Towards Evolution Capabilities in Data Pipelines

Fuente: arXiv
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Main Author: Kramer, Kevin M.
Format: Preprint
Published: 2023
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author Kramer, Kevin M.
author_facet Kramer, Kevin M.
contents Evolutionary change over time in the context of data pipelines is certain, especially with regard to the structure and semantics of data as well as to the pipeline operators. Dealing with these changes, i.e. providing long-term maintenance, is costly. The present work explores the need for evolution capabilities within pipeline frameworks. In this context dealing with evolution is defined as a two-step process consisting of self-awareness and self-adaption. Furthermore, a conceptual requirements model is provided, which encompasses criteria for self-awareness and self-adaption as well as covering the dimensions data, operator, pipeline and environment. A lack of said capabilities in existing frameworks exposes a major gap. Filling this gap will be a significant contribution for practitioners and scientists alike. The present work envisions and lays the foundation for a framework which can handle evolutionary change.
format Preprint
id arxiv_https___arxiv_org_abs_2308_14591
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Towards Evolution Capabilities in Data Pipelines
Kramer, Kevin M.
Databases
Evolutionary change over time in the context of data pipelines is certain, especially with regard to the structure and semantics of data as well as to the pipeline operators. Dealing with these changes, i.e. providing long-term maintenance, is costly. The present work explores the need for evolution capabilities within pipeline frameworks. In this context dealing with evolution is defined as a two-step process consisting of self-awareness and self-adaption. Furthermore, a conceptual requirements model is provided, which encompasses criteria for self-awareness and self-adaption as well as covering the dimensions data, operator, pipeline and environment. A lack of said capabilities in existing frameworks exposes a major gap. Filling this gap will be a significant contribution for practitioners and scientists alike. The present work envisions and lays the foundation for a framework which can handle evolutionary change.
title Towards Evolution Capabilities in Data Pipelines
topic Databases
url https://arxiv.org/abs/2308.14591