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new 24b29adcf53 [SPARK-45079][SQL] Fix an internal error from
`percentile_approx()`on `NULL` accuracy
24b29adcf53 is described below
commit 24b29adcf53616067a9fa2ca201e3f4d2f54436b
Author: Max Gekk <max.g...@gmail.com>
AuthorDate: Wed Sep 6 10:32:37 2023 +0300
[SPARK-45079][SQL] Fix an internal error from `percentile_approx()`on
`NULL` accuracy
### What changes were proposed in this pull request?
In the PR, I propose to check the `accuracy` argument is not a NULL in
`ApproximatePercentile`. And if it is, throw an `AnalysisException` with new
error class `DATATYPE_MISMATCH.UNEXPECTED_NULL`.
### Why are the changes needed?
To fix the issue demonstrated by the example:
```sql
$ spark-sql (default)> SELECT percentile_approx(col, array(0.5, 0.4, 0.1),
NULL) FROM VALUES (0), (1), (2), (10) AS tab(col);
[INTERNAL_ERROR] The Spark SQL phase analysis failed with an internal
error. You hit a bug in Spark or the Spark plugins you use. Please, report this
bug to the corresponding communities or vendors, and provide the full stack
trace.
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
By running new test:
```
$ build/sbt "test:testOnly *.ApproximatePercentileQuerySuite"
```
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #42817 from MaxGekk/fix-internal-error-in-percentile_approx.
Authored-by: Max Gekk <max.g...@gmail.com>
Signed-off-by: Max Gekk <max.g...@gmail.com>
---
.../aggregate/ApproximatePercentile.scala | 7 ++++-
.../sql/ApproximatePercentileQuerySuite.scala | 31 ++++++++++++++++++++++
2 files changed, 37 insertions(+), 1 deletion(-)
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
index 3c3afc1c7e7..5b44c3fa31b 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
@@ -97,7 +97,8 @@ case class ApproximatePercentile(
}
// Mark as lazy so that accuracyExpression is not evaluated during tree
transformation.
- private lazy val accuracy: Long =
accuracyExpression.eval().asInstanceOf[Number].longValue
+ private lazy val accuracyNum = accuracyExpression.eval().asInstanceOf[Number]
+ private lazy val accuracy: Long = accuracyNum.longValue
override def inputTypes: Seq[AbstractDataType] = {
// Support NumericType, DateType, TimestampType and TimestampNTZType since
their internal types
@@ -138,6 +139,10 @@ case class ApproximatePercentile(
"inputExpr" -> toSQLExpr(accuracyExpression)
)
)
+ } else if (accuracyNum == null) {
+ DataTypeMismatch(
+ errorSubClass = "UNEXPECTED_NULL",
+ messageParameters = Map("exprName" -> "accuracy"))
} else if (accuracy <= 0 || accuracy > Int.MaxValue) {
DataTypeMismatch(
errorSubClass = "VALUE_OUT_OF_RANGE",
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala
index 18e8dd6249b..273e8e08fd7 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala
@@ -339,4 +339,35 @@ class ApproximatePercentileQuerySuite extends QueryTest
with SharedSparkSession
Row(Period.ofMonths(200).normalized(), null,
Duration.ofSeconds(200L)))
}
}
+
+ test("SPARK-45079: NULL arguments of percentile_approx") {
+ checkError(
+ exception = intercept[AnalysisException] {
+ sql(
+ """
+ |SELECT percentile_approx(col, array(0.5, 0.4, 0.1), NULL)
+ |FROM VALUES (0), (1), (2), (10) AS tab(col);
+ |""".stripMargin).collect()
+ },
+ errorClass = "DATATYPE_MISMATCH.UNEXPECTED_NULL",
+ parameters = Map(
+ "exprName" -> "accuracy",
+ "sqlExpr" -> "\"percentile_approx(col, array(0.5, 0.4, 0.1), NULL)\""),
+ context = ExpectedContext(
+ "", "", 8, 57, "percentile_approx(col, array(0.5, 0.4, 0.1), NULL)"))
+ checkError(
+ exception = intercept[AnalysisException] {
+ sql(
+ """
+ |SELECT percentile_approx(col, NULL, 100)
+ |FROM VALUES (0), (1), (2), (10) AS tab(col);
+ |""".stripMargin).collect()
+ },
+ errorClass = "DATATYPE_MISMATCH.UNEXPECTED_NULL",
+ parameters = Map(
+ "exprName" -> "percentage",
+ "sqlExpr" -> "\"percentile_approx(col, NULL, 100)\""),
+ context = ExpectedContext(
+ "", "", 8, 40, "percentile_approx(col, NULL, 100)"))
+ }
}
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