You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "koert kuipers (Jira)" <ji...@apache.org> on 2021/12/01 16:58:00 UTC
[jira] [Comment Edited] (SPARK-37476) udaf doesnt work with nullable (or option of) case class result
[ https://issues.apache.org/jira/browse/SPARK-37476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17451921#comment-17451921 ]
koert kuipers edited comment on SPARK-37476 at 12/1/21, 4:57 PM:
-----------------------------------------------------------------
yes it works well
{code:java}
import java.lang.{Double => JDouble}
val sumAgg = new Aggregator[Double, JDouble, JDouble] {
def zero: JDouble = null
def reduce(b: JDouble, a: Double): JDouble =
if (b == null) {
a
} else {
b + a
}
def merge(b1: JDouble, b2: JDouble): JDouble =
if (b1 == null) {
b2
} else if (b2 == null) {
b1
} else {
b1 + b2
}
def finish(r: JDouble): JDouble = r
def bufferEncoder: Encoder[JDouble] = ExpressionEncoder()
def outputEncoder: Encoder[JDouble] = ExpressionEncoder()
}
val df = Seq.empty[Double]
.toDF()
.select(udaf(sumAgg).apply(col("value")))
df.printSchema()
root
|-- $anon$3(value): double (nullable = true)
df.show()
+--------------+
|$anon$3(value)|
+--------------+
| null|
+--------------+
{code}
it works with Option without issues too
was (Author: koert):
yes it works well
{code:java}
import java.lang.{Double => JDouble}
val sumAgg = new Aggregator[Double, JDouble, JDouble] {
def zero: JDouble = null
def reduce(b: JDouble, a: Double): JDouble =
if (b == null) {
a
} else {
b + a
}
def merge(b1: JDouble, b2: JDouble): JDouble =
if (b1 == null) {
b2
} else if (b2 == null) {
b1
} else {
b1 + b2
}
def finish(r: JDouble): JDouble = r
def bufferEncoder: Encoder[JDouble] = ExpressionEncoder()
def outputEncoder: Encoder[JDouble] = ExpressionEncoder()
}
val df = Seq.empty[Double]
.toDF()
.select(udaf(sumAgg).apply(col("value")))
df.printSchema()
root
|-- $anon$3(value): double (nullable = true)
df.show()
+--------------+
|$anon$3(value)|
+--------------+
| null|
+--------------+
{code}
it works with Option without issues too
> udaf doesnt work with nullable (or option of) case class result
> ----------------------------------------------------------------
>
> Key: SPARK-37476
> URL: https://issues.apache.org/jira/browse/SPARK-37476
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.2.0
> Environment: spark master branch on nov 27
> Reporter: koert kuipers
> Priority: Minor
>
> i have a need to have a dataframe aggregation return a nullable case class. there seems to be no way to get this to work. the suggestion to wrap the result in an option doesnt work either.
> first attempt using nulls:
> {code:java}
> case class SumAndProduct(sum: Double, product: Double)
> val sumAndProductAgg = new Aggregator[Double, SumAndProduct, SumAndProduct] {
> def zero: SumAndProduct = null
> def reduce(b: SumAndProduct, a: Double): SumAndProduct =
> if (b == null) {
> SumAndProduct(a, a)
> } else {
> SumAndProduct(b.sum + a, b.product * a)
> }
> def merge(b1: SumAndProduct, b2: SumAndProduct): SumAndProduct =
> if (b1 == null) {
> b2
> } else if (b2 == null) {
> b1
> } else {
> SumAndProduct(b1.sum + b2.sum, b1.product * b2.product)
> }
> def finish(r: SumAndProduct): SumAndProduct = r
> def bufferEncoder: Encoder[SumAndProduct] = ExpressionEncoder()
> def outputEncoder: Encoder[SumAndProduct] = ExpressionEncoder()
> }
> val df = Seq.empty[Double]
> .toDF()
> .select(udaf(sumAndProductAgg).apply(col("value")))
> df.printSchema()
> df.show()
> {code}
> this gives:
> {code:java}
> root
> |-- $anon$3(value): struct (nullable = true)
> | |-- sum: double (nullable = false)
> | |-- product: double (nullable = false)
> 16:44:54.882 ERROR org.apache.spark.executor.Executor: Exception in task 0.0 in stage 1491.0 (TID 1929)
> java.lang.RuntimeException: Error while encoding: java.lang.NullPointerException: Null value appeared in non-nullable field:
> top level Product or row object
> If the schema is inferred from a Scala tuple/case class, or a Java bean, please try to use scala.Option[_] or other nullable types (e.g. java.lang.Integer instead of int/scala.Int).
> knownnotnull(assertnotnull(input[0, org.apache.spark.sql.SumAndProduct, true])).sum AS sum#20070
> knownnotnull(assertnotnull(input[0, org.apache.spark.sql.SumAndProduct, true])).product AS product#20071
> at org.apache.spark.sql.errors.QueryExecutionErrors$.expressionEncodingError(QueryExecutionErrors.scala:1125)
> {code}
> i dont really understand the error, this result is not a top-level row object.
> anyhow taking the advice to heart and using option we get to the second attempt using options:
> {code:java}
> case class SumAndProduct(sum: Double, product: Double)
> val sumAndProductAgg = new Aggregator[Double, Option[SumAndProduct], Option[SumAndProduct]] {
> def zero: Option[SumAndProduct] = None
> def reduce(b: Option[SumAndProduct], a: Double): Option[SumAndProduct] =
> b
> .map{ b => SumAndProduct(b.sum + a, b.product * a) }
> .orElse{ Option(SumAndProduct(a, a)) }
> def merge(b1: Option[SumAndProduct], b2: Option[SumAndProduct]): Option[SumAndProduct] =
> b1.map{ b1 =>
> b2.map{ b2 =>
> SumAndProduct(b1.sum + b2.sum, b1.product * b2.product)
> }.getOrElse(b1)
> }.orElse(b2)
> def finish(r: Option[SumAndProduct]): Option[SumAndProduct] = r
> def bufferEncoder: Encoder[Option[SumAndProduct]] = ExpressionEncoder()
> def outputEncoder: Encoder[Option[SumAndProduct]] = ExpressionEncoder()
> }
> val df = Seq.empty[Double]
> .toDF()
> .select(udaf(sumAndProductAgg).apply(col("value")))
> df.printSchema()
> df.show()
> {code}
> this gives:
> {code:java}
> root
> |-- $anon$4(value): struct (nullable = true)
> | |-- sum: double (nullable = false)
> | |-- product: double (nullable = false)
> 16:44:54.998 ERROR org.apache.spark.executor.Executor: Exception in task 0.0 in stage 1493.0 (TID 1930)
> java.lang.AssertionError: index (1) should < 1
> at org.apache.spark.sql.catalyst.expressions.UnsafeRow.assertIndexIsValid(UnsafeRow.java:142)
> at org.apache.spark.sql.catalyst.expressions.UnsafeRow.isNullAt(UnsafeRow.java:338)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
> at org.apache.spark.sql.execution.aggregate.AggregationIterator.$anonfun$generateResultProjection$5(AggregationIterator.scala:260)
> at org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.outputForEmptyGroupingKeyWithoutInput(ObjectAggregationIterator.scala:107)
> {code}
>
--
This message was sent by Atlassian Jira
(v8.20.1#820001)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org