[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon updated SPARK-34115:
-
Fix Version/s: (was: 3.1.2)
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core, SQL
>Affects Versions: 2.4.0, 2.4.7, 3.0.1
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Assignee: Norbert Schultz
>Priority: Major
> Fix For: 3.0.2, 3.1.1
>
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon updated SPARK-34115:
-
Fix Version/s: 3.1.1
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core, SQL
>Affects Versions: 2.4.0, 2.4.7, 3.0.1
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Assignee: Norbert Schultz
>Priority: Major
> Fix For: 3.0.2, 3.1.1, 3.1.2
>
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dongjoon Hyun updated SPARK-34115:
--
Parent: SPARK-33005
Issue Type: Sub-task (was: Bug)
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core, SQL
>Affects Versions: 2.4.0, 2.4.7, 3.0.1
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Assignee: Norbert Schultz
>Priority: Major
> Fix For: 3.0.2, 3.1.2
>
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Affects Version/s: 3.0.1
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
>Affects Versions: 2.4.0, 2.4.7, 3.0.1
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Component/s: SQL
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
>Affects Versions: 2.4.0, 2.4.7
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
--
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Affects Version/s: 2.4.7
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.4.0, 2.4.7
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
--
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Attachment: spark-bug-34115.tar.gz
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.4.0
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
> Attachments: spark-bug-34115.tar.gz
>
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
--
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Description:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the integration tests
on our build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
{code:java}
sys.env.contains("SPARK_TESTING") {code}
to not make it that expensive.
was:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the unit tests on our
build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
{code:java}
sys.env.contains("SPARK_TESTING") {code}
to not make it that expensive.
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.4.0
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the integration
> tests on our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
--
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Description:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the unit tests on our
build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
```
sys.env.contains("SPARK_TESTING")
```
to not make it that expensive.
was:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the unit tests on our
build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
"sys.env.contains("SPARK_TESTING")" to not make it that expensive.
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.4.0
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the unit tests on
> our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
> ```
> sys.env.contains("SPARK_TESTING")
> ```
> to not make it that expensive.
--
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[jira] [Updated] (SPARK-34115) Long runtime on many environment variables
[
https://issues.apache.org/jira/browse/SPARK-34115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Norbert Schultz updated SPARK-34115:
Description:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the unit tests on our
build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
{code:java}
sys.env.contains("SPARK_TESTING") {code}
to not make it that expensive.
was:
I am not sure if this is a bug report or a feature request. The code is is the
same in current versions of Spark and maybe this ticket saves someone some time
for debugging.
We migrated some older code to Spark 2.4.0, and suddently the unit tests on our
build machine were much slower than expected.
On local machines it was running perfectly.
At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
analyzing in the following functions
* AnalysisHelper.assertNotAnalysisRule calling
* Utils.isTesting
Utils.isTesting is traversing all environment variables.
The offending build machine was a Kubernetes Pod which automatically exposed
all services as environment variables, so it had more than 3000 environment
variables.
As Utils.isTesting is called very often throgh
AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
transformUp).
Of course we will restrict the number of environment variables, on the other
side Utils.isTesting could also use a lazy val for
```
sys.env.contains("SPARK_TESTING")
```
to not make it that expensive.
> Long runtime on many environment variables
> --
>
> Key: SPARK-34115
> URL: https://issues.apache.org/jira/browse/SPARK-34115
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 2.4.0
> Environment: Spark 2.4.0 local[2] on a Kubernetes Pod
>Reporter: Norbert Schultz
>Priority: Major
>
> I am not sure if this is a bug report or a feature request. The code is is
> the same in current versions of Spark and maybe this ticket saves someone
> some time for debugging.
> We migrated some older code to Spark 2.4.0, and suddently the unit tests on
> our build machine were much slower than expected.
> On local machines it was running perfectly.
> At the end it turned out, that Spark was wasting CPU Cycles during DataFrame
> analyzing in the following functions
> * AnalysisHelper.assertNotAnalysisRule calling
> * Utils.isTesting
> Utils.isTesting is traversing all environment variables.
> The offending build machine was a Kubernetes Pod which automatically exposed
> all services as environment variables, so it had more than 3000 environment
> variables.
> As Utils.isTesting is called very often throgh
> AnalysisHelper.assertNotAnalysisRule (via AnalysisHelper.transformDown,
> transformUp).
>
> Of course we will restrict the number of environment variables, on the other
> side Utils.isTesting could also use a lazy val for
>
> {code:java}
> sys.env.contains("SPARK_TESTING") {code}
>
> to not make it that expensive.
--
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