Hello Everyone,

This is the last week for my blog writing the work which i need to done are:

• Evaluation
• Weakness and strength
• Problem faced and resolved

In the last and final stage is conclusion in which i will discussing about the overall finding and recommendation.

Side by side i am writing my report also. Few topic i already done and few are left which i have to done in next few days.

So, overall this is my last meeting with my supervisor and my supervisor Mr. Lars really help a lot in this research topic, he is giving me good direction and as his direction finally i reach at peak of my project.

Pending works like the introduction, outline of the project and other few minor works are done in this week.

Thanks for viewing my blog.

Vikas Mahla!

This class was mandatory for everyone. In this class All students who were registered for the project classes they have to attend this Seminar Session.

So, I also attend this class, the discussion is about the Project, like how’s going the project.

In this class Lars had interacted with all students individually and we all discussed about our project.

This class was interesting for me because Students showed different project with different solutions and work.

This was very interesting class for me.

I also discussed on my project like what i am doing in it and about my progress on project.

Lars has given me a chance to speak on the project what i going to build and progress  of my project.

My Supervisor Mr. Lars gave me a good feedback about my project. That’s was quite interesting.

That’s all for this week.

Thank you !

Vikas Mahla

Hello Everyone..

As you can see my topic is based on same like comparison in both tool Apache Spark and Apache Hadoop on Big Data and individual features are to be provided.

In this part of project, apache spark components and Hadoop components are compared and then there is comparison between Apache spark and hadoop.

In this i compares the Hadoop and Apache spark where Hadoop is a structure for the appropriated preparing of huge information crosswise over packets of PCs utilizing MapReduce programming information display. Hadoop is accepted to be dependable, adaptable, and blame tolerant. It is outstanding that MapReduce is a solid match for utilizations of handling huge information, however it is a poor fit for emphasis calculations and low-inactivity calculations on the grounds that MapReduce depends on tireless capacity to give adaptation to internal failure, and requires the whole informational collection to be stacked into framework before running scientific inquiries. So that is the reason Spark was conceived.

Comparison between Hadoop and Apache Spark

Features	Hadoop	Apache Spark
Engine for processing of Data	MapReduce of Hadoop is batch processing engine at the core.	Similarly, Apache Spark is also batch processing Engine at the core.
Language Support	Streaming of Hadoop are supported by C, C++, Python, Java, Perl, Groovy	Languages supported by AS are Scala, Java, R and Python
Language Developed	Java is used for developing Hadoop	Scala is used for developing Spark

More details are provided in my report on same.

 

ThankYou for viewing my blog.

Vikas Mahla

Hello everyone….

This blog is all about ways to analyse the Big Data. In this week i done research on analysis for telecommunication use cases for Apache Hadoop and second part is use cases for apache spark. The work of this week its represent the difference between Apache Spark and Hadoop also.

To the end of this week work directing huge scale examination of specialized help information, the proposed arrangement gives a conclusion with the help of open source Hadoop stage, which is segments of the Hadoop Extended Ecosystem.

This is all in this week, Thank you

Vikas Mahla

Hello Everyone….

As my research Literature review is very huge topic and it takes a lots of time to collecting a good knowledge on these topics. As given time in my project proposal week two and week three are not sufficient to complete the literature review. That’s why i divided literature review in two week and after that also it takes lots of time.

So, in this blog i am going to talk about my second part of literature that mean component of both tools (component of Apache Spark and component of Apache Hadoop)

The following procedure gives the clear picture of the different components of Spark which i discussed deeply in my report.

The following picture showing the Details about each of the components of Apache Hadoop:

Details about each of the components in this image are discussed in my project report. This is all about in this literature review (component of both tools).

ThankYou for look my blog

Vikas Mahla

Hi everyone….

In the last week i had a lots of work from other subject due to that i am not able to too much focus on PRJ702, but, as my last meeting with my supervisor my project has so many changes as compared to what I was thinking when i start working on it. My supervisor (Mr. Lar) play a vital role to take me on right track. As given feedback i have some changed in my work, like i have to add usecases in my work as well as i have to give a description on them. After all these, i am moving forward for the completion my literature review. Some topic which are left in the last literature review are Hadoop and Spark and its components. After in depth research and analysis needs to be performed in order to complete these literature review.

Literature review is very important part of the report so it needs special attention in process of the literature review. I had some problem also but with the help of my respected supervisor Mr. Lar i am able to work on it.

As i already say in last week i had lots of work due to i didn’t that much focus on PRJ702 but i will cover in this upcoming week.

Thank you very much for giving time to my blog……

 

Hi to everyone,

My research topic is taken into further level to the literature review, in the last week my supervisor suggest me some good path to work and achieve my goal in my research and based on the feedback and instruction I started collecting those information from the various sources. Now, i am going to tell about this week work which i done under the literature review. There are some category under this literature review of my research topic like

1 Big data definition and its characterizes

2 Who utilize the Big Data

3 Big data Processing..

4 Apache Spark architecture

All of the above topics are under literature review. In this week i worked completely on the the Big data and its processing.

Thank You for giving time for my blog

Vikas Mahla

Hello everyone, Welcome to my blog.

finally my project started and my topic for the PRJ702 is research based topic and i am giving my best for my project research.

The name of my research topic is Apace Spark vs Apace Hadoop for “Big Data Analysis”. I started to collecting the information for my topic and its easy to get information related to our topic but difficult thing is to get right and good information. I will be collecting information on spark and hadoop individually and come to the final conclusion. In this week i am collecting some good information of my topic.

Thank You…

Vikas Mahla

I got email confirming approval of requested supervisor received and my supervisor is mr. Lars Dam. I assume this mean my project proposal has been accepted also….

Hi Vikas,

Thanks for joining me!

Good company in a journey makes the way seem shorter. — Izaak Walton