An RDD is, essentially, the Spark representation of a set of data, spread across multiple machines, with APIs to let you act on it. An RDD could come from any datasource, e.g. text files, a database via JDBC, etc. The formal definition is: RDDs are fault-tolerant, parallel data structures that let users explicitly persist intermediate results in memory, control their partitioning to optimize ...
I'm just wondering what is the difference between an RDD and DataFrame (Spark 2.0.0 DataFrame is a mere type alias for Dataset[Row]) in Apache Spark? Can you convert one to the other?
Pair RDD is just a way of referring to an RDD containing key/value pairs, i.e. tuples of data. It's not really a matter of using one as opposed to using the other. For instance, if you want to calculate something based on an ID, you'd group your input together by ID. This example just splits a line of text and returns a Pair RDD using the first word as the key [1]: val pairs = lines.map(x ...
Removing duplicates from rows based on specific columns in an RDD/Spark DataFrame Asked 10 years, 11 months ago Modified 2 years, 5 months ago Viewed 252k times
Removing duplicates from rows based on specific columns in an RDD/Spark ...
java - What are the differences between Dataframe, Dataset, and RDD in ...
The nice thing about this approach - it lets user access records in RDD in order. I'm using this code to feed data from RDD into STDIN of the machine learning tool's process.
Spark: Best practice for retrieving big data from RDD to local machine