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In our use case, the file path will be "/FileStore/tables/complex.json." Unlike reading a CSV, By default, JSON data source infer schema from an input file which means there is no need to mention "inferschema" =true. Using ("path") or ("json").load("path") you can read a JSON file into a Spark DataFrame, these methods take a file path as an argument. path is like /FileStore/tables/your folder name/your file.click browse to upload and upload files from local.In UI, specify the folder name in which you want to save your files.

Click Table in the drop-down menu, it will open a create new table UI.Step 3: Reading the Nested JSON file by the custom schema.įollow the below steps to upload data files from local to DBFS.