A sampling-based approach to information recovery
Junyi Xie, Jun Yang, et al.
ICDE 2008
By providing an integrated and optimized support for user-defined aggregates (UDAs), data stream management systems (DSMS) can achieve superior power and generality while preserving compatibility with current SQL standards. This is demonstrated by the Stream Mill system that, through is Expressive Stream Language (ESL), efficiently supports a wide range of applications - including very advanced ones such as data stream mining, streaming XML processing, time-series queries, and RFID event processing. ESL supports physical and logical windows (with optional slides and tumbles) on both built-in aggregates and UDAs, using a simple framework that applies uniformly to both aggregate functions written in an external procedural languages and those natively written in ESL. The constructs introduced in ESL extend the power and generality of DSMS, and are conducive to UDA-specific optimization and efficient execution as demonstrated by several experiments. Copyright 2006 ACM.
Junyi Xie, Jun Yang, et al.
ICDE 2008
Ruoming Jin, Yang Xiang, et al.
SIGMOD 2008
Haixun Wang, Hao He, et al.
ICDE 2006
Anand Ranganathan, Zhen Liu
CIKM 2006