An XML Data Placement Strategy for Distributed XML Storage and Parallel Query

Since there has been significant amount of XML documents generated in various application domains, efficient XML management has become an important problem. Distributed XML storage and parallel query based on Map Reduce can be an effective solution to this problem. As XML data placement strategy is...

Full description

Saved in:
Bibliographic Details
Main Authors: Jing Zhang, Bo Lang, Yawei Duan
Format: Conference Proceeding
Language:English
Subjects:
Benchmark testing
Distributed databases
distributed XML storage
Estimation
parallel XML query
Partitioning algorithms
Scalability
XML
XML data placement
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Since there has been significant amount of XML documents generated in various application domains, efficient XML management has become an important problem. Distributed XML storage and parallel query based on Map Reduce can be an effective solution to this problem. As XML data placement strategy is a key factor of parallel system performance, in this paper we present an XML placement strategy, which is Query Workload Estimation based XML Placement strategy (QWEXP) for efficient distributed XML storage and parallel query. To achieve query workload balance, it partitions XML based on query workload estimation which is calculated by XML structure without knowing of user queries, considering that in common application scenarios user queries are unknown in advance. The partitioned XML segments are around an XML storage unit W0, to support scalability of parallel XML database. Finally segments are distributed to each processing node evenly to ensure workload balance on parallel query execution. Experimental results have shown that QWEXP promotes the speedup and scale up properties of parallel XML system greatly.
ISSN:2379-5352
DOI:10.1109/PDCAT.2011.19