Pyspark error when running window function (Spark 2.1.0 reporting issue with column not found)?

Update: I created the following JIRA issue: https://issues.apache.org/jira/browse/SPARK-20086    Status: Fixed! (over the weekend! it was amazingly fast!)

Update2: This issue is fixed https://github.com/apache/spark/pull/17432 versions 2.1.1, 2.2.0

. So, I got a new version of spark from nightly compilations at http://people.apache.org/~pwendell/spark-nightly/ You will probably run into this issue anyway if you are on <=2.1.0

.

Original post:

I am getting an error when working with the pyspark window function. here is some sample code:

import pyspark
import pyspark.sql.functions as sf
import pyspark.sql.types as sparktypes
from pyspark.sql import window

sc = pyspark.SparkContext()
sqlc = pyspark.SQLContext(sc)
rdd = sc.parallelize([(1, 2.0), (1, 3.0), (1, 1.), (1, -2.), (1, -1.)])
df = sqlc.createDataFrame(rdd, ["x", "AmtPaid"])
df.show()

      

        
        
        
      

    

gives:

+---+-------+
|  x|AmtPaid|
+---+-------+
|  1|    2.0|
|  1|    3.0|
|  1|    1.0|
|  1|   -2.0|
|  1|   -1.0|
+---+-------+

      

        
        
        
      

    

next, calculate the total

win_spec_max = (window.Window
                .partitionBy(['x'])
                .rowsBetween(window.Window.unboundedPreceding, 0)))
df = df.withColumn('AmtPaidCumSum',
                   sf.sum(sf.col('AmtPaid')).over(win_spec_max))
df.show()

      

        
        
        
      

    

gives

+---+-------+-------------+
|  x|AmtPaid|AmtPaidCumSum|
+---+-------+-------------+
|  1|    2.0|          2.0|
|  1|    3.0|          5.0|
|  1|    1.0|          6.0|
|  1|   -2.0|          4.0|
|  1|   -1.0|          3.0|
+---+-------+-------------+ 

      

        
        
        
      

    

next, calculate the cumulative maximum,

df = df.withColumn('AmtPaidCumSumMax', sf.max(sf.col('AmtPaidCumSum')).over(win_spec_max))

df.show()

      

        
        
        
      

    

provides error log

 Py4JJavaError: An error occurred while calling o2609.showString.

      

        
        
        
      

    

with tracing:

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-215-3106d06b6e49> in <module>()
----> 1 df.show()

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in show(self, n, truncate)
    316         """
    317         if isinstance(truncate, bool) and truncate:
--> 318             print(self._jdf.showString(n, 20))
    319         else:
    320             print(self._jdf.showString(n, int(truncate)))

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/java_gateway.pyc in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/utils.pyc in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

      

        
        
        
      

    

but interesting enough, if I introduce another change before the sencond window works, say by inserting a column, then it won't give this error:

df = df.withColumn('MaxBound', sf.lit(6.))
df.show()
+---+-------+-------------+--------+
|  x|AmtPaid|AmtPaidCumSum|MaxBound|
+---+-------+-------------+--------+
|  1|    2.0|          2.0|     6.0|
|  1|    3.0|          5.0|     6.0|
|  1|    1.0|          6.0|     6.0|
|  1|   -2.0|          4.0|     6.0|
|  1|   -1.0|          3.0|     6.0|
+---+-------+-------------+--------+


#then apply the second window operations
df = df.withColumn('AmtPaidCumSumMax', sf.max(sf.col('AmtPaidCumSum')).over(win_spec_max))
df.show()

+---+-------+-------------+--------+----------------+
|  x|AmtPaid|AmtPaidCumSum|MaxBound|AmtPaidCumSumMax|
+---+-------+-------------+--------+----------------+
|  1|    2.0|          2.0|     6.0|             2.0|
|  1|    3.0|          5.0|     6.0|             5.0|
|  1|    1.0|          6.0|     6.0|             6.0|
|  1|   -2.0|          4.0|     6.0|             6.0|
|  1|   -1.0|          3.0|     6.0|             6.0|
+---+-------+-------------+--------+----------------+   

      

        
        
        
      

    

I don't understand this behavior

ok, so far so good, but then I try another operation and then I get a similar error again:

def _udf_compare_cumsum_sll(x):
    if x['AmtPaidCumSumMax'] >= x['MaxBound']:
        output = 0
    else:
        output = x['AmtPaid']
    return output


udf_compare_cumsum_sll = sf.udf(_udf_compare_cumsum_sll, sparktypes.FloatType())
df = df.withColumn('AmtPaidAdjusted', udf_compare_cumsum_sll(sf.struct([df[x] for x in df.columns])))
df.show()

      

        
        
        
      

    

gives

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-18-3106d06b6e49> in <module>()
----> 1 df.show()

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in show(self, n, truncate)
    316         """
    317         if isinstance(truncate, bool) and truncate:
--> 318             print(self._jdf.showString(n, 20))
    319         else:
    320             print(self._jdf.showString(n, int(truncate)))

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/java_gateway.pyc in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/utils.pyc in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling o91.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 36.0 failed 1 times, most recent failure: Lost task 0.0 in stage 36.0 (TID 645, localhost, executor driver): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: AmtPaidCumSum#10

      

        
        
        
      

    

I wonder if someone can reproduce this behavior ...

here is the full log.

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-69-3106d06b6e49> in <module>()
----> 1 df.show()

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/dataframe.pyc in show(self, n, truncate)
    316         """
    317         if isinstance(truncate, bool) and truncate:
--> 318             print(self._jdf.showString(n, 20))
    319         else:
    320             print(self._jdf.showString(n, int(truncate)))

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/java_gateway.pyc in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134
   1135         for temp_arg in temp_args:

/Users/<>/spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/utils.pyc in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/Users/<>/.virtualenvs/<>/lib/python2.7/site-packages/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling o703.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 119.0 failed 1 times, most recent failure: Lost task 0.0 in stage 119.0 (TID 1817, localhost, executor driver): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: AmtPaidCumSum#2076
    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:88)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:87)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:287)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5$$anonfun$apply$11.apply(TreeNode.scala:360)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.immutable.List.map(List.scala:285)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:358)
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:277)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:87)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$$anonfun$bind$1.apply(GenerateMutableProjection.scala:38)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$$anonfun$bind$1.apply(GenerateMutableProjection.scala:38)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.AbstractTraversable.map(Traversable.scala:104)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.bind(GenerateMutableProjection.scala:38)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.generate(GenerateMutableProjection.scala:44)
    at org.apache.spark.sql.execution.SparkPlan.newMutableProjection(SparkPlan.scala:353)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1$1.apply(WindowExec.scala:203)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1$1.apply(WindowExec.scala:202)
    at org.apache.spark.sql.execution.window.AggregateProcessor$.apply(AggregateProcessor.scala:98)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2.org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1(WindowExec.scala:198)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$6.apply(WindowExec.scala:225)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$6.apply(WindowExec.scala:222)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1$$anonfun$16.apply(WindowExec.scala:318)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1$$anonfun$16.apply(WindowExec.scala:318)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1.<init>(WindowExec.scala:318)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14.apply(WindowExec.scala:290)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14.apply(WindowExec.scala:289)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: Couldn't find AmtPaidCumSum#2076 in [sum#2299,max#2300,x#2066L,AmtPaid#2067]
    at scala.sys.package$.error(package.scala:27)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:94)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:88)
    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
    ... 62 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
    at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112)
    at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
    at sun.reflect.GeneratedMethodAccessor83.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: null
    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:88)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:87)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:287)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5$$anonfun$apply$11.apply(TreeNode.scala:360)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.immutable.List.map(List.scala:285)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:358)
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:277)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:87)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$$anonfun$bind$1.apply(GenerateMutableProjection.scala:38)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$$anonfun$bind$1.apply(GenerateMutableProjection.scala:38)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.AbstractTraversable.map(Traversable.scala:104)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.bind(GenerateMutableProjection.scala:38)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.generate(GenerateMutableProjection.scala:44)
    at org.apache.spark.sql.execution.SparkPlan.newMutableProjection(SparkPlan.scala:353)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1$1.apply(WindowExec.scala:203)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1$1.apply(WindowExec.scala:202)
    at org.apache.spark.sql.execution.window.AggregateProcessor$.apply(AggregateProcessor.scala:98)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2.org$apache$spark$sql$execution$window$WindowExec$$anonfun$$processor$1(WindowExec.scala:198)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$6.apply(WindowExec.scala:225)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$windowFrameExpressionFactoryPairs$2$$anonfun$6.apply(WindowExec.scala:222)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1$$anonfun$16.apply(WindowExec.scala:318)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1$$anonfun$16.apply(WindowExec.scala:318)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14$$anon$1.<init>(WindowExec.scala:318)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14.apply(WindowExec.scala:290)
    at org.apache.spark.sql.execution.window.WindowExec$$anonfun$14.apply(WindowExec.scala:289)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:99)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    ... 1 more
Caused by: java.lang.RuntimeException: Couldn't find AmtPaidCumSum#2076 in [sum#2299,max#2300,x#2066L,AmtPaid#2067]
    at scala.sys.package$.error(package.scala:27)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:94)
    at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:88)
    at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
    ... 62 more