L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. G. Lindsay, H. Pirahesh, M. J. Carey, and E. J. Shekita. Starburst Mid-Flight: As the Dust Clears. IEEE Trans. on Knowledge and Data Engineering, 2(1):143--160, 1990.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....The language and a constraint satisfaction processor are used in UF s automated negotiation server [HAM00, HUA00, SU00a] for evaluating the contents of a negotiation proposal against some pre registered constraints. 7 Event and action oriented rules are commonly used in active database systems [HAA90, HAN92, MCC89, STO88, WID96]. There are two general types of event andaction oriented rules: triggers and event condition action (ECA) rules. Triggers in active databases enforce business knowledge by automatically invoking data operations when a predefined condition is satisfied. In a trigger definition, a condition and ....

....unshipped orders for that customer should be shipped to his her new address. To support this business rule, a trigger is defined to update the shipping address of the unshipped orders of that customer in an Order table whenever that customer s address in the Customer table is modified. ECA rules [HAA90, MCC89] are generalization of database triggers in that events can be any events of interest, not just upon storage operations, and that triggered actions can be any type of operations, not just database operations. The semantics of an ECA rule is, When an event is posted, the condition part is checked. ....

[Article contains additional citation context not shown here]

Haas, L. M., Chang, W., Lohman, G. M., McPherson, J., Wilms, P. F., Lapis, G., Lindsay, B. G., Pirahesh, H., Carey, M. J., and Shekita, E. J., "Starburst Mid-flight: As the Dust Clears," IEEE Transaction on Knowledge and Data Engineering, 2(1), March 1990, pp.143-160.

....entirely or almost entirely in main memory. Such applications will experience performance benefits by having data cached in main memory. However, if the storage manager supporting such applications is tailored to main memory, significant additional performance benefits can be achieved, as shown in [36]. A storage manager provides the core functionality of a database system, such as concurrency control, recovery mechanisms, storage allocation free space management, transaction management and indices. There have been numerous implementations of storage managers for disk resident data. These ....

....of a database system, such as concurrency control, recovery mechanisms, storage allocation free space management, transaction management and indices. There have been numerous implementations of storage managers for disk resident data. These include the storage managers of Exodus [15] and Starburst [36]. With the exception of the Starburst main memory storage component [36] we are not aware of any storage manager that is tailored for mainmemory resident data. System M [64] is a transaction processing test bed for memory resident data, but is not a full feature storage manager. 34 The ....

[Article contains additional citation context not shown here]

L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. Carey, and E. Shekita. Starburst mid-flight: As the dust clears. IEEE Transactions on Knowledge and Data Engineering, 2(1), March 1990.

....controlled in a database. When applied to an open information universe as the Internet, these assumptions no longer hold, and some of the techniques do not easily extend to scale up to the distributed interoperable environment. Comparing with the state of art of research in active databases [12, 9, 10, 4, 11, 3], the JCQ system differs primarily in the following three ways: First, the JCQ system targets at update monitoring on the Web, handling both structured database sources and semistructured sources such as HTML files. Second, the continual query concept can be seen as a practical and useful ....

L. Haas, W. Chang, G. Lohman, J. McPherson, P.Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. Carey, and E. Shekita. Starburst mid-flight: As the dust clears. IEEE Transactions on Knowledge and Data Engineering, pages 37388, March 1990.

....found in traditional DBMS, and include more specialised features which maximise performance. Such systems are very limited to particular applications and most were custom built and remained monolithic. Research has also considered extensible systems to tailor a DBMS to a particular application, [2, 13, 7, 3]. These, though very much in the right direction, were essentially customisable monolithic DBMSs, their architecture being layered resulting in performance overhead problems, which would not suit the types of applications, we wish to focus on. However focus on performance not the only issue. To ....

Haas L., Chang W., Lohman G., McPherson J., Wilms P., Lapis G., Lindsay P.., Pirahesh H., Carey M., Shekita E., 'Starburst Mid-Flight: As the Dust Clears', In IEEE Transactions on Knowledge and Data Engineering, IEEE, March 1990

....triggers an action. Most of the active database systems [43] provide facilities that allow users to specify, in the form of ECA rules, actions to be performed following changes of database state. Some popular active database research prototypes include Ariel [15] Postgres [39] and Starburst [14]. These systems provide powerful rules and allow general events, conditions, and actions, and therefore are more di#cult to provide e#cient implementation. Despite the conceptual generality, rules have been so far supported in a fairly restricted form in practical systems (e.g. by built in ....

....Active queries, introduced in Alert [37] are more sophisticated than database triggers, since they can be defined on multiple tables, on views, and can be nested within other active queries. However, active queries rely heavily on a number of extensions specific to the IBM Starburst DBMS [14]. Compared to the state of art of research in active databases, the WebCQ system di#ers in three ways: First, the WebCQ system targets at monitoring and tracking changes to arbitrary web pages. Second, WebCQ monitors data provided by the content providers on remote servers, and WebCQ monitoring ....

L. Haas, W. Chang, G. Lohman, J. McPherson, P.Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. Carey, and E. Shekita. Starburst mid-flight: As the dust clears. IEEE Transactions on Knowledge and Data Engineering, pages 377--388, March 1990.

....cost estimation techniques or search strategies have to be changed [Cha98] As a result, the last decade has witnessed substantial efforts aiming to develop extensible query optimizers that would make such changes easier. Representative examples of extensible query optimizers include Starburst [Haa90], Volcano [GM93] and OPT [KW99] This paper reports on a specific study that has enhances the Volcano extensible query optimizer to support a relational algebra with temporal operators such as temporal join and aggregation. In addition to new operators, cost formulas, selectivity estimation ....

....EROC aimed to provide a set of carefully defined and implemented abstractions (in C classes) that would reduce this task. The toolkit is not publically available, and thus it is difficult to estimate how much effort is required to build an optimizer using its components. The Starburst optimizer [Haa90] uses query graph models for representing queries, and it employs a two stage optimization. During the query rewrite phase, rules are used to transform one query graph model to another; and during the plan optimization phase, candidate plans are costed and the cheapest one is selected. Starburst ....

L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. G. Lindsay, H. Pirahesh, M. J. Carey, and E. J. Shekita. Starburst Mid-Flight: As the Dust Clears. IEEE TKDE, 2(1):143--160 (1990).

....described here is also based on the concept of precommit, our protocol eliminates the costs of maintaining an additional data structure recording this wait for relationship. An idea originating within IBM s IMS FastPath, see [13] and [9] page 511) and pursued within IBM s Starburst System [15] is to attach some lock information directly to objects themselves [17] These locks are never paged out. Moreover, whenever a lock is required, it is usually to be found already within the CPU cache. In FastPath, lock information is encoded in two bits within object headers. Locking algorithms ....

L. Haas, W. Schang, G. Lohman, J. McPherson, P. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. Carey, and E. Shekita. Starburst mid-flight: As the dust clears. IEEE Trans. on Knowledge and Data Engineering, 2(1):143-160, Mar. 1990.

....database style queries on collections. Extended relational databases are relational database systems that have added constructs to handle more complex data types than can be modeled with records of built in base types. Some representative systems are POSTGRES[53, 55, 56, 57, 58, 59] Starburst[28, 29, 45, 54, 61], Genesis[5, 6, 7] and Exodus[15, 16] In general, these systems allow users to define new base types with richer sets of operations than the built in types. For example, a user could define a box type with operations that compute and compare the areas of boxes. However, the goal of these ....

Laura M. Haas et al. Starburst mid-flight: As the dust clears. IEEE Transactions on Knowledge and Data Engineering, 2(1):143--160, March 1990. Also IBM Almaden Research Center Research Report RJ 7278 (68535).

.... about the type of use envisioned by a query execution plan, so that the system will know if re reference by the plan is likely and can act accordingly (see the Hot Set Model of [SACSCH] the DBMIN algorithm of [CHOUDEW] and its extensions [FNS, NFS, YUCORN] the hint passing approaches of [CHAKA, HAAS, ABG, JCL, COL] and the predictive approach of [PAZDO] This approach can work well in circumstances where re reference by the same plan is the main factor in buffering. In Example 1.2 above, we would presumably know enough to drop pages read in by sequential scans. The DBMIN algorithm would also deal well with ....

Laura M. Haas et al., Starburst Mid-Flight: As the Dust Clears, IEEE Transactions on Knowledge and Data Engineering, v. 2, no. 1, pp. 143-160, March 1990.

....could be characterized as the Pandora method, to stay within Greek mythology and to choose a meaningtiff name as well. The idea is that higher level components of the system pass information on the expected page reference patterns to the memory management, to influence the buffering policy [12] [36], 46] 59] This approach could be viewed as a self tuning method, but we will see that it relies crucially on the quality of the hints from other components. As an example of hint passing, consider scenario 2 from the previous subsection. The query optimizer could pass on the information that a ....

L. M. Haas et al. Starburst Mid-Flight: As the Dust Clears. lfEEE Transactions on Knowledge and Data Engineering7 2 (1)7 143-160 (1990).

....to build extensible optimizers. Lohman [Loh88] proposed using rules to generate plans in a bottom up optimizer; Graefe and DeWitt [GrD87] proposed using transforms (the topdown version of rules) to generate new plans using a topdown approach. Lohmans generative rules were implemented in Starburst[HCL90]. Several Starburst projects have demonstrated Starbursts extensibility, from incremental joins [CSL90] to distributed heterogeneous databases [HKW97] Since there is a huge commercial investment in engineering bottom up optimizers like Starburst, there seems to be little motivation for ....

L. Haas, W. Chang, G. Lohman et al., Starburst MidFlight: as the Dust Clears, TKDE, 2(1), Pg. 143-160, March 1990.

....is established by the MAD model with its molecule query language MQL. MQL is embedded in a host programming language and can be directly used in an application programming environment; interactive operation is also supported. Both interfaces are equally powerful and are described in more detail in [15]. Here, we present an overview of the MAD capabilities for complex object management that is valid for both interface types. From the Relational Model to the MAD Model In the following, we presume that the reader is familiar with the relational model and its well known concepts, e.g. tuples, ....

L. Haas, et al., Starburst Mid-Flight: As the Dust Clears, Data & Knowledge Engrg. 2 (

.... scientific databases with very many constants (e.g. zeroes) 9, 19, 21] and considered a very special operation on compressed data (matrix transposition) 31] For indices, many database systems use prefix and postfix truncation to save space and increase the fan out of nodes, e.g. Starburst [15]. However, actual compression methods are typically not used at all in most database management systems. In particular, the performance effects of data compression on more frequently used database operations such as relational join, duplicate elimination, and set intersection have not been ....

L. Haas, W. Chang, G. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. J. Carey and E. Shekita, Starburst Mid-Flight: As the Dust Clears, IEEE Trans. on Knowledge and Data Eng. 2,1 (March 1990), 143.

....approach does not require much expertise on the part of the database programmer, and can be used to detect termination cases which the conservative approaches reject as non terminating ones. Our approach, thus, complements the conservative approaches. 1 Introduction Active database systems [1, 7 9, 16 18] appear to be a very promising technology. However, users are reluctant to use it because of the uncertainty associated with how a set of active database rules acting on their own will interact with each other and with other transactions [15] To ensure that the application will behave in a ....

L. M. Haas et al. Starburst Mid-flight: As the Dust Clears. IEEE Transactions on Knowledge and Data Engineering, 2(1):143--160, March 1990.

....more measures for absolute security. 7 Related Work There are a lot of extensible database systems allowing the implementation of user defined functions as predicates or general functions operators, in C, C , or Java. Examples for such systems include POSTGRES [23] Iris [25] and Starburst [12], but there are also several commercially available systems like Informix, Oracle, and DB2. These systems are all more or less exposed to the same security risks as ObjectGlobe even if they do not load untrusted code dynamically from function providers like ObjectGlobe. The security measures of ....

L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. J. Carey, and E. Shekita. Starburst Mid-Flight: As the Dust Clears. IEEE Transactions on Knowledge and Data Engineering, 2(1):143-- 160, March 1990.

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L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. G. Lindsay, H. Pirahesh, M. J. Carey, and E. J. Shekita. Starburst Mid-Flight: As the Dust Clears. IEEE Trans. on Knowledge and Data Engineering, 2(1):143--160, 1990.

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L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. J. Carey, and E. Shekita, "Starburst mid-flight: As the dust clears," IEEE Trans. Knowledge and Data Engineering, vol. 2, no. 1, pp. 143-- 160, 1990.

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L. M. Haas et al. Starburst Mid-Flight:As the Dust Clears. IEEETKDE, 2(1):143--160 (1990).

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HAAS, L., CHANG,W.,LOHMAN, G., MCPHERSON, M., WILMS,P.,LAPIS, G., LINDSAY, B., PIRAHESH, H., CAREY, M., AND SHEKITA, E. Starburst mid-flight: As the dust clears. tkde 2,1 (Mar. 1990), 143--160.

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Haas, L., Chang, W., Lohman, G., McPherson, J., P.Wilms, Lapis, G., Lindsay, B., Pirahesh, H., Carey, M., and Shekita, E., "Starburst mid-flight: As the dust clears," IEEE Transactions on Knowledge and Data Engineering, pp. 377--388, March 1990.

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Haas, L.M., Chang, W., Lohman, G.M., McPherson, J., Wilms, P.F., Lapis, G., Lindsay, B., Pirahesh, H., Carey, M., Shekita, E. Starburst midflight: As the dust clears. IEEE Transactions on Knowledge and Data Engineering 2(1):143-160, 1990. 120

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Haas, L.M., W. Chang, G.M. Lohman, J. McPherson, P.F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. Carey, and E. Shekita, Starburst Mid-Flight: As the Dust Clears. IEEE Transactions on Knowledge and Data Engineering, 2, 1990, 143-160.

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L. M. Haas, W. Chang, G. M. Lohman, J. McPherson, P. F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M. J. Carey, and E. Shekita, "Starburst mid-flight: As the dust clears," IEEE Trans. Knowledge and Data Engineering, vol. 2, no. 1, pp. 143-- 160, 1990.

No context found.

L.M. Haas, W. Chang, G.M. Lohman, J. McPherson, P.F. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, M.J. Carey, and E. Shekita. Starburst Mid-Flight: As the Dust Clears. IEEE Trans. on Knowledge and Data Engineering, 2(1):143--160, 1990.

No context found.

L. Haas, W. Chang, G. Lohman, P. McPherson, P. Wilms, G. Lapis, B. Lindsay, H. Pirahesh, Carey. M., and E. Shekita. Starburst Mid-Flight: As the Dust Clears. TKDE, 2(1):143--160, 1990.

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