What is a broadcast join?

A broadcast join is an optimization technique used in distributed data processing frameworks like Apache Spark. In a broadcast join, the smaller dataset is replicated (broadcast) to all worker nodes, while the larger dataset remains partitioned across the cluster. Each node then performs a local join between its partition of the large dataset and the broadcasted small dataset. This eliminates the need for shuffling the large dataset across the network, which is the most expensive operation in distributed joins. Broadcast joins are ideal when one side of the join is significantly smaller than the other (typically less than a few hundred megabytes). Spark automatically decides to broadcast a dataset if it estimates the size to be below a configured threshold, but developers can also manually broadcast using the broadcast() function. The result is faster join performance and reduced network I/O.