The MapReduce programming model is at the heart of large scale data processing in the Hadoop ecosystem. Born out of the need to handle vast amounts of data, MapReduce allows for distributed processing across large datasets. For those taking their first steps in the world of Hadoop and distributed computing, this beginner-centric quiz on MapReduce is the perfect starting point. Let’s dive in!
1. What does MapReduce primarily focus on?
Answer:
Explanation:
While HDFS handles data storage in the Hadoop ecosystem, MapReduce is concerned with data processing across distributed systems.
2. Which phase comes first in a MapReduce job?
Answer:
Explanation:
In the MapReduce model, the "Map" phase precedes the "Reduce" phase. The Combine and Shuffle & Sort phases come in between.
3. What is the role of the Mapper function in MapReduce?
Answer:
Explanation:
The Mapper's primary role is to process input data and break it down into key-value pairs for further processing.
4. The Reduce phase of MapReduce is responsible for:
Answer:
Explanation:
The Reduce phase aggregates or summarizes the key-value pairs provided by the Map phase based on keys.
5. Which component decides the number of reduce tasks?
Answer:
Explanation:
The JobTracker determines the number of reduce tasks based on the configuration. It is responsible for managing and monitoring MapReduce tasks in the cluster.
6. Which step takes place between the Map and Reduce phases?
Answer:
Explanation:
After the Map phase, the Shuffle and Sort step ensures that data belonging to a single key goes to the same reducer.
7. The _______ ensures that only relevant key-value pairs go to a particular Reducer.
Answer:
Explanation:
The Partitioner's role is to make sure that all data for a single key gets sent to the same Reducer, ensuring efficient data processing.
8. What is the primary purpose of the Combiner in a MapReduce job?
Answer:
Explanation:
The Combiner performs a local reduce task on the data generated by the Mapper, which can optimize network traffic.
9. Which of the following languages can be used to write a MapReduce program?
Answer:
Explanation:
While MapReduce was originally developed in Java, one can use streaming to write MapReduce programs in other languages like Python.
10. If no Combiner is specified in a MapReduce job, what happens?
Answer:
Explanation:
If no Combiner is set, there's no local aggregation after the Map phase, so all aggregation is done in the Reduce phase.
11. In a MapReduce job, if you set the number of reducers to zero, what would happen?
Answer:
Explanation:
Setting the number of reducers to zero means no Reduce tasks will run, and the system will only execute the Map phase.