Solved end-to-end Apache Hive Projects

Solved
end-to-end
Apache Hive Projects

Get ready to use Apache Hive Projects for solving real-world business problems

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Apache Hive Projects

 

In this Databricks Azure tutorial project, you will use Spark Sql to analyse the movielens dataset to provide movie recommendations. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.

In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.

Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.

Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.

Build a fully working scalable, reliable and secure AWS EMR complex data pipeline from scratch that provides support for all data stages from data collection to data analysis and visualization.

Bitcoin Mining on AWS - Learn how to use AWS Cloud for building a data pipeline and analysing bitcoin data.

In this hive project, you will design a data warehouse for e-commerce environments.

Use the dataset on aviation for analytics to simulate a complex real-world big data pipeline based on messaging with AWS Quicksight, Druid, NiFi, Kafka, and Hive.

Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.

In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.

In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.

The goal of this hadoop project is to apply some data engineering principles to Yelp Dataset in the areas of processing, storage, and retrieval.

Hadoop Project- Perform basic big data analysis on airline dataset using big data tools -Pig, Hive and Impala.

In this spark project, we will continue building the data warehouse from the previous project Yelp Data Processing Using Spark And Hive Part 1 and will do further data processing to develop diverse data products.

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

This is in continuation of the previous Hive project "Tough engineering choices with large datasets in Hive Part - 1", where we will work on processing big data sets using Hive.

Analyze clickstream data of a website using Hadoop Hive to increase sales by optimizing every aspect of the customer experience on the website from the first mouse click to the last.

In this hive project, you will work on denormalizing the JSON data and create HIVE scripts with ORC file format.

In this NoSQL project, we will use two NoSQL databases(HBase and MongoDB) to store Yelp business attributes and learn how to retrieve this data for processing or query.

Learn to write a Hadoop Hive Program for real-time querying.

In this big data project, we will talk about Apache Zeppelin. We will write code, write notes, build charts and share all in one single data analytics environment using Hive, Spark and Pig.

In this big data project, we'll work with Apache Airflow and write scheduled workflow, which will download data from Wikipedia archives, upload to S3, process them in HIVE and finally analyze on Zeppelin Notebooks.

In this big data project, we will be performing an OLAP cube design using AdventureWorks database. The deliverable for this session will be to design a cube, build and implement it using Kylin, query the cube and even connect familiar tools (like Excel) with our new cube.

In this project, we will evaluate and demonstrate how to handle unstructured data using Spark.

Why you should work on ProjectPro’s Hadoop hive projects?

  • Apache Hive is the gateway for BI and data visualization tools integrated with Hadoop. These hive practice examples will help Hadoop developers innovate new data architecture projects.
  • With increase in Hive performance, the number of Hive use cases in the industry are growing. Working on these hive real time projects will help individuals get exposure to diverse big data problems that can be tackled using Apache hive.

Who should work on Hadoop Hive projects ?

  •  Anybody who is enthusiastic to know and learn more about big data and hadoop ecosystem.
  • Individuals who are already using the Hadoop ecosystem

Key Learnings from ProjectPro’s Hive Projects 

  • Understand what hive is for, and how it works.
  • Learn to design your own data pipeline using HiveQL queries.
  • These hive practice projects will let you explore the end-to-end usage of Hadoop Hive tool for preparing data, importing data, writing and running HiveQL queries, and analyzing data.
  • Learn various approaches and tactics to work on diverse business datasets using Apache Hive.

Hadoop Hive Projects for Beginners

If you are starting your career as a big data enthusiast and are looking for best Hadoop hive projects for practice then you should check out the following best selling hive projects –

What will you get when you enroll for Hadoop Hive projects?

  • Hive Project Source Code: Examine and implement end-to-end real-world big data hadoop projects from the Banking, eCommerce, and Entertainment sector using this source code.
  • Recorded Demo: Watch a video explanation on how to execute these hive project examples.
  • Complete Solution Kit: Get access to the solution design, documents, and supporting reference material, if any for every hadoop hive  project.
  • Mentor Support: Get your technical questions answered with mentorship from the best industry experts for a nominal fee.
  • Hands-On Knowledge: Equip yourself with practical skills on Hive tool in the  hadoop ecosystem.

Apache Hive Use Cases:

Hive is a data warehouse tool used to process structured data in the Hadoop environment. It is built on top of Hadoop and is primarily used to make querying and analysis easy. 

  • Developers use Hive to store schema in a database and store processed data into HDFS. However, it is not a relational database.

  • It is designed for online analytical processing (OLAP) and not meant for online transaction processing (OLTP).

  • Hive provides an SQL-type language for querying and accessing data, commonly referred to as HiveQL or HQL.

  • Hive was built for sophistication and can handle complex queries. It is fast, fault-tolerant, scalable and extensible.

Hive Projects for Practice

The best way to understand any technology or software is with some hands-on experience and practise working with the tools. ProjectPro provides you with end-to-end Hive practice examples containing mini-projects with source code to help you brush up your Big Data and data processing skills by working with Hive projects. The projects may involve only Hive, or the integration of Hive with other tools. 

Finding Unique URLs using Hive

Through this Hive project, you can learn how to write a Hive program to find the first unique URL given a file containing ‘n’ number of URLs.

Recommended Project Categories that Might Interest You

You would have practised quite a few Apache Hadoop projects, but do have a look at some of the other project categories that ProjectPro offers to get more practise working on tools in the Big Data and Data Science fields.

Big Data Projects using Apache Hadoop

Apache Flume Projects

Projects using Spark Streaming

Big Data Projects using Apache HBase

Apache Pig Projects

Spark SQL Projects