According to the documentation they are exactly the same, but in my queries
dataFrame.cache()
results in much faster execution times vs doing
sqlContext.cacheTable("tableName")
Is there any explanation about this? I am not caching the RDD prior to
creating the dataframe. Using Pyspark on Spark 1.5.2
Kind regards,
George
