[SPARK-54442][SQL][FOLLOWUP] Add codegen for TIME numeric conversion functions #53370
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vinodkc
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cloud-fan
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/timeExpressions.scala
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| override def replacement: Expression = StaticInvoke( | ||
| classOf[DateTimeUtils.type], | ||
| DecimalType(14, 6), |
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| DecimalType(14, 6), | |
| dataType, |
to avoid duplication
cloud-fan
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Dec 10, 2025
| case e: DateTimeException => | ||
| throw QueryExecutionErrors.ansiDateTimeArgumentOutOfRange(e) | ||
| case e: ArithmeticException => | ||
| val wrapped = new DateTimeException(s"Overflow in TIME conversion: ${e.getMessage}", e) |
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| val wrapped = new DateTimeException(s"Overflow in TIME conversion: ${e.getMessage}", e) | |
| val wrapped = new DateTimeException(s"Overflow in TIME conversion", e) |
do not duplicate the info in the causedBy error
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| * @param seconds Seconds (0 to 86399.999999) | ||
| * @return Nanoseconds since midnight | ||
| */ | ||
| def timeFromSeconds(seconds: Float): Long = withTimeConversionErrorHandling { |
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do we need the float version? the double version can cover it.
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| if (seconds.isNaN || seconds.isInfinite) { | ||
| throw new DateTimeException("Cannot convert NaN or Infinite value to TIME") | ||
| } | ||
| (seconds * NANOS_PER_SECOND).toLong |
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do we need to consider overflow here when calling toLong?
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Dec 10, 2025
| * @param nanos Nanoseconds since midnight | ||
| * @return Seconds as Decimal(14, 6) | ||
| */ | ||
| def timeToSeconds(nanos: Long): Decimal = { |
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shall we wrap with withTimeConversionErrorHandling?
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Dec 10, 2025
| SELECT time_from_seconds(-1); | ||
| SELECT time_from_seconds(86400); | ||
| SELECT time_from_seconds(90000); | ||
| SELECT time_from_seconds(-1); -- invalid: negative → exception |
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| SELECT time_from_seconds(-1); -- invalid: negative → exception | |
| SELECT time_from_seconds(-1); -- invalid: negative -> exception |
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Dec 10, 2025
| "errorClass" : "DATETIME_FIELD_OUT_OF_BOUNDS.WITH_SUGGESTION", | ||
| "sqlState" : "22023", | ||
| "messageParameters" : { | ||
| "ansiConfig" : "\"spark.sql.ansi.enabled\"", |
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what's the full message? why do we mention ansi conf?
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| if (seconds.isNaN || seconds.isInfinite) { | ||
| throw new DateTimeException("Cannot convert NaN or Infinite value to TIME") | ||
| } | ||
| (seconds * NANOS_PER_SECOND).toLong |
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do we need to consider overflow here when calling toLong?
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What changes were proposed in this pull request?
Implemented whole-stage codegen for TIME conversion functions (IntegralToTimeBase, TimeFromSeconds, TimeToSeconds) by removing CodegenFallback
Why are the changes needed?
Performance: CodegenFallback is 10-50x slower than generated code
Pattern consistency: Follows existing Spark patterns (IntegralToTimestampBase)
Does this PR introduce any user-facing change?
No. performance optimization with identical results.
How was this patch tested?
All existing tests pass
Generated code inspection confirms optimizations
Was this patch authored or co-authored using generative AI tooling?
No