The object data standard: ODMG 3.0
The object data standard: ODMG 3.0
Collective Loop Fusion for Array Contraction
Proceedings of the 5th International Workshop on Languages and Compilers for Parallel Computing
A Database Array Algebra for Spatio-Temporal Data and Beyond
NGIT '99 Proceedings of the 4th International Workshop on Next Generation Information Technologies and Systems
Efficient Execution of Operations in a DBMS for Multidimensional Arrays
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Query processing techniques for arrays
The VLDB Journal — The International Journal on Very Large Data Bases
A performance comparison between an APL interpreter and compiler
APL '83 Proceedings of the international conference on APL
Hosting the .NET Runtime in Microsoft SQL server
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Fast and practical indexing and querying of very large graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Speeding up Array Query Processing by Just-In-Time Compilation
ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Putting Pixels in Place: A Storage Layout Language for Scientific Data
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
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We present a technique to speed up array query processing, just-in-time compilation, which is novel on arrays. Suitable query fragments are detected, compiled, and linked into the server dynamically. This technique has been integrated in an operational array DBMS where its impact on efficiency can be studied in a holistic environment. We will demonstrate this on 1D to 4D real-life spatio-temporal raster data sets taken from the Earth Sciences. Performance results on computationally intensive queries are encouraging and can be examined interactively in a variety of demonstration examples.