Spark SQL joins articles

Articles tagged with Spark SQL joins. There are 5 article(s) corresponding to the tag Spark SQL joins. If you don't find what you're looking for, please check related tags: access pattern, Ad-hoc polymorphism, Akka Distributed Data, Akka examples, algorithm analysis, algorithm complexity, Apache Beam configuration, Apache Beam internals, Apache Beam partitioning, Apache Beam PCollection.

Regression tests with Apache Spark SQL joins

Regressions are one of the risks of our profession. Fortunately, we can limit the risk thanks to different testing strategies. One of them are regression tests that we can use to check whether the modified data processing logic didn't introduce the regressions simply by comparing two datasets. Continue Reading →

Shuffle join in Spark SQL

Shuffle consists on moving data with the same key to the one executor in order to execute some specific processing on it. We could think that it concerns only *ByKey operations but it's not necessarily true. Continue Reading →

Broadcast join in Spark SQL

Joining DataFrames can be a performance-sensitive task. After all, it involves matching data from two data sources and keeping matched results in a single place. As you can deduce, the first thinking goes towards shuffle join operation. However, it's not the single strategy implemented in Spark SQL. For some specific use cases another type called broadcast join can be preferred. Continue Reading →