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sjpark's avatar
sjpark
Frequent Visitor
2 years ago
Solved

Read multiple files in Fabric Notebook

Hi, i'm trying to display data from Fabric Lakehouse's file system using notebook.

 

I suceeded load csv file to Lakehouse's file system from Lakehouse's Table with using notebook.

 

And now, I tried to read that csv files using this code, but it failed.

 

df = spark.read.format("csv").option("header","true").load("Files/sjpark_test_result_job/**")

display(df)

 

 

 
I tried 
load("Files/sjpark_test_result_job/**.csv")load("Files/sjpark_test_result_job/*.csv")
but it doesn't work.
 
And I also tried below code, but it won't work.
 

df = spark.read.option("header","true").option("inferSchema", "true").csv("Files/sjpark_test_result_job")

display(df)

 
The error message is 'PATH NOT FOUND"
 
 
My question is, how can i read mutiple files in Lakehouse file system using notebook?
I appriciate all opinion, thanks a lot.
Park.
  • Anonymous's avatar
    Anonymous
    2 years ago

    Hi sjpark 
    Thanks for using Fabric Community.
    You can use the below code:
    df = spark.read.format("csv").option("header","true").load("Files/sjpark_test_result_job")
    display(df)

    I have created a repro for you. 

    Hope this helps. Please let me know if you have any other questions.

3 Replies

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi sjpark 
    Thanks for using Fabric Community.
    You can use the below code:
    df = spark.read.format("csv").option("header","true").load("Files/sjpark_test_result_job")
    display(df)

    I have created a repro for you. 

    Hope this helps. Please let me know if you have any other questions.

  • sjpark's avatar
    sjpark
    Frequent Visitor

    Thanks a lot Anonymous !!
    I solved it!

    Wish you a best luck.

    • Anonymous's avatar
      Anonymous
      Not applicable

      Hi sjpark 
      Glad that your query got resolved. Thank you for appreciating it. I'm happy to help. Please continue using Fabric Community for any help regarding your queries.
      Good luck to you as well!