Hadoop Project - Choosing the best SQL-on-Hadoop Engine

Hadoop Project - Choosing the best SQL-on-Hadoop Engine

In this project, we will take a look at three different SQL-on-Hadoop engines - Hive, Phoenix, Impala and Presto.
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Camille St. Omer linkedin profile url

Artificial Intelligence Researcher, Quora 'Most Viewed Writer in 'Data Mining'

I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More

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Mohamed Yusef Ahmed linkedin profile url

Software Developer at Taske

Recently I became interested in Hadoop as I think its a great platform for storing and analyzing large structured and unstructured data sets. The experts did a great job not only explaining the... Read More

What will you learn

Apache Phoenix, how it works and how to install it.
Presto, how it works and how to install it.
Impala and how to use it.
Using SQL-on-Hadoop in data processing framework like Spark.
Compare the performance of these various engines.
Lookup other SQL-on-Hadoop out there.

Project Description

The hype around SQL-on-Hadoop had died down and now people want more from these SQL-on-Hadoop engines. More requirements like real-time queries, support from various file formats, support from user-defined functions and support from various client connectivities.

In this Hackerday, we will take a look at three different SQL-on-Hadoop engines - Hive, Phoenix, Impala, and Presto. While our expectations for hive should be relatively expected, we want to to see what it will take to get to adopt other SQL-on-Hadoop engines in our big data infrastructure.

After this Hackerday session, you should be able to make a choice about these engines, make the choice with a real informed decision and be able to extend these to your data processing infrastructure.

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Curriculum For This Mini Project