AXL is a unified solution to a large variety of problems in decision support applications including:

• SQL extensions for more complex OLAP queries;
• new datablades for special data types such as time-series;
• architectural extensions to support data mining functions.

AXL is based on User-Defined Aggregates (UDAs) expressed in an SQL-like language. We will show the architecture and implementation of the AXL prototype and its use and performance in expressing data mining functions and complex OLAP queries.

AXL uses database access methods (B+Tree, Extended Linear Hashing) provided by Berkeley DB.

• AXL Version 1.2 Docs

• AXL by Examples
  • running average
  • minpoint
  • multiple scans
  • recursive aggregates
  • group-by modifiers
  • monotonic aggregates

• Data Mining Functions and Performance Analysis
  • Bayesian Classifier
  • Categorical Decision Tree Classifier
  • The SPRINT Algorithm
  • Association Rules: the Apriori Algorithm

• Previous Systems:
  • LDL++
  • LDL++ Java Interface
  • External Database with JDBC
  • Extendible LDL++ Aggregates, Gzipped Postscript
  • Extendible LDL++ XY Stratification, Gzipped Postscript
  • LDL++ Internals Documentation Gzipped Postscript
  • SQL-AG
  • The SQL-AG System
  • SQL-AG Reference Manual
  • Extending User-Defined Aggregates for SQL3

• AXL Related Publications

  • Haixun Wang and Carlo Zaniolo, ATLaS: A Powerful Database Language and System Based on Simple Extensions of SQL, in Proc. 18th Intl. Conf. on Data Engineering (ICDE), San Jose, USA. Feb 2002.

  • Haixun Wang and Carlo Zaniolo, Using SQL to Build New Aggregates and Extenders for Object-Relational Systems, in Proc. 26th Intl. Conf. on Very Large Databases (VLDB), Cairo, Egypt, Sept. 2000.

  • Haixun Wang and Carlo Zaniolo, Database System Extensions for Decision Support: the AXL Approach, in ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD 2000) in cooperation with SIGMOD'2000 Dallas, TX, May 14, 2000.

  • Haixun Wang and Carlo Zaniolo, User Defined Aggregates in Object-Relational Systems, in the 16th International Conference on Data Engineering (ICDE'2000), San Diego, USA, 2000.