在Spark-Scala中将列表或RDD的列表转换为DataFrame

Question

So basically what I am trying to achieve is - I have a table with 4 columns (say) and I expose it to a DataFrame - DF1. Now I want to store each of the row of the DF1 to another hive table (basically DF2 which schema as - Column1, Column2, Column3) while the column3 value will be the '-' delimited row of DataFrame DF1.

val df = hiveContext.sql("from hive_table SELECT *")
val writeToHiveDf = df.filter(new Column("id").isNotNull)

var builder : List[(String, String, String)] = Nil
    var finalOne  =  new ListBuffer[List[(String, String, String)]]()
    writeToHiveDf.rdd.collect().foreach {
      row =>
        val item = row.mkString("-@")
        builder = List(List("dummy", "NEVER_NULL_CONSTRAINT", "some alpha")).map{case List(a,b,c) => (a,b,c)}
        finalOne += builder
    }

Now I have the finalOne as a list of lists, which I want to convert to a dataframe directly or via RDD.

var listRDD = sc.parallelize(finalOne) //Converts to RDD - It works. 
val dataFrameForHive : DataFrame = listRDD.toDF("table_name", "constraint_applied", "data") //Doesn't work

Error :

java.lang.ClassCastException: org.apache.spark.sql.types.ArrayType cannot be cast to org.apache.spark.sql.types.StructType
    at org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:414)
    at org.apache.spark.sql.SQLImplicits.rddToDataFrameHolder(SQLImplicits.scala:94)

Can some one help me understand the right way to convert this to DataFrame. Thanks a ton in advance for your support.

Answer 1

if you want 3 columns of type string in your dataframe, you should flatten your List[List[(String,String,String)]] to List[(String,String,String)] :

var listRDD = sc.parallelize(finalOne.flatten) // makes List[(String,String,String)]
val dataFrameForHive : DataFrame = listRDD.toDF("table_name", "constraint_applied", "data") 

Answer 2

我相信，在将“ finalOne”数据帧传递到sc.parallelize（）函数之前，先将其展平应该会产生符合您期望的结果。

var listRDD = sc.parallelize(finalOne)

val dataFrameForHive : DataFrame = listRDD.toDF("table_name", "constraint_applied", "data")