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https://issues.apache.org/jira/browse/SPARK-52738?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Max Gekk reassigned SPARK-52738:
--------------------------------
Assignee: Bruce Robbins
> Support aggregating TIME type with a UDAF when the underlying buffer is an
> UnsafeRow
> ------------------------------------------------------------------------------------
>
> Key: SPARK-52738
> URL: https://issues.apache.org/jira/browse/SPARK-52738
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 4.1.0
> Reporter: Bruce Robbins
> Assignee: Bruce Robbins
> Priority: Major
> Labels: pull-request-available
>
> Spark gets an error while aggregating a TIME type with a UDAF when the
> underlying aggregation buffer is an unsafe row (i.e., when all fields in the
> schema are considered mutable by {{UnsafeRow}}).
> Assume this code:
> {noformat}
> import org.apache.spark.sql.expressions.{MutableAggregationBuffer,
> UserDefinedAggregateFunction}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.Row
> class ScalaAggregateFunction(schema: StructType) extends
> UserDefinedAggregateFunction {
> def inputSchema: StructType = schema
> def bufferSchema: StructType = schema
> def dataType: DataType = schema
> def deterministic: Boolean = true
> def initialize(buffer: MutableAggregationBuffer): Unit = {
> (0 until schema.length).foreach { i =>
> buffer.update(i, null)
> }
> }
> def update(buffer: MutableAggregationBuffer, input: Row): Unit = {
> if (!input.isNullAt(0) && input.getInt(0) == 50) {
> (0 until schema.length).foreach { i =>
> buffer.update(i, input.get(i))
> }
> }
> }
> def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit = {
> if (!buffer2.isNullAt(0) && buffer2.getInt(0) == 50) {
> (0 until schema.length).foreach { i =>
> buffer1.update(i, buffer2.get(i))
> }
> }
> }
> def evaluate(buffer: Row): Any = {
> Row.fromSeq(buffer.toSeq)
> }
> }
> import scala.util.Random
> import java.time.LocalTime
> val r = new Random(65676563L)
> val data = Seq.tabulate(50) { x =>
> Row((x + 1).toInt, (x + 2).toDouble, (x + 2).toLong,
> LocalTime.parse("23:33:33.123").minusMinutes(x % 1300 + 1))
> }
> val schema = StructType.fromDDL("id int, col1 double, col2 bigint, col3 time")
> val rdd = spark.sparkContext.parallelize(data, 1)
> val df = spark.createDataFrame(rdd, schema)
> val udaf = new ScalaAggregateFunction(df.schema)
> val allColumns = df.schema.fields.map(f => col(f.name))
> df.groupBy().agg(udaf(allColumns: _*)).show(false)
> {noformat}
> It gets this error:
> {noformat}
> warning: 1 deprecation (since 2.13.0); for details, enable `:setting
> -deprecation` or `:replay -deprecation`
> Exception in task 0.0 in stage 0.0 (TID 0)
> org.apache.spark.SparkUnsupportedOperationException:
> [UNSUPPORTED_CALL.WITHOUT_SUGGESTION] Cannot call the method "update" of the
> class "org.apache.spark.sql.catalyst.expressions.UnsafeRow". SQLSTATE: 0A000
> {noformat}
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