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How important is the database when considering the performance and scalability of your application I would argue that it usually represents about one-third of the overall challenge Think that sounds like a lot It's really not in fact, for many applications this is a conservative estimate Remember that an application consists of three things: an interface, business logic, and persistent data Thus, if we don't consider database integration and the scalability and performance issues involved, we're tackling only two-thirds of the overall problem Nevertheless, there are times when tuning your database system may not be critical Realize that modern commercial database systems are built for speed and scalability In fact, if you buy a database, set it up, and stick a bunch of JDBC calls in your application code to access it, you may get decent performance And, again, based on the nature of your application, that may be good enough Still, for most large and complex applications, database design and optimization are important Part of the reason has to do with application-oriented demands For example, many large applications require the modeling of complex data relationships If answering database queries frequently requires navigating those relationships, overall throughput can be dramatically affected by choices made as a result of the modeling Complex applications also rely on the database to enforce business processes (such as business rules) In this sense, built-in database features such as stored procedures and triggers may be used more heavily than in a simpler application that merely requires a few JDBC simple queries Another example of where database optimization makes sense involves the latency caused by I/O during database query execution Outside Internet-based communication between client and server, stalls during database I/O are likely the most wasteful activity in application execution This is especially true for very large databases, where the database system cache is constantly in flux and the cost of scanning large tables is high A key challenge when designing your database is to reduce this I/O as much as possible This can mean tuning the cache, building efficient data structures (eg, indexes) in the database, modeling your data more strategically, optimizing the placement of your data, or some combination thereof Still another, more system-oriented reason that database design and optimization can be important has to do with the database acting as a logical point of centralization in an otherwise distributed system Many large Web applications have multiple clients, internal and external, both Web based and non-Web based Even though highly scalable application servers, distributed over multiple server machines, may exist to process client requests, they might all be dependent on a common database to complete their processing If this database is distributed replication must still guarantee data consistency There is no way to avoid its cost Distributed though your application logic might be, access to the underlying data generally must often be serialized One trick in optimizing application performance and scalability is to realize that not all data needs to be centralized and that there are ways to reduce the time that access must be serialized One final system-oriented motivation for optimizing the database has to do with the waste/redundancy that can be associated with servicing multiple client interfaces In general, the more interfaces to an application, the more likely redundant data retrievals When different clients use these interfaces, they force the database to do something it has done before and that could have been reused Consider a site that sells products to registered users In addition to pages that display the products and allow the user to order when desired, the site is likely to contain a set of account management pages that are used to make changes to user vital statistics (eg, password, address, etc) Even though these are very different from interfaces that access the database, they both deal with user.

Corporate governance as a discipline has been developing over several decades Nevertheless, many important developments have occurred recently, primarily in the United States, as a reaction to perceived governance failings The tectonic shift in corporate governance

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information and depending on the data model they may need to read and update data in the same tables So, even if the interfaces are connected to different Java servlets running on different machines, they're both going to direct their queries to the same logical database This will often result in redundant data access and application logic We approach this chapter with all of these examples in mind Regardless of the complexity of your data model or the underlying data you store, one thing is certain: If you're persisting data, it's in your best interest to consider optimizing the process To accomplish this it's helpful to understand database technology as well as selective details of your particular system Thus, we begin our journey of optimizing database integration by first considering effective database design and how the relational model works

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Given that not everyone is a database engineer, it's worthwhile to review the important aspects of database systems Discussions later in this book assume this knowledge, so let's make sure that we're comfortable with the concepts and terminology First of all, remember that database systems are commonly known as database management systems (DBMS) This implies two things: that they do more than query data (they manage it) and that their implementation is like that of a "system" In fact, it's more like that of a distributed system: Most commercial databases are composed (at runtime) of a collection of processes and threads on one or more machines that work together efficiently to deliver high performance and scalability For example, the Oracle 8i database architecture consists of instances that act as proxies to the data In this case, the instance is the part of the DBMS that users and applications interact with it's composed of a collection of processes (on UNIX) or threads (Windows) that manage the underlying data on disk

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