By Georg Lausen, Dan Suciu
The papers during this quantity symbolize the technical software of the ninth Biennial WorkshoponDataBasesandProgrammingLanguages(DBPL2003),whichwas hung on September 6-8, 2003, in Potsdam, Germany. The workshop meets each years, and is a well-established discussion board for ideas that lie on the intersection of database and programming language learn. DBPL 2003 persisted the t- dition of excellence initiated by means of its predecessors in Rosco?, Finistre (1987), S- ishan, Oregon (1989), Nafplion, Argolida (1991), long island, long island (1993), Gubbio, Umbria (1995), Estes Park, Colorado (1997), Kinloch Rannoch, Sc- land (1999), and Frascati, Rome (2001). Theprogramcommitteeselected14papersoutof22submissions,andinvited twocontributions.The16talkswerepresentedoverthreedays,insevensessions. In theinvitedtalk Jennifer Widom provided the paper CQL: a Language forContinuousQueriesoverStreamsandRelations,coauthoredbyArvindArasu andShivnathBabu.Whilealotofresearchhasbeendonerecentlyonqueryp- cessingoverdatastreams,CQLisvirtuallythe?rstproposalofaquerylanguage on streams that may be a strict extension of SQL. The language is based round an easy but robust notion: it has particular info varieties, family and streams, with well-de?ned operators for mapping among them. Window speci?cation expressions, comparable to sliding home windows, map streams to relatives, whereas operators equivalent to ’’insert stream,’’ ’’delete stream,’’ and ’’relation stream’’ map kinfolk to streams by way of returning, at every one second in time, the newly inserted tuples, the deleted tuples, or a picture of the full relation. the various examples during this paper make a resounding case for the facility and value of CQL
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Additional resources for Database Programming Languages: 9th International Workshop, DBPL 2003, Potsdam, Germany, September 6-8, 2003, Revised Papers
Proof. It is easy to see that such a string can be guessed and verified in nondeterministic polynomial time To prove NP-hardness we show that there is a polynomial reduction from 3SAT  to this problem. The reduction consists of a mapping of a CNF formula to a set of formulas such that there is a string into which all these patterns can be matched and that is as large as the largest pattern iff this string encodes a truth assignment for the formula. To demonstrate the principle we will first show how the formula with and is translated.
Example 1. The following queries find pairs of employees of the same age (with the schema Emp(name, addr, age)). Suppose we have the following tuples in the relation: Emp(John, Pine St, and Emp(Joe, Walnut Ave, 30). The outputs of and are shown below (on the left and right respectively). The difference in the results of and is due to the implicit equality, through variable Z, in and the explicit equality in It appears that the above problem arises because annotations do not propagate across the equality operator.
There can be multiple annotations attached to the same data element. We sometimes use the phrase “an annotation is attached to a location” to mean the same as an annotation is attached to the data element that resides in that location. If there is an annotation attached to the location (Person(112, “Joe”, 23), 3), we will write the tuple as Person(112, “Joe”, Conjunctive Query. Our results are based on conjunctive queries . A conjunctive query has the form where denote vectors of variables and every variable in occurs in for some Each is called a subgoal and each where is a relation name.
Database Programming Languages: 9th International Workshop, DBPL 2003, Potsdam, Germany, September 6-8, 2003, Revised Papers by Georg Lausen, Dan Suciu