Publications
Search

Publications :: Search

Cost Based optimization and plan selection for XPath

Show publication

On this page you see the details of the selected publication.

    Publication properties
    Title: Cost Based optimization and plan selection for XPath
    Rating: (1)
    Discussion: 0 comments
    Date: 2009
    Publication type: Conference paper
    Authors:
    No. First name Last name Show
    1. Haris Georgiadis
    2. Minas Charalambidis
    3. Vasilis Vassalos
    Bookmark:

    The following keywords have been assigned to this publication so far. If you have logged in, you can tag this publication with additional keywords.

    Keywords
    No keywords have been assigned to this publication yet.

    If you log in you can tag this publication with additional keywords

    A publication can refer to another publication (outgoing references) or it can be referred to by other publications (incoming references).

    Incoming References
    No incoming references have been assigned to this publication yet.
    Outgoing References
    No outgoing references have been assigned to this publication yet.

    If you log in you can add references to other publications

    A publication can be assigned to a conference, a journal or a school.

    Conference Track
    Conference Name: ACM SIGMOD International Conference on Management of Data, SIGMOD 2009, Providence, Rhode Island, USA, June 29 - July 2, 2009 2009
    Track Name: Research
    URL: http://www.sigmod09.org/

    Abstract

    We present a complete XPath cost-based optimization and execution framework and demonstrate its effectiveness and efficiency for a variety of queries and datasets. The framework is based on a logical XPath algebra with novel features and operators and a comprehensive set of rewriting rules that together enable us to algebraically capture many existing and novel processing strategies for XPath queries. An important part of the framework is PSA, a very efficient cost-based plan selection algorithm for XPath queries. In the presented experimental evaluation, PSA picked the cheapest estimated query plan in 100% of the cases. Our cost-based query optimization framework is independent of the underlying physical data model, the storage system, and of the available implementations for the logical algebra operators, depending on a set of well-defined APIs. We also present an implementation of those APIs, including primitive access methods, a large pool of physical operators, statistics estimators and cost models, and experimentally demonstrate the effectiveness of our end-to-end query optimization system.