What Makes Spark a Considerable Choice for Hadoop MapReduce?

A recent survey states that the big data professionals having Spark skills have enjoyed hike in their salary. If we consider the statistics from any part of the world, the conclusion will be- to learn Spark. The big data project known as Spark introduced by the Apache Software Foundation has influenced the analytics world with its increasing speed. It won’t’ be wrong to say that now Spark can be seen as a competitor of Hadoop software.

Hadoop Training in Delhi

Understanding the Apache Spark

→ Apache Spark is an excellent framework that is helpful in executing general data analytics over the distributed system as well as computing clusters like Hadoop. Apache Spark enables in-memory computations at higher speed while the low latency data process on MapReduce.

It doesn’t replace Hadoop, rather operates atop the already existing Hadoop cluster for accessing the HDFS or Hadoop Distributed File System. Apache Spark can also process structured data in Hive and streaming data from Twitter, Flume and HDFS. Madrid Software Trainings provides complete practical hadoop training in delhi.

What Makes Spark Stand Out?

It has been observed that Real time stream processing is getting popular among all the big data functions. It means analyze the data as it is captured and feed it back to the user. Spark can also create difference in the field with its amazing speed. It is excellent when it comes to operating machine learning algorithms. These are the most critical reasons why Spark is popular and the demand of Spark developers are on rise.

Hadoop Vs Spark →

If you are aware of the latest trends in the world of big data, you must be aware that Hadoop has been there for quite some time which has made it a most widely used software system for various big data operations. The advent of Spark has created confusion among many enterprises. Having similar features, they both boast of their unique features and can produce great results if worked together. So, if you are making up your mind for Hadoop training, move ahead as it is the right time. Spark big data training will add benefit to your career if you are already involved in Hadoop oriented functions. Madrid Software Trainings is rated as the best hadoop institute in delhi by professionals.

In-depth Overview → 

Whenever there is a discussion on the topic of Hadoop, the comparison with Spark happens. Reason behind Hadoop’s popularity is that the Hadoop Distributed File System or HDFS. At a time, when organizations were apprehensive about their data yet they could not afford the quantity of storage space needed, HDFS brought in an easy solution at reasonable price. The other tools offered by Hadoop like MapReduce were enjoying a decent job. Spark came in and influenced everyone with its speed. It copies the data into faster RAM memory right from the distributed storage system. Spark’s in memory operations happen 100 times faster than similar Hadoop tools. But it does not offer any distributed file storage. So Spark and Hadoop both should work amazingly with each other- Spark for analyzing it in a flash and HDFS for data storage.

Future of Spark →

The main feature of Spark open source software system that appeals users is, it is cheap and affordable. With the type of functionality and speed offered by Spark, it is just a matter of time when the world starts looking for Spark developers. The analytics industry is all set to experience a global shortage of many professionals within coming couple of years. So it is always better to pre plan your career and get enrolled in Spark big data training.

Apache Spark vs. Hadoop MapReduce →

As we know that Apache Spark is helpful in in-memory data processing, while Hadoop MapReduce does I/O operations on the disc after each and every map and reduces actions. It further boosts Spark’s processing speed which can outperform Hadoop MapReduce. 

It can be said that Apache Spark could replace Hadoop MapReduce but when it comes to Spark, it requires a lot more memory. MapReduce ends the processes once the job is accomplished, hence it can operated with some in-disk memory. Apache Spark works well with iterative computations when cached data is used again and again. Hadoop MapReduce operates better with data which doesn’t fit in the memory and while other services need to be executed. Spark is designed for instances where data adjusts in the memory particularly on individual clusters.

Being written in Java, Hadoop MapReduce is difficult to program whereas Apache Spark is known for its flexibility and ease of usage APIs in languages like Scala, Python and Java. Professionals can write user-defined functions in Spark as well and they can even add interactive mode to run commands.

Observing its speed, flexibility and ease of using, Spark can be accepted more widely. Chances are there that it can replace MapReduce. But we cannot ignore the fact that there are still some areas where MapReduce will be in demand, especially when non-iterative computation takes place with availability of limited memory.

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Learning Hadoop with Python Can Bag You a Desired Job with Reputed Enterprises!

There is no doubt accepting that Hadoop is mostly written in Java language but this doesn`t mean anyway excluding the use of other programming languages. Hadoop acts like a distributed storage and processing framework and especially Python is highly recommended to use with it.

Difference between Hadoop and Python

Like it is said earlier Hadoop is basically a database framework that enables users to save and process Big Data by way of programming models. It has developed into an ecosystem of tools and technologies to support Big Data processing.

While Python is a programming language which is nowhere connected to the Hadoop ecosystem. This object oriented language is same as Java or C++. Being flexible and coupled with plenty of resources and libraries, it is suitable for various applications like artificial intelligence, web development or advanced analytics. Madrid Software trainings in association with industry experts provides complete practical hadoop training in delhi.

Significance of Learning Python!

Python is the best recommendation of a programming language which is a must for people who wish to step in the field of Big Data. This high-level programming language is easy to learn which has made it a preferred choice for game developers as well as web developers.

• Unlike Java, C and Perl, Python has easy to grab basics for newbies.
• A programmer coding writes less code in this because it boasts of user-friendly features. This includes simple syntax, code readability and easy implementation.
• Unlike other languages, Python is far easy to debug. Bugs are a threat for every programmer. The unique design of Python lends itself well to programmers that enter in data science. Writing less code denotes to easier debugging. The various programs complied in Python are less likely to issue instead of other languages.
• Python is extensively used in various software packages and industries. Python empowers Google’s search engine, DropBox, YouTube, Quora, FriendFeed, Reddit and Disqus. IBM, NASA and Mozilla rely on Python. If you have got Python skills, you may get a job in reputed companies.
• Python acts as an object-oriented language. A strong understanding of the fundamentals enables you to shift to any other similar language as you will need to learn the syntax of it.
• Python is an open source which appeals startups and small companies. Due to its simplicity, it is highly preferred by small teams. It is a high-performance language which makes it a preferred choice to build business critical applications.
• No matter whether you are an amateur or an expert programmer, you can build a real-world application by using Python.

Reasons Why Companies Prefer Python with Hadoop!

Nowadays, most of companies are seeking out employees with proficiency in Python. Reason being is that Python boasts of versatility of the language’s application. They prefer Hadoop Streaming API coupled with other frameworks to handle Big Data issues using Python language. This utility acts along with Hadoop Distribution. Hadoop streaming enables user to create as well as execute MapReduce jobs along with any script or make it executable according to the mapper or the reducer. Madrid Software Trainings is rated as the best hadoop institute in delhi.

Let’s understand through few examples of how companies are making the most of Hadoop with Python.

Social Media for Face Finding Application

Who has not heard of Facebook, the leading social media platform? It is the foremost research and development with regards to image processing. It has to process enormous unstructured data that is based on image. Facebook eases off HDFS with storing as well as extracting the huge data. It also uses Python for most of image related applications. These include resizing image or extracting facial image. It makes use of Hadoop Streaming API for accessing and editing the data.

Community User Site for Search Algorithm

The popular question and answer site Quora has to manage enormous amount of textual data using Hadoop or Apache Spark and various other data-warehousing technologies. The back end of Quora is developed on Python and that is why it is used for interacting with the HDFS. Quora makes use of Hadoop with Python for extracting question on search or even for suggestion.

Shopping Platform for Recommending Products

Most of us are aware of Amazon which has a great platform for suggesting suitable products to existing users. It studies their search and buying pattern and then produces results. The machine learning engine is built on using Python which interacts with the database system like Hadoop Ecosystem. The two technologies work together to suggest the best products and equally work on fault tolerant database interactions.

Thus, it is evident that if a language is so likable among coders, the employers will surely feel confident about its usage. Disney, the leading Animation enterprise also uses Python and Hadoop to manage clusters for the tasks of image processing as well as CGI rendering. The increasing numbers of popular web sites that are made off using Python will definitely surprising. YouTube, Spotify, Instagram run on Python. The demand is increasing for Python developers around the world. Both big companies and startups express their interest in hiring Hadoop professionals with Python skills.