JSON (S3 hosted) to Excel File Conversion

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# Project Name - JSON (S3 HOSTED) TO EXCEL FILE CONVERSION

# Recipe ID - 
# Recipe URL - https://app.lingk.io/a/10932/tf/17880

# Description - # This recipe converts JSON (nested or flat) to an Excel file.
                # To use this recipe, configure the Amazon S3 connector in your environment and upload the file into your S3 bucket. Then download the file from Local File area for your environment.

# Industry - Higher Ed
# Business Process - Graduate Reporting

# Systems - S3Bucket
# Connectors - LocalFile, S3Bucket
# Data Flows - Single Direction
# Connection Type - S3Bucket to Excel

# Add Recipe notes / Change log information here!

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# CONNECTORS specify what data will be pulled into the in-memory database during processing

connectors:

# Configure S3Bucket credentials in your Environment before running this recipe
  # S3Bucket Setup - https://help.lingk.io/en/articles/298-amazon-s3-connector-setup-guide
  # LocalFile Setup - https://help.lingk.io/en/articles/126-local-file-connector-reference

###### Start: S3 Connectors #######

# note you can specify file directly 
-
    name: s3FileReader
    type: s3Reader
    format: jsonFormat
    #properties:
      #s3ObjectKey: myfile.json

###### End: S3 Connectors #######

###### Start: LocalFile Connectors #######

-
    name: convertedFile
    type: localFileWriter
    format: excelFormat
    properties:
      fileName: "s3_output.xlsx"

###### End: LocalFile Connectors #######

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# FORMATS specify how files should be processed as they are being read or written to

readFormats:
-
    name: jsonFormat
    type: json

writeFormats:
-
    name: excelFormat
    type: excel
    properties:
      worksheets: "data"
      useHeader: "true"

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# STATEMENTS specify how the data should be processed while in memory

statements:

#******************************************************************** D I S C L A I M E R ***********************************************************************************************
#                                                                                                                                                                                       * 
# Note that in an effort to keep recipes optimized for DPH (Data Processing Hours), print statements should be commented out after development has concluded for a recipe.              *
# For more information on DPH optimization, please visit the following help article - https://help.lingk.io/en/articles/212-minimizing-data-processing-hours-on-the-lingk-platform      *
#                                                                                                                                                                                       * 
#******************************************************************** D I S C L A I M E R ***********************************************************************************************

# Note: you can use dot notation in your SELECT statement to reach into nested data. You can also access nested arrays with explore() or inline() functions.
  - statement: (outputData) => SELECT * FROM s3FileReader
  #- statement: print outputData

- statement: INSERT outputData INTO convertedFile

# Add more statements to convert, join, aggregrate, transform, and integrate your data