Pyspark Scenarios 13 : how to handle complex json data file in pyspark

Pyspark Scenarios 13 : how to handle complex json data file in pyspark #pyspark #databricks
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notebook location:
github.com/raveendratal/ravi_...
Complete Pyspark Real Time Scenarios Videos.
Pyspark Scenarios 1: How to create partition by month and year in pyspark
• Pyspark Scenarios 1: H...
pyspark scenarios 2 : how to read variable number of columns data in pyspark dataframe #pyspark
• pyspark scenarios 2 : ...
Pyspark Scenarios 3 : how to skip first few rows from data file in pyspark
• Pyspark Scenarios 3 : ...
Pyspark Scenarios 4 : how to remove duplicate rows in pyspark dataframe #pyspark #Databricks
• Pyspark Scenarios 4 : ...
Pyspark Scenarios 5 : how read all files from nested folder in pySpark dataframe
• Pyspark Scenarios 5 : ...
Pyspark Scenarios 6 How to Get no of rows from each file in pyspark dataframe
• Pyspark Scenarios 6 Ho...
Pyspark Scenarios 7 : how to get no of rows at each partition in pyspark dataframe
• Pyspark Scenarios 7 : ...
Pyspark Scenarios 8: How to add Sequence generated surrogate key as a column in dataframe.
• Pyspark Scenarios 8: H...
Pyspark Scenarios 9 : How to get Individual column wise null records count
• Pyspark Scenarios 9 : ...
Pyspark Scenarios 10:Why we should not use crc32 for Surrogate Keys Generation?
• Pyspark Scenarios 10:W...
Pyspark Scenarios 11 : how to handle double delimiter or multi delimiters in pyspark
• Pyspark Scenarios 11 :...
Pyspark Scenarios 12 : how to get 53 week number years in pyspark extract 53rd week number in spark
• Pyspark Scenarios 12 :...
Pyspark Scenarios 13 : how to handle complex json data file in pyspark
• Pyspark Scenarios 13 :...
Pyspark Scenarios 14 : How to implement Multiprocessing in Azure Databricks
• Pyspark Scenarios 14 :...
Pyspark Scenarios 15 : how to take table ddl backup in databricks
• Pyspark Scenarios 15 :...
Pyspark Scenarios 16: Convert pyspark string to date format issue dd-mm-yy old format
• Pyspark Scenarios 16: ...
Pyspark Scenarios 17 : How to handle duplicate column errors in delta table
• Pyspark Scenarios 17 :...
Pyspark Scenarios 18 : How to Handle Bad Data in pyspark dataframe using pyspark schema
• Pyspark Scenarios 18 :...
Pyspark Scenarios 19 : difference between #OrderBy #Sort and #sortWithinPartitions Transformations
• Pyspark Scenarios 19 :...
Pyspark Scenarios 20 : difference between coalesce and repartition in pyspark #coalesce #repartition
• Pyspark Scenarios 20 :...
Pyspark Scenarios 21 : Dynamically processing complex json file in pyspark #complexjson #databricks
• Pyspark Scenarios 21 :...
Pyspark Scenarios 22 : How To create data files based on the number of rows in PySpark #pyspark
• Pyspark Scenarios 22 :...
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[@anubhavoberoy837]

Excellent tutorial, looking forward to many more scenario based questions. Thanks a lot :)

[@varun8952]

Super bro, looking forward for next json tutorial

[@JeFFiNat0R]

super! thank you!

[@fchehwan7314]

Very good explanation sir! Kudos

[@samk_jg]

Awesome tutorial👏

[@deepakkumar3301]

Nice explain sir

[@sureshajj]

Thank you. Good one.

[@TRRaveendra]

Thank you too!

[@nakkavenkataramana7445]

Thankyou Brother

[@TRRaveendra]

Thank you Ramana 👍

[@ak1232003]

Very good tutorial! Can you please show how to 1. extract json schema file from data frame and 2. load complex json files based on json schema file? Thanks!

[@TRRaveendra]

kzbin.info/www/bejne/p5etk2driNqmg9E

[@shubhamaggarwal3676]

Nice Explanation with good example. Can you please give the video link, that you were talking about, dynamically add columns?

[@TRRaveendra]

kzbin.info/www/bejne/p5etk2driNqmg9E

[@saiveeramalla5507]

Can you try it dynamically..like if the schema is changing is constantly and without mentioning the column names and all , dynamically parse it

[@thebossismael1511]

Muchas gracias amigo, me sirvió de mucho. 1)existen en un json datos vacios y quisiera que no aparecieran. 2) Cómo hacer para que en un json me cargue las columnas por defecto y no me agregue el nombre de la columna principal sino el el nombre solo

[@shreyaspatil4861]

Thanks very much for the tutorial :) , I have a query regarding reading in json files. so i have an array of structs where each struct has a different structure/schema. And based on a certain property value of struct I apply filter to get that nested struct , however when I display using printschema it contains fields that do not belong to that object but are somehow being associated with the object from the schema of other structs , how can i possibly fix this issue ?

[@amanpal5958]

Hi, thanks for the video. In my case my nested struct type column does not contain any nested array type column instead it contains nested struct type. Is there any other way I could use?

[@RD-st4vk]

Can u show how to create this multiline json file from table

[@4802798649]

How to extract if it is JSON object. This works only for array. Any idea?

[@rocku4evr]

great ..did you upload the dynamically exploding one? not able to locate

[@TRRaveendra]

kzbin.info/www/bejne/p5etk2driNqmg9E

[@omglucky1063]

hi, can you increase video quality: 360p only current video -> increase to 720p, 1080p for better visibility.

[@TRRaveendra]

Just now uploaded It will take some time to convert full hd

[@srikanthpatil9469]

Can I add a column in nested json array??

[@TRRaveendra]

Yes, you can add any datatype on dataframe using withcolumn

[@srikanthpatil9469]

@@TRRaveendra In dataframe you cannot modify json nested array

[@TRRaveendra]

@@srikanthpatil9469 you add a new column dataframe and you can change data in dataframe using cast function. you can try that. using withColumn() for adding a new column and chaging data type