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[D] Methods to handle streaming/real-time data storage, wrangling and prediction?

Say that there is data being streamed into Python (Kafka, Kinesis etc) every 10 seconds that I would like to wrangle and predict on. What is the best way to store this streaming data in order to do this? In the past, I have used online learning methods to do this. I am curious how to do this with a batch learning method.

I was thinking we iteratively populate a DataFrame with this data until stream stops, preprocess on the entire dataframe, predict, clear/delete the DataFrame. A caveat of this method that I am able to think of would be scenarios in which this preprocessing and predicting takes longer than 10 seconds.

What are some ways to handle this?

submitted by /u/Straighteight424
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.