Which of the following about the MapReduce framework is/are correct?Question 7Select one or more:Select one or more:a.The MapReduce framework must be able to handle concurrent transactions, which are common in a distributed computing environment.b.The key/value pairs generated by map workers are directly sent to reduce workers as input.c.A reduce worker can only start a reduce task after all map workers finish their map tasks.d.A reduce worker may start a reduce task while some map workers are still running their map tasks.e.In the MapReduce framework, developers need to handle load balancing by writing code in the map and reduce functions.

The correct statements about the MapReduce framework are:

c. A reduce worker can only start a reduce task after all map workers finish their map tasks. This is because the reduce task needs the output from all map tasks as its input. It cannot start processing until all map tasks are complete.

d. A reduce worker may start a reduce task while some map workers are still running their map tasks. This is possible because of the shuffle and sort phase that happens between the map and reduce tasks. During this phase, the MapReduce framework groups together all key/value pairs with the same key, which can then be processed by a reduce task. This can happen while other map tasks are still running.

The other statements are incorrect:

a. The MapReduce framework does not handle concurrent transactions. It is designed for batch processing of large amounts of data, not for real-time transaction processing.

b. The key/value pairs generated by map

The correct statements about the MapReduce framework are:

c. A reduce worker can only start a reduce task after all map workers finish their map tasks. This is because the reduce task needs the output from all map tasks as its input.

d. A reduce worker may start a reduce task while some map workers are still running their map tasks. This is possible because of the shuffle and sort phase that happens between the map and reduce tasks. The MapReduce framework allows for overlapping of computation and transfer of intermediate data.

The incorrect statements are:

a. The MapReduce framework does not handle concurrent transactions. It is designed for processing large amounts of data in a batch-oriented manner, not for transactional data.

b. The key/value pairs generated by map workers are not directly sent to reduce workers as input. There is a shuffle and sort phase in between where the framework groups all values of the same key together.

e. In the MapReduce framework, developers do not need to handle load balancing by writing code in the map and reduce functions. The framework itself handles the load balancing.