[jira] [Commented] (SPARK-19737) New analysis rule for reporting unregistered functions without relying on relation resolution
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https://issues.apache.org/jira/browse/SPARK-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15896127#comment-15896127
]
Apache Spark commented on SPARK-19737:
--
User 'liancheng' has created a pull request for this issue:
https://github.com/apache/spark/pull/17168
> New analysis rule for reporting unregistered functions without relying on
> relation resolution
> -
>
> Key: SPARK-19737
> URL: https://issues.apache.org/jira/browse/SPARK-19737
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.2.0
>Reporter: Cheng Lian
> Fix For: 2.2.0
>
>
> Let's consider the following simple SQL query that reference an invalid
> function {{foo}} that is never registered in the function registry:
> {code:sql}
> SELECT foo(a) FROM t
> {code}
> Assuming table {{t}} is a partitioned temporary view consisting of a large
> number of files stored on S3, then it may take the analyzer a long time
> before realizing that {{foo}} is not registered yet.
> The reason is that the existing analysis rule {{ResolveFunctions}} requires
> all child expressions to be resolved first. Therefore, {{ResolveRelations}}
> has to be executed first to resolve all columns referenced by the unresolved
> function invocation. This further leads to partition discovery for {{t}},
> which may take a long time.
> To address this case, we propose a new lightweight analysis rule
> {{LookupFunctions}} that
> # Matches all unresolved function invocations
> # Look up the function names from the function registry
> # Report analysis error for any unregistered functions
> Since this rule doesn't actually try to resolve the unresolved functions, it
> doesn't rely on {{ResolveRelations}} and therefore doesn't trigger partition
> discovery.
> We may put this analysis rule in a separate {{Once}} rule batch that sits
> between the "Substitution" batch and the "Resolution" batch to avoid running
> it repeatedly and make sure it gets executed before {{ResolveRelations}}.
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[jira] [Assigned] (SPARK-19737) New analysis rule for reporting unregistered functions without relying on relation resolution
[
https://issues.apache.org/jira/browse/SPARK-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-19737:
Assignee: (was: Apache Spark)
> New analysis rule for reporting unregistered functions without relying on
> relation resolution
> -
>
> Key: SPARK-19737
> URL: https://issues.apache.org/jira/browse/SPARK-19737
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.2.0
>Reporter: Cheng Lian
> Fix For: 2.2.0
>
>
> Let's consider the following simple SQL query that reference an invalid
> function {{foo}} that is never registered in the function registry:
> {code:sql}
> SELECT foo(a) FROM t
> {code}
> Assuming table {{t}} is a partitioned temporary view consisting of a large
> number of files stored on S3, then it may take the analyzer a long time
> before realizing that {{foo}} is not registered yet.
> The reason is that the existing analysis rule {{ResolveFunctions}} requires
> all child expressions to be resolved first. Therefore, {{ResolveRelations}}
> has to be executed first to resolve all columns referenced by the unresolved
> function invocation. This further leads to partition discovery for {{t}},
> which may take a long time.
> To address this case, we propose a new lightweight analysis rule
> {{LookupFunctions}} that
> # Matches all unresolved function invocations
> # Look up the function names from the function registry
> # Report analysis error for any unregistered functions
> Since this rule doesn't actually try to resolve the unresolved functions, it
> doesn't rely on {{ResolveRelations}} and therefore doesn't trigger partition
> discovery.
> We may put this analysis rule in a separate {{Once}} rule batch that sits
> between the "Substitution" batch and the "Resolution" batch to avoid running
> it repeatedly and make sure it gets executed before {{ResolveRelations}}.
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[jira] [Assigned] (SPARK-19737) New analysis rule for reporting unregistered functions without relying on relation resolution
[
https://issues.apache.org/jira/browse/SPARK-19737?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-19737:
Assignee: Apache Spark
> New analysis rule for reporting unregistered functions without relying on
> relation resolution
> -
>
> Key: SPARK-19737
> URL: https://issues.apache.org/jira/browse/SPARK-19737
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.2.0
>Reporter: Cheng Lian
>Assignee: Apache Spark
> Fix For: 2.2.0
>
>
> Let's consider the following simple SQL query that reference an invalid
> function {{foo}} that is never registered in the function registry:
> {code:sql}
> SELECT foo(a) FROM t
> {code}
> Assuming table {{t}} is a partitioned temporary view consisting of a large
> number of files stored on S3, then it may take the analyzer a long time
> before realizing that {{foo}} is not registered yet.
> The reason is that the existing analysis rule {{ResolveFunctions}} requires
> all child expressions to be resolved first. Therefore, {{ResolveRelations}}
> has to be executed first to resolve all columns referenced by the unresolved
> function invocation. This further leads to partition discovery for {{t}},
> which may take a long time.
> To address this case, we propose a new lightweight analysis rule
> {{LookupFunctions}} that
> # Matches all unresolved function invocations
> # Look up the function names from the function registry
> # Report analysis error for any unregistered functions
> Since this rule doesn't actually try to resolve the unresolved functions, it
> doesn't rely on {{ResolveRelations}} and therefore doesn't trigger partition
> discovery.
> We may put this analysis rule in a separate {{Once}} rule batch that sits
> between the "Substitution" batch and the "Resolution" batch to avoid running
> it repeatedly and make sure it gets executed before {{ResolveRelations}}.
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[jira] [Created] (SPARK-19824) Standalone master JSON not showing cores for running applications
Dan created SPARK-19824:
---
Summary: Standalone master JSON not showing cores for running
applications
Key: SPARK-19824
URL: https://issues.apache.org/jira/browse/SPARK-19824
Project: Spark
Issue Type: Bug
Components: Deploy
Affects Versions: 2.1.0
Reporter: Dan
Priority: Minor
The JSON API of the standalone master ("/json") does not show the number of
cores for a running application, which is available on the UI.
"activeapps" : [ {
"starttime" : 1488702337788,
"id" : "app-20170305102537-19717",
"name" : "POPAI_Aggregated",
"user" : "ibiuser",
"memoryperslave" : 16384,
"submitdate" : "Sun Mar 05 10:25:37 IST 2017",
"state" : "RUNNING",
"duration" : 1141934
} ],
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