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Oracle DBA - Oracle Optimization


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Redo Write Multiplexing

If an Oracle log file group has multiple members, LGWR must write the redo to each active member. If non-blocking writes are available (that is, if operating system asynchronous I/O is available and disk_asynch_io is enabled) then LGWR will perform these writes in parallel.



Redo Write Size

The size of redo writes varies depending on the amount of redo available for writing. In OLTP environments where redo writes are triggered quickly by frequent commits, it is normal for LGWR to write just a few log blocks in each write. Whereas in intensive batch environments with few commits, very large redo writes are common.

The Importance Of Partition Key Statistics

A partitioning-related performance problem came my way last week that had me scratching my head, until a 10053 trace illuminated the path to a solution. The problem was one of poor performance for a query that joined two range partitioned tables (having different partitioning keys  in fact one is multicolumn range/list composite partitioned, the other single column range partitioned) via two dimension tables. The immediate sign of a problem was the extensive use of nested loop joins, and that led to the observation that the cardinality of the result set from one of the partitioned tables was low. Initially I thought that this was due to the use of global statistics, as the query required the use of dynamic partition pruning (albeit to a single partition).



Tips for Using Oracle Stored Procedures

Stored procedures and triggers are faster than traditional code, which means they are becoming increasingly popular. As application code moves away from external programs and into the database engine, DBAs need to understand the related memory requirements and know how to manage them for optimal database performance.

Oracle Optimizer: Moving to and working with CBO

Great article on the various facets of the cost based optimizer and how it has changed from versions 8, 8i and 9i In Oracle, a query may be executed in more than one way. The execution plan that has the best ranking or the lowest cost is the one that will return output with the fastest rate and optimal utilization of resources. The execution plan is generated by the Optimizer. Optimizer is an 'engine' running in the database that is dedicated to deriving a list of execution paths based on various conditions and then choosing the most efficient for running a query. Once an execution plan choice is made, it is then carried out to arrive at the output.

Transportable Table Partitions

Transportable Tablespaces are the most efficient way to move large amounts of data from one Oracle database to another. When combined with a properly designed table partitioning scheme this feature provides an ideal method of refreshing a data warehouse or archiving transactional data quickly and with minimum interruption. To review, the basic premise of Transportable Tablespace is copying the actual Oracle datafile(s) from one database to another, then exporting metadata from the source database and importing it into the target, thus "plugging in" a tablespace. The export includes descriptions of the tables and other objects contained in the tablespace set, but no actual data, making it much faster than a conventional export. The source database requires the Enterprise Edition license.

True Session Wait Activity in Oracle 10g

Catching a session waiting on a resource used to be hit or miss. Let's take a look at how Oracle has helped give us a better mousetrap for seeing the waits experienced by sessions.

Tweaking Oracle SQL Performance Parameters

There are some things that the CBO cannot detect, which is where the DBA comes in. The types of SQL statements, the speed of the disks and the load on the CPUs, all affect the "best" execution plan for a SQL statement.

Upscaling Your Database Application Performance: Bind Variables

Recently Iíve had several encounters with issues that I would consider to be part of basic scalable application design. These arenít design issues that are new. Most of them have been addressed many times over the past years, however, they are issues that continually seem to appear. My guess is that itís not the same people making the same mistakes, but rather new people making the same mistakes. Each of my next few posts will be taking one of these application design issues and addressing it.

Upscaling Your Database Application Performance: Cursor Management

In my previous post, Bind Variables, I discussed why using bind variables is one of the most important fundamentals in engineering scalable database applications. I briefly touch on the point that cursor management is also very important. In this post I will go into why this is important, demonstrating by example. As a precursor to this post, you may want to read the section ďAnalyzing Cursor OperationsĒ in Designing Applications For Performance And Scalability.

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