tailieunhanh - Query Languages and Data Models for Database Sequences and Data Streams
Finally, the HPDD sheds light on one of the leading issues of the day: the relationship between debt and growth. Separating countries into fast-, medium-, or slow–paced growers over 1885–2009, we find an intuitive pattern. 15 Fast growers consistently registered low debt ratios, while slow growers carried the highest debts for much of the sample period (Figure 7, upper panel). Further light is shed on the debt-growth relationship by a bubble chart that compares debt ratios and (total) PPP GDP (Figure 7, lower panel). If debt and growth are inversely related, the bubble movements should follow one of two directions: north-west. | Query Languages and Data Models for Database Sequences and Data Streams Yan-Nei Law Haixun Wang1 Carlo Zaniolo Computer Science Dept. UCLA Los Angeles CA 90095 ynlaw zaniolog@ IBM T. J. Watson Research1 Hawthorne NY 10532 haixun@ Abstract We study the fundamental limitations of relational algebra RA and SQL in supporting sequence and stream queries and present effective query language and data model enrichments to deal with them. We begin by observing the well-known limitations of SQL in application domains which are important for data streams such as sequence queries and data mining. Then we present a formal proof that for continuous queries on data streams SQL su ers from additional expressive power problems. We begin by focusing on the notion of nonblocking NB queries that are the only continuous queries that can be supported on data streams. We characterize the notion of nonblocking queries by showing that they are equivalent to monotonic queries. Therefore the notion of NB-completeness for RA can be formalized as its ability to express all monotonic queries expressible in RA using only the monotonic operators of RA. We show that RA is not N B-complete and SQL is not more powerful than RA for monotonic queries. To solve these problems we propose extensions that allow SQL to support all the monotonic queries expressible by a Turing machine using only monotonic operators. We show that these extensions are i user-defined aggregates UDAs natively coded in SQL rather than in an external language and ii a generalization of the union operator to Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage the VLDB copyright notice and the title of the publication and its date appear and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise or to republish requires a fee and or special permission from the .
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