MapReduce Interview Questions
In this post we will look at MapReduce Interview questions. Examples are provided with explanation.
- What is MapReduce?
- What are the advantages of MapReduce?
- What are the components of MapReduce?
- What is Big Data?
- What are Algorithm?
- What is JobContext Interface in MapReduce?
- What is JobTracker in MapReduce?
- What is Identity Mapper?
- What is a MapReduce Combiner?
- What are the parameters of Mappers and Reducers?
- What is Partition?
- What are Master Nodes and Slave Nodes?
What is MapReduce?MapReduce helps in processing larger sets of data through the servers of Hadoop Cluster.MapReduce consists of two tasks:
Map - used in taking and converting the set of data into another set of data.
Reduce - used in taking the output from one map as input and helps in combining data tuples in small sets of tuples.
What are the advantages of MapReduce?
- Highly Scalable - MapReduce is used in storing and distributing data sets through the servers.
- Cost Effective - MapReduce helps by allowing the data Storage and Processing at minimal prices.
- Security - MapReduce helps the users in operating the data and incorporating HDFS and HBase Security.
What are the components of MapReduce?There are 2 main components of MapReduce:
Main Driver - helps by providing Job Configuration Parameters.
Mapper Class - helps by extending the commands and executing them.
What is Big Data?Big Data contains a large number of datasets which cannot be processed by using Traditional Computing Techniques.It can help collecting and managing the volume of these datasets that can fall into Big Data.
What are Algorithm?There are 2 types of Algorithms:
Mapper Class- inputs and maps, sorts and tokenizes the data.
Reducer Class- used in searching matching pairs and helps in reducing them.
What is JobContext Interface in MapReduce?JobContext Interface is a super interface that gives us read-only view of the Jobs which are provided in the tasks.It contains 2 Sub-Interfaces such as:
MapContext - this context is given to the mapper.
ReduceContext - this context is passed to the reducer.