark 2.3
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16349532#comment-16349532
]
Dongjoon Hyun commented on SPARK-23309:
---
According to the issue title, there is no regression without caching, isn't it?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16349516#comment-16349516
]
Xiao Li commented on SPARK-23309:
-
[~tgraves] We are just hoping the new Hive reader does not introduce a
regression. Otherwise, we might need to change the default value of ORC reader
to hive.
I expect the cache reader should be faster after the PR
https://github.com/apache/spark/pull/18747. If not, we might need to change the
codes for avoiding the performance regression.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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]
Dongjoon Hyun commented on SPARK-23309:
---
Thank you for reporting this, [~tgraves].
In addition to `spark.sql.orc.impl=hive`, could you try this with Parquet file
format, too?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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Thomas Graves commented on SPARK-23309:
---
sure, I can also run with the --conf spark.sql.orc.impl=hive --conf
spark.sql.orc.filterPushdown=false --conf
spark.sql.hive.convertMetastoreOrc=false configs to make sure it doesn't just
have to do with # of partitions
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Blocker
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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]
Xiao Li commented on SPARK-23309:
-
[~tgraves] Could you first run count before you run the show?
{noformat}
val dailycached = spark.sql("select something from table where dt = '20170301'
AND something IS NOT NULL")
dailycached.createOrReplaceTempView("dailycached")
spark.catalog.cacheTable("dailyCached")
spark.table("dailyCached").count()
spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
{noformat}
You know our cache is lazy. We run the query when first reading from the cache.
Just want to see whether this regression is from cache or from query reading.
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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[jira] [Commented] (SPARK-23309) Spark 2.3 cached query performance 20-30% worse then spark 2.2
[
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]
Thomas Graves commented on SPARK-23309:
---
I'm curious if anyone else is seeing the same behavior?
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
> --
>
> Key: SPARK-23309
> URL: https://issues.apache.org/jira/browse/SPARK-23309
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.3.0
>Reporter: Thomas Graves
>Priority: Major
>
> I was testing spark 2.3 rc2 and I am seeing a performance regression in sql
> queries on cached data.
> The size of the data: 10.4GB input from hive orc files /18.8 GB cached/5592
> partitions
> Here is the example query:
> val dailycached = spark.sql("select something from table where dt =
> '20170301' AND something IS NOT NULL")
> dailycached.createOrReplaceTempView("dailycached")
> spark.catalog.cacheTable("dailyCached")
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
>
> On spark 2.2 I see queries times average 13 seconds
> On the same nodes I see spark 2.3 queries times average 17 seconds
> Note these are times of queries after the initial caching. so just running
> the last line again:
> spark.sql("SELECT COUNT(DISTINCT(something)) from dailycached").show()
> multiple times.
>
> I also ran a query over more data (335GB input/587.5 GB cached) and saw a
> similar discrepancy in the performance of querying cached data between spark
> 2.3 and spark 2.2, where 2.2 was better by like 20%.
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