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Hadoop Project for Beginners-SQL Analytics with Hive

In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.

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What will you learn

  • Hive high-level recap
  • Data ingestion/transformation using Sqoop, Spark and Hive
  • File formats and query performance
  • Writing aggregate queries using UDAFs.
  • Aggregation using widowing functions.
  • Query optimizations in Hive

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.
  • It is also essential for students to have a fair knowledge of Hadoop.
  • No knowledge of Hive is required for this hackerday as we will do a little overview of hive before we begin.

Project Description

In this hive project, we want to take a deeper dive into some analytical features in Hive. Using SQL is still very dominant and will remain so for the nearest features. Most big data tools have been adapted to allow users interact with them using the familiar SQL language. This is because of years of knowledge and skill that has gone into training, acceptance, tooling, standards development and re-engineering. So in many cases, using these cool features of SQL to access data solves a lot of analytical questions without ever needing us to resort to machine learning, BI or data mining.

In this big data project, we want to look at these features in Hive that allows us to perform analytical queries over large datasets.

We will be using the adventure works dataset in a MySQL dataset. Therefore, there will be a need to ingest and transform the data before we proceed to analytics.

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...

Curriculum For This Mini Project

 
  Overview
11m
  SerDes
03m
  Cloning the dataset
02m
  Understanding the dataset
05m
  Load the data
06m
  Query the data
11m
  Create a Sqoop job
19m
  Executing the Sqoop job
15m
  Why is append used ?
04m
  Build hive tables on top of the data
11m
  Troubleshooting hive table
03m
  Using Parquet and xpath
18m
  Select statement
12m
  Use case based aggregations
09m
  Q&A - the problem statement
14m
  Q&A - Hive versus myql database
08m
  Enhancing aggregate functions
25m
  Grouping sets
08m
  Rollup versus Cube
16m
  Windowing analytic functions
18m
  Properties of windowing analytic functions
24m
  Solving an example - finding %
16m