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https://issues.apache.org/jira/browse/SPARK-33539?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17245459#comment-17245459
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Allison Wang commented on SPARK-33539:
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Hi [~srowen], this is to breakdown more than 1000+ error messages into smaller
tasks for each component and module so that each task contains a reasonable
amount of exceptions to work with.
> Standardize exception messages in Spark
> ---------------------------------------
>
> Key: SPARK-33539
> URL: https://issues.apache.org/jira/browse/SPARK-33539
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core, SQL
> Affects Versions: 3.1.0
> Reporter: Allison Wang
> Priority: Major
>
> In the SPIP: Standardize Exception Messages in Spark, there are three major
> improvements proposed:
> # Group error messages in dedicated files.
> # Establish an error message guideline for developers.
> # Improve error message quality.
> The first step is to centralize error messages for each component into its
> own dedicated file(s). This can help with auditing error messages and
> subsequent tasks to establish a guideline and improve message quality in the
> future.
> A general rule of thumb for grouping exceptions:
> * AnalysisException => QueryCompilationErrors
> * SparkException, RuntimeException(UnsupportedOperationException,
> IllegalStateException...) => QueryExecutionErrors
> Here is an example RP to group all `AnalysisExcpetion` in Analyzer into
> QueryCompilationErrors:
> [SPARK-32670|https://github.com/apache/spark/pull/29497]
> Please see the
> [SPIP|https://docs.google.com/document/d/1XGj1o3xAFh8BA7RCn3DtwIPC6--hIFOaNUNSlpaOIZs/edit?usp=sharing]
> for more details.
> Exceptions per component:
> ||component||exception||
> |sql|714|
> |core|334|
> |mllib|161|
> |streaming|43|
> |resource-managers|42|
> |external|35|
> |examples|20|
> |mllib-local|10|
> |graphx|6|
> |repl|5|
> |hadoop-cloud|1|
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