Measurement-oriented non-relational databases often have a fixed structure schema to better manage and guarantee integrity of their data. However, this leads to a redundancy of field values into the database or does not allow storing most of the existing measurement files. We propose a solution to massively load various format.csv datasets without requiring any user modification of the original file. The core of the solution is given by a key-value pair.json file mapping the database resources to the.csv columns, and adding further context information, if not already present. The solution aims at effectiveness, efficiency and flexibility. The implemented module has been successfully tested in a couple of use cases using existing datasets.
Efficient Uploading of.Csv Datasets into a Non-Relational Database Management System
Fresta M.;Bellotti F.;Capello A.;Cossu M.;Lazzaroni L.;De Gloria A.;Berta R.
2023-01-01
Abstract
Measurement-oriented non-relational databases often have a fixed structure schema to better manage and guarantee integrity of their data. However, this leads to a redundancy of field values into the database or does not allow storing most of the existing measurement files. We propose a solution to massively load various format.csv datasets without requiring any user modification of the original file. The core of the solution is given by a key-value pair.json file mapping the database resources to the.csv columns, and adding further context information, if not already present. The solution aims at effectiveness, efficiency and flexibility. The implemented module has been successfully tested in a couple of use cases using existing datasets.
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