Comparing Common Programming Languages to Parse Big XML File in Terms of Executing Time, Memory Usage, CPU Consumption and Line Number on Two Platforms

Abstract

XML files are used widely to save the information especially in the field of bioinformatics about the whole genome. There are many programming languages and modules used to parse XML files in different platforms such as Linux, Macintosh and Windows. The aim of this report is to reveal and determine which common programming language to use and on which platform is better to parse XML files in terms of memory usage, CPU time consumption and executing time.

Assessing internet and web services based webdom and virtual web-data-centric geographical study

“…Lastly semi-structural data like XML are also not followed any predefined type therefore they are not processed easily (Khan et al, 2014). Many online resources used XML format for data representation (Abdo & Alali, 2016). Problems in bigdata are therefore unstructured to semi-structured data complexity especially during their extraction and separation as and also between academic, governmental, and commercial data from the large influx of information and validation of all items (Khan et al, 2014;Linnettaylor, 2012) as Talia ( 2013) also mentioned bigdata often have unstructured digital content and their processing is highly difficult using traditional data management tools and techniques.…”