Description
Use case: let's say you want to coalesce the RDD underpinning a DataFrame so that you get a certain number of partitions when you go to save it:
RDDsAndDataFrames.scala
val sc: SparkContext // An existing SparkContext. val sqlContext = new org.apache.spark.sql.SQLContext(sc) val df = sqlContext.load("hdfs://examples/src/main/resources/people.avro", "avro") val coalescedRowRdd = df.rdd.coalesce(8) // Now the tricky part, you have to get the schema of the original dataframe: val originalSchema = df.schema val finallyCoalescedDF = sqlContext.createDataFrame(coalescedRowRdd , originalSchema )
Basically, it would be nice to have an "attachRDD" method on DataFrames, that requires a RDD[Row], so long as it has the same schema, we should be good:
SimplierRDDsAndDataFrames.scala
val sc: SparkContext // An existing SparkContext. val sqlContext = new org.apache.spark.sql.SQLContext(sc) val df = sqlContext.load("hdfs://examples/src/main/resources/people.avro", "avro") val finallyCoalescedDF = df.attachRDD(df.rdd.coalesce(8)