Apache Spark Certification 2025 – 400 Free Practice Questions to Pass the Exam

An accumulator in Apache Spark is a special type of shared variable that is used to aggregate or accumulate values across multiple tasks running in a distributed manner. Once created, new tasks can be added to the accumulator using the method designed for that purpose, which in this case is often referred to in documentation as the "add" method or command. This method allows you to increase the accumulator's value by a specified amount, and it ensures that the operation is performed in a thread-safe manner to maintain data integrity.

The use of the "add" command is prevalent in various programming contexts within Spark, particularly for summing counts or aggregating numeric values. This enables functions to contribute to a collective result without needing to manage complex data state manually. It’s essential to understand that while other terms such as "insert," "append," or "update" might imply adding new data or changing existing state, they do not accurately describe the mechanism provided by accumulators in Spark. The emphasis on the correct terminology helps clarify how accumulators function in a distributed system.