Ericsson SSE Interview Questions and Answers

MapReduce is a programming model used in Hadoop for processing large datasets in parallel.

• MapReduce breaks down a big data processing task into smaller chunks that can be processed in parallel.

• The 'map' phase processes input data and produces key-value pairs.

• The 'reduce' phase aggregates the key-value pairs generated by the map phase.

• MapReduce is fault-tolerant and scalable, making it ideal for processing large dataset...read more

Multithreading can be used to process large files efficiently by dividing the work among multiple threads.

• Divide the file into smaller chunks and assign each chunk to a separate thread for processing.

• Use synchronization techniques to ensure data integrity and avoid race conditions.

• Consider using a thread pool to manage the creation and execution of threads efficiently.

• Example: Reading a large CSV file and processing ea