Description
I am trying to run a pivot transformation which I ran on a spark1.6 cluster,
namely
sc.parallelize(Seq((2,3,4), (3,4,5))).toDF("a", "b", "c")
res1: org.apache.spark.sql.DataFrame = [a: int, b: int, c: int]
scala> res1.groupBy("a").pivot("b").agg(count("c"), avg("c")).na.fill(0)
res2: org.apache.spark.sql.DataFrame = [a: int, 3_count(c): bigint, 3_avg(c): double, 4_count(c): bigint, 4_avg(c): double]
scala> res1.groupBy("a").pivot("b").agg(count("c"), avg("c")).na.fill(0).show
-------------------------------
a | 3_count(c) | 3_avg(c) | 4_count(c) | 4_avg(c) |
-------------------------------
2 | 1 | 4.0 | 0 | 0.0 |
3 | 0 | 0.0 | 1 | 5.0 |
-------------------------------
after upgrade the environment to spark2.0, got an error while executing .na.fill method
scala> sc.parallelize(Seq((2,3,4), (3,4,5))).toDF("a", "b", "c")
res3: org.apache.spark.sql.DataFrame = [a: int, b: int ... 1 more field]
scala> res3.groupBy("a").pivot("b").agg(count("c"), avg("c")).na.fill(0)
org.apache.spark.sql.AnalysisException: syntax error in attribute name: `3_count(`c`)`;
at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.e$1(unresolved.scala:103)
at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.parseAttributeName(unresolved.scala:113)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveQuoted(LogicalPlan.scala:168)
at org.apache.spark.sql.Dataset.resolve(Dataset.scala:218)
at org.apache.spark.sql.Dataset.col(Dataset.scala:921)
at org.apache.spark.sql.DataFrameNaFunctions.org$apache$spark$sql$DataFrameNaFunctions$$fillCol(DataFrameNaFunctions.scala:411)
at org.apache.spark.sql.DataFrameNaFunctions$$anonfun$2.apply(DataFrameNaFunctions.scala:162)
at org.apache.spark.sql.DataFrameNaFunctions$$anonfun$2.apply(DataFrameNaFunctions.scala:159)
at scala.collection.TraversableLike$$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.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:159)
at org.apache.spark.sql.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:149)
at org.apache.spark.sql.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:134)