X) Functional Programming and Big Data

A language where each line of code calls a function, which is made up of other functions or result in a value. • Statements are written as a series of functions. • Each accepts input data as arguments and returns an output.

A language that declares or specifies what properties a result should have. Example; Functional Programming.

A language where the programmer specifies the steps that must be carried out in order to achieve a result.

• Code is much easier to write. • Easier for the programmer to understand. • Easier to predict how the program will run. • Used for writing programs which take advantage of parallel processing.

Refers to the way in which an expression is created.

A domain is a set of data of the same type, which are the inputs of the function. A Co-domain is a set of values from which the outputs of a function must be drawn.

Functional languages such as Haskell use types such as; Integer, FLOAT, Bool & Char. Typeclasses are sets of types, e.g. Num; Includes, Integer + Float.

A first-class object is any object that can be used as an argument or result of a function call. These objects can be assigned to a variable, assigned as an argument and can be returned in a function call.

In a procedual program the following statement is able to be executed: x = 5 x = x + 1 In a functional programming language, the value of a variable cannot change. Variables are immutable and the program is said to be stateless.

The only thing a function can do is calculate and return a result, it has no SIDE EFFECTS. On the other hand, not being able to change the value of an object, results in the function returning the same result.

The process of giving particular inputs to a function. Example: add3integers x y z = x + y + z add3integers :: integer [2] -> (integer [4] -> ( integer [5] -> integer [11] ) ) add3integers 2 4 5 11

Big data is data that is collected on such a large scale that it cannot be easily analysed. Large organisations collect and use big data, such as the police, NHS and the government.

Volume- the amount of data being collected is on a very large scale. Variety- the type of data being collected is wide, can be difficult to classify. Velocity- the data changes quickly and may include constant changes in data sources.

Map and reduce operations can be efficiently paeallelised, many processors can work simultaneously on parts of a dataset without affecting other parts.

Can represent the structure and relationships between data items.

The process of calculating the result of a function by passing it some data to produce an output.