[SPARK-24019] AnalysisException for Window function expression to compute derivative

• Type: Bug
• Status: Resolved
• Priority: Minor
• Resolution: Incomplete
• Affects Version/s: 2.1.1
• Component/s: SQL
• Labels: bulk-closed

Environment

Ubuntu, spark 2.1.1, standalone.

• Assignee: Unassigned
• Reporter: Barry Becker
• Created: 18/Apr/18 20:25
• Updated: 21/May/19 04:15
• Resolved: 21/May/19 04:15

Description

I am using spark 2.1.1 currently.

I created an expression to compute the derivative of some series data using a window function.

I have a simple reproducible case of the error.

I'm only filing this bug because the error message says "Please file a bug report with this error message, stack trace, and the query."

Here they are:

((coalesce(lead(value#9, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), value#9) - coalesce(lag(value#9, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING), value#9)) / cast((coalesce(lead(sequence_num#7, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), sequence_num#7) - coalesce(lag(sequence_num#7, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING), sequence_num#7)) as double)) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS derivative#14 has multiple Window Specifications (ArrayBuffer(windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW), windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING))).

Please file a bug report with this error message, stack trace, and the query.;
org.apache.spark.sql.AnalysisException: ((coalesce(lead(value#9, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), value#9) - coalesce(lag(value#9, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING), value#9)) / cast((coalesce(lead(sequence_num#7, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), sequence_num#7) - coalesce(lag(sequence_num#7, 1, null) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING), sequence_num#7)) as double)) windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS derivative#14 has multiple Window Specifications (ArrayBuffer(windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW), windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING), windowspecdefinition(category#8, sequence_num#7 ASC NULLS FIRST, ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING))).
Please file a bug report with this error message, stack trace, and the query.;
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:39)
at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:57)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ExtractWindowExpressions$$anonfun$78.apply(Analyzer.scala:1772)

And here is a simple unit test that can be used to reproduce the problem:

import com.mineset.spark.testsupport.SparkTestCase.SPARK_SESSION
import org.apache.spark.sql.Column
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions._
import org.scalatest.FunSuite
import com.mineset.spark.testsupport.SparkTestCase._


/**
* Test to see that window functions work as expected on spark.
* @author Barry Becker
*/
class WindowFunctionSuite extends FunSuite {

val simpleDf = createSimpleData()


test("Window function for finding derivatives for 2 series") {

val window =    Window.partitionBy("category").orderBy("sequence_num")//.rangeBetween(-1, 1)
// Consider the three sequential series points (Xlag, Ylag), (X, Y), (Xlead, Ylead).
// This defines the derivative as (Ylead - Ylag) / (Xlead - Xlag)
// If the lead or lag points are null, then we fall back on using the middle point.
val yLead = coalesce(lead("value", 1).over(window), col("value"))
val yLag = coalesce(lag("value", 1).over(window), col("value"))
val xLead = coalesce(lead("sequence_num", 1).over(window), col("sequence_num"))
val xLag = coalesce(lag("sequence_num", 1).over(window), col("sequence_num"))
val derivative: Column = (yLead - yLag) / (xLead - xLag)

val resultDf = simpleDf.withColumn("derivative", derivative.over(window))

resultDf.show()
assertResult("???") {
  resultDf.collect().map(row => row.mkString(", ")).mkString("\n")
}
}

def createSimpleData() = {
val data = Seq(
(1, "a", 2.1),
(2, "a", 2.4),
(1, "b", 100.0),
(3, "a", 3.7),
(2, "b", 70.0),
(4, "a", 3.6),
(3, "b", 60.0))
SPARK_SESSION.sqlContext.createDataFrame(data).toDF("sequence_num", "category", "value")
}
}