It would be great if you could try with the 2.0.2 RC. Thanks for creating an issue.
On Wed, Nov 9, 2016 at 1:22 PM, Raviteja Lokineni < raviteja.lokin...@gmail.com> wrote: > Well I've tried with 1.5.2, 1.6.2 and 2.0.1 > > FYI, I have created https://issues.apache.org/jira/browse/SPARK-18388 > > On Wed, Nov 9, 2016 at 3:08 PM, Michael Armbrust <mich...@databricks.com> > wrote: > >> Which version of Spark? Does seem like a bug. >> >> On Wed, Nov 9, 2016 at 10:06 AM, Raviteja Lokineni < >> raviteja.lokin...@gmail.com> wrote: >> >>> Does this stacktrace look like a bug guys? Definitely seems like one to >>> me. >>> >>> Caused by: java.lang.StackOverflowError >>> at org.apache.spark.sql.execution.SparkPlan.prepare(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at scala.collection.immutable.List.foreach(List.scala:381) >>> at org.apache.spark.sql.execution.SparkPlan.prepare(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at scala.collection.immutable.List.foreach(List.scala:381) >>> at org.apache.spark.sql.execution.SparkPlan.prepare(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at scala.collection.immutable.List.foreach(List.scala:381) >>> at org.apache.spark.sql.execution.SparkPlan.prepare(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$prepare$1.apply(SparkPlan.scala:195) >>> at scala.collection.immutable.List.foreach(List.scala:381) >>> >>> >>> On Wed, Nov 9, 2016 at 10:48 AM, Raviteja Lokineni < >>> raviteja.lokin...@gmail.com> wrote: >>> >>>> Hi all, >>>> >>>> I am not sure if this is a bug or not. Basically I am generating weekly >>>> aggregates of every column of data. >>>> >>>> Adding source code here (also attached): >>>> >>>> from pyspark.sql.window import Window >>>> from pyspark.sql.functions import * >>>> >>>> timeSeries = sqlContext.read.option("header", >>>> "true").format("org.apache.spark.sql.execution.datasources.csv.CSVFileFormat").load("file:///tmp/spark-bug.csv") >>>> >>>> # Hive timestamp is interpreted as UNIX timestamp in seconds* >>>> days = lambda i: i * 86400 >>>> >>>> w = (Window() >>>> .partitionBy("id") >>>> .orderBy(col("dt").cast("timestamp").cast("long")) >>>> .rangeBetween(-days(6), 0)) >>>> >>>> cols = ["id", "dt"] >>>> skipCols = ["id", "dt"] >>>> >>>> for col in timeSeries.columns: >>>> if col in skipCols: >>>> continue >>>> cols.append(mean(col).over(w).alias("mean_7_"+col)) >>>> cols.append(count(col).over(w).alias("count_7_"+col)) >>>> cols.append(sum(col).over(w).alias("sum_7_"+col)) >>>> cols.append(min(col).over(w).alias("min_7_"+col)) >>>> cols.append(max(col).over(w).alias("max_7_"+col)) >>>> >>>> df = timeSeries.select(cols) >>>> df.orderBy('id', 'dt').write\ >>>> >>>> .format("org.apache.spark.sql.execution.datasources.csv.CSVFileFormat")\ >>>> .save("file:///tmp/spark-bug-out.csv") >>>> >>>> >>>> Thanks, >>>> -- >>>> *Raviteja Lokineni* | Business Intelligence Developer >>>> TD Ameritrade >>>> >>>> E: raviteja.lokin...@gmail.com >>>> >>>> [image: View Raviteja Lokineni's profile on LinkedIn] >>>> <http://in.linkedin.com/in/ravitejalokineni> >>>> >>>> >>> >>> >>> -- >>> *Raviteja Lokineni* | Business Intelligence Developer >>> TD Ameritrade >>> >>> E: raviteja.lokin...@gmail.com >>> >>> [image: View Raviteja Lokineni's profile on LinkedIn] >>> <http://in.linkedin.com/in/ravitejalokineni> >>> >>> >> > > > -- > *Raviteja Lokineni* | Business Intelligence Developer > TD Ameritrade > > E: raviteja.lokin...@gmail.com > > [image: View Raviteja Lokineni's profile on LinkedIn] > <http://in.linkedin.com/in/ravitejalokineni> > >
