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'm working through these two concepts right now and would like some clarity. From working through the command line, I've …
apache-spark pyspark rddI'm looking for a way to split an RDD into two or more RDDs. The closest I've seen is Scala …
apache-spark pyspark rddHow would you perform basic joins in Spark using python? In R you could use merg() to do this. What …
python join apache-spark pyspark rddI am trying to leverage spark partitioning. I was trying to do something like data.write.partitionBy("key").parquet("/location") …
apache-spark spark-dataframe rdd apache-spark-2.0 bigdataI prefer Python over Scala. But, as Spark is natively written in Scala, I was expecting my code to run …
scala performance apache-spark pyspark rddIs there a way to concatenate datasets of two different RDDs in spark? Requirement is - I create two intermediate …
scala apache-spark apache-spark-sql distributed-computing rddI have a simple line: line = "Hello, world" I would like to convert it to an RDD with only one …
python apache-spark pyspark distributed-computing rddThe Spark research paper has prescribed a new distributed programming model over classic Hadoop MapReduce, claiming the simplification and vast …
apache-spark rdd directed-acyclic-graphsI want to create a DataFrame from a list of string that could match existing schema. Here is my code. …
scala apache-spark dataframe rdd union-allI am new to Spark and Scala. I was confused about the way reduceByKey function works in Spark. Suppose we …
scala apache-spark rdd