The selection of any programming
language is such a crucial task when we plan to get a software development or
application developed. This is due to the fact that there is a specific
language over which the performance and the success of that particular software
Among various programing
languages, here we will talk about one of the most trendy languages that is Python. Python is indeed one of the
most famous programming languages which has been considered to be the most
suitable language for Machine learning
development because its coding structure is easy to understand.
The simplicity of Python is what
makes it so popular!
Let’s look at some of its
Here in this blog, we will share
some words about the connection between Big data and Python. Before diving too
much into the exact difference, let’s know little about what Big Data is.
What is Big data?
Big data as the name suggests, is basically the analysis of big data by
discovering hidden patterns or extracting information from it. So it is
basically a huge information analytic where the analysis is completed on huge
Big data is known as the process
in which we collect and analyze the large volume of data sets (called Big Data)
which helps in discovering useful hidden patterns and other information such as
customer choices, market trends, etc. which is really beneficial for the
organizations to remain informed and taking customer-oriented business
Big data takes care of the
extreme volume of data, different types of data types and the velocity at which
the data must be processed. Big data helps in taking better business decisions
as well as the future steps that should be taken by the organization.
Why Python is best for Big data?
The reason behind
why Python is the best language for Big Data is that Python has a lots of
libraries to work on big Data. Python is much better in comparison
to other languages in terms of developing code for Big Data because Python is
having shorter codes that can be managed easily. These two aspects are enabling
developers worldwide to embrace Python as the language of choice for Big Data
Moreover, it is very easy to
manage any data type in Python. Let’s prove this by providing a simple example.
In the below image where you can
see that the data type of ‘a’ is string and the datatype of ‘b’ is an integer.
Here the advantage is that there is no need to manage the data type. It is
already managed by Python.
I would like to recommend Python
for Big data because if we talk about other languages like Java, if you write
200 lines of code, the same thing can be done in just 20 lines of code with
Python. According to various developers, Java is much better than Python, but
according to my personal experience and observations, I can say that Python is
much better for Big Data because when you are working with a huge amount of
data, the performance could be seen the same with Python as well as with java
but Python is more time saving.
From this above-given brief
description, it could be said that Python is an excellent tool and a perfect
fit as python big data combination for data analysis for the following reasons:
Less is More
Python is able to to make programs
work in the least lines of code. It automatically helps identifying and
associating data types and follows an indentation based nesting structure.
In a nutshell, it could be better to say
that the language is too easy to complete the process within a shorter span of
time. You can compute data in commodity machines, laptop, cloud, desktop,
basically everywhere as there is no
limitation to the data processing.
There was a time when Python was
considered to be a slower language in comparison to some of its counterparts
like Java and Scala but with Anaconda platform it has caught up to speed. Since
then it became one of the most simple and famous languages for software
Python is known as an open-source
programming language which is developed with the help of using a
community-based model. As python is an open source language so it is able to
support multiple platforms and apart from this, it can be run on Windows and
Python is a famous programming
language in fields like scientific computing in both academic and multiple
industry. There are a large number of well-tested analytics libraries which
consists of packages like
- Numerical computing
- Data analysis
- Statistical analysis
- Machine learning
Compatibility with Hadoop
The reason why Python is
compatible with Hadoop is that both Hadoop and Python are open-source big data
platforms. So, this is the main reason why Python is more compatible with
Hadoop instead of other languages. Combining these both, the Pydoop package
provides you an access to the HDFS API for Hadoop and hence allows to write
Hadoop MapReduce programs and applications.
In order to connect your program
to an HDFS installation, you can make use of HDFS API, so it will become easy
and possible to read, write and obtain information on files, directories, and
global file system properties.
In order to solve complex
problems with minimal programming efforts, Pydoop offers MapReduce API thus
helping to solve all your issues. This API can be used to seamlessly apply
advanced data science concepts like ‘Counters’ and ‘Record Readers’.
Talking about the speed and the
performance of the Python, it could be said that Python is a high-level
programming language so it has been considered to be one of the most suitable
language for the software development as it accelerates the code really well.
As it supports prototyping ideas which is really helpful for making coding fast
and understanding while keeping in mind the transparency between code and the
As the code is readable and
transparent, this helps in the maintenance of the code and the process and
finally, this all makes the development environment so easy.
Python supports advanced data
structures as it is an object-oriented programming language. The things which
are being managed by Python are lists,
sets, tuples, dictionaries and many more. Apart from this, it helps in
supporting many scientific computing operations like matrix operations, data
frames, etc. All these specifications and abilities of Python helps in
enhancing the scope in order to simplify and speed up data operations.
With the help of Python language,
you can get support for image and voice data because it is having an inbuilt
feature of supporting data processing for unstructured and unconventional data.
This could be considered one of the major requirements in big data while
talking about the social media data.
In a nutshell, it is true that
Python is one of the simplest languages having simple and readable codes which
makes it most suitable for Big Data analysis.
The above-mentioned points are properly highlighting the benefits of Python for Big Data as well as they are also mentioning the strong bond between The Big Data and the Python. So, keeping in mind these facts, it is suggested here that if you want to enjoy the benefits of Python with Big Data, then hire python developers from good python web development companies who would be able to understand your needs.
Without stretching much time, take a further step to do good big data analysis with the help of Python.