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Posted to reviews@spark.apache.org by "zzzzming95 (via GitHub)" <gi...@apache.org> on 2023/09/04 13:30:53 UTC
[GitHub] [spark] zzzzming95 opened a new pull request, #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
zzzzming95 opened a new pull request, #42804:
URL: https://github.com/apache/spark/pull/42804
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### What changes were proposed in this pull request?
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Since `BinaryArithmetic#dataType` will recursively process the datatype of each node, the driver will be very slow when multiple columns are processed.
For example, the following code:
```
import spark.implicits._
import scala.util.Random
import org.apache.spark.sql.functions.sum
import org.apache.spark.sql.types.{StructType, StructField, IntegerType}
val N = 30
val M = 100
val columns = Seq.fill(N)(Random.alphanumeric.take(8).mkString)
val data = Seq.fill(M)(Seq.fill(N)(Random.nextInt(16) - 5))
val schema = StructType(columns.map(StructField(_, IntegerType)))
val rdd = spark.sparkContext.parallelize(data.map(Row.fromSeq(_)))
val df = spark.createDataFrame(rdd, schema)
val colExprs = columns.map(sum(_))
// gen a new column , and add the other 30 column
df.withColumn("new_col_sum", expr(columns.mkString(" + ")))
```
This code will take a few minutes for the driver to execute in the spark3.4 version, but only takes a few seconds to execute in the spark3.2 version. Related issue: [SPARK-39316](https://github.com/apache/spark/pull/36698)
### Why are the changes needed?
<!--
Please clarify why the changes are needed. For instance,
1. If you propose a new API, clarify the use case for a new API.
2. If you fix a bug, you can clarify why it is a bug.
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Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
### Does this PR introduce _any_ user-facing change?
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If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible.
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No
### How was this patch tested?
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manual testing
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no
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[GitHub] [spark] cloud-fan commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1316665134
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,11 +240,7 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
- }
+ override def dataType: DataType = internalDataType
Review Comment:
ah then it's not an option. We are good to go.
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[GitHub] [spark] zzzzming95 commented on pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "zzzzming95 (via GitHub)" <gi...@apache.org>.
zzzzming95 commented on PR #42804:
URL: https://github.com/apache/spark/pull/42804#issuecomment-1705803286
@ulysses-you cc
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[GitHub] [spark] zzzzming95 commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "zzzzming95 (via GitHub)" <gi...@apache.org>.
zzzzming95 commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1316079522
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,11 +240,7 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
- }
+ override def dataType: DataType = internalDataType
Review Comment:
Sorry for the late reply. Change `dataType` is a big change. We need to change all implement of the `Expression` . I think we should not make this modification in this issue, What do you think?
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[GitHub] [spark] wangyum commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1315032583
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,10 +234,17 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
+ override def dataType: DataType = (left, right) match {
+ case (_, r: AttributeReference) if !r.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (l: AttributeReference, _) if !l.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (_, _) =>
+ (left.dataType, right.dataType) match {
+ case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
+ resultDecimalType(p1, s1, p2, s2)
+ case _ => left.dataType
+ }
Review Comment:
Can we change it to lazy val? For example:
```scala
private lazy val internalDataType: DataType = (left.dataType, right.dataType) match {
case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
resultDecimalType(p1, s1, p2, s2)
case _ => left.dataType
}
override def dataType: DataType = internalDataType
```
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[GitHub] [spark] cloud-fan commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1315502363
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,11 +240,7 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
- }
+ override def dataType: DataType = internalDataType
Review Comment:
can we simply make `dataType` a lazy val?
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[GitHub] [spark] ulysses-you commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "ulysses-you (via GitHub)" <gi...@apache.org>.
ulysses-you commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1315314032
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,10 +234,17 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
+ override def dataType: DataType = (left, right) match {
+ case (_, r: AttributeReference) if !r.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (l: AttributeReference, _) if !l.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (_, _) =>
+ (left.dataType, right.dataType) match {
+ case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
+ resultDecimalType(p1, s1, p2, s2)
+ case _ => left.dataType
+ }
Review Comment:
+1
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[GitHub] [spark] zzzzming95 commented on pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "zzzzming95 (via GitHub)" <gi...@apache.org>.
zzzzming95 commented on PR #42804:
URL: https://github.com/apache/spark/pull/42804#issuecomment-1706594949
@cloud-fan @wangyum
Please merge it to master , thanks
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[GitHub] [spark] wangyum commented on pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum commented on PR #42804:
URL: https://github.com/apache/spark/pull/42804#issuecomment-1706074040
cc @cloud-fan
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[GitHub] [spark] wangyum commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1315905477
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,11 +240,7 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
- }
+ override def dataType: DataType = internalDataType
Review Comment:
@zzzzming95 Please address this comment.
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[GitHub] [spark] wangyum commented on pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum commented on PR #42804:
URL: https://github.com/apache/spark/pull/42804#issuecomment-1707606993
Merged to master, branch-3.5 and branch-3.4.
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[GitHub] [spark] wangyum commented on a diff in pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum commented on code in PR #42804:
URL: https://github.com/apache/spark/pull/42804#discussion_r1315255094
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -234,10 +234,17 @@ abstract class BinaryArithmetic extends BinaryOperator
case _ => super.checkInputDataTypes()
}
- override def dataType: DataType = (left.dataType, right.dataType) match {
- case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
- resultDecimalType(p1, s1, p2, s2)
- case _ => left.dataType
+ override def dataType: DataType = (left, right) match {
+ case (_, r: AttributeReference) if !r.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (l: AttributeReference, _) if !l.dataType.isInstanceOf[DecimalType] =>
+ left.dataType
+ case (_, _) =>
+ (left.dataType, right.dataType) match {
+ case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
+ resultDecimalType(p1, s1, p2, s2)
+ case _ => left.dataType
+ }
Review Comment:
Can we just change it to lazy val? For example:
```scala
private lazy val internalDataType: DataType = {
(left.dataType, right.dataType) match {
case (DecimalType.Fixed(p1, s1), DecimalType.Fixed(p2, s2)) =>
resultDecimalType(p1, s1, p2, s2)
case _ => left.dataType
}
}
override def dataType: DataType = internalDataType
```
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[GitHub] [spark] wangyum closed pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
Posted by "wangyum (via GitHub)" <gi...@apache.org>.
wangyum closed pull request #42804: [SPARK-45071][SQL] Optimize the processing speed of `BinaryArithmetic#dataType` when processing multi-column data
URL: https://github.com/apache/spark/pull/42804
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