Big Data is one of the recently and greatly used solution systems in different organizations. Some of the common job opportunities available in this field are in Data Analyst, Database administrator, Big Data Engineer, Data Scientist, Database administrator, Hadoop Big Data Engineer, etc.
The biggest benefit Big Data provides companies is that it increases their revenue and interaction with customers and clients. Some of the other advantages include its efficient way of resolving various business glitches. With regard to this, many recruiters are in the hunt for individuals who have the right technical knowledge along with adequate work experience.
In order to find the right candidate companies ask a diverse range of Big Data interview questions to not only freshers but also to the experienced individuals wishing to display their talent and knowledge in this field. Here are some important Big Data interview questions that will not only give you a basic idea of the field but also help to clear the interview.
Big Data is a term related to large and complex data sets. Big Data is required in order to manage and perform different operation on a wide set of data.
The five important V’s of Big Data are:
Hadoop and Big Data are nearly equivalent terms with respect to each other. However, with the ascent of Big Data, Hadoop has also been commonly used. It is a system, which has practical experience in Big Data and also performs additional tasks. Experts can utilize this system in order to break down Big Data and help organizations to make further decisions.
Big Data has been widely used by a number of organizations in order to increase their business revenue. It is done by helping organizations to distinguish themselves from other competitors in the market. Big Data provides organizations with customized suggestions and recommendations through a series of predictive analysis. Big Data also allows organizations to release new products in accordance with the needs of the customer and their preferences. All these factors contribute to the increase in revenue of a particular business.
The three essential steps involved in Big Data are:
Data Ingestion is the first step of Big Data Solutions. This step refers to the extraction of data from different sources. Different sources data could include CRM, for instance, Salesforce; RDBMS such as MySQL, various Enterprise Resource Planning Systems such as SAP other with other log files, social media feeds, documents, papers, etc. All the data that is extracted is then stored in HDFS.
Data Storage is the next step in Big Data Solutions. In this step, the data is extracted from the first step is stored in HDFS or NoSQL database, also known as HBase. The HDFS storage is widely used for sequential access. On the contrary, HBase is used for random read or write access.
Data Processing is the final step of Big Data Solutions. In this step, with the help of different processing frameworks, the data is processed. Various processing frameworks used are Pig, MapReduce, Spark, etc.
The components of HDFS include:
The components of YARN include:
Hadoop is mainly used for Big Data Analysis for the following benefits:
In order to recover a NameNode, following steps need to be carried out:
Some of the common input formats used in Hadoop include:
Some of the different modes used in Hadoop are:
The core components used in Hadoop include:
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