TY - GEN
T1 - Projecting XML documents
AU - Marian, Amélie
AU - Siméon, Jérôme
PY - 2003
Y1 - 2003
N2 - XQuery is not only useful to query XML in databases, but also to applications that must process XML documents as files or streams. These applications suffer from the limitations of current main-memory XQuery processors which break for rather small documents. In this paper we propose techniques, based on a notion of projection for XML, which can be used to drastically reduce memory requirements in XQuery processors. The main contribution of the paper is a static analysis technique that can identify at compile time which parts of the input document are needed to answer an arbitrary XQuery. We present a loading algorithm that takes the resulting information to build a projected document, which is smaller than the original document, and on which the query yields the same result. We implemented projection in the Galax XQuery processor. Our experiments show that projection reduces memory requirements by a factor of 20 on average, and is effective for a wide variety of queries. In addition, projection results in some speedup during query evaluation.
AB - XQuery is not only useful to query XML in databases, but also to applications that must process XML documents as files or streams. These applications suffer from the limitations of current main-memory XQuery processors which break for rather small documents. In this paper we propose techniques, based on a notion of projection for XML, which can be used to drastically reduce memory requirements in XQuery processors. The main contribution of the paper is a static analysis technique that can identify at compile time which parts of the input document are needed to answer an arbitrary XQuery. We present a loading algorithm that takes the resulting information to build a projected document, which is smaller than the original document, and on which the query yields the same result. We implemented projection in the Galax XQuery processor. Our experiments show that projection reduces memory requirements by a factor of 20 on average, and is effective for a wide variety of queries. In addition, projection results in some speedup during query evaluation.
UR - http://www.scopus.com/inward/record.url?scp=85012154596&partnerID=8YFLogxK
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U2 - 10.1016/b978-012722442-8/50027-6
DO - 10.1016/b978-012722442-8/50027-6
M3 - Conference contribution
AN - SCOPUS:85012154596
T3 - Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003
SP - 213
EP - 224
BT - Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003
A2 - Freytag, Johann Christoph
A2 - Lockemann, Peter C.
A2 - Abiteboul, Serge
A2 - Carey, Michael J.
A2 - Selinger, Patricia G.
A2 - Heuer, Andreas
PB - Morgan Kaufmann
T2 - 29th International Conference on Very Large Data Bases, VLDB 2003
Y2 - 9 September 2003 through 12 September 2003
ER -