Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[GLUTEN-7749][VL] Trim ISOControl characters in string for casting to integral type #7806

Merged
merged 7 commits into from
Nov 6, 2024
Merged
Show file tree
Hide file tree
Changes from 6 commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
Expand Up @@ -723,30 +723,29 @@ class VeloxSparkPlanExecApi extends SparkPlanExecApi {
val trimParaSepStr = "\u2029"
// Needs to be trimmed for casting to float/double/decimal
val trimSpaceStr = ('\u0000' to '\u0020').toList.mkString
// ISOControl characters, refer java.lang.Character.isISOControl(int)
val isoControlControlStr = (('\u0000' to '\u001F') ++ ('\u007F' to '\u009F')).toList.mkString
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

isoControlControlStr->isoControlStr, a typo?

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

thanks, fixed

// scalastyle:on nonascii
c.dataType match {
case BinaryType | _: ArrayType | _: MapType | _: StructType | _: UserDefinedType[_] =>
c
case FloatType | DoubleType | _: DecimalType =>
c.child.dataType match {
case StringType if GlutenConfig.getConf.castFromVarcharAddTrimNode =>
val trimNode = StringTrim(c.child, Some(Literal(trimSpaceStr)))
c.withNewChildren(Seq(trimNode)).asInstanceOf[Cast]
case _ =>
c
}
case _ =>
c.child.dataType match {
case StringType if GlutenConfig.getConf.castFromVarcharAddTrimNode =>
val trimNode = StringTrim(
c.child,
Some(
Literal(trimWhitespaceStr +
trimSpaceSepStr + trimLineSepStr + trimParaSepStr)))
c.withNewChildren(Seq(trimNode)).asInstanceOf[Cast]
case _ =>
c
if (GlutenConfig.getConf.castFromVarcharAddTrimNode && c.child.dataType == StringType) {
val trimStr = c.dataType match {
case BinaryType | _: ArrayType | _: MapType | _: StructType | _: UserDefinedType[_] =>
None
case FloatType | DoubleType | _: DecimalType =>
Some(trimSpaceStr)
case _ =>
Some(
(trimWhitespaceStr + trimSpaceSepStr + trimLineSepStr
+ trimParaSepStr + isoControlControlStr).toSet.mkString
)
}
trimStr
.map {
trim =>
c.withNewChildren(Seq(StringTrim(c.child, Some(Literal(trim))))).asInstanceOf[Cast]
}
.getOrElse(c)
} else {
c
}
}

Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
*/
package org.apache.spark.sql

import org.apache.gluten.GlutenConfig
import org.apache.gluten.execution.{ProjectExecTransformer, WholeStageTransformer}

import org.apache.spark.SparkException
Expand Down Expand Up @@ -323,41 +324,52 @@ class GlutenDataFrameSuite extends DataFrameSuite with GlutenSQLTestsTrait {
}

testGluten("Allow leading/trailing whitespace in string before casting") {
def checkResult(df: DataFrame, expectedResult: Seq[Row]): Unit = {
checkAnswer(df, expectedResult)
assert(find(df.queryExecution.executedPlan)(_.isInstanceOf[ProjectExecTransformer]).isDefined)
}
withSQLConf(GlutenConfig.CAST_FROM_VARCHAR_ADD_TRIM_NODE.key -> "true") {
def checkResult(df: DataFrame, expectedResult: Seq[Row]): Unit = {
checkAnswer(df, expectedResult)
assert(
find(df.queryExecution.executedPlan)(_.isInstanceOf[ProjectExecTransformer]).isDefined)
}

// scalastyle:off nonascii
Seq(" 123", "123 ", " 123 ", "\u2000123\n\n\n", "123\r\r\r", "123\f\f\f", "123\u000C")
.toDF("col1")
.createOrReplaceTempView("t1")
// scalastyle:on nonascii
val expectedIntResult = Row(123) :: Row(123) ::
Row(123) :: Row(123) :: Row(123) :: Row(123) :: Row(123) :: Nil
var df = spark.sql("select cast(col1 as int) from t1")
checkResult(df, expectedIntResult)
df = spark.sql("select cast(col1 as long) from t1")
checkResult(df, expectedIntResult)

Seq(" 123.5", "123.5 ", " 123.5 ", "123.5\n\n\n", "123.5\r\r\r", "123.5\f\f\f", "123.5\u000C")
.toDF("col1")
.createOrReplaceTempView("t1")
val expectedFloatResult = Row(123.5) :: Row(123.5) ::
Row(123.5) :: Row(123.5) :: Row(123.5) :: Row(123.5) :: Row(123.5) :: Nil
df = spark.sql("select cast(col1 as float) from t1")
checkResult(df, expectedFloatResult)
df = spark.sql("select cast(col1 as double) from t1")
checkResult(df, expectedFloatResult)

// scalastyle:off nonascii
val rawData =
Seq(" abc", "abc ", " abc ", "\u2000abc\n\n\n", "abc\r\r\r", "abc\f\f\f", "abc\u000C")
// scalastyle:on nonascii
rawData.toDF("col1").createOrReplaceTempView("t1")
val expectedBinaryResult = rawData.map(d => Row(d.getBytes(StandardCharsets.UTF_8))).seq
df = spark.sql("select cast(col1 as binary) from t1")
checkResult(df, expectedBinaryResult)
// scalastyle:off nonascii
Seq(
" 123",
"123 ",
" 123 ",
"\u2000123\n\n\n",
"123\r\r\r",
"123\f\f\f",
"123\u000C",
"123\u0000")
.toDF("col1")
.createOrReplaceTempView("t1")
// scalastyle:on nonascii
val expectedIntResult = Row(123) :: Row(123) ::
Row(123) :: Row(123) :: Row(123) :: Row(123) :: Row(123) :: Row(123) :: Nil
var df = spark.sql("select cast(col1 as int) from t1")
checkResult(df, expectedIntResult)
df = spark.sql("select cast(col1 as long) from t1")
checkResult(df, expectedIntResult)

Seq(" 123.5", "123.5 ", " 123.5 ", "123.5\n\n\n", "123.5\r\r\r", "123.5\f\f\f", "123.5\u000C")
.toDF("col1")
.createOrReplaceTempView("t1")
val expectedFloatResult = Row(123.5) :: Row(123.5) ::
Row(123.5) :: Row(123.5) :: Row(123.5) :: Row(123.5) :: Row(123.5) :: Nil
df = spark.sql("select cast(col1 as float) from t1")
checkResult(df, expectedFloatResult)
df = spark.sql("select cast(col1 as double) from t1")
checkResult(df, expectedFloatResult)

// scalastyle:off nonascii
val rawData =
Seq(" abc", "abc ", " abc ", "\u2000abc\n\n\n", "abc\r\r\r", "abc\f\f\f", "abc\u000C")
// scalastyle:on nonascii
rawData.toDF("col1").createOrReplaceTempView("t1")
val expectedBinaryResult = rawData.map(d => Row(d.getBytes(StandardCharsets.UTF_8))).seq
df = spark.sql("select cast(col1 as binary) from t1")
checkResult(df, expectedBinaryResult)
}
}

private def withExpr(newExpr: Expression): Column = new Column(newExpr)
Expand Down
Loading