Use the Prepared Statement Cache Use Logging Last Resource Optimization Tune Connection Backlog Buffering Tune the Chunk Size Use Optimistic or Read-only Concurrency
2.2 Use the Prepared Statement Cache
The prepared statement cache keeps compiled SQL statements in memory, thus avoiding a round-trip to the database when the same statement is used later. See Chapter 12, Tuning Data Sources .2.3 Use Logging Last Resource Optimization
When using transactional database applications, consider using the JDBC data source Logging Last Resource LLR transaction policy instead of XA. The LLR optimization can significantly improve transaction performance by safely eliminating some of the 2PC XA overhead for database processing, especially for two-phase commit database insert, update, and delete operations. For more information, see Chapter 12, Tuning Data Sources .2.4 Tune Connection Backlog Buffering
You can tune the number of connection requests that a WebLogic Server instance accepts before refusing additional requests. This tunable applies primarily for Web applications. See Section 7.5.8, Tuning Connection Backlog Buffering .2.5 Tune the Chunk Size
A chunk is a unit of memory that the WebLogic Server network layer, both on the client and server side, uses to read data from and write data to sockets. A server instance maintains a pool of these chunks. For applications that handle large amounts of data per request, increasing the value on both the client and server sides can boost performance. See Section 7.5.7, Tune the Chunk Parameters .2.6 Use Optimistic or Read-only Concurrency
Use optimistic concurrency with cache-between-transactions or read-only concurrency with query-caching for CMP EJBs wherever possible. Both of these two options leverage the Entity Bean cache provided by the EJB container. ■ Optimistic-concurrency with cache-between-transactions work best with read-mostly beans. Using verify-reads in combination with these provides high data consistency guarantees with the performance gain of caching. See Chapter 10, Tuning WebLogic Server EJBs . ■ Query-caching is a WebLogic Server 9.0 feature that allows the EJB container to cache results for arbitrary non-primary-key finders defined on read-only EJBs. All of these parameters can be set in the applicationmodule deployment descriptors. See Section 10.4.8, Concurrency Strategy .2.7 Use Local Interfaces
Parts
» Oracle Fusion Middleware Online Documentation Library
» Document Scope and Audience Guide to this Document
» Performance Features of this Release Tune Pool Sizes
» Understand Your Performance Objectives
» Locate Bottlenecks in Your System Minimize Impact of Bottlenecks Tune Your Application
» VM Heap Size and Garbage Collection
» Choosing a Garbage Collection Scheme Using Verbose Garbage Collection to Determine Heap Size
» Other Java HotSpot VM Options
» Specifying Heap Size Values Tuning Tips for Heap Sizes Automatically Logging Low Memory Conditions
» JVM Tuning Considerations Using JRockit Flight Recorder Tuning Considerations
» Setting Java Parameters for Starting WebLogic Server
» Development vs. Production Mode Default Tuning Values
» Tuning Muxers Tuning Network IO
» Tuning Message Size Tuning Complete Message Timeout Tuning Number of File Descriptors
» Tune the Chunk Parameters Tuning Connection Backlog Buffering
» Tuning Cached Connections Tuning Network IO
» Scalability and High Availability
» JNDI Binding, Unbinding and Rebinding Running Multiple Server Instances on Multi-Core Machines
» Filtering Loader Mechanism Class Caching
» Using the Default Persistent Store Using Custom File Stores and JDBC Stores
» Basic Tuning Information Tuning File Stores
» Best Practices When Using Persistent Stores Tuning JDBC Stores General Suggestions
» Transaction-Level Caching Caching between Transactions Ready Bean Caching
» Tuning the Stateless Session Bean Pool Tuning the MDB Pool Tuning the Entity Bean Pool
» Use JDBC Batch Operations Tuned Updates Using Field Groups include-updates
» call-by-reference Bean-level Pessimistic Locking Concurrency Strategy
» Cache Miss Ratio Lock Waiter Ratio
» Lock Timeout Ratio Pool Miss Ratio
» Destroyed Bean Ratio Pool Timeout Ratio
» Determining the Number of Concurrent MDBs Selecting a Concurrency Strategy
» Thread Utilization When Using WebLogic Destinations Limitations for Multi-threaded Topic MDBs
» Use Test Connections on Reserve with Care Cache Prepared and Callable Statements
» Read-only, One-Phase Commit Optimizations JMS Performance Tuning Check List
» Improving Message Processing Performance
» Cache and Re-use Client Resources Tuning Distributed Queues
» Quota Resources Destination-Level Quota
» Defining a Send Timeout on Connection Factories
» Tuning Topics Tuning for Large Messages Setting Maximum Message Size for Network Protocols
» Compressing Messages Oracle Fusion Middleware Online Documentation Library
» How Flow Control Works Configuring Flow Control
» Defining a Message Expiration Policy Configuring an Expiration Policy on Topics
» Configuring an Expiration Policy on Queues Configuring an Expiration Policy on Templates
» Defining an Expiration Logging Policy Expiration Log Output Format
» Best Practices Using UOO and Distributed Destinations Migrating Old Applications to Use UOO
» Messaging Performance Configuration Parameters
» Client-side Thread Pools Best Practices for JMS .NET Client Applications
» Best Practices Changing the Batch Size Changing the Batch Interval
» Changing the Quality of Service Using Multiple Bridge Instances Changing the Thread Pool Size
» Classloading Optimizations for Resource Adapters Connection Optimizations
» Disable Page Checks Use Custom JSP Tags Precompile JSPs
» Managing Session Persistence Session Management
» Thread Management InteractionSpec Interface Pub-Sub Tuning Guidelines
» Setting the Buffering Sessions Releasing Asynchronous Resources
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