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Apache Hive Online Training

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Gain the Best Practices In Apache Hive Training

  • Those who want to learn large data processing and analytics abilities can enroll in our Apache Hive course. Developers, analysts, data engineers, and anyone else dealing with massive data sets can all benefit from it.
  • Data warehousing principles, Hive architecture, HiveQL, data modeling, performance optimization, and integration with other big data tools are just a few of the topics that we usually cover in our Apache Hive training.
  • Students gain practical skills in big data processing with Hadoop Hive through hands-on learning experiences, including exercises, projects, and real-world scenarios.
  • Upon successful completion of our Apache Hive training, certification is awarded. By certifying participant's proficiency with Hive for data processing and analytics, employers will see them more favorably on the job market.
  • To ensure students are well-prepared for successful careers in big data processing, our dedicated Placement Support Team conducts tailored interview preparation sessions.
  • Our instructors are experienced in big data processing and data engineering, offer valuable insights on deploying and leveraging Hadoop Hive effectively.
  • After completing the Apache Hive training, students can pursue careers in big data processing, including roles like data analyst, big data consultant, and Hadoop developer.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
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Course Objectives

  • HiveQL
  • Apache Spark
  • HUE
  • Apache Kafka
  • Apache Ambari
  • Apache Zeppelin
  • Big Data Engineer
  • Data Analyst
  • Data Scientist
  • Database Administrator
  • Business Intelligence Developer
HiveQL, a language similar to SQL, is the primary tool used by Apache Hive for managing and querying data kept in the Hadoop Distributed File System (HDFS). Basic operations in Hive usually don't require much writing, while more complex operations or bespoke functions might.
  • Introduction to Apache Hive
  • Hive Architecture
  • Data Management
  • Schema Design
  • Partitioning and Bucketing
  • Hive Data Formats
  • Hive Joins and Subqueries
  • User-Defined Aggregate Functions (UDAFs)
Yes, the Hadoop Hive course caters to beginners by providing a comprehensive understanding of Hadoop Hive, beginning with basic ideas and working up to more complex subjects.
Our dependable Apache Hive training provides in-depth knowledge of Apache Hive. After finishing successfully, you will receive a certification that will attest to your skills and improve your standing in the big data analytics industry.
  • Writing and executing HiveQL queries to manipulate data
  • Designing and implementing Hive schemas for different use cases
  • Optimizing queries for improved performance
  • Working with various file formats and storage systems supported by Hive
  • Building and deploying Hive applications in a Hadoop environment

How difficult is it to learn Apache Hive?

Learning Hadoop Hive can be complex, depending on individual backgrounds and experiences. However, with dedication and practice, learners can effectively grasp the concepts and techniques involved.

What skills can one expect to acquire through the Apache Hive course?

  • Proficiency in querying and managing large datasets using HiveQL
  • Understanding of Hadoop ecosystem components and their integration with Hive
  • Knowledge of data warehousing concepts and schema design
  • Ability to optimize Hive queries for performance
  • Familiarity with Hive administration and troubleshooting

What prerequisites are necessary for the Apache Hive course?

Prerequisites for the Hadoop Hive course encompass basic SQL proficiency, familiarity with the Linux command line, and a grasp of programming concepts like Java and Python. These skills are fundamental for effectively navigating and utilizing the Hadoop ecosystem, facilitating tasks such as data querying, cluster management, and custom solution development.

Does working at Apache Hive pay well?

Proficiency in Apache Hive can result in lucrative employment, particularly in sectors such as technology, finance, and healthcare that heavily depend on big data analytics. Experience, geography, and certain job positions all affect salary, but knowing Apache Hive can greatly increase one's earning potential.
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An Comprehensive Overview of the Apache Hive

One application that makes working with massive data easier is Apache Hive. It resembles a sizable, well-organized filing system for a vast amount of data kept on numerous machines. It doesn't require any specialized knowledge; you can ask it questions in a language that is comparable to standard English. Hive then makes sense of all that disorganized data to find the answers you require. It works with many file types and is excellent at managing big volumes of data. It is also compatible with other Hadoop tools, which makes it a versatile tool for a variety of applications. Additionally, it is secure, allowing you to manage who has access to and shield your data from prying eyes. Hive essentially removes the requirement for expertise in complicated programming to handle and analyze massive volumes of data for those who are familiar with SQL.


Additional Info

Trends and Techniques Used by Apache Hive Experts

  • SQL-on-Hadoop Optimization: Experts in Hadoop Hive concentrate on enhancing SQL queries to increase effectiveness and speed. Queries are executed more quickly and efficiently with techniques like bucketing, indexing, partitioning, and optimization.
  • Vectorization: Vectorization, a batch data processing method, significantly improves query performance by reducing CPU overhead, and Hadoop Hive specialists utilize vectorized query execution engines like Apache Tez or LLAP.
  • Data Lake Architecture: Hive professionals create data lake designs, utilizing object storage technologies like Amazon S3, Azure Data Lake Storage, and HDFS for scalable and affordable data storage.
  • Data Compression and Storage Formats: Hadoop Hive specialists utilize data compression techniques and select suitable store formats like Parquet or ORC for efficient data encoding and predicate pushdown for columnar storage.
  • Query Federation: Hadoop Hive utilizes query federation techniques to efficiently access and combine data from various external sources like relational databases, NoSQL databases, and cloud storage.
  • Containerization and Orchestration: Hadoop Hive experts utilize the Kubernetes orchestration framework and Docker containerization technologies to efficiently deploy, manage, and scale Hadoop clusters, ensuring repeatability and portability across various infrastructure platforms.
  • Cloud Integration: Cloud computing, utilizing services like Azure HDInsight and Amazon EMR, enables Hadoop Hive specialists to create and manage clusters in the cloud, enhancing flexibility, scalability, and cost-effectiveness.

Requirements for Enrolling in the Apache Hive Course

  • Basic Programming Skills: While it's not necessarily required, knowing the fundamentals of programming might help you better comprehend HiveQL syntax and interact with data in Hive. It can be beneficial to be proficient in languages like Python, Java, or SQL.
  • Familiarity with SQL: It can be helpful to have some knowledge of SQL principles like SELECT statements, JOINs, GROUP BY, and WHERE clauses because Hive employs a language called HiveQL, which is similar to SQL.
  • Knowledge of Hadoop Ecosystem: Understanding the Hadoop ecosystem and distributed computing principles can enhance understanding of Hive functions, HDFS, MapReduce, YARN, and Hadoop's architecture.
  • Understanding of Data Warehousing Concepts: Understanding Hive's function in the data warehousing process can be aided by familiarity with data warehousing concepts like ETL (Extract, Transform, Load), data modelling, and data warehousing architectures.
  • Experience with Data Processing and Analysis: Prior experience with data processing and analysis, whether in the context of other big data technologies or traditional relational databases, can facilitate learning about Hive.

Apache Hive Future prospects

  • Performance Enhancements: Continuous efforts to refine query performance and reduce latency are anticipated to bolster Hive's competitiveness against emerging technologies. This could involve optimizing query execution engines and implementing advanced optimization strategies.
  • Integration with Modern Tools: Hive is poised to continue integrating with contemporary data processing tools like Apache Spark and Apache Flink. This integration offers users the flexibility to harness different technologies within a unified ecosystem, enhancing overall data processing efficiency.
  • Adaptation to Cloud-Native Architectures: With the rise of cloud computing, Hive is expected to evolve to support cloud-native architectures better. This may include seamless integration with cloud storage services, improved scalability, and streamlined deployment options tailored to cloud environments.
  • Shift towards Real-Time Processing: While traditionally focused on batch processing, Hive may increasingly cater to real-time analytics demands. Future iterations might incorporate features to support better real-time processing, such as enhanced compatibility with streaming data sources and accelerated query processing.
  • Community-Led Development: Hive's future trajectory will be significantly influenced by the continued contributions and support from its vibrant open-source community. The project's direction and progress will be greatly influenced by the cooperative efforts of organizations and developers.

Some of the widely used Apache Hive Tools

  • Apache Tez: Renowned for its extensibility in high-performance batch and interactive data processing tasks, Apache Tez functions as an execution engine for Hive queries, optimizing performance and resource utilization.
  • Apache Spark: While not strictly a component of Hadoop Hive, Apache Spark is often utilized alongside it for in-memory data processing and iterative algorithms. Spark SQL, offering functionalities akin to HiveQL, enables users to leverage SQL-like syntax for data querying and analysis.
  • Apache HBase: Positioned as a distributed, scalable NoSQL database atop HDFS, Apache HBase acts as a data store for real-time processing and interactive queries, complementing Hive's batch-oriented processing capabilities.
  • Apache Kafka: Apache Kafka, a distributed streaming platform, is instrumental in constructing real-time data pipelines and streaming applications. Integration with Hive facilitates the ingestion and processing of streaming data in near real-time.
  • Apache Drill: Known for its distributed SQL query engine, Apache Drill enables interactive querying of large-scale datasets across diverse data sources. Used alongside Hive, it provides SQL access to varied data sources without necessitating data movement or transformation.
  • Hive Metastore: The Hive Metastore is a central repository for metadata regarding Hive tables, partitions, columns, and storage attributes. It allows Hive to handle table information without being dependent on the location or type of the underlying data storage.
  • Beeline: Beeline is a JDBC client for HiveServer2 that allows you to connect to Hive and run queries using a command-line interface. It provides alternatives for connecting to Hive clusters through setup, history persistence, and tab completion.
  • Hive Extensions: Hive offers plugins and extensions for enhanced functionality and integration with other frameworks and applications, such as SerDes for data formats, storage handlers for storage systems, and input/output formats for external data sources.

Discover the Job roles for Apache Hive

  • Big Data Engineer: Responsible for designing, implementing, and maintaining Hadoop-based solutions, such as establishing Hive environments, developing data processing pipelines, and optimizing Hive queries for improved performance.
  • Data Engineer: Data Engineers build and manage data pipelines, ETL (Extract, Transform, Load) procedures, and Hadoop Hive data warehouses.
  • Data Analyst: Data Analysts use Hadoop Hive to analyze massive datasets, extract insights, and produce reports for business stakeholders. They write HiveQL queries to access and modify data, create data visualizations, and identify trends or patterns.
  • Data Scientist: Data Scientists use complex statistical and machine learning approaches to analyze Hadoop Hive data, uncover actionable insights, and build predictive models. They use HiveQL to prepare and manipulate data for analysis and model creation.
  • Hadoop Administrator: Manages and maintains Hadoop clusters, including Hive installation, setup, and performance upgrades. They monitor cluster health, resolve issues, enforce security measures, and assure scalability and dependability.
  • Business Intelligence Developer: Creates and refines BI (Business Intelligence) solutions that leverage Hadoop Hive to provide data-driven insights and reports to business customers.
  • Data Architect: Creates data structures and models that meet analytics and reporting requirements using Hadoop Hive. They design Hive table architectures, partitioning strategies, and storage formats to maximize data storage and retrieval.
  • Machine Learning Engineer: Develops machine learning techniques and models using data from Hadoop Hive. They preprocess and engineer data characteristics, train and evaluate models, and implement machine learning solutions that interface with Hive.
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Key Features

ACTE offers Apache Hive Training in more than 27+ branches with expert trainers. Here are the key features,

  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.


Syllabus of Apache Hive Online Training
Module 1: Introduction to Apache Hive
  • Overview of Apache Hive
  • Role of Hive in Big Data Analytics
  • Comparison with Traditional Databases
Module 2: Hive Architecture and Components
  • Architecture Overview
  • It's Components (Metastore, Query Compiler, Execution Engine)
  • Hive Execution Flow
Module 3: Installation and Configuration
  • Installing Hive on Hadoop Cluster
  • Configuration Settings and Parameters
  • Hive CLI and Beeline Setup
Module 4: Data Definition in Hive
  • Hive Data Types
  • Creating Databases and Tables
  • Partitioning and Bucketing
Module 5: Data Manipulation in Hive
  • Loading Data into Hive Tables
  • Inserting, Updating, and Deleting Data
  • Altering Tables and Schemas
Module 6: Querying Data with HiveQL
  • Introduction to HiveQL
  • Basic SELECT Queries
  • Joins, Subqueries, and Aggregations
Module 7: Advanced HiveQL
  • Window Functions
  • User-Defined Functions (UDFs)
  • Working with Complex Data Types
Module 8: Optimization Techniques
  • Query Optimization Strategies
  • Partitioning
  • Bucketing Optimization
  • Statistics
  • Cost-Based Optimization
Module 9: Hive Security
  • Authentication and Authorization
  • Role-Based Access Control (RBAC)
  • Encryption
  • Data Protection
Module 10: Integration with Hadoop Ecosystem
  • Hive and HDFS Integration
  • Using Hive with HBase, Spark, and Kafka
  • External Data Sources and SerDes
Module 11: Real-time Processing with Hive
  • Introduction to Streaming Data Processing
  • Hive Integration with Streaming Platforms
  • Processing Real-time Data with Hive
Module 12: Performance Tuning and Best Practices
  • Performance Tuning Techniques
  • Query Optimization Tips
  • Best Practices for Hive Development
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Need customized curriculum?

Get Hands-on Knowledge about Real-Time Apache Hive Projects

Project 1
E-commerce Data Warehouse

In this project, Students design e-commerce data warehouse, store transactions, customers, products, and sales using Hive.

Project 2
Social Media Sentiment Analysis

in this project, Students analyze social media data in Hive, perform sentiment analysis, topic modeling, and visualization.

Elevate Your Potential with Our Apache Hive Job Support

  • Our training includes Apache Hive job placement support, including CV crafting, interview preparation, and connecting students with big data analytics employers.
  • To assist students in determining their talents, professional objectives, and the most effective routes to a career in Apache Hive and similar industries, we provide career counseling sessions.
  • Our Apache Hive Job Support hosts exclusive job fairs and networking events tailored for Hadoop Hive-certified individuals, providing prime opportunities to showcase your skills and interact with potential employers.
  • We offer promising career prospects at top-tier companies in the big data industry, such as IBM, Amazon, Google, Microsoft, and others, for our Hadoop Hive-trained students.
  • Internship options with partner firms are provided by our Apache Hive training programs, giving students practical experience working on real-world projects and expanding their professional network.
  • For students who want to boost their chances of being seen by employers and establish a strong professional presence, workshops on resume writing and LinkedIn profile optimization will be provided.
  • We facilitate networking opportunities with various businesses and organizations, fostering collaboration and creating avenues for Hadoop Hive-trained professionals to connect.

Get Industry Recognised Apache Hive Certification

Our Apache Hive Certification is esteemed among top multinational corporations worldwide. It caters to individuals new to the field and corporate trainees who complete rigorous theoretical and practical training sessions. This prestigious certification substantially enhances your resume, opening doors to coveted positions within leading multinational organizations globally. To attain certification, candidates must meet the exacting criteria of our comprehensive training program and demonstrate proficiency through practical assignments.

Obtaining Apache Hive certifications validates your expertise in Apache Hive, enhancing your credibility and marketability in the field. It demonstrates proficiency in data processing, querying, and analysis using Apache Hive, which is highly valued by employers seeking skilled professionals in big data technologies.
  • Cloudera Certified Professional (CCP) Data Engineer
  • Hortonworks Data Platform (HDP) Certified Developer
  • MapR Certified Data Analyst (MCDA)
  • IBM Certified Data Engineer - Big Data
  • Apache Hive Certified Developer
  • Understanding big data conceptsM
  • SQL skillsM
  • Knowledge of the Hadoop ecosystemM
  • Data warehousing experienceM
  • Hands-on experience with Apache Hive
Yes. Acquiring an Apache Hive certification substantially enhances job prospects. With its increasing adoption in organizations globally, certification validates proficiency and dedication, making candidates highly sought after by employers.
  • Big Data Engineers
  • Data Analysts
  • Data Scientists
  • Database Administrators
  • Business Intelligence Developers

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

Get Certified

Improve Your Career Growth with Our Apache Hive Trainers

  • Our Apache Hive online Training ensures a comprehensive learning journey, covering foundational concepts to advanced techniques and providing a holistic educational experience.
  • Our trainers possess an extensive understanding of Apache Hive and associated technologies, such as big data processing frameworks, SQL-on-Hadoop solutions, and Hadoop ecosystem components.
  • Our Apache Hive trainers, with extensive industry experience at leading IT firms like eBay, JPMorgan Chase, Google, Amazon, Facebook, and Microsoft offers unique industry perspectives in the classroom.
  • Our Apache Hive Trainers are skilled communicators who use various instructional strategies like case studies, lectures, demonstrations, and practical exercises to engage students and promote learning.
  • We prioritize creating an inclusive and supportive learning environment where student participation is encouraged, questions are welcomed, and our skilled trainers promptly address challenges.
  • Throughout the learning process, our trainers act as mentors and guides, offering tailored assistance, criticism, and motivation to help students overcome obstacles and meet their learning objectives.
  • Our Hadoop Hive Trainers stay updated with the latest advancements in Hadoop Hive, ensuring our curriculum reflects current industry trends and students receive relevant and up-to-date knowledge.

Apache Hive Course FAQs

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Call now: +91 93833 99991 and learn about the exciting offers available to you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Student list.
  • on our website
  • We have solid working relationships with more than 700 of the world's leading multinational corporations, including SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM, and more
  • More than 3500+ students placed last year in India & Globally
  • ACTE conducts development sessions, including mock interviews and presentation skills, to prepare students to easily face a challenging interview situation
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in a better MNC
  • Please Visit Your Student Portal | Here, the FREE Lifetime Online Student Portal helps you to access Job Openings, Study Materials, Videos, Recorded sections & Top MNC interview Questions
In the world of technology, ACTE certification is regarded as a respectable qualification. It exhibits competence and knowledge in particular technical areas, improving professional prospects and credibility for workers looking to progress in their industries.
Yes, real datasets are used in live projects in Apache Hive courses to help students solve real-world problems. By giving students practical experience, these projects improve their learning process by enabling them to use their knowledge of data analysis, query optimization, and data management in a real-world setting.
All the trainers at ACTE are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
You can request make-up lessons or see recorded sessions if you are unable to attend a class at ACTE. Furthermore, tools and course materials are offered to assist you in making up for lost content.
Our course is available in Classroom, One-to-One Training, Fast Track, Customised Training & Online Training modes, giving you the flexibility to seamlessly manage it alongside your real-life commitments.

Why Should I Learn a Apache hive Course at ACTE?

At ACTE, mastering Apache Hive comes with numerous benefits. Our courses, crafted by industry professionals, offer practical exposure through real projects. With adaptable learning formats, individualized guidance, and a holistic syllabus, you'll gain profound insights into Hive's functionalities and practical uses. Additionally, our career assistance services facilitate smooth transitions into data engineering and analytics roles, ensuring a fulfilling learning experience.
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive the globally recognized ACTE course completion certification from the National Institute of Education (NIE) in Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
While the size of each Apache Hive batch at ACTE varies, it usually consists of 10 to 15 students, allowing for individualized attention and a productive learning environment for each student.
Certainly! In the Apache Hive course, you'll receive extensive practical training to complement your theoretical understanding. Through hands-on exercises, real-world projects, and interactive labs, you'll gain valuable experience in working with HiveQL, data manipulation, and query optimization. Our holistic approach ensures you develop the essential skills and confidence to tackle real-world data processing and analytics challenges using Apache Hive proficiently.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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