DocumentCode :
710165
Title :
PIGEON: Progress indicator for subgraph queries
Author :
Xiaojing Xie ; Zhe Fan ; Choi, Byron ; Peipei Yi ; Bhowmick, Sourav S. ; Shuigeng Zhou
Author_Institution :
Fudan Univ., Shanghai, China
fYear :
2015
fDate :
13-17 April 2015
Firstpage :
1492
Lastpage :
1495
Abstract :
Subgraph queries have been a fundamental query for retrieving patterns from graph data. Due to the well known NP hardness of subgraph queries, those queries may sometimes take a long time to complete. Our recent investigation on real- world datasets revealed that the performance of queries on graphs generally varies greatly. In other words, query clients may occasionally encounter “unexpectedly” long execution from a subgraph query processor. This paper aims to demonstrate a tool that alleviates the problem by monitoring subgraph query progress. Specifically, we present a novel subgraph query progress indicator called PIGEON that exploits query-time information to report to users accurate estimated query progress. In the demonstration, users may interact with PIGEON to gain insights on the query evaluation, which include the following: Users are enabled to (i) monitor query progress; (ii) analyze the causes of long query times; and (iii) abort queries that run abnormally long, which may sometimes contain human errors.
Keywords :
computational complexity; graph theory; query processing; user interfaces; NP hardness; PIGEON; graph data; long query time cause analysis; pattern retrieval; query abortion; query evaluation; query-time information; subgraph query progress indicator; subgraph query progress monitoring; Cascading style sheets; Databases; Estimation; Optimization; Runtime; Visualization; YouTube;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2015 IEEE 31st International Conference on
Conference_Location :
Seoul
Type :
conf
DOI :
10.1109/ICDE.2015.7113409
Filename :
7113409
Link To Document :
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