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05_​SAS_​SPSS_​MATLAB_​meet_​S3

SAS SPSS and MATLAB meet S3
In this example, proprietary files can either be loaded directly into Amazon S3 or alternatively first converted to an open format then directly written to AmazonS3. The proprietary software is not required to do this. Downloading and uploading files is not required either.You will need to provide your own Amazon S3 Access Key ID and Secret Access Key for the example to function (see article linked in the description). Connect to S3 using Access Key ID Folders created on root level are created as buckets on S3. The virtual filesystemfunctionality is fully supported by the file handling nodes. Load from local file system directly to S3 Convert each file to CSV and write directly to S3 SASSPSSMatlabChoose option toUpload orconvert and uploadSet Option to Delete or keep all files(good for cleaning up)Create a list of the 5proprietary files: SAS,SPSS and MATLABEnter your own Access Key ID +Security KeyWrite CSV directly to S3 Loop over eachfile, choosing anappropriate actionbased on file typeWrite CSVdirectly to S3Write CSVdirectly to S3Check that filesare on S3Create bucketCreate CSV filevariable on S3Create CSV filevariable on S3Create CSV filevariable on S3Create directoryTransfer files (only SAS, SPSS,and MATLAB) from the localsystem to Amazon S3SAS7BDAT Reader R Source (Table) R Source (Table) Choose Load Type End IF Delete Bucket List Files/Folders Amazon S3 Connector AmazonAuthentication CSV Writer Table Row ToVariable Loop Start CSV Writer CSV Writer Variable Loop End List Files/Folders Create Folder Create File/FolderVariables Create File/FolderVariables Create File/FolderVariables Extract filesmetadata Create unique bucket nameand path to it on S3 Create Folder Transfer Files CASE Switch Start CASE Switch End In this example, proprietary files can either be loaded directly into Amazon S3 or alternatively first converted to an open format then directly written to AmazonS3. The proprietary software is not required to do this. Downloading and uploading files is not required either.You will need to provide your own Amazon S3 Access Key ID and Secret Access Key for the example to function (see article linked in the description). Connect to S3 using Access Key ID Folders created on root level are created as buckets on S3. The virtual filesystemfunctionality is fully supported by the file handling nodes. Load from local file system directly to S3 Convert each file to CSV and write directly to S3 SASSPSSMatlabChoose option toUpload orconvert and uploadSet Option to Delete or keep all files(good for cleaning up)Create a list of the 5proprietary files: SAS,SPSS and MATLABEnter your own Access Key ID +Security KeyWrite CSV directly to S3 Loop over eachfile, choosing anappropriate actionbased on file typeWrite CSVdirectly to S3Write CSVdirectly to S3Check that filesare on S3Create bucketCreate CSV filevariable on S3Create CSV filevariable on S3Create CSV filevariable on S3Create directoryTransfer files (only SAS, SPSS,and MATLAB) from the localsystem to Amazon S3SAS7BDAT Reader R Source (Table) R Source (Table) Choose Load Type End IF Delete Bucket List Files/Folders Amazon S3 Connector AmazonAuthentication CSV Writer Table Row ToVariable Loop Start CSV Writer CSV Writer Variable Loop End List Files/Folders Create Folder Create File/FolderVariables Create File/FolderVariables Create File/FolderVariables Extract filesmetadata Create unique bucket nameand path to it on S3 Create Folder Transfer Files CASE Switch Start CASE Switch End

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: koetter
Created at: 2016-10-13
On NodePit since: 2019-07-12
Last update: 2024-04-25
Created with KNIME version: v4.6.1
Tags: SASSPSSMATLABSASB7DATSAVMATAmazon S3

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