Flood forecasting methods based on deep learning rely on a large number of observational data, and are facing serious challenges in areas with scarce data. Aiming at the problems of flood inundated range prediction in...
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In recent years, the rise of big data has popularized data-driven decision-making. However, the interpretability shortcomings of artificial intelligence (AI) models limit their reliability for critical decisions. this...
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the extract, transform, load (ETL) process is becoming more important as larger and larger amounts of data are created daily. In this work, ETL software products that can load data, conduct transformations on it, and ...
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ISBN:
(数字)9798331509934
ISBN:
(纸本)9798331509941
the extract, transform, load (ETL) process is becoming more important as larger and larger amounts of data are created daily. In this work, ETL software products that can load data, conduct transformations on it, and either save or upload that data to cloud databases were tested. the selected software is either open source or freely available and two datasets have been tested to create aggregated performance evaluations on a local machine. the tested measures are processor use, available memory amount, and committed memory amount. Analysis of the results has determined that Pentaho Kettle and CloverDX are the most hardware-efficient ETL software tested after comparing the results with baseline values of the test computer. Talend Open Studio performed as the least efficient among the tools.
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