The correct answer is: B. SparseArray
A SparseArray is a base layer for all of the sparse indexed data structures. It is a multidimensional array that can store data in a sparse format, which means that only the non-zero values are stored. This makes SparseArray more efficient than a dense array for storing large amounts of data with a lot of missing values.
SArray is a sparse array implementation in Apache Spark. It is a distributed array that can be used to store and process large amounts of data. SArray is based on the SparseArray class in Python, and it provides a number of features that make it well-suited for use in Spark, such as support for distributed processing and efficient storage of sparse data.
PyArray is a Python object that represents a multidimensional array. It is a subclass of the NumPy ndarray object, and it provides a number of methods for manipulating arrays, such as indexing, slicing, and broadcasting. PyArray is a good choice for storing and processing small amounts of data, but it is not as efficient as SparseArray for storing large amounts of data with a lot of missing values.
None of the mentioned is not the correct answer.