Top 50+ Hbase Interview Questions And Answers

50+ [REAL-TIME] Hbase Interview Questions And Answers

Last updated on 15th Feb 2024, Popular Course

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Sindhu (Database Developer - HBase )

Sindhu is a highly skilled Database Developer Expert boasting over 8 years of extensive experience in various facets of HBase, including architecture design, data modeling, Java programming, seamless integration within the Hadoop ecosystem, meticulous performance tuning, and in-depth understanding of NoSQL database principles.

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HBase, a component within the Apache Hadoop ecosystem, is a distributed and scalable database system tailored for managing extensive volumes of structured data across multiple commodity hardware nodes. Engineered for real-time applications, it ensures swift access to data with low latency. Embracing a column-oriented storage approach, HBase incorporates features like automatic sharding, replication, and fault tolerance, rendering it a favored solution for big data scenarios demanding high throughput and scalability.

1. Enumerate the essential HBase critical structures.

Ans:

The row key and Column key are HBase’s primary and most basic vital structures. They are the two main critical structures in HBase. Both can communicate meaning by using the data they store or by using their sorting order. These keys will be used in the ensuing sections to address frequent issues encountered during the design of storage systems.

2. When might one employ HBase?

Ans:

  • Because it can process many operations per second on big data sets, HBase is employed when random read and write operations are required.
  • Strong data consistency is provided via HBase.
  • On top of a cluster of commodity hardware, it can manage huge tables with billions of rows and millions of columns.

3. How is the get() method used?

Ans:

  • The data is read from the table using the get() method. Unlike Hive, HBase uses a database for real-time operations instead of MapReduce jobs. HBase partitions the tables and then further divides them into column families.
  • Two distinct Hadoop-based technologies are Hive and HBase: Hive is a NoSQL key/value database for Hadoop, whereas HBase is a SQL-like engine used for MapReduce tasks. 

4. Explain the distinction between HBase and Hive?

Ans:

Feature HBase Hive
Purpose NoSQL distributed database for real-time, random access to large-scale structured data. Data warehousing infrastructure for running SQL-like queries on large datasets stored in HDFS.
Data Model Column-oriented storage model. Row-oriented storage model.
Query Language NoSQL (e.g., HBase API). SQL-like (HiveQL).
Latency Low-latency access to individual records. Higher latency due to batch processing.
Schema Dynamic schema, schema-on-read. Static schema, schema-on-write.

5. Describe the HBase data model.

Ans:

HBase consists of:

  • A group of tables.
  • Rows and column families make up each table.
  • Row essential performances 

as an HBase primary key, which is used for all access to HBase tables. Every column qualifier in HBase indicates properties related to the object that is contained in the cell.

6. Enumerate the many kinds of filters that Apache HBase offers.

Ans:

The available filters are:

  • ColumnPrefixFilter.
  • TimestampsFilter.
  • PageFilter.
  • MultipleColumnPrefixFilter.
  • ColumnPaginationFilter.
  • SingleColumnValueFilter.
  • RowFilter.

7. Describe the use of the HColumnDescriptor class.

Ans:

The HColumnDescriptor class serves as a crucial container for vital details regarding a column family within HBase. It encapsulates essential attributes like the count of versions, configurations for compression, and various parameters necessary during table creation or column addition. By encapsulating these details, it provides a comprehensive blueprint for managing column families efficiently within the HBase architecture, ensuring optimal performance and data organization.

8. Could you elaborate on what Thrift is?

Ans:

Thrift is a remote procedure call (RPC) framework developed by Facebook for scalable cross-language services development. It enables efficient communication between different programming languages, facilitating seamless integration across diverse systems. By defining data types and service interfaces in a platform-independent manner, Thrift streamlines the process of building robust and interoperable distributed systems.

9. Are you familiar with HBase Nagios?

Ans:

Yes, HBase Nagios is a monitoring tool designed specifically for HBase. It integrates with Nagios to provide real-time monitoring and alerting capabilities for HBase clusters. With HBase Nagios, administrators can track cluster health, performance metrics, and detect potential issues proactively, ensuring smooth operation of HBase deployments.

10. What are the HBase instructions for manipulating data?

Ans:

  • put: This command enters a cell value in a given table at a given row and column.
  • obtain: Retrieves the contents get Retrieves data from a cell or a row.
  • delete: This command removes a table cell’s value.
  • deleteall: Removes every cell in a specified row.
  • scan: Returns the table data after scanning.
  • The function count counts and gives the total number of rows in a table.
  • truncate: This command removes, drops, and recreates a given table.

11. In HBase, what code is used to establish a connection?

Ans:

To establish an HBase connection, use the code below:

import org.apache.hadoop.hbase.client.Connection;

import org.apache.hadoop.hbase.client.ConnectionFactory;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.hbase.HBaseConfiguration;

Configuration config = HBaseConfiguration.create();

Connection connection = ConnectionFactory.createConnection(config);

This code initializes the HBase configuration and creates a connection using the ‘ConnectionFactory’.

12. Explain what “REST” means in HBase.

Ans:

The acronym REST stands for Representational State Transfer, which provides semantics so that a protocol may be used universally to efficiently identify distant resources. Additionally, it supports a number of message types, making it easy for a client application to communicate with the server.

13. What occurs in HBase when a delete command is issued?

Ans:

In HBase, a delete command for a cell, column, or column family is not immediately erased. A gravestone marker has been added. In addition to regular data, a tombstone is a type of designated data that is stored. This tombstone hides all of the erased data. The actual data is removed during a significant compaction. HBase combines and recommits a region’s smaller HFiles to a new HFile during considerable Compaction. The same column families are grouped in the new HFile throughout this process. 

14. What kind of tombstone markers are there in HBase?

Ans:

  • Version Marker: Designates for deletion only one iteration of a column.
  • Column Marker: Designates all versions of the column as being marked for deletion.
  • Family Marker: Designates all of the columns in the column family as being marked for deletion.

15. Could you elaborate on the fundamental idea of HBase Fsck?

Ans:

The HBase Fsck class or hack is the sole way to use the tool hack that comes with the database. It is used to examine region consistency, troubleshoot table integrity issues, and fix all HBase-related issues. That has been tainted. 

There are two modes of operation for HBase Fsck: 

  • A read-only inconsistency identifying the mode
  • A read-write repair mode with multiple phases

16. Which command launches the HBase Shell program?

Ans:

The HBase shell is executed with the./bin/hbase shell command. Run this command inside the HBase directory. Status gives information about HBase’s current state, such as the number of servers.

Version: Gives the HBase version that is in use.

table_help – Offers assistance with commands related to tables.

whoami – Offers details about the individual

17. How is HBase structured?

Ans:

The three primary parts of the HBase architecture are Zookeeper, Region Server, and HMaster. HMaster is the HBase implementation of the Controller Server. During this process, regions are assigned to region servers and DDL (new, delete table) operations are carried out. It keeps an eye on every instance of the Region Server in the cluster.

18. What does MSLAB stand for in total?

Ans:

MSLAB stands for MemStoreLAB, which is a memory allocation mechanism within Apache HBase. It optimizes memory usage by allocating contiguous memory blocks for MemStore data structures. This helps reduce memory fragmentation and improves performance by reducing garbage collection overhead. MSLAB is a critical component for enhancing the efficiency and scalability of HBase’s write operations.

19. Can you write down the described command’s syntax?

Ans:

  • The table name in hbase> describe is the syntax for the describe command. Petabytes of data can be accessed and scaled over thousands of machines with HBase’s design. 
  • Massive data sets can be accessed online using HBase thanks to the scalability of Amazon S3 and the elasticity of Amazon EC2.

20. What is Fsck in HBase?

Ans:

The HBaseFsck class implements the hack tool included with HBase. The tool HBaseFsck (hack) is used to examine for issues with table integrity and Region consistency and fix a damaged HBase. It functions in two primary modes: multi-phase read-write correction and read-only inconsistency identification.

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    21. What’s REST?

    Ans:

    • Representational State Transfer, or Rest, establishes the protocol’s semantics so that it can be used generally to access remote resources. 
    • Additionally, it offers support for many message formats, giving a client application a variety of options for interacting with the server.

    22. Why does HBase utilize the shutdown command?

    Ans:

    The shutdown command in HBase can terminate a cluster. HBase’s design allows for the access and scaling of petabytes of data over thousands of machines. Thanks to EC2 and Amazon S3’s scalability, Amazon’s flexibility allows HBase to support online access to large data sets.

    23. Why is the tools command in HBase essential to use?

    Ans:

    The tools command in HBase lists the HBase surgery tools. HBase’s design allows for access to and scaling of petabytes of data over thousands of machines. Massive data sets can also be accessed online using HBase, thanks to the scalability of Amazon S3 and the elasticity of Amazon EC2.

    24. What is ZooKeeper used for?

    Ans:

    • The ZooKeeper manages the configuration data and communication between region servers and clients. 
    • Furthermore, distributed synchronization is offered. Via session communication, it aids in the upkeep of the server state within the cluster. 
    • Zookeeper receives a continuous heartbeat from each Region Server and HMaster Server at regular intervals, allowing it to determine whether servers are online and operational. 
    • Additionally, it notifies server failures so that corrective action can be taken.

    25. In HBase, define catalogue tables.

    Ans:

    In HBase, catalogue tables are responsible for keeping the metadata up to date. An HBase table consists of multiple regions, which are the fundamental units of work. These regions manage a contiguous range of rows and are essential for distributing data across the cluster. The map-reduce framework uses regions as splits for parallel processing, enabling efficient data processing.

    26. How does HBase define Compaction?

    Ans:

    HBase aggregates HFiles to minimize storage and the quantity of disk searches required for a read. We refer to this procedure as Compaction. Compaction selects and aggregates certain HFiles from a region. Two different kinds of compactions exist.

    • Minor Compaction: HBase selects and recommits smaller HFiles to larger HFiles on its own.
    • Major Compaction involves HBase merging and recommitting a region’s smaller HFiles.
    • An updated HFile.

    27. How does the HColumnDescriptor class get used? And explain any filter.

    Ans:

    An HColumnDescriptor stores details about a column family, such as the number of versions and compression settings. It is used as input when building a table or adding a column.

    • KeyOnlyFilter: requires no input. Gives back the critical component of every key-value pair.
    • FamilyFilter: requires a comparator and comparison operator. It uses the comparison operator to compare each family name with the comparator; if the comparison is successful, it returns all of the key values for that family.
    • CustomFilter: By implementing the Filter class, you can make a custom filter. 

    28. In HBase, which filter takes the page size as a parameter?

    Ans:

    PageFilter takes a page size parameter. This implementation of the filter interface restricts results to a given page size. As soon as the number of rows that the filter has passed exceeds the specified page size, the scanning process ends.

    PageFilter () is the syntax.

    29. List the various operating modes for HBase.

    Ans:

    • Standalone Mode: Runs HBase without Hadoop, suitable for development and testing.
    • Pseudo-Distributed Mode: Operates HBase with Hadoop in a single-node cluster for development and small-scale deployments.
    • Fully-Distributed Mode: Deploys HBase across multiple nodes in a cluster, suitable for production environments.
    • Backup Mode: Temporarily suspends writes to HBase tables for backup and restore operations.
    • Read-only Mode: Restricts HBase to read-only access, useful for maintenance or troubleshooting tasks.

    30. Which filters are offered by Apache HBase?

    Ans:

    • ColumnPrefixFilter: accepts a column prefix as its only input. It only gives back the fundamental values found in the column that begins with the prefix for the column that is specified.
    • TimestampsFilter: requires a timestamp list. The fundamental values whose timestamps coincide with any of the given timestamps are returned.
    • PageFilter: accepts a single parameter, the page size. The page size and number of rows from the table are returned.
    • MultipleColumnPrefixFilter: Any column that begins with one of the designated column prefixes will have its critical values returned.
    • ColumnPaginationFilter: requires an offset and a limit as inputs. After the offset number of columns, it returns the limit number of columns. This is carried out for every row.

    31. How would you use joins in an HBase database?

    Terabytes of data can be processed in a scalable manner by HBase using MapReduce jobs. Although joins aren’t supported directly, join queries can be used to retrieve data from HBase tables. The best use case for HBase is to store non-relational data that can be retrieved through the HBase API. You can insert, remove, and query data saved in HBase using familiar SQL syntax by using Apache Phoenix, which is frequently used as an SQL layer on top of HBase.

    32. How Is the Write Failure Handled by HBase?

    Ans:

    Large distributed systems frequently experience failures, and HBase is not an anomaly. In the event that the server housing an unflushed MemStore crashes. The information that was stored in memory but did not yet persist is gone. HBase prevents such from happening by writing to the WALL before the write completion. Every server is included in the group.

    33. From which three locations is data reconciled during HBase reading before returning the value?

    Ans:

    • The Scanner searches the Block cache for the Row cell before reading the data. Here are all of the key-value pairs that have been read recently.
    • Since the MemStore is the write cache memory, if the Scanner is unable to locate the needed result, it proceeds there. There, it looks for the most current files that haven’t been dumped into HFile yet.
    • Lastly, it will load the data from the HFile using block cache and bloom filters.

    34. Is data versioning comprehensible, i

    Ans:

    HBase implicitly saves a new version of a cell whenever you execute an operation on it. All cell operations—creation, modification, and deletion—are handled the same way and result in new versions. During the significant Compaction, additional records are discarded from cells that have more versions than allowed. You can work on a particular version within a cell rather than erasing it whole. 

    35. Describe Row Key.

    Ans:

    In HBase, the RowKey serves as a unique identifier assigned to each row in a table. It is used to logically group related cells together, ensuring that all cells with the same RowKey are stored on the same server. This facilitates efficient access and retrieval of data associated with a particular RowKey. Internally, the RowKey is represented as a byte array, which provides flexibility in terms of the types of data that can be used as RowKeys, such as strings, numbers, or composite keys. 

    36. In your opinion, what are the strongest arguments in favour of using Hbase as the DBMS?

    Ans:

    • One of Hbase’s strongest features is its scalability in terms of modules and all other factors. 
    • Simply said, users can ensure that a large number of tables are served in a brief amount of time. Furthermore, it offers extensive support for all CRUD functions.
    • It can handle the same tasks with ease and can store more data. 
    • Additionally, users can maintain a constant pace because the stores are column-oriented and have a huge number of rows and columns available.

    37. In the HBase, how many tombstone markers are there? Identify them.

    Ans:

    In HBase, there are three types of tombstone markers used to handle deletions:

    • Delete: Marks a single version of a cell as deleted.
    • Delete Column: Marks all versions of a column as deleted.
    • Delete Family: Marks all columns of a column family as deleted.

    38. Describe a few situations in which you plan to use HBase.

    Ans:

    This method is usually chosen when a whole database needs to be moved. Furthermore, Hbase may be taken into consideration for data activities that are too big for one person to handle. Furthermore, Hbase can be readily considered when a large number of features, like inner joins and transaction maintenance, are required on a regular basis.

    39. In what way can you claim that the Hbase can provide high availability?

    Ans:

    One unique characteristic is called region replication. The complete Region is defined in a table by many replicas. It is the system’s load balancer. Hbase, which merely ensures that replicas are not repeatedly housed on servers with comparable geographic areas. This is precisely what guarantees Hbase’s constant high availability.

    40. By WAL, what do you mean?

    Ans:

    It stands for Log of Writing Ahead. Basically, it’s a log that keeps track of every modification to the data, regardless of how the changes were made. It is regarded as the typical sequence file in general. In fact, it is beneficial to take into account following problems such as a server failure or crash. In the event of such issues, users can still access data through it.

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    41. Could you list a few key Hbase components that data managers might find helpful?

    Ans:

    • Along with Hbase, users may easily manage larger volumes of data thanks to a unique component called “Region.” 
    • It also contains an additional component called “Zookeeper,” which is primarily in charge of coordinating the communication between the client and the master on the other end. 
    • They have “Catalogue Tables” that are readily available and comprise Root and MetaData.

    42. Is it possible to remove a call straight from the HBase?

    Ans:

    In HBase, direct deletion of cells often doesn’t immediately remove the data. Instead, when a cell is deleted, it becomes invisible and is marked with a tombstone marker. These tombstone markers indicate that the data has been logically deleted but still physically exists on the server. Over time, HBase performs compactions, which are processes that clean up and permanently remove these tombstone markers along with the actual deleted data.

    43. In your opinion, what is the significance of data management?

    Ans:

    • In general, businesses must handle large amounts of data. When work is organized or managed, it is simple to use or deploy. Of course, if a task is well-managed, it reduces the total amount of time needed to complete it.
    • With well-organized or controlled data, users may effortlessly stay up to date at all times. 
    • Numerous additional factors also come into play, allowing the consumers to guarantee error-free results.

    44. Regarding the collection of tables in the Hbase, what do you know?

    Ans:

    A protracted arrangement of rows and columns makes up these structures, which are similar to conventional databases. Each table contains rows that represent records and columns that represent attributes of these records. Every table has a unique element known as the primary key, which uniquely identifies each record in the table. This primary key ensures that each row can be individually accessed and managed. 

    45. Could you please list the prerequisites that must be met in order to maximize the benefits of the Hbase?

    Ans:

    • A well-configured Hadoop Distributed File System (HDFS) as HBase relies on it for storage.
    • Sufficient hardware resources, including ample RAM and CPU, for handling high throughput.
    • Properly tuned HBase configuration parameters based on workload characteristics.
    • Regular maintenance and monitoring to ensure optimal performance and health of the HBase cluster.

    46. Is Hbase a method that is independent of the OS?

    Ans:

    Yes, HBase is OS-agnostic, operating independently across platforms like Windows, Linux, and Unix. It relies solely on Java support, making it adaptable to various environments. This ensures seamless deployment and usage regardless of the underlying operating system, offering flexibility to users across different platforms.

    47. Where in HBase is the compression feature applicable?

    Ans:

    • Usually, it is carried out when users must use the Any feature linked to the physical storage assessment. 
    • For this, there are no intricate requirements that must be met. Since you may have worked with relational databases.

    48. Could you list some of the main distinctions between them and HBase?

    Ans:

    • The primary distinction is that, unlike relational databases, Hbase is not built on schema. Relational databases do not have this feature, whereas Hbase allows for simple automated partitioning.
    • Compared to relational databases, Hbase has a more significant number of tables. Furthermore, Hbase is a column-oriented data store, whereas it is a row-oriented data store.

    49. How can one ensure that the cells in an HBase are logically grouped?

    Ans:

    Logical grouping of cells in HBase can be ensured by organizing them within the same row key. By maintaining consistent row keys for related data, cells can be logically grouped together, facilitating efficient retrieval and processing operations. Utilizing appropriate row key designs aligned with the data access patterns further enhances the effectiveness of logical cell grouping in HBase.

    50. Could you briefly describe the process of removing a row from HBase?

    Ans:

    The best thing about Hbase is that anything written in RAM is automatically saved to disk. There are several that stay the same, barring Compaction. These compactions can be divided into major and minor categories. Small files are restricted from being deleted, but significant compactions can destroy the files with ease.

    51. What is the actual relationship between a File and its owner in an HBase?

    Ans:

    • It is a specified HBase storage format that is typically associated with a column family.
    •  In the column families, there is no hard cap on them. 
    • Users can deploy an Hfile with ease to store data from various families.

    52. Is it possible for users to change the block size of the column family?

    Ans:

    Yes, users can change the block size of a column family in HBase. This can be achieved by altering the column family’s configuration using the `HColumnDescriptor` class. By adjusting the `BLOCKSIZE` parameter, users can modify the block size to suit their requirements. After making the necessary changes, users can update the column family’s configuration to apply the new block size.

    53. Describe WAL and HLog in HBase.

    Ans:

    The HLog contains all edits made in the HStore. There is only one HLog per Region server, and a given Region Server’s HLog has entries for every edit made to every Region.WAL stands for Write Ahead Log, where all HLog edits are written right away. In the event of a delayed log flush, WAL modifications are retained in memory until the flush time. 

    54. What are the various operational commands that are available at the record and table levels?

    Ans:

    • Drop
    • List
    • scan and disable are often used commands at the table level
    • while get
    • Put
    • scan, and increment are instructions connected to the record level. 

    55. When you say “region server,” what do you mean?

    Ans:

    • Databases typically have enormous amounts of data to manage. It’s only sometimes feasible or required for every piece of data to be connected to a single server. 
    • There is a central controller, and it should also identify the server on which specific data is stored.
    • The Region server is the name given to the same. It is also regarded as a file on the system that enables users to see the related defined server names.

    56. What is the Hbase’s standalone mode?

    Ans:

    • This mode can be activated when users don’t require Hbase to access HDFS. It essentially functions as Hbase, and users are generally allowed to use it whenever they choose. 
    • When the user activates this option, Hbase uses a file system instead of HDFS.
    • This mode can save a significant amount of time when completing crucial chores. During this mode, different temporal constraints on the data can also be applied or removed.

    57. What is a shell of Hbase?

    Ans:

    The HBase shell is a command-line interface tool used for interacting with HBase databases. It provides commands for administrative tasks like creating tables, inserting data, and performing queries. Users can execute commands directly in the shell to manage HBase without writing custom code.

    58. Describe a few salient characteristics of Apache Hbase.

    Ans:

    Every table on the cluster is dispersed via regions; Hbase can be utilized for a variety of jobs requiring modular or linear scaling. Hbase’s regions automatically expand and split in response to data growth. It supports multiple bloom filters. Block cache usage is fully permitted. When data requirements are complex, Hbase can handle volume query optimization.

    59. Can you list the top five Hbase filters that you are familiar with?

    Ans:

    In Hbase, there are five filters:

    • Filtering by Page
    • Filter by Family
    • Column Separator
    • The Row Filter
    • All-Inclusive Stop Screen

    60. Can users iteratively go through the rows? Why not, and why not?

    Ans:

    It is feasible, yes. It is not permitted to complete the same work in reverse order, though. This is due to the fact that column values are typically saved on a disk and that their length needs to be specified in full. Additionally, the value-related bytes must be written after it. These values must be stored one more time to complete this task in reverse order, which may cause compatibility issues and strain the Hbase’s memory. 

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    61. Why is Hbase a database without a schema?

    Ans:

    • This is so that users won’t have to stress over defining the information before the time. 
    • All you have to do is define the column family name. 
    • As a result, the Hbase database lacks a schema. 
    • Developers are not required to follow a schema model to add new data, but they would have to adhere to a rigid schema model in a standard relational database paradigm.

    62. How does one go about writing data to Hbase?

    Ans:

    Any time there is a data modification or change, the information is initially transferred to a commit log, also called WAL. Following this, the information is kept in the memory. Should the data be above the specified threshold, it is stored on the disk in the form of a Hfile. Users can proceed with the saved data and are free to dispose of the commit logs.

    63. What does TTL mean in Hbase?

    Ans:

    • In essence, it is a helpful data retention strategy. It is feasible to grow capacity. Additionally, unlike RDBMSs, HBase does not require data to fit into a strict schema, which makes it perfect for storing unstructured or semi-structured data.
    • Wide-Column: HBase can hold billions of rows and millions of columns of data in a table-like manner. Row values can be physically distributed over various cluster nodes by grouping columns into “column families.”

    64. Without utilizing HBase, what command allows you to retrieve files directly?

    Ans:

    • The command or method that allows us to access Hfiles immediately without requiring HBase is HFile. Central (). 
    • Hbase does not support table Jons. 
    • However, we can provide join queries to retrieve data from many Hbase tables using a MapReduce task.

    65. How is Apache HBase used?

    Ans:

    When you require random, real-time read/write access to your big data, Apache HBase is utilized. The purpose of this project is to host huge tables on top of clusters of commodity hardware, with billions of rows and millions of columns. Based on Google Bigtable, Apache HBase is a distributed, versioned, non-relational database that is free and open source Chang et al. present A Distributed Storage System for Structured Data. 

    66. What characteristics does Apache HBase have?

    Ans:

    • Scalability both linearly and modularly.
    • Rigid consistency in both reading and writing.
    • Adaptable and automated table sharding
    • Support for automatic failover between RegionServers.
    • Easy-to-use foundation classes supporting Hadoop MapUtilize Apache HBase tables to decrease tasks.
    • Java API for client access is simple to use.
    • Bloom filters and block cache for instantaneous queries.

    67. How can I upgrade from HBase 0.94 to HBase 0.96+ for Maven-managed projects?

    Ans:

    The project switched to a modular framework in HBase 0.96. Instead of depending solely on one JAR, change the dependencies in your project to rely on the HBase-client module or another module as needed. Depending on whatever version of HBase you are targeting, you can model your Maven dependency after one of the following.  “Upgrading from 0.96.x to 0.98.x,” and 3.5, “Upgrading from 0.94.x to 0.96.x.”. Maven Dependency for org.apache.hbase.HBase-client 0.98.5-hadoop2 and HBase 0.98 Maven Requirement for org. Apache.HBase/HBase 0.96

    68. How should my HBase schema be designed?

    Ans:

    Admin in the Java API or “The Apache HBase Shell” can be used to create or alter HBase schemas.

    Disabling tables is necessary for making changes to ColumnFamily, such as:

    1, 2, 3, 4, 5, 6, 7, 8, and 9Administrator admin = new Admin(conf); Configuration config = HBaseConfiguration.create();

    ColumnFamily added: String table = “myTable”; admin.disableTable(table); HColumnDescriptor cf1 =…; admin.addColumn(table, cf1); //

    admin.modifyColumn(table, cf2); // altering the current ColumnFamily admin.enableTable(table); HColumnDescriptor cf2 =…

    69. What Does Apache HBase’s Table Hierarchy Mean?

    Ans:

    • One or two tables Families in Columns Columns Rows >> Cellular
    • One or more column families are established as high-level categories for storing data pertaining to an entry in the table during its creation. 
    • Table. Because HBase is “column-oriented,” all table entries, or rows, have their column family data stored together.
    • Multiple columns can be written at the same time as the data is recorded for a specific (row, column family) combination. 
    • As a result, two rows in an HBase table need to share column families rather than identical columns. HBase can store many cells for each 

    70. How can my HBase cluster be troubleshooted?

    Ans:

    • The master log should always come first (TODO: Which lines?). Usually, it simply prints the same lines repeatedly. 
    • If not, something needs to be fixed. You should get some results for the exceptions you’re seeing from Google or search-hadoop.com.
    • In Apache HBase, errors seldom occur by themselves. Instead, hundreds of exceptions and stack traces from various locations are typically the result of a problem. 
    • The easiest method to tackle this kind of issue is to walk the log up to the beginning. 

    71. How Do HBase and Cassandra Compare?

    Ans:

    • HBase and Cassandra are both distributed NoSQL databases. 
    • HBase is part of the Hadoop ecosystem, while Cassandra is standalone.
    • HBase is consistent and relies on Hadoop’s HDFS, while Cassandra is highly available and uses its own distributed architecture.
    • Cassandra offers a decentralized architecture with eventual consistency, while HBase follows a centralized architecture with strong consistency.

    72. Describe NoSql.

    Ans:

    Among the “NoSQL” database types is Apache HBase. The name “NoSQL” refers to any database that isn’t an RDBMS and doesn’t use SQL as its primary access language. There are numerous varieties of NoSQL databases, including: HBase is a distributed database, while BerkeleyDB is an example of a local NoSQL database. HBase is actually more of a “Data Store” than a “Database” technically since it lacks several of the capabilities of an RDBMS, like typed columns, secondary indexes, triggers, and sophisticated query languages.

    73. Which Hadoop version is required to operate HBase?

    Ans:

    Release Number for HBase Hadoop Release Number: 0.16.x, 0.16.x, 0.17.x, 0.18.x, 0.18.x, 0.19.x, 0.20.x, 0.20.x, 0.90.4 (stable as of right now) Hadoop releases are available here. Since the most recent version of Hadoop will have the most bug patches, we advise utilizing it whenever possible. Hadoop-0.18.x can be used with HBase-0.2.x. In order to use Hadoop-0.18.x, you must recompile Hadoop-0.18.x, delete the Hadoop-0.17.x jars from HBase, and replace them with the jars from Hadoop-0.18.x. HBase-0.2.x ships with Hadoop-0.17.x.

    74. Describe how the HBase and RDBMS data models differ from one another.

    Ans:

    • HBase is a schema-less data model, whereas RDBMS is a schema-based database.
    • While HBase offers automated partitioning,
    •  RDBMS does not support partitioning internally.
    • HBase stores denormalized data, 
    • while RDBMS stores normalized data.

    75. What does a delete marking mean?

    Ans:

    In databases, a delete marking signifies that a record or entry has been marked for deletion but may still exist in the system. This approach is often used for soft deletes, where data isn’t immediately removed but rather flagged for later removal or archiving. Delete markings facilitate data integrity and allow for potential recovery or audit trails without permanently erasing the data.

    76. What are Hbase’s Principal Elements?

    Ans:

    • Tables: Organize data into rows and columns.
    • Rows: Key-based storage units containing column families.
    • Column Families: Group columns together for efficient storage.
    • Cells: Intersection of rows and columns storing data values.

    77. Define HBase Bloom Filter.

    Ans:

    The sole method to determine whether a row key is a row key Typically, the only method to determine whether a row key is present in a store file is to look up the start row key for each block in the store file using the file’s block index. By acting as an in-memory data structure, bloom filters limit the number of files that need to be read from the disk to just those that are likely to contain that row. 

    78. What occurs if a row is deleted?

    Ans:

    When command data is destroyed, it is not actually erased from the file system; instead, a marker is set to make it invisible. Compaction causes physical loss.

    Three distinct markers—Column, Version, and Family Delete Markers—indicate the removal of a column, a column family, and a version of a column, respectively.

    79. What kinds of grave markings are there in HBase that can be removed?

    Ans:

    Here are three distinct kinds of tombstone markers that can be removed from HBase:

    • Family Delete Marker: This marker designates every column within a family of columns.
    • Version Delete Marker: This marker designates a column’s single version.
    • Column Delete Marker: This marker designates every iteration inside a column.

    80. What is the proper relationship between an Hfile and its owner in an HBase, in your opinion?

    Ans:

    In my opinion, the proper relationship between an HFile and its owner in HBase is one of ownership and control. The HFile belongs to the HBase system, managed by the HBase storage layer. The owner, typically the HBase RegionServer, maintains control over the HFile for efficient read and write operations, ensuring data integrity and consistency within the HBase ecosystem.

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    81. What are the main features of HBase, and when should you utilize it?

    Ans:

    • Scalability: HBase is designed to handle large-scale datasets, making it suitable for applications with massive data storage requirements.
    • Fault Tolerance: It offers built-in fault tolerance mechanisms, ensuring data integrity and availability even in the event of node failures.
    • Low-Latency Operations: HBase provides low-latency reads and writes, making it ideal for applications requiring real-time data access and processing.
    • Linear Scalability: As the dataset grows, HBase scales linearly by adding more nodes, enabling seamless expansion without sacrificing performance.

    82. Describe the main elements of HBase.

    Ans:

    The main elements of HBase are:

    • Tables: Organize data into rows and columns.
    • Rows: Key-based storage units containing column families.
    • Column Families: Group columns together for efficient storage.
    • Cells: Intersection of rows and columns storing data values.

    83. What kinds of operational commands are there in HBase?

    Ans:

    HBase has five essential operating commands: Increment, Scan, Delete, Put, and Get. Read the table with ease. We conducted using HTable.Essentially, it provides information or characteristics of a particular table row. Put adds or modifies rows to a table, whereas Delete removes rows from it. Increment allows one row to be used for increment operations. Lastly, to iterate over several rows for specific attributes, Scan is employed.

    84. What do WAL and Hlog mean to you?

    Ans:

    • Write Ahead Log, or WAL, is a log format similar to MySQL’s BIN log. It logs every modification made to the data.
    • The standard in-memory sequence file for Hadoop that keeps track of the Hockey store is called HLog.
    • When a server fails, or data is lost, WAL and HLog are lifesavers. 
    • In the event that the RegionServer malfunctions or crashes, WAL files ensure that replaying the data changes is possible.

    85. List some scenarios in which you might apply Hbase.

    Ans:

    • Time Series Data Storage: Storing large volumes of timestamped data like sensor readings, logs, or financial transactions where fast read/write access is crucial.
    • Ad-hoc Analytics: Supporting real-time or near-real-time analytical queries on massive datasets, such as user behavior analysis or IoT data analysis.
    • Hierarchical Data Storage: Storing hierarchical or nested data structures like JSON or XML efficiently, commonly used in social media feeds or product catalogs.
    • NoSQL Database for Web Applications: Utilizing HBase as a scalable NoSQL database backend for web applications, handling user profiles, session management, or content management.

    86. By “row keys” and “column families,” what do you mean?

    Ans:

    In HBase, column families make up the fundamental storage units. These are specified when a table is created and kept collectively on the disk, which subsequently permits the use of features like compression. A row key allows cells to be arranged logically. It comes before the combined key, enabling the application to specify the sort order. This allows for the saving of all the cells on the same server that have the same row key.

    87. What distinguishes a relational database from HBase?

    Ans:

    HBase is a schema-less, column-oriented data storage with minimally populated tables, which sets it apart from relational databases. Normalized data is kept in thin tables within a relational database, which is row-oriented and schema-based. Furthermore, HBase offers automated partitioning, something that RDBMS does not provide by default.

    88. What does an HBase cell consist of?

    Ans:

    • The minor units in an HBase database are called cells, and they store data as tuples. A tuple is a multipartite data structure. 
    • It is composed of {row, column, version).HBase stores data as a group of values or cells. HBase uniquely identifies each cell by a key. 
    • Using a key, you can look up the data for records stored in HBase very quickly. 
    • You can also insert, modify, or delete records in the middle of a dataset.

    89. Explain what HBase compaction is.

    Ans:

    HBase compaction is the process of merging smaller HFiles, which are physical files containing sorted key-value pairs, into larger files. This process helps improve read performance by reducing the number of files that need to be scanned. Compaction also helps in reclaiming disk space by removing obsolete or deleted data. It ensures data integrity and maintains optimal performance by organizing data efficiently within HBase tables.

    90. Describe tombstone markers and deletion in HBase.

    Ans:

    In HBase, tombstone markers are placeholders indicating deleted data. When a row or column is deleted, instead of immediate removal, a tombstone marker is inserted, marking the data as deleted. During compaction, marked data is removed permanently. This approach ensures consistency in distributed systems, supporting rollback and recovery.

    91. What occurs when a column family’s block size is changed?

    Ans:

    • It affects the storage efficiency and read/write performance of data stored within that column family.
    • A smaller block size increases the number of blocks required to store data, potentially reducing storage overhead but increasing metadata overhead.
    • Conversely, a larger block size reduces metadata overhead but may lead to increased storage overhead and longer seek times for reads.
    • The change impacts the organization of data on disk, necessitating potential data reorganization or compaction processes.

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