02. Databricks | PySpark: RDD, Dataframe and Dataset

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Raja's Data Engineering

Raja's Data Engineering

3 жыл бұрын

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Пікірлер: 61
@reach2puneeths
@reach2puneeths 2 жыл бұрын
very informative, please come up with end to end projects using databricks
@amanpathak7507
@amanpathak7507 Жыл бұрын
Hi, could you please provide the slides and notebooks, that would be really helpful for a quick revisions before interview
@user-le3ix8vg7j
@user-le3ix8vg7j Ай бұрын
Thank you for providing such detailed videos.
@rajasdataengineering7585
@rajasdataengineering7585 Ай бұрын
Glad you like them! Keep watching
@velaatechsolutions9738
@velaatechsolutions9738 3 жыл бұрын
Super
@maruthiraoyarapathineni2012
@maruthiraoyarapathineni2012 9 ай бұрын
Great work. 👍👏👏
@rajasdataengineering7585
@rajasdataengineering7585 9 ай бұрын
Thank you! Cheers!
@dineshdeshpande6197
@dineshdeshpande6197 5 ай бұрын
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
@Sandani_Aduri_Group 2 жыл бұрын
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?
@rajasdataengineering7585
@rajasdataengineering7585 2 жыл бұрын
Hi Sandani, good question. RDD is native api for Spark. So whatever we use dataset or dataframe, it would be internally converted to RDD. But rdd is quite outdated for programming nowadays. Dataframe is widely used across projects due to developer convenience. Would recommend to go with dataframe. Dataset has limitations with programming languages. For detailed information, please refer this video kzbin.info/www/bejne/nWW3Y2iVaa16g5I
@labib8aug
@labib8aug 2 жыл бұрын
Could you make a repo for all your videos.. Otherwise it is hard to follow you , thanks a lot Raja
@meghagavade8672
@meghagavade8672 7 ай бұрын
Best One
@rajasdataengineering7585
@rajasdataengineering7585 7 ай бұрын
Thanks!
@ranjansrivastava9256
@ranjansrivastava9256 6 ай бұрын
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.
@rajasdataengineering7585
@rajasdataengineering7585 6 ай бұрын
Hi Ranjan, yes spark SQL is also supported by dataframe api
@ourmind8677
@ourmind8677 7 ай бұрын
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.
@rajasdataengineering7585
@rajasdataengineering7585 7 ай бұрын
GC is related to on heap memory, not related to dataframe or RDD.
@pavanjavvadi9902
@pavanjavvadi9902 6 ай бұрын
So does it mean dataframes don’t run in heap memory ?
@harithad1757
@harithad1757 2 ай бұрын
amazing
@rajasdataengineering7585
@rajasdataengineering7585 2 ай бұрын
Thank you! Cheers!
@simachala
@simachala 2 жыл бұрын
can we have the github link for these PPT and code.
@rkjunnu7224
@rkjunnu7224 2 ай бұрын
May I know the first video of the series?
@gulsahtanay2341
@gulsahtanay2341 4 ай бұрын
Thank you
@rajasdataengineering7585
@rajasdataengineering7585 4 ай бұрын
You're welcome
@Abdullahkbc
@Abdullahkbc Жыл бұрын
Hi Raja, could you please fix the order of the playlist? thanks in advance
@rajasdataengineering7585
@rajasdataengineering7585 Жыл бұрын
Hi Abdullah, sure I will do it
@ramangangwani9203
@ramangangwani9203 3 ай бұрын
sir can you please explain what is serialization
@rajasdataengineering7585
@rajasdataengineering7585 3 ай бұрын
Sure, will create a video on this requirement
@kanstantsinhulevich4313
@kanstantsinhulevich4313 7 ай бұрын
dataset also has catalyst optimizations, but in slide it is just "optimization"
@rajasdataengineering7585
@rajasdataengineering7585 7 ай бұрын
Yes dataset and spark SQL also uses catalyst optimizer. Optimization means catalyst optimizer. In the previous slide, mentioned that dataset consolidates best features from both rdd and dataframe
@premsaikarampudi3944
@premsaikarampudi3944 11 ай бұрын
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.
@ranaumershamshad
@ranaumershamshad 9 ай бұрын
I checked this with ChatGPT. It says that RDDs in Spark offer flexibility and can handle various data types and do not provide strong type safety by default. To ensure type safety in RDD-based Spark applications, you should use best practices, perform explicit type checks and conversions, and consider higher-level abstractions like DataFrames and Datasets for structured data processing tasks.
@rajasdataengineering7585
@rajasdataengineering7585 9 ай бұрын
Pls check spark official documentation instead of chatgpt to know the truth
@krishnamohan5950
@krishnamohan5950 2 жыл бұрын
Can you please provide sequence number for your vedioes please
@rajasdataengineering7585
@rajasdataengineering7585 2 жыл бұрын
Sure Krishna, I will arrange the videos and create perfect playlist. Please allow me sometime for that.
@krishnamohan5950
@krishnamohan5950 2 жыл бұрын
Ru providing real time training raja ji
@krishnamohan5950
@krishnamohan5950 2 жыл бұрын
@@rajasdataengineering7585 sent email
@rajasdataengineering7585
@rajasdataengineering7585 2 жыл бұрын
Thanks, will respond asap
@navjotsingh-hl1jg
@navjotsingh-hl1jg Ай бұрын
sir can you share pdf sir
@gunar4831
@gunar4831 Жыл бұрын
So pyspark uses dataframe and not dataset right?
@rajasdataengineering7585
@rajasdataengineering7585 Жыл бұрын
Yes dataset is only available in scala and Java while dataframe is available with pyspark, R, scala, SQL
@aravind5310
@aravind5310 Жыл бұрын
DataFrames are strong Type safety and RDD are not right. I think you need modify the slide.
@rajasdataengineering7585
@rajasdataengineering7585 Жыл бұрын
No, dataframes are weak type safety, whereas rdd and datasets are strong type safety. For spark engine, dataframe is collection of rows (not individual columns) so it can't validate the column data type during compile time. So it is not strong type safety. Hope you understand. Pls refer spark documentation to know more about type safety
@akash4517
@akash4517 Жыл бұрын
Dataframes are mutable .
@rajasdataengineering7585
@rajasdataengineering7585 Жыл бұрын
No, dataframe is immutable
@akash4517
@akash4517 Жыл бұрын
In Pyspark we can do this Df = Df . Select or any other transformation . Which will change its state ? Or am I considering mutability wrong ? .
@rajasdataengineering7585
@rajasdataengineering7585 Жыл бұрын
Yes you can do df=df.select but it does not mean that dataframe is mutable. What happens internally is previous dataframe is dropped and another new df is created based on lazy evaluation, not the previous df is getting modified. Dataframe is always immutable
@akash4517
@akash4517 Жыл бұрын
Ok thank you Raja for helping out . Got it .
@akash4517
@akash4517 Жыл бұрын
Raja i am confused between two topics , optimize write and auto compact . I saw you had made video on optimize still confused .
@Abdullahkbc
@Abdullahkbc 9 ай бұрын
Hi, could you please activate the subtitles for this and other videos? these are really great sources, i don't wanna miss anything.
@rajasdataengineering7585
@rajasdataengineering7585 9 ай бұрын
Hi Abdul, sure will activate the subtitles
@Christy-du9jw
@Christy-du9jw 5 ай бұрын
@@rajasdataengineering7585 I would also appreciate the subtitles so I don't miss information
@GovardhanaReddy-kp6jt
@GovardhanaReddy-kp6jt Жыл бұрын
Raja Bro could you please provide your email id i need to learn This couse
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