XML Query Optimization for Improvement of Data Warehouses Information Processing
DOI:
https://doi.org/10.37591/jomtra.v10i1.541Keywords:
XML, stream, Query processing, Indexing method, Twig pattern queryAbstract
XML data warehouses give decision-support systems a chance to use complicated data by giving them a place to start. But native-XML database management systems are slow right now, so it is important to look into ways to make them faster. This study presents two strategies to think about. To start, we suggest using a link index that was made with the fact that XML warehouses have a lot of dimensions in mind. The join procedures are taken out, but the data from the first warehouse stays the same. Second, we show how to choose XML materialized views by grouping the query load to show how this can be done. To prove that these ideas work, we built a set of decision support XQuery tools and ran them against an XML data warehouse. We compared the results obtained with and without our optimization methods. Our tests show that it works, even though the queries themselves are a little hard to understand and the datasets themselves are very big. XML has emerged as the widely accepted standard for transmitting data over mobile wireless networks. In these kinds of networks, mobile clients can use a wireless broadcast channel to send queries to get the XML data they need. Because mobile devices are so small and have so little storage space and a short battery life, it may be hard for customers to download the whole XML data set on one of these devices. To solve this problem, you need to index XML data so that mobile clients only have to download the parts of the file they need. Users who want to access only certain parts of the XML content in an XML stream could use one of several indexing methods. Still, the indexing methods that are used now add more data to an XML stream that is already very large. This research comes up with a new XML stream structure for broadcasting XML data by compressing and summarizing the information about how XML nodes are put together. This study was conducted in the United Kingdom. When data is summed up before being sent, the time it takes to get it in XML format over a wireless broadcast channel can be cut down. The recommended XML stream structure also has indexes that will help you skip over any data that is not important. So, it could make it less likely that XML query results will drain the batteries of mobile devices when they are being processed. We also found that our suggested XML stream design was better than its predecessors in terms of access and tuning times for processing XML queries over the XML data stream. So, our architecture can be used to answer a wide range of XML questions.
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