Updating Schema reading procedures and refactoring #78
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Hsankesara
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Jan 16, 2024
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Hsankesara
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- Updated data reading procedure
- refactor to make all modules more spark dependent
- Added and updated tests + upgraded spark version to 3.5.0
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Added custom data reading module that can be used independently
afolarin
approved these changes
May 17, 2024
| @@ -4,7 +4,7 @@ project: | |||
| version: mock_version | |||
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| input: | |||
| data_type: local # couldbe mock, local, sftp, s3 | |||
| data_type: mock # couldbe mock, local, sftp, s3 | |||
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would this be better as data_source or source_type data type is more specific to the data, this I think relates more to the source of the data
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While SFTP (though rsync might be useful for restart function) and S3 (implemented?) probably cover a lot of cases, I don't want to really support every method here as we can't support the long tail of the distribution. It should probably be the user's responsibility to provide a way to expose the remote data with network mounts, local copies, etc.
| logger = logging.getLogger(__name__) | ||
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| class CustomDataReader(): |
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What is the distinction here between ingestion and reader?
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