4 Configuring a Database for Performance

4.1.1 Initialization Parameters

A running Oracle instance is configured using initialization parameters, which are set in the initialization parameter file. These parameters influence the behavior of the running instance, including influencing performance. In general, a very simple initialization file with few relevant settings covers most situations, and the initialization file should not be the first place you expect to do performance tuning, except for the few parameters shown in Table 4-2.

Table 4-1 describes the parameters necessary in a minimal initialization file. Although these parameters are necessary, they have no performance impact.

Table 4-2 includes the most important parameters to set with performance implications:

4.1.2 Configuring Undo Space

Oracle Database uses undo space to store data used for read consistency, recovery purposes, and actual rollback statements. This data is saved in one or more undo tablespaces. If you use the Database Configuration Assistant (DBCA) to create a database, the undo tablespace will be created automatically. To manually create an undo tablespace, add the UNDO TABLESPACE clause in the CREATE DATABASE statement when creating the database.

To automate the management of undo data, Oracle Database uses automatic undo management, which transparently creates and manages undo segments. Automatic undo management is controlled by the UNDO_MANAGEMENT initialization parameter. To enable automatic undo management, set the UNDO_MANAGEMENT initialization parameter to AUTO (the default setting). If unspecified, the UNDO_MANAGEMENT initialization parameter will use the AUTO setting. Oracle strongly recommends using automatic undo management, because it significantly simplifies database management and eliminates the need for any manual tuning of undo (rollback) segments. Manual undo management using rollback segments is supported for backward compatibility reasons.

The V$UNDOSTAT view contains statistics for monitoring and tuning undo space. Using this view, you can better estimate the amount of undo space required for the current workload. Oracle Database also uses this information to help tune undo usage. The V$ROLLSTAT view contains information about the behavior of the undo segments in the undo tablespace.

4.1.3 Sizing Redo Log Files

The size of the redo log files can influence performance, because the behavior of the database writer and archiver processes depend on the redo log sizes. Generally, larger redo log files provide better performance. Undersized log files increase checkpoint activity and reduce performance.

Although the size of the redo log files does not affect LGWR performance, it can affect DBWR and checkpoint behavior. Checkpoint frequency is affected by several factors, including log file size and the setting of the FAST_START_MTTR_TARGET initialization parameter. If the FAST_START_MTTR_TARGET parameter is set to limit the instance recovery time, Oracle automatically tries to checkpoint as frequently as necessary. Under this condition, the size of the log files should be large enough to avoid additional checkpointing due to under sized log files. The optimal size can be obtained by querying the OPTIMAL_LOGFILE_SIZE column from the V$INSTANCE_RECOVERY view. You can also obtain sizing advice on the Redo Log Groups page of Oracle Enterprise Manager Database Control.

It may not always be possible to provide a specific size recommendation for redo log files, but redo log files in the range of a hundred megabytes to a few gigabytes are considered reasonable. Size your online redo log files according to the amount of redo your system generates. A rough guide is to switch logs at most once every twenty minutes.

4.1.4 Creating Subsequent Tablespaces

If you use the Database Configuration Assistant (DBCA) to create a database, the supplied seed database automatically includes all the necessary tablespaces. If you choose not to use DBCA, you need to create extra tablespaces after creating the initial database.

All databases should have several tablespaces in addition to the SYSTEM and SYSAUX tablespaces. These additional tablespaces include:

• A temporary tablespace, which is used for things like sorting

• An undo tablespace to contain information for read consistency, recovery, and rollback statements

• At least one tablespace for actual application use

In most cases, applications require several tablespaces. For extremely large tablespaces with many datafiles, multiple ALTER TABLESPACE x ADD DATAFILE Y statements can also be run in parallel.

During tablespace creation, the datafiles that make up the tablespace are initialized with special empty block images. Temporary files are not initialized.

Oracle does this to ensure that all datafiles can be written in their entirety, but this can obviously be a lengthy process if done serially. Therefore, run multiple CREATE TABLESPACE statements concurrently to speed up the tablespace creation process. For permanent tables, the choice between local and global extent management on tablespace creation can have a large effect on performance. For any permanent tablespace that has moderate to large insert, modify, or delete operations compared to reads, local extent management should be chosen.

4.2.1 Table Compression

Heap-organized tables can be stored in a compressed format that is transparent for any kind of application. Table compression was designed primarily for read-only environments and can cause processing overhead for DML operations in some cases. However, it increases performance for many read operations, especially when your system is I/O bound.

Compressed data in a database block is self-contained which means that all the information needed to re-create the uncompressed data in a block is available within that block. A block will also be kept compressed in the buffer cache. Table compression not only reduces the disk storage but also the memory usage, specifically the buffer cache requirements. Performance improvements are accomplished by reducing the amount of necessary I/O operations for accessing a table and by increasing the probability of buffer cache hits.

4.2.2 Reclaiming Unused Space

Over time, it is common for segment space to become fragmented or for a segment to acquire a lot of free space as the result of update and delete operations. The resulting sparsely populated objects can suffer performance degradation during queries and DML operations.

Oracle Database provides a Segment Advisor that provides advice on whether an object has space available for reclamation based on the level of space fragmentation within an object.

If an object does have space available for reclamation, you can compact and shrink database segments or you can deallocate unused space at the end of a database segment.

4.2.3 Indexing Data

The most efficient way to create indexes is to create them after data has been loaded. By doing this, space management becomes much simpler, and no index maintenance takes place for each row inserted. SQL*Loader automatically does this, but if you are using other methods to do initial data load, you might need to do this manually. Additionally, index creation can be done in parallel using the PARALLEL clause of the CREATE INDEX statement. However, SQL*Loader is not able to do this, so you must manually create indexes in parallel after loading data.

4.3.1 Identifying Contention Using the Dispatcher-Specific Views

The following views provide dispatcher performance statistics:

• V$DISPATCHER - general information about dispatcher processes

• V$DISPATCHER_RATE - dispatcher processing statistics

The V$DISPATCHER_RATE view contains current, average, and maximum dispatcher statistics for several categories. Statistics with the prefix CUR_ are statistics for the current sample. Statistics with the prefix AVG_ are the average values for the statistics since the collection period began. Statistics with the prefix MAX_ are the maximum values for these categories since statistics collection began.

To assess dispatcher performance, query the V$DISPATCHER_RATE view and compare the current values with the maximums. If your present system throughput provides adequate response time and current values from this view are near the average and less than the maximum, then you likely have an optimally tuned shared server environment.

If the current and average rates are significantly less than the maximums, then consider reducing the number of dispatchers. Conversely, if current and average rates are close to the maximums, then you might need to add more dispatchers. A general rule is to examine V$DISPATCHER_RATE statistics during both light and heavy system use periods. After identifying your shared server load patterns, adjust your parameters accordingly.

If needed, you can also mimic processing loads by running system stress tests and periodically polling the V$DISPATCHER_RATE statistics. Proper interpretation of these statistics varies from platform to platform. Different types of applications also can cause significant variations on the statistical values recorded in V$DISPATCHER_RATE.

4.3.2 Identifying Contention for Shared Servers

This section discusses how to identify contention for shared servers.

Steadily increasing wait times in the requests queue indicate contention for shared servers. To examine wait time data, use the dynamic performance view V$QUEUE. This view contains statistics showing request queue activity for shared servers. By default, this view is available only to the user SYS and to other users with SELECT ANY TABLE system privilege, such as SYSTEM. Table 4-3 lists the columns showing the wait times for requests and the number of requests in the queue.

Monitor these statistics occasionally while your application is running by issuing the following SQL statement:

SELECT DECODE(TOTALQ, 0, 'No Requests',
   WAIT/TOTALQ || ' HUNDREDTHS OF SECONDS') "AVERAGE WAIT TIME PER REQUESTS"
  FROM V$QUEUE
 WHERE TYPE = 'COMMON';

This query returns the results of a calculation that show the following:

AVERAGE WAIT TIME PER REQUEST
-----------------------------
.090909 HUNDREDTHS OF SECONDS

From the result, you can tell that a request waits an average of 0.09 hundredths of a second in the queue before processing.

You can also determine how many shared servers are currently running by issuing the following query:

SELECT COUNT(*) "Shared Server Processes"
  FROM V$SHARED_SERVER
 WHERE STATUS != 'QUIT';

The result of this query could look like the following:

Shared Server Processes
-----------------------
10

If you detect resource contention with shared servers, then first make sure that this is not a memory contention issue by examining the shared pool and the large pool. If performance remains poor, then you might want to create more resources to reduce shared server process contention. You can do this by modifying the optional server process initialization parameters:

• MAX_DISPATCHERS

• MAX_SHARED_SERVERS

• DISPATCHERS

• SHARED_SERVERS

  See Also:

  Oracle Database Administrator's Guide for information on setting the shared server process initialization parameters