HBase is an important component of the Apache Hadoop ecosystem, that is widely used for processing and analyzing large-scale data. As more and more companies adopt big data technologies, there is a rising demand for HBase experts. Studying the below-listed HBase interview questions can help you understand the key concepts and topics that interviewers often focus on. This can improve your chances of performing well in the interview and securing the job. Have a look!
If you're looking for HBase Interview Questions for Experienced or Freshers, you are at the right place. There are a lot of opportunities from many reputed companies in the world. According to research, HBase has gained a major market share. So, You still have the opportunity to move ahead in your career in HBase Development. Mindmajix offers Advanced HBase Interview Questions 2023 that helps you in cracking your interview & acquire a dream career as HBase Developer.
It is one of the best available Database Management systems which are based on Hadoop. As compared to others, it is actually not a relational DBMS and it cannot be considered when it comes to any structured query language. All the clusters are generally managed by a master node in this approach and this is exactly what makes it simply the best.
|Related Article: Introduction to HBase|
One of the best things about Hbase is it is scalable in all aspects and modules. The users can simply make sure of catering to a very large number of tables in a short time period. In addition to this, it has vast support available for all CRUD operations.
It is capable to store more data and can manage the same simply. Also, the stores are column-oriented and there are a very large number of rows and columns available that enable users to keep the pace up all the time.
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There is a total of 3 tombstone markers that you can consider anytime. They are
When there is a need to shift an entire database, this approach generally opts. In addition to this, during the data operations which are large to handle, Hbase can be considered. Moreover, when there are a lot of features such as inner joins and transactions maintenance that need to be used frequently, the Hbase can be considered easily.
There is a special feature known as region replication. There are several replicas available that define the entire region in a table. It is the load balancer in the Hbase that simply makes sure that the replicas are not hosted again and again in the servers with similar regions. This is exactly what makes sure of the high availability of Hbase all the time.
It stands for Write Ahead Log. It is basically a log that is responsible for recording all the changes in the data irrespective of the mode of their change. Generally, it is considered the standard sequence file. It is actually very useful to consider after the issues like a server crash or failure. The users can still access data through it during such problems.
With Hbase, the users are able to simply handle more amount of data through a special component “Region”. It has another component called “Zookeeper” which is mainly responsible for the co-ordination of the maser and the client on the other side. There are “Catalog Tables” which consists of Root and MetaData simply available with them.
No, it is not possible in most cases. When the users actually do so, the cells get invisible and remain present in the server in the form of a tombstone marker. They are generally removed by the compactions periods. The direct deleting doesn’t work in most cases.
Generally, organizations have to work with bulk data. When the same is structured or managed, it is easy to utilize or to deploy for any task. Of course, it cut down the overall time period required to accomplish a task if it is well-managed.
The users are always free to keep up the pace simply with the structured or the properly managed data. There are a lot of other reasons too that matter and always let the users assure error-free outcomes.
They consist of a long series of rows and columns. It seems quite similar to that of a traditional database. There is one element in every table and the same is called the primary key. The columns generally denote an attribute of the concerned objects.
The users must make sure that there are enough nodes and clusters so that Hbase can perform its task reliably and easily. With more nodes, more efficiency can simply be assured by the users.
Yes, it is totally independent of the operating system and the users are free to consider it on Windows, Linux, Unix, etc. the only basic requirement is it should have Java support installed on it.
It is generally done when the users need to use any of the features related to the physical storage assessment. There are no complex restrictions that need to be fulfilled for this.
Well, the first difference is Hbase is not based on schema whereas relation database is. The automated partitioning can easily be done in Hbase while relational databases lack this feature.
There are more tables in Hbase than in the relational database. Also, it is a row-oriented data store while Hbase is a column-oriented data store.
This can be assured by paying attention to the Row key. The users are free to make sure that all the cells with similar row keys can be located to each other and have a presence on a similar server. If the need for defining is realized, the Row key can be considered.
The best part about the Hbase is everything written on the RAM gets stored automatically on the Disk. There are some barring compaction remains present with the same. These compactions can be categorized into two parts and they are major and minor. The major compaction can easily delete the files while there is a restriction on the minor ones for the same.
It is basically a defined storage format for the HBase and generally, it is related to a column family. There is no strict upper limit on them in the column families. The users can easily deploy an Hfile for storing data that belong to different families.
It is possible. Generally, when this is done by the users, the fresh version of data simply occupies the new block size without affecting the old data. The entire old data consume the new one during the compaction.
Both are based on Hadoop but both are different from one another. Hive is generally considered as one of the best available data warehouse infrastructure. The operations of Hbase are limited when compared to the Hive. However, when it comes to handling real-time operations, the Hbase is good. On the other hand, the Hive is preferred only when the querying of data is the prime need.
|Related Article: Hive vs HBase|
At table level, the commonly used commands are drop, list, scan, and disable whereas on the other side, get, put, scan, and increment are the commands related to a record level.
Generally, databases have a huge volume of data to deal with. It is not always possible and necessary that all the data is linked to a single server. There is a central controller and the same should specify the server with which specific data is concerned or placed on.
The same is known as the Region server. It is also considered as a file on the system that lets the users display the defined server names which are associated.
When the users don’t need the Hbase to use the HDFS, this mode can be turned on. It is basically a default mode in the Hbase and the users are generally free to use it anytime they want. Instead of HDFS, the Hbase makes use of a file system when this mode is activated by the user.
It is possible to save a lot of time while enabling this mode during the performance of some important tasks. It is also possible to apply or remove various time restrictions on the data during this mode.
It is basically a Java API that is used for establishing a connection with the Hbase. The users need not worry about anything when it comes to dealing with this problem. Also, the users are free to keep up the pace without worrying about anything about the connectivity when the Hbase shell is deployed.
The following are the features of the Apache Hbase
There are 5 filters in Hbase:
Yes, it is possible. However, when the same task is performed in reverse order, it is not allowed. This is because the column values are generally stored on a disk and their length should be completely defined. Also, the bytes which are related to the value should be written after it.
For performing this task in the reverse order, these values should be stored one more time and this can create compatibility problems and can affect the memory of the Hbase. Thus, it is not allowed.
This is because the users need not worry about defining the data prior to the time. You only need to define the column family name and nothing else. This makes the Hbase a schema-less database.
During any modification or change in the data, it is first sent to a commit log which is also known as WAL. It is after this the data is stored in the memory. In case the data exceed the defined limit, the same is transferred to the disk as an Hfile. The users are free to discard the commit logs and can proceed with the stored data.
It is basically a technique that is useful when it comes to data retention. It is possible for the users to preserve the version of a cell for a defined time period. The same get deleted automatically upon the completion of such a time.
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Ravindra Savaram is a Technical Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.
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