For example, a system that has two 4-core processors with two threads enterprise per core, reports that it has 16 CPUs.
The logical page size determines the number of bytes: using a 2K page, it is 4 terabytes, on a 16K page Adaptive server Server, it is 32 terabytes.
Number of logins Table 1-1 lists the limits for the number of logins, users, and groups for Adaptive Server.
Information in this document is subject to change without notice.For example, if your server uses a 16K page, then one allocation unit is 4MB (16K times 256).In 2001, ASE.5 was released, providing features such as dynamic memory allocation, an EJB container, support for XML, SSL and ldap.Threads, thread pools, engines and CPUs In process mode, Adaptive Server adaptive typically consumes client one CPU per configured engine.At the application layer, these issues are relevant: Decision-support systems (DSS) and online transaction processing (oltp) require different client performance strategies.It included support for partitioning table rows in a database server across individual disk devices, and "virtual columns" which are computed only when required.9 Varying server logical page sizes Number of columns and column size Maximum enterprise length of expressions, variables, and stored procedure arguments Number of logins Performance implications for limits Size of kernel resource memory Analyzing performance Normal forms Locking Special considerations chapter 2 Networks and Performance Potential.In threaded mode, Adaptive Server typically consumes one CPU per configured engine thread, plus additional CPU for nonengine threads, such as I/O handling threads in syb_system_pool.
Issues at the Adaptive Server safe layer include: The application types to be supported: oltp, DSS, ebook or a mix.
This per-packet overhead has the most effect on effects performance.
Contents, history edit, originally for, ebook unix platforms in 1987, Sybase Corporation 's primary relational database management system product was initially marketed under the name Sybase SQL Server.
The physical limits of the network have been reached.When you increase the number of disk I/Os, Adaptive Server quickly balances the distribution across the controllers.You must restart Adaptive Server to reduce the number of I/O tasks.Virtually all Adaptive Server users access their data via a network.It is not to be confused with.For example, if you use norton a data-only-locked table with a char(2000) column, Adaptive Server must allocate memory to perform column copying while scanning the table.You may find that bulk copy works best sound at one packet size, while large image data retrievals perform better at a different packet size.Locking is necessary in a multiuser environment, since several users may be working with the same data at the same time.You may find that the performance between the client and Adaptive Server improves if the client consolidates or batches the rows it optimizer sends to Adaptive Server, greatly simplifying the process and requiring less interaction between Adaptive Server and the client.Any other appropriate tools.Database designers and administrators must decide on the various techniques best suited their environment.Performance and Tuning Series: Basics 19 28 How Adaptive Server uses the network Network listeners in process mode In process mode, each Adaptive Server engine is a separate process; therefore, network listeners run slightly differently than they do in threaded mode, when Adaptive Server.So, after creating a network listener, Adaptive Server can accept one less user connection.The number of listener ports is determined at startup by the number of master entries in the interfaces file.7 Test the hypothesis by implementing the solutions from the last step: Adjust wings configuration parameters.
Adaptive Server creates and uses three of these segments: adaptive server enterprise client system segment contains most system catalogs.
A lock timeout option and task-to-engine affinity were added, query optimization is now delayed until a cursor is opened and the values of the variables are known.
Minimizing wait times (for example, by improving network, physical, and logical lock contention) In some cases, Adaptive Server is automatically optimized to reduce initial response time, that is, the time it takes to return the first row to the user.