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Apache Hive Training

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Inspire Your Profession with Our Apache Hive Online Course

  • The Apache Hive Online Course is intended to teach users how to deal with large-scale data processing using Hive, a Hadoop-based data warehouse and SQL-like query language tool.
  • Students will learn how to load data into Hive tables from various sources and perform data transformation using HiveQL functions.
  • The course will cover how to use Hive for data analysis, including filtering, aggregating, and joining datasets.
  • Participants will explore techniques to optimize query performance in Hive, such as partitioning, bucketing, and using appropriate file formats.
  • The course may provide examples and use cases from the real world to demonstrate how businesses use Hive to address data processing problems.
  • The course will cover the fundamentals of Apache Hive, its architecture, and its integration with the Hadoop ecosystem.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

This is How ACTE Students Prepare for Better Jobs

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Course Objectives

  • Master big data processing with Hive.
  • Learn HiveQL for data querying and manipulation.
  • Understand integration with the Hadoop ecosystem.
  • Perform data transformation and analysis.
  • Optimize queries for faster processing.

Choosing Apache Hive as a career path can be a rewarding decision, especially if you have an interest in big data processing and data analysis. As the number of data generated by enterprises grows at an exponential rate, so does the demand for experts skilled in big data technologies such as Apache Hive.

  • Basic programming knowledge (SQL, Java, or Python).
  • Familiarity with SQL concepts is helpful.
  • Knowledge of Hadoop and the fundamentals of big data.
  • Knowledge of data warehousing and databases.
  • Comfort with the Linux command line.
  • Introduction to Apache Hive.
  • Hive Architecture and its major components.
  • Hive Data Model.
  • HiveQL Basics.
  • Hive Security and Administration.

Yes, the scope of Apache Hive is likely to have a significant effect on the future, especially in the context of big data processing and data analytics. As the volume of data continues to grow exponentially, organizations face the challenge of managing and analyzing vast amounts of information effectively.

  • Big Data Engineer
  • Data Engineer
  • Data Analyst
  • Data Scientist
  • Business Intelligence (BI) Developer

Yes, working with Apache Hive in India can be highly desirable and rewarding for several reasons. India has become a significant participant in the global IT and technology sector, and with the increasing expansion of big data and analytics, there is an increased demand for professionals with Hive expertise has increased significantly.

What kinds of educational resources are provided for the Apache Hive training?

  • Video Lectures
  • Interactive Tutorials
  • Quizzes and Assessments
  • Hands-on Projects
  • Online Documentation

Will there be opportunities for students to work on projects that affect the real world?

Yes, there are often opportunities for students to work on tasks that have an influence on the actual world during Apache Hive training or any other data-related training. Through these projects, students can analyze data, identify trends, and derive valuable insights that can lead to data-driven decisions.

Which tools does Apache Hive employ?

  • Hadoop Distributed File System (HDFS)
  • MapReduce
  • Apache Tez
  • Apache Spark
  • Hive Metastore

What abilities do you gain via Apache Hive Training?

  • Proficiency in HiveQL for data processing.
  • Working with the Hadoop ecosystem.
  • Data loading, transformation, and analysis.
  • Query optimization for performance.
  • Hive Metastore management and security.
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Overview of Apache Hive

Apache Hive is a free open-source data warehouse and SQL-like query language system built on top of the Hadoop ecosystem. It provides an interface to manage and query large datasets stored in distributed storage like Hadoop Distributed File System. Apache Hive training equips learners with the skills and knowledge needed to work effectively with Hive for big data processing and analytics. Apache Hive training enables learners to become proficient in working with Hive for big data processing, making them valuable assets in the field of data engineering and analytics.

 

Additional Info

Technologies Developing in Apache Hive

Apache Hive continues to evolve with advancements in the big data ecosystem, introducing new technologies and features to enhance its capabilities and performance. Some of the key technologies developing in Apache Hive include:

Apache Hive LLAP (Low Latency Analytical Processing): LLAP is an optimization feature that improves query performance by keeping data in memory and reusing resources between queries, reducing query latency significantly.

Hive on Tez: Due to the proliferation of vocal assistants and smart devices, voice search is becoming more prevalent. Optimizing websites for voice search queries and conversational language will be essential for capturing voice-based search traffic.

Vectorized Query Execution: Hive introduced vectorized query execution to process multiple rows at once, reducing the overhead of individual row processing and further improving query performance.

ACID Transactions: Hive introduced ACID (Atomicity, Consistency, Isolation, Durability) transactions, enabling users to perform transactional operations on Hive tables, making it suitable for more real-time and operational use cases.

Materialized Views: Hive introduced materialized views to store pre-computed query results, reducing query execution time and speeding up analytical workloads.

Hive Warehouse Connector (HWC): HWC allows integration with external data storage systems, such as Apache HBase and Amazon S3, providing more flexibility in data storage options.

Hive-on-Spark: Hive can now use Apache Spark as an execution engine, offering faster data processing and in-memory capabilities.

Dynamic Partition Pruning: This feature optimizes queries by skipping irrelevant partitions during query execution, reducing processing overhead.

Improved Security: Hive has been continuously improving security features, including support for Apache Ranger for centralized authorization, fine-grained access controls, and encryption.

Hive View 2.0: An enhanced web-based GUI, Hive View 2.0, provides an interactive and user-friendly environment for Hive users to query and analyze data.

The Fundamentals of Apache Hive Training

  • Apache Hive training is designed to provide learners who have a firm grasp of how to successfully use Hive for big data processing and analytics.
  • The training begins with an introduction to Apache Hive, explaining its role within the Hadoop ecosystem and its significance in facilitating data warehousing and querying large datasets.
  • Data loading and transformation are crucial aspects covered in the training. Learners understand how to efficiently load data into Hive tables from diverse sources, and they acquire skills in transforming and processing the data using HiveQL functions.
  • Learners are familiarized with the architecture of Hive, including its major components such as the Hive Metastore, Hive Server, and various execution engine options like MapReduce, Tez, and Spark.
  • To optimize query performance, learners are introduced to essential optimization techniques. These techniques, including partitioning, bucketing, and predicate pushdown, help improve query execution speed and reduce processing time, especially for large datasets.
  • Another significant aspect of Apache Hive training is exploring its integration with other components of the Hadoop ecosystem. Learners understand how Hive works seamlessly with HDFS, MapReduce, and Spark, enabling efficient data processing and analytics across the entire Hadoop infrastructure.

Apache Hive's Organizational Advantages:

Apache Hive offers several organizational advantages that make it a valuable tool for businesses and enterprises working with big data. Some of these advantages include:

Scalability: Hive is designed to handle massive volumes of data distributed across a cluster of machines. Its ability to scale horizontally allows organizations to process and analyze ever-growing datasets without compromising performance.

Cost-Effectiveness: Hive is an open-source solution that integrates with existing Hadoop infrastructure, which makes it a cost-effective choice for organizations. It leverages the power of commodity hardware, reducing the need for expensive specialized hardware.

SQL-like Interface: Hive's SQL-like query language (HiveQL) makes it user-friendly, especially for individuals familiar with SQL. This lowers the learning curve for data analysts and database administrators, enabling them to quickly adopt Hive for data processing and analytics.

Integration with Hadoop Ecosystem: As part of the Hadoop ecosystem, Hive seamlessly integrates with various other big data tools and components, such as HDFS, MapReduce, Spark, HBase, and more. This integration allows organizations to leverage the strengths of multiple technologies within a unified data processing platform.

Data Warehousing Capabilities: Hive's data warehousing capabilities enable organizations to perform Extract, Transform, Load (ETL) operations and process structured and semi-structured data efficiently. It provides a familiar relational database-like environment for data storage and querying.

Flexibility in Data Formats: Hive supports a wide range of data formats, including Avro, Parquet, ORC, and more. This adaptability enables organizations to make the best suitable data format for their specific use cases, optimizing storage and query performance.

Advanced Query Optimization: Hive employs optimization techniques like partitioning, bucketing, and predicate pushdown to improve query performance. These optimizations ensure that queries execute efficiently, even on large datasets.

Extensibility: User-Defined Functions and User-Defined Aggregations in Hive provide for flexibility. Organizations can develop custom functions to meet specific data processing requirements.

Real-time and Batch Processing: With features like Apache Hive LLAP (Low Latency Analytical Processing) and ACID transactions, Hive can handle real-time processing needs along with traditional batch processing.

Job Responsibilities and Duties in Apache Hive

  • In an organization, job responsibilities and duties related to Apache Hive can vary based on specific roles and levels of expertise.
  • Big data engineers are in charge of creating and implementing data processing workflows using Hive for ETL (Extract, Transform, Load) tasks. Part of their role includes implementing data partitioning, bucketing, and optimization techniques to enhance query performance.
  • Data analysts and data scientists utilize Hive to perform data analysis and derive insights from large datasets. They write HiveQL queries to analyze data and create data transformations for preparatory tasks.
  • Database administrators are responsible for Installing, configuring, and maintaining databases, management of Apache Hive clusters and services.They monitor Hive performance and resource utilization to optimize query execution.
  • BI developers design and build Hive-based data models and data marts for reporting and analytics. They create HiveQL queries to extract and aggregate data for business reports and dashboards. Collaborating with data analysts and stakeholders to understand reporting requirements is an essential part of their role.
  • Data architects or solution architects are responsible for designing and architecting data solutions that leverage Apache Hive as a critical component. They develop data models, schema designs, and data storage strategies using Hive tables and databases.

Tools Used for Apache Hive

Apache Hive is a powerful data warehousing and SQL-like query language system that integrates with various tools and components to support big data processing. These tools collectively enhance Apache Hive's capabilities, providing a comprehensive ecosystem for efficient big data processing, data warehousing, and analytics.

Hadoop Distributed File System (HDFS): Hive leverages HDFS as its primary storage system for distributed data storage. HDFS allows Hive to store and manage massive volumes of structured and semi-structured data across a cluster of commodity hardware.

MapReduce: Historically, Hive used MapReduce as its default execution engine to process HiveQL queries. MapReduce is a batch processing framework in Hadoop that efficiently processes data in parallel across multiple nodes in the cluster.

Apache Tez: Tez is an alternative execution engine that improves query performance and is commonly used with Hive. It tries to reduce query latency and increase resource utilisation by constructing intricate data processing pipelines and sharing resources across processes.

Apache Spark: Hive can be integrated with Apache Spark, a fast and versatile data processing engine. Spark's in-memory processing capabilities enable faster data processing and iterative analytics, making it an attractive choice for Hive users looking for real-time and interactive data analysis.

Apache HBase: Hive can integrate with Apache HBase , a NoSQL database, to combine the strengths of both systems for data processing. HBase provides low-latency access to large datasets, making it suitable for real-time data applications, while Hive offers a more familiar SQL-like interface for querying and analysis.

Apache ORC and Apache Parquet: These are columnar storage formats optimized for Hadoop. Hive supports both formats for better performance and compression. Columnar storage reduces I/O and improves query performance, making it well-suited for analytical workloads.

Apache Avro: Hive can work with Avro, a data serialization system, facilitating data exchange between different data processing tools within the Hadoop ecosystem. Avro offers a schema-based, small-footprint data serialization standard.

Apache Ranger: Ranger provides centralized authorization and access control policies for Hive, enhancing security. It enables administrators to define fine-grained access controls for users and groups, ensuring that sensitive data is protected from unauthorized access.

Apache Ambari: Ambari simplifies the management and monitoring of Hadoop clusters, including Hive services. It provides a user-friendly web interface for cluster administration, allowing administrators to manage Hive configurations and monitor performance.

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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.

Curriculum

Syllabus of Apache Hive Training
Module 1: Introduction
  • Hadoop
  • What is Hive?
  • Features of Hive
  • Architecture of Hive
  • Working of Hive
Module 2: HIVE Installation
  • Verifying JAVA Installation
  • Verifying Hadoop Installation
  • Downloading Hive
  • Installing Hive
  • Configuring Hive
  • Downloading and Installing Apache
  • Derby
  • Configuring Metastore of Hive
  • Verifying Hive Installation
Module 3: HIVE Data Types
  • Column Types
  • Literals
  • Null Value
  • Complex Types
  • Apache Hive
Module 4: Create Database
  • Create Dat
  • abase Statement
Module 5: DROP Database
  • Drop Database Statement
Module 6: CREATE Table
  • Create Table Statement
  • Load Data Statement
Module 7: ALTER Table
  • Alter Table Statement
  • Rename To… Statement
  • Change Statement
  • Add Columns Statement
  • Replace Statement
Module 8: DROP Table
  • Drop Table Statement
Module 9: Partitioning
  • Adding a Partition
  • Renaming a Partition
  • Dropping a Partition
Module 10: Built-In Operators
  • Relational Operators
  • Arithmetic Operators
  • Logical Operators
  • Complex Operators
Module 11: Built-In Functions
  • Apache Hive
  • Built-In Functions
  • Aggregate Functions
Module 12: Views And Indexes
  • Creating a View
  • Example
  • Dropping a View
  • Creating an Index
  • Example
  • Dropping an Index
Module 13: HiveQL SELECT…WHERE
  • Syntax
  • Example
Module 14: HiveQL SELECT…ORDER BY
  • Syntax
  • Example
Module 15: HiveQL GROUP BY
  • Syntax
  • Example
Module 16: HiveQL JOINS
  • Syntax
  • Example
  • JOIN
  • LEFT OUTER JOIN
  • RIGHT OUTER JOIN
  • FULL OUTER JOIN
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Need customized curriculum?

Hands-on Real Time Apache Hive Projects

Project 1
Building a Data Warehouse using Spark on Hive

This hive project , we will build a Hive data warehouse from a raw dataset stored in HDFS and present the data in a relational structure so that querying the data will be natural.

Project 2
Tough engineering choices with large datasets in Hive project

Explore hive usage efficiently in this hadoop hive project using various file formats such as JSON, CSV, ORC, AVRO and compare their relative performances.

Get Train With Our Effective Apache Hive Training With Placements

  • Every professional and student who successfully completes our course on Apache Hive with placement will have the opportunity to be placed.
  • We provide Apache Hive students internship and job placement options through collaborative corporate relationships.
  • All of our candidates have access to excellent placement opportunities in top companies like Wipro, Accenture, CTS, Siemens, Dell, and others.
  • Our trained placement specialists can help students with their resumes, interview preparation, and networking with top organizations.
  • After completing our Apache Hive course, students will be able to successfully join the job market with the necessary skills, knowledge, and assistance.
  • Our Apache Hive teachers excellent in explaining complex concepts to students in a way that is understandable.

Succeed Our Resourceful Apache Hive Certification

Earning a recognized Apache Hive certification can provide valuable career advantages, demonstrating your proficiency in big data technologies and data engineering. It can enhance your professional profile and increase your credibility in the job market, potentially opening up new career opportunities. While certifications can be beneficial, it is important to remember that practical hands-on experience with Apache Hive and related technologies is equally vital.

  • Validates expertise in Hive.
  • Enhances employability and credibility.
  • Provides a competitive edge in job market.
  • Enables career growth and promotions.
  • Widely recognized in the industry.

Organizations that extensively utilize the Hadoop ecosystem, with Hive as a critical component, are more likely to appreciate the certifications, as they highlight a candidate's expertise in a core technology they heavily rely on.

  • Hadoop knowledge
  • SQL skills (HiveQL)
  • Data warehousing concepts
  • Understanding of Hive architecture
  • Data loading and transformation abilities

Obtaining an Apache Hive certification can significantly impact career advancement in the field of big data and data engineering. The certification serves as tangible evidence of a professional's specialized expertise in Apache Hive, demonstrating their proficiency in using Hive for data processing and analytics.

  • Big Data Engineer
  • Data Analyst
  • Data Scientist
  • Business Intelligence (BI) Developer
  • Data Warehouse Specialist

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

Enhance Your Career With Help Of Our Apache Hive Trainers

  • Our Apache Hive training instructors are employed by international corporations and have at least seven years of expertise.
  • To ensure that our students receive the most up-to-date and relevant teaching, our Apache Hive professionals read industry literature on a regular basis to learn about new advancements and best practices in the area.
  • They can give practical assistance and in-depth real-world insights to understudies due to their wide understanding of Apache Hive features and capabilities.
  • During the training sessions, the Apache Hive trainer will provide each candidate a personal demonstration of various job-related responsibilities.
  • For the advantage of their learners, our educators are skilled in simplifying difficult Apache Hive ideas.
  • Experts can offer students useful guidance and in-depth knowledge since they have a thorough understanding of Apache Hive's features and capabilities.

Apache Hive Course Reviews

Our ACTE Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.

Priya

Student

Best place to learn Apache Hive . I have done training from here. Nice experience.Gopal sirs teaching was awesome everyone can understand subject very easily compare from other institute faculties his teaching is very good. In ACTE institutes to learn Apache Hive technology I referred best to go for Gopal sirs class in ACTE Institute in Tambaram.

Sree Priya

Software Engineer

I am attending the Apache Hive Online training on ACTE. While going through this curriculum, I could get insights into new architecture and detailed knowledge about those features. Our Instructor - Vinay Thota is quite knowledgeable and is through with the concepts. I am looking forward to not only gaining more architecture knowledge but also clear my certification too.

Venkat

Software Engineer

ACTE is best institute for Apache Hive training in Velachery. The faculty explains each and every module with real time scenarios. This is the best institute for Apache Hive . Thanks a lot…

Sowmiya

"I would like to recommend to the learners who wants to be an expert on Apache Hive just one place i.e., ACTE. After several research with several Training Institutes I ended up with ACTE. My Apache Hive trainer was so helpful in replying, solving the issues and Explanations are clean, clear, easy to understand the concepts and it is one of the Best Training Institute for Apache Hive Training"

Lawvanya

Software Testing

I joined in ACTE omr for Apache Hive course here without any basic knowledge on Big Data concepts.Now i can say this is the Best Apache Hive training institute in chennai. Here the trainers provide you complete knowledge on each course with Real- time scenarios, project, case studies, Interview questions and all possible ways to make you a successful Professional.

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Apache Hive Course FAQs

Looking for better Discount Price?

Call now: +91 93833 99991 and know the exciting offers available for you!

  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
ACTE
    • Gives
Certificate
    • For Completing A Course


  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Apache Hive training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed

All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.

No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.

We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Apache Hive Course At ACTE?

  • Apache Hive Course in ACTE is designed & conducted by Apache Hive experts with 10+ years of experience in the Apache Hive domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies

Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.

You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), 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.

We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Apache Hive batch to 5 or 6 members

Our courseware is designed to give a hands-on approach to the students in Apache Hive . The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.

You can contact our support number at +91 93800 99996/ Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India

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