On probabilistic fixpoint and Markov chain query languages

We study highly expressive query languages such as datalog, fixpoint, and while-languages on probabilistic databases. We generalize these languages such that computation steps (e.g. datalog rules) can fire probabilistically. We define two possible semantics for such query languages, namely inflationary semantics where the results of each computation step are added to the current database and non-inflationary queries that induce a random walk in-between database instances. We then study the complexity of exact and approximate query evaluation under these semantics. Categories and Subject Descriptors H.2.3 [Database Management]: [Languages] ; H.2.1 [Database Management]: [Logical Design] ; G.3 [Mathematics of Computing]: [Probability and Statistics] General Terms Algorithms, Languages, Theory

• Type: Conference
• Year: 2010
• Where: PODS
• Authors: Daniel Deutch, Christoph Koch, Tova Milo
• Keywords: Computation Step, Database, Expressive Query Languages, PODS 2010, Query Languages