A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets - Jules Damji 

this guy is such a good speaker

Amazing talk, I left off Spark to move in to ML when there was only RDD, I came back and see DataFrame in Spark and I am totally confused, your video helped a lot, Thank you

Now i know about RDDs, DataFrames and Datasets. Thanks for explaining it more precisely. Appreciated.

Such a pleasure to hear him talk!

What an amazing talk! Crisp and Clear! truly impressed.

This is best and clear talk on 3 APIs

Thanks for in-depth explaining RDD DF And DS...

this is a brilliant and fluid explanation

Only 300 likes for such an informative, crystal clear talk??

Excellent talk. Thanks Jules Damji.

Thank you!

An excellent talk by a clear master.

I had a nice learning time thanks for the talk!

Amazing presentation. Very intuitive..Thanks Boss!

Great Talk

Amazing talk! very well explained indeed.

What a brilliant talk!! Thanks

Thanks for the video. Very understandable!

it was very insightful, such talks really helps developer why/how one should use structure API

Amazing Talk. Thank you!

Very well explained !! Thank's

Very good talk!

so good!!! thanks for this

Nice and informative video

brilliant talk!

excellent explanation!! :D

I am wondering how the "type safe" feature combines with the "unstructured data" that is the nature of data in the systems that spark would be used in.

awwwwesome talk thanks!

I was trying out the example you mentioned @10:46 and as i am getting compile time error, I had to rewrite the final statement as below. parsedRdd.filter( content => content._2 == "en").map(filteredContent => filteredContent._3).reduce(_+_).take(100).foreach(reducedContent => printf(s"$reducedContent._1: $reducedContent._2")) I would really appreciate if you can review above statement

wow

Thanks! Can you attach the links here?

No SS

Hibud

This was amazing! Pretty well explained! Thanks!

Amazing Talk