Windowing Functions in Spark SQL Part 3 | Aggregation Functions | Windowing Functions Tutorial
Windowing Functions in Spark SQL Part 3 | Aggregation Functions | Windowing Functions Tutorial
https://acadgild.com/big-data/big-dat...
Hello and welcome back to the series of windowing functions in Spark. In the previous video, you learned the internals of lag and lead functions. If you had missed it, please click the following video link for the better continuation.
Windowing Functions in Spark Part 1 - • Windowing Functions in Spark SQL Part...
Windowing Functions in Spark Part 2 - • Windowing Functions in Spark SQL Part...
In this Hadoop tutorial, you will be able to learn, how to perform aggregation with window functions using over clause.
To perform aggregations, we have pre-built functions like
• Min
• Max
• Count
• Average and Sum
To give you a brief idea of these aggregation functions, we will be using stock market data. You can download the sample stock data from the following links
Dataset Link: https://drive.google.com/open?id=1nWG...
Command Download Link: https://docs.google.com/document/d/1P...
The problem we are trying to solve here using this dataset is to get least closing value for all the tickers in the dataset.
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