Solved end-to-end Apache Hive Projects

Apache Hive Projects

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Apache Hive Projects


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 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.

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

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

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

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.

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

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

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.

In this Spark project, we are going to bring processing to the speed layer of the lambda architecture which opens up capabilities to monitor application real time performance, measure real time comfort with applications and real time alert in case of security

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

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

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

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.

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 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.

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.

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

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.

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Hadoop Hive Projects for Beginners

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