The correct answer is: B. Hadoop stores data in HDFS and supports data compression/decompression.
Hadoop is a distributed processing framework that allows for the processing of large datasets across a cluster of commodity hardware. HDFS (Hadoop Distributed File System) is a distributed file system that stores data in a redundant manner across multiple nodes in the cluster. This makes it ideal for storing large datasets that need to be accessed by multiple users. Hadoop also supports data compression/decompression, which can be used to reduce the size of data files and improve the performance of Hadoop jobs.
Option A is incorrect because Hadoop is not an ideal environment for extracting and transforming small volumes of data. Hadoop is designed for processing large datasets, and it can be inefficient to use it for processing small datasets.
Option C is incorrect because the Giraph framework is a graph processing framework that is more useful than a MapReduce job to solve graph and machine learning problems. Giraph can efficiently process large graphs, and it provides a number of features that are useful for graph processing, such as support for parallel processing and iterative algorithms.
Option D is incorrect because all of the statements are correct.