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D. Chamberlin. A complete guide to DB2 Universal Database. Morgan Kaufmann Publishers, Inc., San Francisco, California, 1998.

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Database Support for Multimedia Applications - Ortega-Binderberger, al. (2001)   (Correct)

....a less radical evolution than the OODBMS approach. The ORDBMS approach produced such research prototypes as Postgres [103] and Starburst [46] and commercial products such as Illustra [104] The ORDBMS technology has now been embraced by all major vendors including Informix [53] IBM DB2 [22], Oracle [74] Sybase [107] and UniSQL [60] among others. The ORDBMS model has been incorporated in the SQL 3 standards. While OODBMSs provide the full power of an object oriented language, they have lost ground to ORDBMSs. Interested readers are referred to [104] for good insight from both a ....

.... user defined functions (i.e. user level aggregation and grouping operators) While Informix offers a potentially more powerful model for extensibility, IBM DB2 is the only system that isolates the server from faults in UDFs by allowing the execution of UDFs in their own separate address space [22] in addition to the server address space. With this fine grained fault containment, errors in UDFs will not bring the database server off line. 4 Image Retrieval Extensions to Commercial DBMSs In this section, we discuss the image retrieval extensions available in commercial systems. We ....

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Donald D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann, July 1998.


Yemanja - A Layered Event Correlation Engine for.. - Appleby, Goldszmidt.. (2001)   (Correct)

....an entity determines that the events it received does not indicate a failure in its corresponding device or layer, it publishes an impact event. Impact events are viewed as symptoms by their recipients. In the process of event correlation Yemanja entities may initiate database queries (in SQL [5]) and or issue SNMP [4] commands to obtain configuration information. If an entity fault is isolated recovery actions may be taken. Recovery actions can include system reconfiguration which is performed by a separate Resource Manager component, or directly by Yemanja through SNMP. In addition, ....

D. D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann Publishers, 1998.


Aggregate Queries over Conditional Tables - Lechtenbörger, Shu, Vossen (2000)   (Correct)

.... as IBM s DB2 UDB, where in the situation that a group by clause involving an aggregate function is run over a column that may contain null values, that column can be equipped with the grouping function in order to distinguish entries with null values from entries representing a group as a whole [3]. Next, 11] is, to our knowledge, the first paper addressing the issue of using conditional tables for representing and maintaining materialized views, which can potentially be used in the context of data warehousing. Finally, 1] emphasized the potential use of conditional tables for incomplete ....

....representation for Table 3 is shown in Table 6. Again, the number of tuples in the resulting representation is bounded by the number of tuples in the original table. Table 6: Interval representation of 798; A (assuming ) A D [1,4] 1 [1,7] [3,12] 6 Conclusions In this paper, we have extended the theory of conditional tables with the definition of aggregate queries. This has been done carefully, so that we have been able to present a strong representation system with the desirable closure property that the result of an aggregate query ....

D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann, 1998.


Decision Tables: Scalable Classification Exploring RDBMS.. - Lu, Liu   (Correct)

....operations and the related process strategies have been proposed [GCB 97, AAD 96, ZDN97] The results have been quickly integrated into the commercial products. For example, IBM DB2 extended the traditional GROUP BY functions to include GROUP BY GROUPING SETS, GROUP BY CUBE, GROUP BY ROLLUP [Cham98]. Although such data aggregation and summarization are basic operations of a classification process, those new developments have not attracted much attentions from the data miners yet. Based on the above observations, we developed a new approach, GAC (Grouping And Counting) for scalable ....

D.D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann Publishers, 1998.


Multi-Cube Computation - Jeffrey Xu Yu (2001)   (8 citations)  (Correct)

....[5] generalizes the standard GROUP BY operator to compute aggregates for every combination of GROUP BY attributes, and is now supported by commercial database systems like IBM DB2. IBM DB2 extended the traditional GROUP BY functions by adding GROUP BY GROUPING SETS, GROUP BY CUBE, GROUP BY ROLLUP [2]. For example, with a relation Sales(date, product, customer, amount) the following datacube query SELECT date, product, customer, SUM(amount) FROM Sales GROUP BY CUBE (date, product, customer) produces the SUM of amount for all groups generated by 8 GROUP BYs, i.e. date, product, ....

D. Chamberlin. A Complete Guide To DB2 Universal Database. Morgan Kaufmann, 1998.


A Layered Optimizer For Mining Association Rules Over Relational .. - Dudgikar (2000)   (Correct)

....) A UDF in DB2 is created explicitly by a user using the CREATE FUNCTION, which declares the new function and specifies its semantics. UDFs are always created in a specific database and can be used only in that database. Within that database, UDFs can be used in the same way as built in functions [Cha98, Pod98]. Use of a UDF does not require authorization, but the creation of one, does require certain privileges. As described in section 2.5, UDFs can return either a scalar value or a table. Table functions are very powerful because they enable the user to make almost any source of data to appear to be ....

Chamberlin, D. A complete guide to DB2 Universal Database, Morgan Kaufmann Publishers, Inc, San Mateo, California, 1998.


Mining And Visualization Of Association Rules Over Relational DBMSs - Zhang (2000)   (Correct)

....Execution of function inside the server can minimize the network traffic because some of the business logic can be processed in the Server, and only the results are sent back to the client. In DB2, when a UDF (User Defined Function) is created, there is an option of FENCED or UNFENCED modes [CHA1998]. The FENCED option Database Server Java Application JDBC Driver Manager JDBC API JDBCODBC ODBC Drivers Oracle Driver DB2 Driver 15 specifies that the UDF must always be run in an address space that is separate from the database, while UNFENCED option specifies that the UDF runs in the ....

Chamberlin D., A Complete Guide to DB2 Universal Database, Morgan Kaufmann Publishers, Inc, San Mateo, California, 1998.


Optimization and Evaluation of Generalized Top Queries - Ciaccia, Cornacchia, Ghidini   (Correct)

.... and are also of great interest for decision support and data mining activities ( nd the 10 cheapest products ) For this reason, several DBMS vendors have already introduced proprietary SQL extensions for the speci cation of Top queries (e.g. IBM DB2 UDB uses a FETCH FIRST N ROWS ONLY clause [Cha98] and Oracle 8 has LIMIT TO N ROWS ) as well as internal support for their ecient execution [Loh] In all cases the ranking criterion, which determines how good an object is, is expressed through the ORDER BY clause, so that ranking and ordering of results coincide. Without loss of generality, ....

D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann Publishers, 1998.


Distributed Hypertext Resource Discovery Through Examples - Chakrabarti, van den Berg.. (1999)   (11 citations)  (Correct)

....COMPLETE as C left outer join PARTIAL as P on C.did = P.did and C.cid = P.cid Figure 3: Hierarchical bulk classification expressed as a ODBC JDBC subroutine. This is repeatedly called at all path nodes in topological order to evaluate the score of the good nodes. inner and one left outer join [11]: X t#d#F (c0 )#c i freq(d, t) logtheta(c i , t) logdenom(c i ) logdenom(c i ) X t#d#F (c0 ) freq(d, t) Figure 3 shows a high level pseudocode for an ODBC JDBC routine with one parameter c 0 which indicates the node at which bulk evaluation is desired. For simplicity, the code ....

D. Chamberlin. A complete guide to DB2 universal database. Morgan-Kaufmann, 1998.


Towards Self-tuning Multimedia Delivery for Advanced.. - Wagner, Holland.. (1999)   (3 citations)  (Correct)

....databases, image databases, web enabled databases, format optimization. 1 Introduction The capability of modern object relational database systems to integrate multimedia data and traditional alphanumeric data widens the area of database applications. Systems like DB2 Universal Database [2] can be deployed to monitor multimedia web sites, interactive kiosk systems, large multimedia libraries or advanced value added information services. Hence, multimedia database systems are hot topics in database research and system development [1, 6] Setting up web enabled services based on ....

D. Chamberlin. A Complete Guide to DB2 Universal Database. M. Kaufmann, 1998.


Exploiting ORDBMS Technology to Implement the ZYX Data.. - Boll, Klas, Westermann (1999)   (2 citations)  (Correct)

....The extensibility features of an ORDBMS can be exploited to introduce multimedia data types into the system. However, when considering object relational database technology we must distinguish the extent to which object oriented features are introduced to the ORDBMS. For example, IBM s DB2 [IBM98,Cha98] offers only used defined functions but no user defined complex data types. Oracle8 [Ora98,KL97] offers no support for inheritance and user defined indexing techniques. With the Informix Dynamic Server Universal Data Option (IDS UD) Inf97] we find a system that provides a high degree of ....

D. Chamberlin. A complete guide to DB2 Universal Database. Morgan Kaufmann Publishers, Inc., San Francisco, California, 1998.


Exploiting ORDBMS Technology to Implement the ZYX Data.. - Boll, Klas, Westermann (1999)   (2 citations)  (Correct)

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D. Chamberlin. A complete guide to DB2 Universal Database. Morgan Kaufmann Publishers, Inc., San Francisco, California, 1998.


Limiting Disclosure in Hippocratic Databases - LeFevre, Agrawal, Ercegovac.. (2004)   (Correct)

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D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kau#mann, San Francisco, California, USA, 1998.


Biological Data Integration: Wrapping Data and Tools - Lacroix (2002)   (Correct)

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D. Chamberlin, A Complete Guide to DB2 Universal Database. San Francisco, CA: Morgan Kaufmann, 1998.


Optimized Seamless Integration of Biomolecular Data - Eckman, Lacroix, Raschid (2001)   (2 citations)  (Correct)

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D. Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann, San Francisco, CA, 1998.


Data Models and Query Languages of Spatio-Temporal Information - Chen (2001)   (Correct)

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D. Chamberlin. A complete Guide to DB2 Universal Database, Morgan Kaufmann, 1998


User-Defined Aggregates for Advanced Database Applications - Wang (2000)   (Correct)

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Donald D Chamberlin. A Complete Guide to DB2 Universal Database. Morgan Kaufmann Publishers, July 1998. 159

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