16 Questions
Hadoop is designed for small-scale data processing.
False
HDFS stands for Hadoop Distributed File System and provides reliable storage.
True
The master node in Hadoop manages the file system namespace and block information.
True
Hadoop follows a distributed computing environment with a master-slave architecture.
True
Each file in Hadoop is stored as a single block on the cluster.
False
The NameNode in Hadoop is responsible for maintaining and managing the file system namespace.
True
NameNode manages and maintains the DataNodes in Hadoop HDFS.
True
DataNode is responsible for serving the client read/write requests in Hadoop HDFS.
True
MapReduce works by breaking the data processing into three phases: Map phase, Shuffle phase, and Reduce phase.
False
Yarn provides resource management for Hadoop through the ResourceManager running on the slave machines only.
False
Hadoop includes additional modules such as Hive, which is a relational, distributed database.
False
Hadoop is commonly used in big data scenarios such as data warehousing, business intelligence, and machine learning.
True
The Edit log in Hadoop contains all the recent changes performed to the file system namespace up to the most recent Fsimage.
True
DataNodes send block reports to NameNode to report the health of HDFS.
True
NameNode takes care of the replication factor of all the blocks in Hadoop HDFS.
True
The Reduce phase in MapReduce is where light-weight processing like aggregation/summation is specified.
True
This quiz covers the main components and functions of Hadoop, an open-source software framework designed for storing and processing large amounts of data in a distributed computing environment. It includes questions about HDFS (Hadoop Distributed File System), the MapReduce programming model, and the parallel processing of large datasets.
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