Spark Interview Question | Scenario Based |DataFrameReader - Handle Corrupt Record | LearntoSpark

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In this video, we will learn how to handle the corrupted records in our dataset using Apache Spark. We will also learn about the mode available in option while reading a file as dataframe using Spark DataFrameReader API. Hope it will be useful for your interview preparation.

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  1. Azarudeen Shahul
  2. Spark Interview Question
  3. Scenario Based Question
  4. Spark
  5. Pyspark
  6. learntospark
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Комментарии
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Explanation in Simple words.. Really good to follow.

madhubalagnanamoorthy
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Thanks for sharing your knowledge. May you be blessed with more of it.

faizalimuhammadzoda
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underrated content! Thanks for providing such info!

billcates
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thanks Azar ...it is help ing for invterwive prospect

moulalichebolu
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Hi videos are very helpful and it would be great if you can share the sample files also for practice

areeshkumar
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Hi, what if i want the corrupted data for checking which records are going for reject…
how to get the corrupted records into another dataframe ?

nareshgiduthuri
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But In real time it we need to capture or save malformed records for analysis. So wrote those malformed ones in textfile. Use either option and capture the malformed ones.

umamahesh
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Really useful.Can you please make complete playlist for pyspark tutorial, covering all topics.

varungupta
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How it identifies those records are invalid ? Because we gave schema for all 3 columns with StringType, also we setted nullable = True, in that case those records are valid only right ? Kindly help me to understand this...

prabuchandrakumar
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Is there a way to store the malformed rows in a separate file. Or count the number of records dropped in the dropmalformed mode?

ASHISH
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Could you please explain why u renamed the column to c1, c2 And why it is not advisable for header true

amitpadhi
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How will one fine all available options for the given api method/option of spark ??

SpiritOfIndiaaa
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Do you have Facebook page as well?
Please provide the link

ManishKumar-sreu
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How to capture bad records in separate file for analysis

MultiSuresh
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How to avoid bad email format in dataframe, i want only email correct format data..?

kollurusrinivasarao