Yannis Kotidis and Nick Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 371--382, Philadelphia, Pennsylvania, June 1999.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....caching system for OLAP queries on a dedicated infrastructure. In this work we follow a di#erent approach focusing on the client side. Continuing the previous example, assume that users from Hong Kong pose queries to the NYSE warehouse and some results are cached at their local computer [4, 5, 15, 21] hoping that subsequent queries can reuse this data. However, the size of each client s cache is relatively small compared to the size of the warehouse, while the network cost of transferring large amounts of data from overseas is high. On the other hand, it is possible that some other user in ....

....cache the results of the query together with the query string. Subsequent queries can be answered by the cached data if there is an exact match on their query strings. The authors present admission and replacement algorithms that consider the cost of re evaluating a result and its size. Dynamat [15] is another OLAP cache manager, which stores fragments instead of arbitrarily shaped query results. Fragments are aggregate query results in a finer granularity than views since they may include equality selections on some dimensions. They may be further aggregated to answer more general queries, ....

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Y. Kotidis and N. Roussopoulos. Dynamat: A dynamic view management system for data warehouses. In SIGMOD, pages 371--382, 1999.

....queries of the legacy system. A. Banks Pidduck et al. Eds. CAISE 2002, LNCS 2348, pp. 361 376, 2002. Springer Verlag Berlin Heidelberg 2002 362 Jianguo Lu The first problem can be viewed as the traditional object relational mapping problem that has been thoroughly studied for a long time [22] [3] 4] Those studies have proposed a variety of methods and tools to support such a mapping, ranging from design patterns [5] to tools that generate the EJB skeletons from database schemas [17] This paper focuses on the second and the third problems, which can be viewed as the other half of ....

Yannis Kofidis, Nick Roussopoulos, DynaMat: A Dynamic View Management System for Data Warehouses, SIGMOD 99, June.

....these algorithms is proposed, to select both views and indices on them. 1] employs a method which identifies the relevant views of a lattice for a given workload. 22] uses a simple and fast algorithm for selecting views in lattices with special properties. Dynamic alternatives are exploited in [18, 3, 11]. These systems reside between the data warehouse and the clients and implement a disk cache that stores aggregated query results in a finer granularity than views. Most of these papers assume that the OLAP queries are sent to the system one at a time. Nevertheless, this is not always true. In ....

....as shown in figure 4a. The fact table contains 6M tuples. For the APB dataset, we used the full schema for the dimensions (figure 4b) but only one measure. The size of the fact table is 1.3M tuples. SYNTH dataset is a 10 dimensional database that models supermarket transactions, also used in [11]. The cardinality of each dimension is shown in table 1. The fact table contains 20M tuples. The sizes of the nodes in the lattice are calculated by the analytical algorithm of [21] All experiments were run on an UltraSparc2 workstation (200MHz) with 256MB of main memory. 10 SUPPLIER Suppkey ....

Kotidis Y., Roussopoulos N., "DynaMat: A Dynamic View Management System for Data Warehouses", Proc. ACM-SIGMOD, 1999.

....of views in databases. The paper [32] is a survey of containment and rewriting optimization of queries using views. 1] discusses the complexity of answering queries using materialized views and conrains references to major results in the areas of query containment and view materialization. Papers [16,17, 21, 30] describe approaches to view materialization. 3, 12, 13, 23] treat the problem of using available materialized views for query evaluation. Nearly all results described in the literature concern rewriting of single queries; notice that the database reformulation approach we propose involves ....

Yannis Kotidis and Nick Roussopoulos. Dynamat: a dynamic view management system for data warehouses. In SIGMOD-99.

....for a given workload. 22] use a simple and fast algorithm for selecting views in configurations with special properties. 26] study the minimization of both query execution and view maintenance costs, under the constraint that all queries should be answered from the selected views. Finally, [18] propose the dynamic materialization and maintenance of query results considering both space and time constraints. The above methods are effective when the number of views is relatively small but they do not scale well with dimensionality. The complexity of the greedy methods does not allow their ....

....quality guarantee for the picked selection. 2. 2 View selection under the Maintenance Cost Constraint As the ratio of price capacity of secondary storage media is constantly dropping, the maintenance cost (i.e. the update time) constraint becomes the limiting factor in the view selection problem [6, 18]. Although the space constraint seems similar to the maintenance cost constraint, they have a significant difference. The space occupied by a set of views always increases when a new view is inserted, while the maintenance cost does not; it is possible for the update time of a set of views to ....

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Y. Kotidis, N. Roussopoulos, "DynaMat: A Dynamic View Management System for Data Warehouses", in: Proc. ACM SIGMOD, 1999.

....query performance over multidimensional queries. The idea was to store previous query results in the cache; incoming queries were broken up into fragments which could be answered using the cache or had to be recovered from the database. This idea was extended in the Dynamat system described in [KR99] Recent work [DN00] has examined a variation of this problem, namely determining when it is possible to answer a query aggregating data in the cache and determining the fastest path for this aggregation since there are many possible ways this aggregation can be carried out. 2.3.7 Integrated ....

Y. Kotidis and N. Roussopoulos. Dynamat: A dynamic view management system for data warehouses. In Proceedings of the

....to the set of a priori known queries. Dynamic VSP The static selection of views contradicts the dynamic nature of decision support analysis. Especially for ad hoc queries where the expert user is looking for interesting trends in the data repository, the query pattern is difficult to predict [46]. In addition, as the data and these trends are changing overtime, a static selection of views might very quickly become outdated. This means that the DWA should monitor the query pattern and periodically re calibrate the materialized views by running theses algorithms. Kotidis and Roussopoulos ....

....In addition, as the data and these trends are changing overtime, a static selection of views might very quickly become outdated. This means that the DWA should monitor the query pattern and periodically re calibrate the materialized views by running theses algorithms. Kotidis and Roussopoulos [46] present a system called DynaMat that dynamically materializes information at multiple levels of granularity in order to match the demand (workload) but also takes into account the maintenance restrictions for the warehouse, such as down time to update the views and space availability. This ....

[Article contains additional citation context not shown here]

Y. Kotidis and N. Roussopoulos. Dynamat: A dynamic view management system for data warehouses. Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 371--382, June 1999.

.... for assisting decision making by offering a global view of the enterprise data and providing mechanisms for On Line Analytical Processing (OLAP) CCS93] A common technique to accelerate OLAP operations is to store some redundant data, either statically [Gupt97, GM99, SDN98] or dynamically [KR99]. Most of OLAP literature assumes that queries are sent to the system one at a time. In multi user environments, however, many queries can be submitted concurrently. In addition, the new API proposed by Microsoft [MS] for Multi Dimensional Expressions (MDX) which becomes de facto standard for ....

Kotidis Y., Roussopoulos N., "DynaMat: A Dynamic View Management System for Data Warehouses", Proc. ACM-SIGMOD, 1999.

....the first set of chunks from the cache and will send a query for the missing chunks to the backend. Only chunks at the same aggregation level as the query can be used, i.e. no aggregation is done on the cached results. The admission and replacement algorithms are similar to watchman. Dynamat [KR99] is another OLAP cache manager which considers both the size and maintenance cost constraints. Dynamat stores fragments , which are aggregate query results in a finer granularity than views (they may include selection on single values on some dimensions) During the on line phase, when a query ....

....the queries involve whole views, so we chose to fragment the data cube at the granularity of views. The same approach is used in [HRU96, GHRU97, SDN98] However, the OCS architecture is independent from the granularity of fragmentation, therefore any of the other methods proposed in the literature [KR99, DRSN98] can be employed, if the expected workload is different. Actually, since each OCS is an independent entity, it can use its own method of fragmentation. For instance, an OCS that is close to the data warehouse can cache whole views, since it is expected to serve in parallel many queries for many ....

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Kotidis Y., Roussopoulos N., "DynaMat: A Dynamic View Management System for Data Warehouses", Proc. ACM-SIGMOD, 1999.

....in the data warehouse aggregate materialization problem. Issues concerning maintenance of materialized views have been addressed by Blakeley et al. 2] Colby et al. 5,6] and Kotidis and Roussopoulos Fig. 2. The greedy algorithm. 188 C.I. Ezeife Data Knowledge Engineering 36 (2001) 185210 [18]. However, these view maintenance solutions are mostly relevant to non fragmented materialized views. Some view maintenance issues that are relevant to horizontally fragmented, materialized views are raised and addressed in [26,25] 1.2. Motivations and contributions Before the advent of data ....

Y. Kotidis, N. Roussopoulos, DynaMat: A dynamic view management system for data warehouses, in: ACM SIGMOD International Conference on Management of Data, Philadelphia, USA, June 1999, pp. 371382.

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Yannis Kotidis and Nick Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 371--382, Philadelphia, Pennsylvania, June 1999.

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KOTIDIS,Y.AND ROUSSOPOULOS, N. 1999. DynaMat: A dynamic view management system for data warehouses. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Philadelphia, Pa., June). ACM, New York, pp. 371--382.

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Yannis Kotidis and Nick Roussopoulos. "DynaMat: A Dynamic View Management System for Data Warehouses ". In Proc. of the ACM SIGMOD Conference, Philadelphia, USA, June 1999.

....The view selection problem aims at balancing the trade off between performance improvement and maintenance overhead because of materialization. View selection has been studiedextensively in relational databases and data warehouses [Rou82, Han87, Sel88, BM90, GM95, RCK 95, SSV96, Gup97, CD97, KR99] In data warehouses, View Selection is performed off line during the down time of the warehouse. Web servers, on the other hand, must remain online all the time and thus, updates are applied in the back end database while the web server continues to serve user requests. Therefore, in a web ....

....Figure 15: QoS over time 5 Related Work To the best of our knowledge this is the first paper that attempts to solve the Online View Selection problem. There is a lot of research on the off line version of the view selection problem in Data Warehousing literature [Sel88, GM95, SSV96, Gup97, GM99, KR99] Materialization has also been explored in [YFIV00] where multiple maintenance policies were supported, but the selection problem was not addressed. LR00] presented a cost model for the view selection problem, but did not provide an algorithm. CIW 00] described a system to support caching ....

Yannis Kotidis and Nick Roussopoulos. "DynaMat: A Dynamic View Management System for Data Warehouses". In Proc. of the ACM SIGMOD Conference, Philadelphia, USA, June 1999.

....much like a cache, the views get dirty whenever the data warehouse tables are modified. Thus, one should also take into account the view maintenance overhead, which is payable each time new data is shipped to the data warehouse and its base tables get refreshed. In this paper, we present DynaMat [Kotidis and Roussopoulos 1999], a system that manages dynamic collections of materialized views in a data warehouse. At query time DynaMat utilizes a dedicated disk space (called the View Pool) for storing computed aggregates (called view fragments) that are further engaged for answering new queries. The View Pool is ....

Kotidis, Y. and Roussopoulos, N. 1999. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Philadelphia, Pennsylvania, June 1999), pp. 371--382.

....WebViews are materialized to avoid repeated execution of many small OLTP style queries. Finally, the general case of the WebView materialization problem has no constraints, whereas most view selection algorithms impose some resource constraints (e.g. maximum storage or maintenance window limits [KR99] In the next section we briefly describe the architecture of typical database backed web servers, followed by some motivating examples of WebViews. 1.1 Architecture When only servicing requests for static pages, the web server simply parses user requests, reads the appropriate files from a ....

Yannis Kotidis and Nick Roussopoulos. "DynaMat: A Dynamic View Management System for Data Warehouses". In Proc. of the ACM SIGMOD Conference, Philadelphia, USA, June 1999.

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Y. Kotidis and N. Roussopoulos. DynaMat: a dynamic view management system for data warehouses. pages 371--382, 1999.

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Yannis Kotidis, Nick Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of SIGMOD, 1999.

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Y. Kotidis and N. Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of the ACM SIGMOD International Conference on the Management of Data, pp. 371--382, 1999.

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Kotidis Y., Roussopoulos N. DynaMat: A Dynamic View Management System for Data Warehouses. ACM SIGMOD 1999.

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Y. Kotidis and N. Roussopoulos. DynaMat: a dynamic view management system for data warehouses. pages 371--382, 1999.

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Y. Kotidis and N. Roussopoulos, DynaMat: A Dynamic View Management System for Data Warehouses, Best Paper Award, SIGMOD 1999.

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Yannis Kotidis and Nick Roussopoulos. DynaMat: a dynamic view management system for data warehouses. In SIGMOD, pages 371-382, 1999.

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Y. Kotidis and N. Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In SIGMOD, pages 371--382, 1999.

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Y. Kotidis and N. Roussopoulos. DynaMat: A Dynamic View Management System for Data Warehouses. In Proceedings of ACM SIGMOD, 1999.

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