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.
2023
978-3-031-30332-6
978-3-031-30333-3
File in questo prodotto:
File Dimensione Formato  
applepies_2022_Matteo_Fresta no rev.pdf

accesso chiuso

Tipologia: Documento in Pre-print
Dimensione 203.23 kB
Formato Adobe PDF
203.23 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
978-3-031-30333-3_2.pdf

accesso chiuso

Tipologia: Documento in versione editoriale
Dimensione 317.97 kB
Formato Adobe PDF
317.97 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1142300
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? ND
social impact