Ajay Gupta takes us through join operations in Apache Spark:
Join operations are often used in a typical data analytics flow in order to correlate two data sets. Apache Spark, being a unified analytics engine, has also provided a solid foundation to execute a wide variety of Join scenarios.
At a very high level, Join operates on two input data sets and the operation works by matching each of the data records belonging to one of the input data sets with every other data record belonging to another input data set. On finding a match or a non-match (as per a given condition), the Join operation could either output an individual record, being matched, from either of the two data sets or a Joined record. The joined record basically represents the combination of individual records, being matched, from both the data sets.
Click through for more information on the mechanics of joining, including trade-offs between types of physical join operators.