Apache Hive Explained in 5 Minutes or Less [+5 Learning Resources]

Apache Hive is a distributed, fault-tolerant knowledge warehouse system that allows analytics at an enormous scale.

A knowledge warehouse is an information administration system that shops massive quantities of historic knowledge derived from varied sources for the aim of information evaluation and reporting. This, in flip, helps enterprise intelligence resulting in extra knowledgeable decision-making.

The info utilized in Apache Hive is saved in Apache Hadoop, an open-source knowledge storage framework for distributed knowledge storage and processing. Apache Hive is constructed on prime of Apache Hadoop and thus shops and extracts knowledge from Apache Hadoop. Nevertheless, different knowledge storage programs, comparable to Apache HBase, may also be used.

The most effective factor about Apache Hive is that it permits customers to learn, write and handle massive datasets and question and analyze the information utilizing Hive Question Language(HQL), just like SQL.

How Apache Hive Works


Apache Hive supplies a high-level, SQL-like interface for querying and managing massive quantities of information saved within the Hadoop Distributed File System(HDFS). When a consumer executes a question in Apache Hive, the question is translated right into a sequence of MapReduce jobs executed by the Hadoop cluster.

MapReduce is a mannequin for processing massive quantities of information in parallel acrosses distributed clusters of computer systems. As soon as the MapReduce jobs are accomplished, their outcomes are processed and mixed to supply a single ultimate consequence. The ultimate consequence might be saved in a Hive desk or exported to HDFS for additional processing or evaluation.

Queries in Hive might be executed quicker by utilizing partitions to divide Hive tables into completely different components based mostly on the desk info. These partitions might be damaged down even additional to permit very quick querying of huge knowledge units. This course of is named bucketing.

Apache Hive is a must have for organizations working with large knowledge. It is because it permits them to simply handle massive datasets, course of the information in a really quick method and simply carry out advanced knowledge evaluation on the information. This results in complete and detailed reviews from obtainable knowledge permitting for higher decision-making.

Advantages of Utilizing Apache Hive


Among the advantages of utilizing Apache Hive embrace the next:

Simple to make use of

By permitting querying of information utilizing HQL, just like SQL, utilizing Apache Hive turns into accessible to programmers and non-programmers alike. Due to this fact, knowledge evaluation might be accomplished on massive knowledge units with out studying any new language or syntax. This has been a key contributor to the adoption and use of Apache Hive by organizations. 


Apache Hive permits for very quick knowledge evaluation of huge datasets by way of batch processing. In batch processing, massive datasets are collected and processed in teams. The outcomes are later mixed to supply the ultimate outcomes. By batch processing, Apache Hive permits for quick processing and knowledge evaluation.


Hive makes use of the Hadoop Distributed File System(HDFS) for knowledge storage. By working collectively, knowledge might be replicated when it’s being analyzed. This creates a fault-tolerant atmosphere the place knowledge can’t be misplaced even when pc programs malfunction.

This enables Apache Hive to be very dependable and fault-tolerant, which makes it stand out amongst different knowledge warehouse programs.


Apache Hive is designed in a way that enables it to scale and deal with rising datasets simply. This supplies customers with an information warehouse answer that scales in response to their wants.


In comparison with different knowledge warehousing options, Apache Hive, which is open supply, is comparatively cheaper to run and, thus, the best choice for organizations eager on minimizing the prices of operations being worthwhile.

Apache Hive is a sturdy and dependable knowledge warehousing answer that not solely scales in response to a consumer’s wants but in addition supplies a quick, cost-effective, and easy-to-use knowledge warehousing answer.

Apache Hive Options


Key options in Apache hive embrace:

#1. Hive Server 2(HS2)

It helps authentication and multi-client concurrency and is designed to supply higher assist for open API purchasers like Java Database Connectivity(JDBC) and Open Database Connectivity (ODBC).

#2. Hive Metastore Server(HMS)

HMS acts as a central retailer for the metadata of Hive Tables and partitions for a relational database. The metadata saved in HMS is made obtainable to purchasers utilizing metastore service API.

#3. Hive ACID

Hive ensures that each one transactions accomplished are ACID compliant. ACID represents the 4 fascinating traits of database transactions. This consists of atomicity, consistency, isolation, and sturdiness.

#4. Hive Knowledge Compaction

knowledge compaction is the method of decreasing the information measurement that’s saved and transmitted with out compromising the standard and integrity of the information. That is accomplished by eradicating redundancy and irrelevant knowledge or utilizing particular encoding with out compromising the standard and integrity of the information being compacted. Hive gives out-of-the-box assist for knowledge compaction.

#5. Hive Replication

Hive has a framework that helps the replication of Hive metadata and knowledge modifications between clusters for the aim of making backups and knowledge restoration.

#6. Safety and Observability

Hive might be built-in with Apache Ranger, a framework that allows monitoring and managing knowledge safety, and with Apache Atlas, which permits enterprises to fulfill their compliance necessities. Hive additionally helps Kerberos authentication, a community protocol that secures communication in a community. The three collectively make Hive safe and observable.

#7. Hive LLAP

Hive has Low Latency Analytical Processing (LLAP) which makes Hive very quick by optimizing knowledge caching and utilizing persistent question infrastructure.

#8. Price-based Optimization

Hive makes use of a cost-based question optimizer and question execution framer by Apache Calcite to optimize its SQL queries. Apache Calcite is utilized in constructing databases and knowledge administration programs.

The above options make Apache Hive a superb knowledge warehouse system

Use Circumstances For Apache Hive


Apache Hive is a flexible knowledge warehouse and knowledge evaluation answer that enables customers to simply course of and analyze massive quantities of information. Among the use circumstances for Apache Hive embrace:

Knowledge Evaluation

Apache Hive helps the evaluation of huge knowledge units utilizing SQL-like statements. This enables organizations to determine patterns within the knowledge and draw significant conclusions from extracted knowledge. That is helpful in design making. Examples of corporations that use Apache Hive for knowledge evaluation and querying embrace AirBnB, FINRA, and Vanguard.

Batch Processing

This includes utilizing Apache Hive to course of very massive datasets by way of distributed knowledge processing in teams. This has the benefit of permitting quick processing of huge datasets. An instance of an organization that makes use of Apache Hive for this objective is Guardian, an insurance coverage and wealth administration firm.

Knowledge Warehousing

this includes utilizing Apache hive to retailer and handle very massive datasets. Along with this, the information saved might be analyzed, and reviews generated from the. Firms that use Apache Hive as an information warehouse answer embrace JPMorgan Chase and Goal.

Advertising and buyer evaluation

organizations can use Apache Hive to research their buyer knowledge, carry out buyer segmentation and be capable to perceive their prospects higher, and tweak their advertising efforts to match their understanding of their prospects. That is an software that each one corporations that deal with buyer knowledge can use Apache Hive for.

ETL(Extract, Remodel, Load) processing

When working with a variety of knowledge in an information warehouse, it’s essential to carry out operations comparable to knowledge cleansing, extraction, and transformation earlier than knowledge might be loaded and saved in an information warehouse system.

This manner, knowledge processing and evaluation will likely be quick, straightforward, and error-free. Apache Hive can carry out all these operations earlier than knowledge is loaded into an information warehouse.

The above make up the principle makes use of circumstances for Apache Hive

Studying Assets

Apache hive is a really great tool for knowledge warehousing and knowledge evaluation of huge datasets. Organizations and people working with massive datasets stand to profit by utilizing Apache hive. To study extra about Apache Hive and the right way to use it, take into account the next assets:

#1. Hive To ADVANCE Hive (Actual-time utilization)


Hive to Advance Hive is a best-selling course on Udemy created by J Garg, a senior large knowledge marketing consultant with over a decade of expertise working with Apache applied sciences for knowledge evaluation and coaching different customers.

This can be a one-of-a-kind course that takes learners from the fundamentals of Apache Hive to superior ideas and likewise features a part on use circumstances utilized in Apache Hive Job interviews. It additionally supplies knowledge units and Apache Hive queries that learners can use to apply whereas studying.

Among the Apache Hive ideas lined embrace superior features in Hive, compression methods in Hive, configuration settings of Hive, working with a number of tables in Hive, and loading unstructured knowledge in Hive. 

The power of this course lies within the in-depth protection of superior Hive ideas utilized in real-world initiatives.

#2. Apache Hive For Knowledge Engineers


This can be a hands-on, project-based Udemy Course that teaches learners the right way to work with Apache Hive from a newbie degree to a sophisticated degree by engaged on real-world initiatives.

The course begins with an summary of Apache Hive and covers why it’s a vital device for knowledge engineers. It then explores the Hive structure, its set up, and the mandatory Apache Hive configurations. After laying the inspiration, the course proceeds to cowl hive question flows, hive options, limitations, and the information mannequin utilized in Apache hive.

It additionally covers knowledge sort, knowledge definition language, and knowledge manipulation language in Hive. The ultimate sections cowl superior Hive ideas comparable to views, partitioning, bucketing, joins,  and built-in features and operators.

To cap all of it,  the course covers regularly requested interview questions and solutions. This is a wonderful course to find out about Apache Hive and the way it may be utilized in the actual world.

#3. Apache Hive Primary to advance


Apache Hive Primary to advance is a course by Anshul Jain, a senior knowledge engineer with tons of expertise working with Apache Hive and different Massive knowledge instruments. 

This presents Apache Hive ideas in an easy-to-understand method and is appropriate for rookies trying to study the ropes of Apache Hive.

The course covers HQL clauses, window features, materialized view, CRUD operations in Hive, trade of partitions, and efficiency optimization to permit quick knowledge querying.

This course will provide you with a hands-on expertise with Apache Hive along with serving to sort out frequent interview questions you’re prone to encounter when making use of for a job.

#4. Apache Hive Necessities

This ebook is especially helpful to knowledge analysts, builders, or anybody keen on studying the right way to use Apache Hive.

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Apache Hive Essentials: Essential techniques to help you process, and get unique insights from, big data, 2nd Edition

Apache Hive Necessities: Important methods that will help you course of, and get distinctive insights from, large… $30.99

The writer has over a decade of expertise working as an enormous knowledge practitioner designing and implementing enterprise large knowledge structure and analytics in varied industries.

The ebook covers the right way to create and arrange a Hive atmosphere, successfully describe knowledge utilizing Hive’s definition language, and be a part of and filter knowledge units in Hive.

Moreover, it covers knowledge transformations utilizing Hive sorting, ordering, and features, the right way to combination and pattern knowledge, and the right way to enhance the efficiency of Hive queries and improve safety in Hive. Lastly, it covers customizations in Apache hive, educating customers the right way to tweak Apache Hive to serve their large knowledge wants.

#5. Apache Hive Cookbook

Apache Hive Cookbook, obtainable in Kindle and paperback, supplies an easy-to-follow, hands-on tackle Apache Hive, permitting you to study and perceive Apache Hive and its integration with in style frameworks in large knowledge.

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Apache Hive Cookbook

Apache Hive Cookbook $48.99

This ebook, meant for readers with prior data of SQL, covers the right way to configure Apache Hive with Hadoop, companies in Hive, the Hive knowledge mannequin, and Hive knowledge definition and manipulation language.

Moreover, it covers extensibility options in Hive, joins and be a part of optimization, statistics in Hive, Hive features, Hive tuning for optimization, and safety in Hive, and concludes with in-depth protection of the mixing of Hive with different frameworks.


It’s price noting that Apache Hive is greatest used for conventional knowledge warehousing duties and unsuitable for processing on-line transactions. Apache is designed to maximise efficiency, scalability, fault tolerance, and unfastened coupling with its enter codecs.

Organizations that deal with and course of massive quantities of information stand to profit tremendously from the strong options provided by Apache Hive. These options are very helpful in storing and analyzing massive datasets.

You might also discover some main variations between Apache Hive and Apache Impala.

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