Big data is processed using relational databases.

Question:- A.     Big data is processed using relational databases.

False

True

B.   Which value is not an argument to the “hello” function?

def hello(name):

print (“Hey,”, name)

hello(John”)

hello( “Mya”)

Answer

A. False.

Generally, big data is not processed using traditional relational databases. Structured, predefined data models and schemas are designed for relational databases like SQL. They may not be able to effectively handle the size, variety and speed of big data. NoSQL databases, distributed file systems like Hadoop, in-memory computing and other technologies meant to handle the processing of large volumes of unstructured or semi structured data from various sources are commonly used. Big data processing is better supported by NoSQL databases like MongoDB and Cassandra, which provide more flexibility and scalability. Real-time stream processing at scale can be achieved through technologies such as Kafka and Spark . Most big data applications are ill-suited for relational databases, as they use rigid schemas and have scalability limitations.

B. This implies that value “John” is no valid argument to the hello () function # Finding the hello() function that accepts a single parameter named name which is of string value. The name parameter is the second one when calling the function, there we should pass a string in quotes. For example:

hello(“John”)

If John were unquoted value such syntax error would have passed, because the programming language interprets as a variable and not string literal. The other two function calls:

hello(“Mya”)

and

hello(“John”)

string values enclosed in quotes are valid, as they pass the name argument. Now, “John” without quotes is the value that cannot be accepted as a valid argument to hello ( ) . Since the name attribute is a string, we will have to enclose the name in quotes when invoking this function so as not to receive an error.