02. Databricks | PySpark: RDD, Dataframe and Dataset

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[reachpuneeths]

very informative, please come up with end to end projects using databricks

[shivachaitanyachinna]

Thanks for providing indepth knowledge about these topics. Amazing.

[amanpathak]

Hi, could you please provide the slides and notebooks, that would be really helpful for a quick revisions before interview

[leixvgj]

Thank you for providing such detailed videos.

[sorathiyasmit]

Your content is very good can you provide pdf of ppt

[dineshdeshpande]

Hi Raja Sir, The contents are very good in this video and playlist. But not able to understand the sequence to follow as the numbers are missing in serial numbers you given. Also playlist has 65 videos but the serial numbers are above 100 also, can you pl help with sequencing of videos to go through the playlist.

[Sandani_Aduri_Group]

Hi Raja, Your videos are very informative and interms of RDD/DataFrame/Dataset if some one which one is faster in execution what would be your answer?

[labibaug]

Could you make a repo for all your videos.. Otherwise it is hard to follow you, thanks a lot Raja

[ranjansrivastava]

As per your slide for the Differences among the RDD, Dataframe and Dataset- you mentioned the supported language for Dataframe is Java, Scala, Python and R. What about the SQL for these. Could you please clarify on this Raja. If possible.

[simachala]

can we have the github link for these PPT and code.

[ourmind]

A doubt: As you said, ultimately spark converts dataframes into RDDs while processing. Then how the benefits like avoiding GC-process and others will eventually comes into play while using DFs instead of RDDs? I'm fairly new in this area. And thanks for this playlist.

[rkjunnu]

May I know the first video of the series?

[kanstantsinhulevich]

dataset also has catalyst optimizations, but in slide it is just "optimization"

[Abdullahkbc]

Hi Raja, could you please fix the order of the playlist? thanks in advance

[ramangangwani]

sir can you please explain what is serialization

[premsaikarampudi]

RDD is not type safety right? they don't enforce datatype; This means that the type of the data in an RDD can change at runtime. This can lead to errors if the data is not properly checked.

[krishnamohan]

Can you please provide sequence number for your vedioes please

[aravind]

DataFrames are strong Type safety and RDD are not right. I think you need modify the slide.

[gunar]

So pyspark uses dataframe and not dataset right?

[Abdullahkbc]

Hi, could you please activate the subtitles for this and other videos? these are really great sources, i don't wanna miss anything.