So today’s article is specially framed for the purpose of serving the programmers out there. So, with internet serving as one of the best mediums of providing the required information within the blink of an eye. However, while browsing the net we stumble across loads of articles which doesn’t helps the user to meet the level of requirement. Therefore, a lot of time, energy as well as data is consumed in the process of hunting the required info without the assurance of getting the things done right on time.
Considering this situations, here we have mentioned the best articles you can go through at just a single click, without wasting you precious time, energy and data.
So below are the 10 best Hadoop articles from 2016 that you should read:
- Spark vs Hadoop : not enemies but sidekicks:
Ok, so a lot of you might be thinking that, as far as the big data management is concerned, spark and Hadoop act as the main ingredient in its vitality. Since both of them play a crucial role in the overall structure of big data management, therefore people assume these two to be tough competitors of one another. Whereas the truth is that these two complement each other, and output is unbeatable when both of them are combined together. Because of such assumptions, people usually fall into a dilemma that weather they should be practicing spark or they should be emphasizing more on Hadoop. To get your answers in detail you can refer the following link:
http://www.kdnuggets.com/2015/08/big-data-question-hadoop-spark.html
- How much java is required to learn Hadoop?
So many people before falling into the category of professional programmers usually get confused because they aren’t aware of how much java is required to learn Hadoop. Here the answer is both a YES and a NO. Here it is important to understand that what is the programmer deciding for his profession?
In case they want to use Hadoop like pig they don’t need to have an in-depth knowledge of java. Whereas is they are planning to pursue their career in MapReduce they with have to have a hive knowledge of java. For information regarding the importance of java in Hadoop you can refer the flowing link:
https://www.dezyre.com/article/-how-much-java-is-required-to-learn-hadoop/103
3).how big data analyses helped increase Walmart’s sales turnover?
Walmart! A very well-known name all over the world, concerned with retailing worldwide. When it comes to technology people usually seek for a demo, and what could be a better example other than Walmart!
A company’s success is interpreted to be a result of its quality of products it sells, with the aid of its management. But has anybody ever wondered that why so many technicians are concerned with a brand which is particularly known for retailing?
Follow the link below to get an insight to your questions:
https://www.dezyre.com/article/how-big-data-analysis-helped-increase-walmart-s-sales-turnover/109
4). Hadoop: which version to choose:
Since Hadoop has its various versions available in the market, therefore people tend to get confuse about the kind of version which would be suitable for their organizations. Considering this situation below is a link that would clear your doubts and give you an ultimate solution of choosing the appropriate version for your organization.
http://www.hadoop360.com/blog/hadoop-whose-to-choose
5) The accelerating fame of Hadoop:
We all know that Hadoop is an excellent platform for storage of data, now the question arises that are the capabilities of Hadoop only confined up to its storage capacities or there is anything beyond that?
Technology is developed to put the associated tasks at ease therefore to harness it properly it is important to know its qualities. Below is the link which would provide you the complete information about Hadoop’s capabilities:
6) The best books based on Hadoop, big data and apache:
Not everybody relies on the information provided over the internet, or the fragments provided by some random people, for such people below is the link which would help them to have a complete knowledge about Hadoop, big data and apache , all of them in their pockets:
http://www.analyticsvidhya.com/blog/2015/10/books-big-data-hadoop-apache-spark/
7) Requirements of Hadoop:
With the rising popularity of Hadoop, a large number of organizations have starting installing Hadoop. Unknown and ignorant of the fact that Hadoop being there latest big data processing technology people usually don’t understand the importance of having the latest equipments need by Hadoop to run. Therefore people assume Hadoop to be yet another experimental technology. Below is the link that would give you an insight of the requirements run Hadoop:
http://www.smartdatacollective.com/paige-roberts/321761/hadoop-can-t-do
8) Predictions by data expert:
Since Hadoop made it big in the year 2015, based on those performances many experts have made a few predictions based on Hadoop, and the organizations which harness it the way it should be. Read the article below to know more:
https://datafloq.com/read/22-data-experts-share-their-predictions-for-2016/1751
9) Hadoop’s biggest challenges:
Many Hadoop deplorers aren’t satisfied by the way Hadoop gives the output, which is mostly lower than what the organizations expected. Many organizations use the wrong version of Hadoop, some use outdated equipment’s whereas some people hire the people who aren’t capable of, managing the big data management. Therefore after the mismanagement from the deplorer’s side Hadoop is mostly considered to be at fault. Read the article below to have a clear vison of what it takes Hadoop to run successfully:
https://dzone.com/articles/what-are-the-biggest-hadoop-challenges
10) the most common Hadoop practices:
Hadoop is used by professionals in an organization to manage big data efficiently. However people tend to get confuse amongst the different versions of Hadoop and the manner in which it is deployed by the organizations to undertake its various projects. Below is an article of the projects undertaken by the used of different versions of Hadoop which has also become a common practice in various organizations: