Unless you’ve been living under the rock, you must have heard or read the term – Big Data. But many people don’t know what Big Data actually means. Even if they do then the definition of the same is not clear to them. If you’re one of them then don’t be disheartened. By the time you complete reading this very article, you will have a clear idea about Big Data and its terminology.
What is Big Data?
In very simple words, Big Data is data of very big size which can not be processed with usual tools like file systems & relational databases. And to process such data we need to have distributed architecture. In other words, we need multiple systems to process the data to achieve a common goal.
Here are the top Apache Spark interview questions and answers. There is a massive growth in the big data space, and job opportunities are skyrocketing, making this the perfect time to launch your career in this space.
Our experts have curated these questions to give you an idea of the type of questions which may be asked in an interview. Hope these Apache Spark interview questions and answers guide will help you in getting prepared for your next interview.
Spark Interview Questions
1. What is Apache Spark and what are the benefits of Spark over MapReduce?
Spark is really fast. If run in-memory it is 100x faster than Hadoop MapReduce.
In Hadoop MapReduce, you write many MapReduce jobs and then tie these jobs together using Oozie/shell script. This mechanism is very time consuming and MapReduce tasks have heavy latency. Between two consecutive MapReduce jobs, the data has to be written to HDFS and read from HDFS. This is time-consuming. In case of Spark, this is avoided using RDDs and utilizing memory (RAM). And quite often, translating the output of one MapReduce job into the input of another MapReduce job might require writing another code because Oozie may not suffice.
In Spark, you can basically do everything from single code or console (PySpark or Scala console) and get the results immediately. Switching between ‘Running something on cluster’ and ‘doing something locally’ is fairly easy and straightforward. This also leads to less context switch of the developer and more productivity.
Spark kind of equals to MapReduce and Oozie put together.
Watch this video to learn more about benefits of using Apache Spark over MapReduce.
The advancements in the field of Big Data & Artificial Intelligence (AI) are occurring at an unprecedented pace and everyone from researchers to engineers to common folk are wondering how their lives will be affected. While almost all industries are estimating significant disruption from advancements in Big Data & AI, I believe the industry that will actually experience the maximum impact will be the Automotive or Transportation industry. Here is my perspective on how Big Data & AI will change the Automotive & Transportation industry landscape. It should appeal to engineers as well as to common folk interested in technological developments. I will discuss the challenges, existing solutions and will propose two alternative solutions.
Artificial Intelligence (AI) is the buzzword that is resounding and echoing all over the world. While large corporations, organizations & institutions are publicly proclaiming and publicizing their massive investments toward development and deployment of AI capabilities, people, in general, are feeling perplexed regarding the meaning and nuances of AI. This blog is an attempt to demystify AI and provide a brief introduction to the various aspects of AI to all such persons, engineers, non-engineers & beginners, who are seeking to understand AI. In the forthcoming discussion, we will explore the following questions:
What is AI & what does it seek to accomplish?
How will the goals of AI be accomplished, through which methodologies?
CloudxLab is proud to announce its partnership with TechMahindra’s UpX Academy. TechM’s e-learning platform, UpX Academy, delivers courses in Big Data & Data Sciences. With programs spanning over 6-12 weeks and covering in-demand skills such as Hadoop, Spark, Machine Learning, R and Tableau, UpX has tied up with CloudxLab to provide the latest to its course takers.
Run by an excellent team, we at CloudxLab are in awe of the attention UpX pays to the users needs. As Sandeep (CEO at CloudxLab) puts it, “We were not surprised when UpX decided to come on board. Their ultimate interest is in keeping their users happy and we are more than glad to work with them on this.”
Adding to an already impressive list of collaborations, International School of Engineering (INSOFE) has recently signed up with CloudxLab (CxL). This move will enable INSOFE’s students to practice in a real world scenario through the cloud based labs offered by CloudxLab.
INSOFE’s flagship program, CPEE – Certificate Program in Engineering Excellence – was created to transform “individuals into analytics professionals”. It is listed at #3 between Columbia and Stanford at #2 and #4 respectively, and holds the distinction of being the only institute outside the US to hold a spot in this list by CIO.com. This within an admirable 3 years of inception. Having established itself as one of the top institutes globally, INSOFE is ceaselessly on the look out for innovative ways to engage and enhance student experience.
In a recent strategic partnership that demonstrates SCMHRD’s superior vision in pedagogy, the Post Graduate Program in Business Analytics (PGPBA) has tied up with well known learning innovation firm CloudxLab. With this partnership, SCMHRD’s students will get to learn and work with Big Data and analytics tools in the same manner that enterprises learn and use them.
SCMHRD’s flagship Analytics program PGPBA with its emphasis on Big Data analytics, as opposed to standard analytics, makes it relevant to a bigger gamut of employers and hence the better choice. This emphasis isn’t easy to cater to. Providing Big Data tools to learners entails providing a cluster (a bunch of computers) that they can practice on which in turn translates to expensive infrastructure, big support teams, and the operational costs that go with everything.
