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NoSQL Project on Yelp Dataset using HBase and MongoDB

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.
4.94.9

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What will you learn

  • Why store data in a NoSQL database
  • Revisit NoSQL databases concepts
  • Storing sparse business attributes in HBase
  • Storing sparse business attributes in MongoDB
  • Integrating Hive and NoSQL databases for data retrieval using query
  • Integrating Spark and NoSQL databases for retrieving data for processing

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Installation Cloudera Quickstart VM
  • An installation of MongoDB on your host machine

Project Description

Still on the series on Data engineering using Yelp dataset, we have established several concepts - from data warehousing to graph analysis. Well done.

But in today's world, not all data are best stored on HDFS. Some special requirements and scenario could require a data storage with a very low latency that could also handle large dataset. Here comes the use of NoSQL databases.

In this NoSQL project, we will use two NoSQL databases(HBase and MongoDB) to store Yelp business attributes and also learn how to retrieve these data for processing or query. We will substantiate the value of these other ways to store data over using HDFS and how to join them with data stored in HDFS in real time.

Seeing that MongoDB is not available in Cloudera Quickstart VM, we are encouraged to install MongoDB on our host machine while setting up a host network interface between the host and the VM for this big data project.

Instructors

 
Michael

Big Data & Enterprise Software Engineer

I am passionate about software development, databases, data analysis and the android platform. My native language is java but no one has stopped me so far from learning and using angular and node.js. Data and data analysis is thrilling and so are my experiences with SQL on Oracle, Microsoft SQL Server, Postgres and MyS see more...