Hadoop interview questions is the widely searched term over the internet. Big companies carry big data and processes to maintain the working of the confidential information of the company. They get millions of data entries in a single day. And all the data collected in the system needs proper processing of the unwanted data.
Many processing frameworks managed the data. But not all are capable of doing so. Many multinational companies use Hadoop. It is an open-source Java-based processing framework where all the data are being collected and processed for the application they are used for.
Hadoop stores all the processed data in a scalable cluster in the field of computer servers. The Hadoop software supports the most advanced analytics. It includes Machine Learning, Predictive Analytics, and Data Mining. It has the capability of handling many forms of vague data. Some are unstructured and structured data. This feature makes it different from the relational database.
The cost of affording the Hadoop is very low. That makes it even more popular in the industry. It also holds the capability to support as many hardware nodes as possible. It can easily handle big data, with ease giving you the best output possible.
Many of the new generation students are drifting to this field. In this rat-race world, where all the companies need a highly skilled engineer. The student is getting mastery in the field they are interested in. They have the core knowledge of molding big, complicated data into a small and simple way. They store all the data in a cluster, which makes this possible.
Let’s draw the attention of every student who is willing to prepare for a Hadoop interview. With some most frequently asked questions that can nail the interview in no time.
Top 10 Hadoop interview questions
What is a Hadoop?
Hadoop is the key solution for every big data stored in the company. It is an open-source Java-based processing framework that works in a cluster for each data set. It provides tools and techniques that are capable of storing and processing enormous data. The reason why Hadoop is used majorly. Because it gives the best decisions based on the data collected for a business. It is one of the basic Hadoop interview questions.
Two main components make Hadoop. They are processing Framework and Storage Unit. The processing framework comprises YARN (Node Manager, Resource Manager) and HDFS (DataNode, NameNode).
What are the basic differences between a relational database and HDFS?
The data types in Hadoop are stored in many different ways, like semi-structured, structured, and unstructured. Whereas in the Relational database, the data types are mostly structured ones. The processing function in Hadoop allows the distribution of data in the cluster in a parallel manner. On the other hand, the processing function in the Relational database is very limited.
There is no cost in using Hadoop in the company as it is an open-source platform. At the same time, there is a cost of charge using the relational database licensed software. The main key feature of using Hadoop is for OLAP system, Data Discovery, and Data analytics. On the other hand, relational database works on Online Transactional Processing (OLTP) system.
What is Big Data, and also mention the five vs of Big Data?
Big Data means assemblages of complex and huge datasets, which hinders the process that is dependable by working traditional data processing and relational database tools applications. Big Data becomes the most chance for companies. It is strenuous to search, transfer, capture, store, curate, share, visualize Big Data and analyze. It is one of the basic Hadoop interview questions.
Now let’s check out the five vs of Big Data.
- Velocity: it refers to the pace of growing data at a certain speed. The data which we collected today about 2 hours ago. It is counted as old data.
- Value: it refers to collecting some useful data from the ocean of big data. Which has some value and benefits.
- Variety: It refers to the different formats of data being collected from big data. That variety can be CSV, Audio, Videos, and much more.
- Volume: It refers to the data which is growing at a rampant rate in a huge amount.
- Veracity: It refers to the unwanted data that has been collected uncertainly from the Big Data. It is very difficult to manage the incomplete data from the pool of Big Data.
Why does one remove or add nodes in a Hadoop cluster frequently?
There are many other cool features in a Hadoop platform. But the most essential is the utilization of commodity hardware. It is responsible for the DataNode crash in the Hadoop cluster. Due to the quick growth in Data volume, another cool feature in Hadoop is the “ease of scale”. These two are responsible for creating decommission (Remove) and commission (Add) DataNodes frequently in a Hadoop cluster.
What is a Checkpoint?
The checkpoint is when a FsImage is edited to a log, and then it gets compacts to make into a new FsImage. The NameNode can load the end final into the memory state right from the FsImage, alternatively replaying the edit log. The reason why this process works brilliantly. It lowers the time taking in NameNode start-up and has good efficiency. It is one of the basic Hadoop interview questions.
What is “speculative execution” in Hadoop?
The master node executes the same task on another node in a more diffuse way, only if the nodes’ execution process is slow. In this case, the task which gets finished first will be approved while the other task will automatically shut down.
What is the difference between an “Input Split” and “HDFS Block”?
The “Input Split” is defined as the logical division of data. At the same time, the “HDFS Block” is defined as the physical division of data. In the processing, the input split uses MapReduce to divide the data and allocate it to the mapper function. Whereas on the other hand, the HDFS comes in a block that divides the data and storing them together.
What is the purpose of “RecordReader” in a Hadoop?
The “RecordReader” is termed as “Input Format”. The “InputSplit” doesn’t show the procedure for using it, but it does give a glimpse of its work. The “RecordReader” collects the data from its source and then transforms it into pairs, which are acceptable by the “Mapper” task for reading. It is one of the basic Hadoop interview questions.
This article will surely help you to understand the basic meaning of Hadoop. And also, it will give you some tips to go through some of the important questions. This article will prepare a candidate for the basic Hadoop interview question. Many students are drifting to this field because of the range of opportunities the software gives. IT sector is the main focus for many students to build their careers.