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
@HardyDolores-m8n
13 күн бұрын
Williams Mary Gonzalez Robert Jones Donald
@AllForLove3
5 жыл бұрын
Amazing talk! very well explained indeed.
@tdkboxster
5 жыл бұрын
What an amazing talk! Crisp and Clear! truly impressed.
@anibaldk
5 жыл бұрын
Only 300 likes for such an informative, crystal clear talk??
@ctriz76
6 жыл бұрын
this is a brilliant and fluid explanation
@puja9689
4 жыл бұрын
Amazing presentation. Very intuitive..Thanks Boss!
@rahultiwari2860
5 жыл бұрын
Thanks for in-depth explaining RDD DF And DS...
@soufianebenkhaldoun7765
5 жыл бұрын
Very well explained !! Thank's
@techoral2261
2 жыл бұрын
Now i know about RDDs, DataFrames and Datasets. Thanks for explaining it more precisely. Appreciated.
@varundosapati7148
4 жыл бұрын
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
@BasemKhalaf-uj7cc
4 ай бұрын
Thank you!
@jijotitus1755
4 жыл бұрын
Amazing Talk. Thank you!
@TheTambourinist
2 жыл бұрын
Thanks for the video. Very understandable!
@daviduzumaki
Жыл бұрын
this guy is such a good speaker
@chiranjibghorai6950
6 жыл бұрын
Such a pleasure to hear him talk!
@pauliewalnuts6734
4 жыл бұрын
so good!!! thanks for this
@sayandbhattacharya1100
9 ай бұрын
I had a nice learning time thanks for the talk!
@shannithssachin
2 жыл бұрын
Great Talk
@mjrajeshmj
4 жыл бұрын
Excellent talk. Thanks Jules Damji.
@shemantkr
4 жыл бұрын
it was very insightful, such talks really helps developer why/how one should use structure API
@lbasavaraj
6 жыл бұрын
What a brilliant talk!! Thanks
@nareshgb1
6 жыл бұрын
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.
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