Resilient Distributed Datasets (RDDs) are a distributed memory abstraction that allows programmers to perform in-memory computations on large clusters while retaining the fault tolerance of data flow models like MapReduce.
I am a novice to spark, and I want to transform below source dataframe (load from JSON file): +--+-----+…
python apache-spark dataframe apache-spark-sql rddRDD has a meaningful (as opposed to some random order imposed by the storage model) order if it was processed …
apache-spark rddI'm getting confused about spill to disk and shuffle write. Using the default Sort shuffle manager, we use an appendOnlyMap …
apache-spark rdd shuffleI am trying to perform matrix multiplication using Apache Spark and Java. I have 2 main questions: How to create RDD …
java scala apache-spark rdd apache-spark-mllibI am an Apache Spark learner and have come across a RDD action aggregate which I have no clue of …
scala apache-spark rddWhat is the syntax to reverse the ordering for the takeOrdered() method of an RDD in Spark? For bonus points, …
apache-spark rddI have an RDD which I am creating by loading a text file and preprocessing it. I dont want to …
python apache-spark pyspark rddI am new to Apache Spark, and I know that the core data structure is RDD. Now I am writing …
position apache-spark rddWill rdd1.join(rdd2) cause a shuffle to happen if rdd1 and rdd2 have the same partitioner?
apache-spark spark-streaming rddI am able to print data in two RDD with the below code. usersRDD.foreach(println) empRDD.foreach(println) I …
apache-spark scala-2.10 cloudera-cdh rdd