Hadoop is an open-source framework that allows distributed storage and processing of big data. If you’re preparing for an exam, or interview, or just looking to refresh your Hadoop knowledge, you’re in the right place! Below is a compilation of 25 multiple-choice questions (MCQs) that cover the fundamental concepts of Hadoop.
1. What does HDFS stand for?
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HDFS stands for Hadoop Distributed File System. It is designed to store a large volume of data across multiple machines in a Hadoop cluster.
2. What is the default block size in HDFS?
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The default block size in HDFS is 128 MB. This large block size facilitates the storage and processing of big data.
3. Who is the primary developer of Hadoop?
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The Apache Software Foundation is the primary developer of Hadoop. The project is open-source and community-driven.
4. Which of the following is not a core component of Hadoop?
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Spark is not a core component of Hadoop. While it can run on Hadoop and process data from HDFS, it is a separate project.
5. What does YARN stand for?
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YARN stands for Yet Another Resource Negotiator. It is the resource management layer for Hadoop, managing and scheduling resources across the cluster.
6. What is the purpose of the JobTracker in Hadoop?
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The JobTracker is responsible for scheduling and keeping track of MapReduce jobs in a Hadoop cluster. It allocates resources and monitors job execution.
7. What is a DataNode in HDFS?
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A DataNode in HDFS is responsible for storing the actual data blocks. DataNodes are the workhorses of HDFS, providing storage and data retrieval services.
8. What is the NameNode responsible for in HDFS?
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The NameNode manages metadata and the namespace of the HDFS. It keeps track of the file system tree and metadata for all the files and directories.
9. What programming model does Hadoop use for processing large data sets?
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Hadoop uses the MapReduce programming model for distributed data processing. It involves a Mapper phase for filtering and sorting data and a Reducer phase for summarizing the data.
10. What is the primary language for developing Hadoop?
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Hadoop is primarily written in Java, and the core libraries are Java-based. Although you can write MapReduce programs in other languages, Java is the most commonly used.
11. Which of the following can be used for data serialization in Hadoop?
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Avro is a framework for data serialization in Hadoop. It provides functionalities for data serialization and deserialization in a compact and efficient binary or JSON format.
12. Which Hadoop ecosystem component is used as a data warehousing tool?
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Hive is used as a data warehousing tool in the Hadoop ecosystem. It facilitates querying and managing large datasets residing in distributed storage using SQL-like language called HiveQL.
13. What is the role of ZooKeeper in the Hadoop ecosystem?
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ZooKeeper is used for cluster coordination in Hadoop. It provides distributed synchronization, maintains configuration information, and provides group services.
14. Which tool can be used to import/export data from RDBMS to HDFS?
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Sqoop is a tool designed to transfer data between Hadoop and relational database systems. It facilitates the import and export of data between HDFS and RDBMS.
15. Which of the following is not a function of the NameNode?
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The NameNode does not store actual data blocks. Instead, it manages the file system namespace, keeps metadata information, and handles client requests related to these tasks.
16. What is the replication factor in HDFS?
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The replication factor in HDFS refers to the number of copies of a data block that are stored. By default, this number is set to three, ensuring data reliability and fault tolerance.
17. Which of the following is a scheduler in Hadoop?
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Oozie is a scheduler in Hadoop. It's a server-based workflow scheduling system to manage Hadoop jobs.
18. Which daemon is responsible for MapReduce job submission and distribution?
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ResourceManager is responsible for the allocation of resources and the management of job submissions in a Hadoop cluster. It plays a pivotal role in the distribution and scheduling of MapReduce tasks.
19. What is a Combiner in Hadoop?
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A Combiner in Hadoop acts as a local reducer, operating on the output of the Mapper phase, before the data is passed to the actual Reducer. It helps in reducing the amount of data that needs to be transferred across the network.
20. In which directory Hadoop is installed by default?
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By default, Hadoop is installed in the /usr/local/hadoop directory. However, this can be changed based on user preferences or system requirements.
21. Which of the following is responsible for storing large datasets in a distributed environment?
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HBase is a distributed column-oriented database built on top of HDFS (Hadoop Distributed File System). It's designed to store large datasets in a distributed environment, providing real-time read/write access.
22. In a Hadoop cluster, if a DataNode fails:
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In Hadoop's HDFS, data is protected through replication. If a DataNode fails, the NameNode is aware of this and will ensure that the data blocks from the failed node are re-replicated to other available nodes to maintain the system's fault tolerance.
23. Which scripting language is used by Pig?
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Pig uses a high-level scripting language called "Pig Latin". It's designed for processing and analyzing large datasets in Hadoop.
24. What does "speculative execution" in Hadoop mean?
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Speculative execution in Hadoop is a mechanism to enhance the reliability and speed of the system. If certain nodes are executing tasks slower than expected, Hadoop might redundantly execute another instance of the same task on another node. The task that finishes first will be accepted.
25. What is the role of a "Shuffler" in a MapReduce job?
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In the MapReduce paradigm, after the map phase and before the reduce phase, there is an essential step called the shuffle and sort. The shuffling phase is responsible for sorting and grouping the keys of the intermediate output from the mapper before they are presented to the reducer.