Subacini, the short answer is that we don't really support that yet, but the good news is that I can show you how to work around it.
The good thing is that we nowadays internally actually convert the Tuples to Seqs, so we can actually leverage that. The bad thing is that before converting tuples to sequences we extract the static type of the different tuple fields. We need those types when we create the table for you to automatically setup the schema during saveAsTable(). The way around it is to call the underlying API and supply the types of the elements of the sequence (beware, this API might change in the future): // assume "rdd" is of type RDD[Seq[Any]], where the Seq actually consists of two elements, one Int and one String val tableObject = new RDDTableFunctions(rdd, Seq(implicitly[ClassTag[Int]], implicitly[ClassTag[String]])) tableObject.saveAsTable("mySeqTable", Seq("my_int", "my_string")) Hope that helps, Best, Ali On Fri, Mar 21, 2014 at 4:53 PM, subacini Arunkumar <subac...@gmail.com>wrote: > Hi, > > I am able to successfully create shark table with 3 columns and 2 rows. > > > val recList = List((" value A1", "value B1","value C1"), > ("value A2", "value B2","value c2")); > val dbFields =List ("Col A", "Col B","Col C") > val rdd = sc.parallelize(recList) > RDDTable(rdd).saveAsTable("table_1", dbFields) > > > I have a scenario where table will have 60 columns. How to achieve it > using RDDTable. > > I tried creating a List[(Seq[String],Seq[String])] , but it throws below > exception.Any help /pointer will help. > > Exception in thread "main" shark.api.DataTypes$UnknownDataTypeException: > scala.collection.Seq > at shark.api.DataTypes.fromClassTag(DataTypes.java:133) > at shark.util.HiveUtils$$anonfun$1.apply(HiveUtils.scala:106) > at shark.util.HiveUtils$$anonfun$1.apply(HiveUtils.scala:105) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) > at scala.collection.immutable.List.foreach(List.scala:318) > at > scala.collection.TraversableLike$class.map(TraversableLike.scala:244) > at scala.collection.AbstractTraversable.map(Traversable.scala:105) > at shark.util.HiveUtils$.createTableInHive(HiveUtils.scala:105) > at shark.api.RDDTableFunctions.saveAsTable(RDDTableFunctions.scala:63) > > Thanks > Subacini >