Dont Tune What You Dont Need to Tune
1.8 Dont Tune What You Dont Need to Tune
The most efficient tuning you can do is not to alter what works well. As they say, If it aint broke, dont fix it. This may seem obvious, but the temptation to tweak something just because you have thought of an improvement has a tendency to override this obvious statement. The second most efficient tuning is to discard work that doesnt need doing. It is not at all uncommon for an application to be started with one set of specifications and to have some of the specifications change over time. Many times the initial specifications are much more generic than the final product. However, the earlier generic specifications often still have their stamps in the application. I frequently find routines, variables, objects, and subsystems that are still being maintained but are never used and never will be used, since some critical aspect of these resources is no longer supported. These redundant parts of the application can usually be chopped without any bad consequences, often resulting in a performance gain. In general, you need to ask yourself exactly what the application is doing and why. Then question whether it needs to do it in that way, or even if it needs to do it at all. If you have third-party products and tools being used by the application, consider exactly what they are doing. Try to be aware of the main resources they use from their documentation. For example, a zippy DLL shared library that is speeding up all your network transfers is using some resources to achieve that speedup. You should know that it is allocating larger and larger buffers before you start trying to hunt down the source of your mysteriously disappearing memory. Then you can realize that you need to use the more complicated interface to the DLL that restricts resource usage, rather than a simple and convenient interface. And you will have realized this before doing extensive and useless object profiling, because you would have been trying to determine why your application is being a memory hog. When benchmarking third-party components, you need to apply a good simulation of exactly how you will use those products. Determine characteristics from your benchmarks and put the numbers into your overall model to determine if performance can be reached. Be aware that vendor benchmarks are typically useless for a particular application. Break your application down into a hugely simplified version for a preliminary benchmark implementation to test third-party components. You should make a strong attempt to include all the scaling necessary so that you are benchmarking a fully scaled usage of the components, not some reduced version that will reveal little about the components in full use. - 20 -1.9 Performance Checklist
Parts
» OReilly.Java.performance tuning
» The Tuning Game System Limitations and What to Tune
» A Tuning Strategy Introduction
» Threading to Appear Quicker Streaming to Appear Quicker
» User Agreements Starting to Tune
» Setting Benchmarks Starting to Tune
» The Benchmark Harness Starting to Tune
» Taking Measurements Starting to Tune
» What to Measure Introduction
» Dont Tune What You Dont Need to Tune
» Measurements and Timings Profiling Tools
» Garbage Collection Profiling Tools
» Profiling Methodology Method Calls
» Java 2 cpu=samples Profile Output
» HotSpot and 1.3 -Xprof Profile Output
» JDK 1.1.x -prof and Java 2 cpu=old Profile Output
» Object-Creation Profiling Profiling Tools
» Monitoring Gross Memory Usage
» Replacing Sockets ClientServer Communications
» Performance Checklist Profiling Tools
» Garbage Collection Underlying JDK Improvements
» Replacing JDK Classes Underlying JDK Improvements
» VM Speed Variations VMs with JIT Compilers
» Other VM Optimizations Faster VMs
» Inline calls Remove dynamic type checks Unroll loops Code motion
» Literal constants are folded String concatenation is sometimes folded Constant fields are inlined
» Optimizations Performed When Using the -O Option
» Performance Effects From Runtime Options
» Compile to Native Machine Code
» Native Method Calls Underlying JDK Improvements
» Uncompressed ZIPJAR Files Underlying JDK Improvements
» Performance Checklist Underlying JDK Improvements
» Object-Creation Statistics Object Creation
» Pool Management Object Reuse
» Reusable Parameters Object Reuse
» String canonicalization Changeable objects
» Weak references Canonicalizing Objects
» Avoiding Garbage Collection Object Creation
» Preallocating Objects Lazy Initialization
» Performance Checklist Object Creation
» The Performance Effects of Strings
» Compile-Time Versus Runtime Resolution of Strings
» Converting bytes, shorts, chars, and booleans to Strings Converting floats to Strings
» Converting doubles to Strings
» Converting Objects to Strings
» Word-Counting Example Strings Versus char Arrays
» Line Filter Example HotSpot 1.0
» String Comparisons and Searches
» Sorting Internationalized Strings Strings
» The Cost of try-catch Blocks Without an Exception
» The Cost of try-catch Blocks with an Exception
» Using Exceptions Without the Stack Trace Overhead Conditional Error Checking
» no JIT 1.3 Variables Strings
» Method Parameters Performance Checklist
» Exception-Terminated Loops Loops and Switches
» no JIT 1.3 Loops and Switches
» Recursion Loops and Switches
» no HotSpot 1.0 2nd Loops and Switches
» Recursion and Stacks Loops and Switches
» Performance Checklist Loops and Switches
» Replacing System.out IO, Logging, and Console Output
» Logging From Raw IO to Smokin IO
» no JIT HotSpot 1.0 no JIT HotSpot 1.0 Serialization
» no IO, Logging, and Console Output
» Clustering Objects and Counting IO Operations
» Compression IO, Logging, and Console Output
» Performance Checklist IO, Logging, and Console Output
» Avoiding Unnecessary Sorting Overhead
» An Efficient Sorting Framework
» no HotSpot Better Than Onlogn Sorting
» User-Interface Thread and Other Threads
» Desynchronization and Synchronized Wrappers
» Avoiding Serialized Execution HotSpot 1.0
» no JIT no JIT HotSpot 1.0 Timing Multithreaded Tests
» Atomic Access and Assignment
» Free Load Balancing from TCPIP
» Load-Balancing Classes Load Balancing
» A Load-Balancing Example Load Balancing
» Threaded Problem-Solving Strategies Threading
» Collections Appropriate Data Structures and Algorithms
» Java 2 Collections Appropriate Data Structures and Algorithms
» Hashtables and HashMaps Appropriate Data Structures and Algorithms
» Cached Access Appropriate Data Structures and Algorithms
» Caching Example I Appropriate Data Structures and Algorithms
» Caching Example II Appropriate Data Structures and Algorithms
» Finding the Index for Partially Matched Strings
» Search Trees Appropriate Data Structures and Algorithms
» Comparing Communication Layers Distributed Computing
» Batching I Application Partitioning
» Compression Caching Low-Level Communication Optimizations
» Transfer Batching Low-Level Communication Optimizations
» Batching II Distributed Garbage Collection
» Performance Checklist Distributed Computing
» When Not to Optimize Tuning Class Libraries and Beans
» Scaling Design and Architecture
» Distributed Applications Design and Architecture
» Object Design Design and Architecture
» Use simulations and benchmarks Consider the total work done and the design overhead
» Tuning After Deployment When to Optimize
» User Interface Usability Training Server Downtime
» Performance Checklist When to Optimize
» Clustering Files Cached Filesystems RAM Disks, tmpfs, cachefs
» Disk Fragmentation Disk Sweet Spots
» RAM Underlying Operating System and Network Improvements
» Network Bottlenecks Network IO
» Performance Checklist Underlying Operating System and Network Improvements
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