SQL and Machine Learning on Hadoop using HAWQ

It is true to the extent it is almost considered rhetorical to say

“Many Enterprises have adopted HDFS as the foundational layer for their Data Lakes. HDFS provides the flexibility to store any kind of data and more importantly it’s infinitely scaleable on commodity hardware.”

But the conundrum till date is the solution for a low latency query engine for HDFS.

At Pivotal, we cracked that problem and the answer is HAWQ, which we intend to open source this year. During this event, we will present and demo HAWQ’s Architecture, it’s powerful ANSI SQL features and it’s ability to transcend traditional BI in the form of in-database analytics (or machine learning).

Agenda

[6.30p - 7.00p] - Food & Drinks.

[7.00p - 7.20p] - HDFS Architecture, HAWQ's Architecture, Installing HAWQ on a Hadoop Cluster using Ambari.

[7.20p - 7.40p] - Demo on: Loading Data into HDFS, Querying HDFS using HAWQ's external and internal tables.

[7.40p - 8.00p] - Demo on: Writing advanced SQLs using HAWQ.

[8.00p - 8.20p] - Demo on: In-Database Machine Learning from HAWQ using MADLib, PL/Python & PL/R.

[8.20p - 8.45p] - Q & A.

[We are hiring locally and for many other locations in the US!! Come talk to us, We have open positions for Data Engineering and Data Science roles at Associate and Senior levels.]