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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
My Interaction was very short but left a positive impression. I enrolled and asked for a refund since I could not find the time. What happened next: They initiated Refund immediately. Their... Read More
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.
Bitcoin Mining on AWS - Learn how to use AWS Cloud for building a data pipeline and analysing bitcoin data.
In this big data project, we will embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.
In this hive project, you will work on denormalizing the JSON data and create HIVE scripts with ORC file format.