distributed data manipulation articles

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Articles tagged with distributed data manipulation. There are 5 article(s) corresponding to the tag distributed data manipulation. If you don't find what you're looking for, please check related tags: access pattern, Ad-hoc polymorphism, Akka Distributed Data, Akka examples, Apache Beam configuration, Apache Beam internals, Apache Beam partitioning, Apache Beam PCollection, Apache Beam pipeline, Apache Beam stateful transforms.

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Tree aggregations in Spark

As every library, Spark has methods than are used more often than the others. As often used methods we could certainly define map or filter. In the other side of less popular transformations we could place, among others, tree-like methods that will be presented in this post. Continue Reading →

Per-partition operations in Spark

Spark was developed to work on big amount of data. If big means millions of items. For every item one or several costly operations are done, it'll lead quick to performance problems. It's one of the reasons why Spark proposes operations executed once per partition. Continue Reading →

Transformations in Spark

One of methods generating new RDD consists on applying transformations on already existent RDDs. But transformations not only makes new RDDs but also gives a sense to all data processing. Continue Reading →