What is Reduce Function?
Reduce function has been part of many functional programming languages over the years, it has been known by different names like “fold” in some languages but its behavior is similar to that of reduce function.
In a brief, reduce function takes the output of the map function and function as input and reduces the input list in whatever manner the programmer requires. The reduce function applies a certain set of rules derived by the programmer to all the values in the input list.
But before going forward with our journey in understanding reduce function we have to backtrack to understand functional programming and map function.
Features of Reduce function
The reduce function is dependent on the output from the map function for its work. The map takes the original data as input, applies a function to all the elements, and returns a key-value pair in form of a new list.
This list is then taken as input for reduce functions with a set of rules and conditions defined by the programmer. The reduce function takes the output of the map function and reduces it according to the conditions provided by the programmer.
The reduce function first takes the starting value and stores it in an accumulator, the function then proceeds to process each element on the list according to the rules defined. In the end, the reduce function returns a value based on what operations you wanted to perform on the output list.
Reduce function can be run on the output list multiple times due to the features of functional programming with a different set of conditions until the desired result is obtained.
Working of Reduce Function.
- At first 2 elements of the list are picked up and the operation is done on them to obtain the result.
- In the next step, the same operation is applied to the result obtained in the first step and at the next value in the list, the result is stored.
- the same process is repeated until no more elements are left.
- the final result obtained is returned as the output.
Syntax
In general, reduce function reduce() has 2 inputs and run to give out the result. The proper syntax includes,
reduce(function, iterable)
The two-parameter described above is
- The first argument in reduce is function. It is the pre-defined set of rules to be run on all the elements of the iterable, in a cumulative manner to obtain results.
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The second argument in reduce is iterable, they are defined as objects in Python that can be looped/iterated one value at a time this includes lists, arrays, tuples, sets, dictionaries, generators, iterators, etc.
Frequently Asked Questions
Can you reduce a break?
Yes, you can reduce a break by adding .reduce() on any iteration.
What do you mean by a call-back function?
A callback function is a function that is supplied as an input to another function and then invoked inside the outer function to finish a routine or operation.
Explain the use of reduce in Java.
Reduce is a Java terminal operation for aggregating a stream into a type of basic type. Java provides stream APIs containing set of predefined reduction operations such as sum(), average(), count(), min(), and max().
Conclusion
In this article, we have extensively discussed Reduce function in big data, its features, and syntax as well. We hope that this blog has helped you enhance your knowledge regarding the subject of the reduce function in Big Data and how it can be used to process large amounts of data in this article, and if you would like to learn more, check out our other articles on MapReduce. Still, the knowledge never stops, have a look at more related articles: Hadoop, Data Warehouse, MongoDB, AWS, and many more. Do upvote our blog to help other ninjas grow.
Recommended Readings:
Difference Between Procedural and Object Oriented Programming
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