[jira] [Assigned] (SPARK-39040) Respect NaNvl in EquivalentExpressions for expression elimination
[
https://issues.apache.org/jira/browse/SPARK-39040?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wenchen Fan reassigned SPARK-39040:
---
Assignee: XiDuo You
> Respect NaNvl in EquivalentExpressions for expression elimination
> -
>
> Key: SPARK-39040
> URL: https://issues.apache.org/jira/browse/SPARK-39040
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.4.0
>Reporter: XiDuo You
>Assignee: XiDuo You
>Priority: Major
> Fix For: 3.3.0
>
>
> For example the query will fail:
> {code:java}
> set spark.sql.ansi.enabled=true;
> set
> spark.sql.optimizer.excludedRules=org.apache.spark.sql.catalyst.optimizer.ConstantFolding;
> SELECT nanvl(1, 1/0 + 1/0); {code}
> {code:java}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0
> (TID 4) (10.221.98.68 executor driver):
> org.apache.spark.SparkArithmeticException: divide by zero. To return NULL
> instead, use 'try_divide'. If necessary set spark.sql.ansi.enabled to false
> (except for ANSI interval type) to bypass this error.
> == SQL(line 1, position 17) ==
> select nanvl(1 , 1/0 + 1/0)
> ^^^ at
> org.apache.spark.sql.errors.QueryExecutionErrors$.divideByZeroError(QueryExecutionErrors.scala:151)
> {code}
> We should respect the ordering of conditional expression that always evaluate
> the predicate branch first, so the query above should not fail.
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[jira] [Assigned] (SPARK-39040) Respect NaNvl in EquivalentExpressions for expression elimination
[
https://issues.apache.org/jira/browse/SPARK-39040?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-39040:
Assignee: (was: Apache Spark)
> Respect NaNvl in EquivalentExpressions for expression elimination
> -
>
> Key: SPARK-39040
> URL: https://issues.apache.org/jira/browse/SPARK-39040
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.4.0
>Reporter: XiDuo You
>Priority: Major
>
> For example the query will fail:
> {code:java}
> set spark.sql.ansi.enabled=true;
> set
> spark.sql.optimizer.excludedRules=org.apache.spark.sql.catalyst.optimizer.ConstantFolding;
> SELECT nanvl(1, 1/0 + 1/0); {code}
> {code:java}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0
> (TID 4) (10.221.98.68 executor driver):
> org.apache.spark.SparkArithmeticException: divide by zero. To return NULL
> instead, use 'try_divide'. If necessary set spark.sql.ansi.enabled to false
> (except for ANSI interval type) to bypass this error.
> == SQL(line 1, position 17) ==
> select nanvl(1 , 1/0 + 1/0)
> ^^^ at
> org.apache.spark.sql.errors.QueryExecutionErrors$.divideByZeroError(QueryExecutionErrors.scala:151)
> {code}
> We should respect the ordering of conditional expression that always evaluate
> the predicate branch first, so the query above should not fail.
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[jira] [Assigned] (SPARK-39040) Respect NaNvl in EquivalentExpressions for expression elimination
[
https://issues.apache.org/jira/browse/SPARK-39040?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-39040:
Assignee: Apache Spark
> Respect NaNvl in EquivalentExpressions for expression elimination
> -
>
> Key: SPARK-39040
> URL: https://issues.apache.org/jira/browse/SPARK-39040
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
>Affects Versions: 3.4.0
>Reporter: XiDuo You
>Assignee: Apache Spark
>Priority: Major
>
> For example the query will fail:
> {code:java}
> set spark.sql.ansi.enabled=true;
> set
> spark.sql.optimizer.excludedRules=org.apache.spark.sql.catalyst.optimizer.ConstantFolding;
> SELECT nanvl(1, 1/0 + 1/0); {code}
> {code:java}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0
> (TID 4) (10.221.98.68 executor driver):
> org.apache.spark.SparkArithmeticException: divide by zero. To return NULL
> instead, use 'try_divide'. If necessary set spark.sql.ansi.enabled to false
> (except for ANSI interval type) to bypass this error.
> == SQL(line 1, position 17) ==
> select nanvl(1 , 1/0 + 1/0)
> ^^^ at
> org.apache.spark.sql.errors.QueryExecutionErrors$.divideByZeroError(QueryExecutionErrors.scala:151)
> {code}
> We should respect the ordering of conditional expression that always evaluate
> the predicate branch first, so the query above should not fail.
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