31 October 2009

Database Architecture: Views I

    Typically the RDBMS vendors offer on top of their table-based storage 3 types of database objects used for data access: stored procedures, functions and views, each with their pluses and minuses. The views, same as the functions and stored procedures, can be seen as abstraction layers that stand between the physical database and users, allowing functionality reuse, logical structuring and better code maintenance . As Tony Regerson mentions, logically (and it only is logically) a view can be visualized as a virtual table, but from an optimization perspective a view is not a virtual table – “this is extremely important to remember when designing queries that you want to scale and perform well in a real environment”(T. Regerson, 2007). The view as virtual table is maybe the most realistic definition for a view, without reusing the term of view redundantly, as in “a view offers a view within a data set based on one or more tables”.

    Over the years I saw several pros and cons against using views, even several fights on whether to use views or not in database-based development. I’m not an SQL guru, though I often dealt with various applications making heavily use of database side programming, and I’m using the old fashioned views on a daily basis because of one of the below benefits.

    Structure the code in logical table-like query-able units that can cover many possibilities of querying the same data and which can be reused in other database objects, including views (nesting views). It can be thus created an abstract model on top of the existing table model, with multiple levels of details and perspectives.

    Hide implementation complexity from users, being easier to use than the base tables. There are situations in which users want to query the data by themselves, instead of using an existing report, a simple view can reduce the complexity of a query by hiding the implementation details and it simplifies data manipulation by focusing on a restrained scope specific to the problem is supposed to model. Making use of a often met quip, the users don’t have to “reinvent the wheel”, a view reducing concomitantly the effort and potential mistakes which can occur in queries’ construction; as somebody was remarking sarcastically, “not everybody is a Bill Gates”, so you can’t expect from users to be good query developers and know in and outs of a database model.

    When accessing data over MS Access or other similar tools, views might allow reducing the network traffic and increase query performance compared with the queries built on top of linked tables, in theory the fewer linked tables, the less network traffic and better the performance as the heavy processing is moved from the client to the server. Based on their use, the reduction of network traffic and the increased in performance can be relative.

    Stored as database objects, views keep code duplication and maintenance at minimum, offering better code traceability and testability. Imagine creating a set of queries for each possible scenario the users might use to query a set of tables, the simplest such scenario being the one in which the only difference resides in the attributes the users need; it’s must easier to create a view with all the attributes, the users selecting then only the attributes they need. In some situations might be necessary to create several views for the same set of tables, when are targeted different levels of details or views. There is another important aspect, the more queries you use on the same topic, the more maintenance work is needed when changes occurred in their logic; not to mention that often queries are run directly by users, the synchronization and testing of the various versions of the same query can become a nightmare. Even more, working with a named entity facilitates the communication between users and developers, allowing to easier identifying the piece of code in discussion.

    Views allow changing the order of attributes, adding formatting, calculations and scalar functions on top of the existing attributes, using table-valued functions and views.

    Views allow enforcing security at object, vertical (column) and horizontal (rows) level, partitioning thus data access based on the required security levels.

    Another “unorthodox” feature of views is that they allow developers to directly insert, update or delete data from tables they are based on, however this can be done under certain circumstances (e.g. such views need to reference directly and individually table’s columns, thus no aggregations and transformations can be performed).

    There are several cases against using views, the most important of them stresses the lower views’ performance when compared with the one of queries or stored procedures, however the benefit of caching query-plans can be relative, and the balancing between the cost of flexibility and maintainability vs. the cost of performance can favour the views. I find somehow paradoxical that in applications programming everybody goes for OOP weighting reusability more than performance, often creating allegorical monsters deviating from their purpose, and when it comes to databases, everyone is against views though the performance decrease is not so big, while the structures built derive intrinsically from data. On the other side it’s true that databases have a higher workload and are more sensitive to it, but I think people should learn to make use of tools and knowledge more wisely than hiding behind philosophies.

    Tony Regerson considers that views are more difficult to understand when nested, this making tuning and debugging more difficult. I can partially agree with him; from my point of view the code becomes easier to read, understand, maintain and test when logic is split in smaller fragments, and even if it can be more difficult to identify the source of a field from the final query, for this needing to traverse multiple views, the benefits of views can diminish the impact of this downside. It remains the problem of tuning, though actually this reflects the need for smarter database engines, while the other understanding related issues reflect the need for development tools that can identify the source tables and fields from nested objects. Documentation like ERDs and other types of mappings can improve the understanding of nested views.

    Several applications I worked with, for example Oracle APPS, built the data access on top of views, each form being based on one or more views, which encapsulate the basic layer of business logic, further processing and customization being done in the form itself. This architecture facilitates to some degree developers’ work. The same views can be used also for the various reports, however such views often have the inconvenience they resume only on the attributes needed by a form, thus the adding of other attributes resume at extending the views, the creation of similar views that include the needing attributes, or at the recombination of views. The extension of standard views is not recommended because there is the risk the vendor might decline the responsibility for the errors occurring in a view, another important risk residing the fact that the views might be replaced with the installation of patches or during version upgrade. The combination of views might lead to the unnecessary reuse of the same table more than once, resulting in performance decrease which can be substantial. The remaining approach, often the best, is to create another view replicating the needed logic, though the developed views need to be synchronized with the standard views in case changes occur.

    A similar scenario occurs when users recombine views in order to obtain the attributes needed in their analysis, again is recommended to provide a view which offers the same needed behaviour. The problem is that it’s difficult to identify such issues, because usually the developer has low visibility on how the user is using the tables. This could be theoretically avoided by better communication between users and developers, by moving the code, when possible, from personal databases to production databases.

    Doing changes through (updatable) views diminishes the chances of trapping or raising customized errors from code, letting the application or DBMS to handle the issue and all the implications derived from it. This eventual issue could be partially solved by view triggers, however this functionality is provided only by a few vendors. In web or desktop applications, such direct data access increases also the risk for SQL injection attacks, stored procedure based access being more recommended for such architectures.

    There are several other aspects which need to be considered with views, facts resulting mainly from the various types of views; I’ll try to summarize them in a second post.


T. Regerson. (2007). Views – they offer no optimisation benefits they are simply inline macros use sparingly. [Online] Available from:
http://sqlblogcasts.com/blogs/tonyrogerson/archive/2008/01/03/views-they-offer-no-optimisation-benefits-they-are-simply-inline-macros-use-sparingly.aspx (Accessed: 12 January 2007)
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