What is the function of broadcast variables in Spark?

In Spark, broadcast variables are used to efficiently send a large, read-only value to all worker nodes, reducing the amount of data that needs to be transferred in each task. The purposes of broadcast variables include:

1. Reduce network transmission: Broadcast variables broadcast a read-only value to all worker nodes, avoiding the need to repeatedly transmit the same data in each task, thus reducing the cost of network transmission.
2. Improve performance by using broadcast variables to cache larger read-only data structures in the memory of each node, allowing each task to directly access this data without the need for multiple transmissions or repeated calculations.
3. Optimizing task parallelism: In certain situations, broadcast variables can assist in optimizing dependencies between tasks, increasing parallelism and efficiency in execution.
4. Save memory space: Using broadcast variables can prevent the repeated creation of the same data structure in each task, thus saving memory space.

In conclusion, the purpose of broadcast variables in Spark is to pass large, read-only values and reduce data transmission costs, thereby improving performance and efficiency.