ATLaS:A Complete Database Language for

Streams

Carlo Zaniolo, Haixun WangRichard Luo,Jan-Nei Law

et al.

Documentation and software downloads: http://wis.cs.ucla.edu/

DB-Inspired Approach to DB-Inspired Approach to StreamsStreams

• The Good: – Information-centered, high level Query languages, Data

Independence, Optimization, …– isolate applications from details, amortize investment

• The Bad: SQL lacks expressive power!– New application domain ad-hoc extensions (by

committee)– Designed for secondary store blocking aggregates

assumed

• The Ugly:– The secondary storage mantra is gone– Can SQL designed for secondary store win over languages

such as XQuery, XSLT or Hancock designed for the – web and streams—and also claiming Turing completeness?

A Brave New World

• Just extending SQL for streams will not do, if – SQL remains crippled by its impotency in

expressing applications– and we will lose out against non-DB

approaches since we lost our DB mantra and home field advantage

A Brave New World

• User-Defined Aggregates (UDAs) are a path to salvation because they,– Can be defined in SQL (rather than in a

procedural language)– Turn SQL into a Turing Complete (TC) language– Fit the stream-oriented computation model like

a glove—e.g., non-blocking properties of queries can be characterized syntactically

• ATLaS does all that, and demonstrates the effectiveness of UDAs in expressing data-intensive applications, and delivers good performance.

UDAs: Initialize, Iterate, Terminate

AGGREGATE myavg1(Next Int) :

Real { TABLE state(sm Int, cnt Int);INITIALIZE : {INSERT INTO state

VALUES (Next, 1)}

ITERATE : {UPDATE state SET sm=sm+Next,

cnt=cnt+1;}TERMINATE : {INSERT INTO

RETURN SELECT sm/cnt FROM state;} }

AGGREGATE myavg2(Next Int) : Real

{ TABLE state(sm Int, cnt Int);INITIALIZE : {INSERT INTO state

VALUES (Next, 1)} ITERATE : {UPDATE state SET

sm=sm+Next, cnt=cnt+1;INSERT INTO RETURN

SELECT sm/cnt FROM state WHERE Cnt=100; UPDATE state SET sm=0, cnt=0 WHERE Cnt=100} }

No TERMINATE Non-Blocking

Homework Problems:Solutions in Two Flavors

1. without windows (ATLaS is TC for both blocking and nonblocking functions), and

2. with windows [partition&range construct]• ATLaS provides constructs to simplify the

definition of UDAs on windows,• But ATLaS does not support joins of

windows,since a. Problems when windows are viewed as data sets,b. in SQL:1999 windows are aggregate modifiers (OLAP), c. Simple solutions are already at hand in the TC ATLaS.

• The benefits of TC: we add a new construct only when pros >> cons

Interesting Times Ahead …

Language Design Issues:• Semi-structured information and XML

documents—can they be viewed as streams?• Ditto for references,• Streams of Updates and Events, active

databasesApplications: e.g., micro-climate monitoring,

from UCLA Embedded Networked Sensors Center

. Bridging the gap will not be easy.

References

Stephan Kepser: A Proof of the Turing-completeness of XSLT and Xquery, SFB 441, University of Tubingen Technical Report, SFB 441, May 13, 2002,kepser@sfs.uni-tuebingen.de