Algorithms for deferred view maintenance

Abstract

Materialized views and view maintenance are important for data warehouses, retailing, banking, and billing applications. We consider two related view maintenance problems: 1) how to maintain views after the base tables have already been modified, and 2) how to minimize the time for which the view is inaccessible during maintenance.Typically, a view is maintained immediately, as a part of the transaction that updates the base tables. Immediate maintenance imposes a significant overhead on update transactions that cannot be tolerated in many applications. In contrast, deferred maintenance allows a view to become inconsistent with its definition. A refresh operation is used to reestablish consistency. We present new algorithms to incrementally refresh a view during deferred maintenance. Our algorithms avoid a state bug that has artificially limited techniques previously used for deferred maintenance.Incremental deferred view maintenance requires auxiliary tables that contain information recorded since the last view refresh. We present three scenarios for the use of auxiliary tables and show how these impact per-transaction overhead and view refresh time. Each scenario is described by an invariant that is required to hold in all database states. We then show that, with the proper choice of auxiliary tables, it is possible to lower both per-transaction overhead and view refresh time.

Maintaining large update batches by restructuring and grouping

“…Materialized views need to be maintained upon source changes since a stale view extent may not help or even mislead user applications. Incremental view maintenance, which aims at only computing the deltas of the view result instead of recomputing the view from scratch on data source changes, has been extensively studied in the past [1,[3][4][5][6][7][8][9][10][11]. Among these works, the incremental maintenance of batches of updates [3,7,12,13] is of particular interest because it is attractive from both a resource and a performance perspective to most practical systems.…”

“…Batch maintenance has been shown to be more efficient in terms of the total processing time when maintaining a large set of source updates [3,7,12,13]. Sequential maintenance involves many maintenance queries in the style similar to Queries 2 and 3 in our example to be sent, with each maintenance query reflecting a single source update.…”

“…Early work has studied incremental view maintenance assuming no concurrency [7,20]. In approaches that need to send maintenance queries to the data sources, especially in a environment with autonomous data sources, concurrency problems can arise.…”

“…Refs. [3,7,12,13,21,22] propose algorithms to maintain materialized views incrementally using source-based batching. Salem et al [3] proposed an asynchronous view maintenance algorithm using delta changes of data sources.…”

Incremental maintenance of aggregate and outerjoin expressions

“…A large body of work exists describing different algorithms for incrementally maintaining materialized views [4][5][6][7][8][9][10][11][12][13][23][24][25][26][27][28][29][30]. Each work applies to different classes of views and has various advantages and disadvantages.…”