String canonicalization Changeable objects
4.2.4.1 String canonicalization
There can be some confusion about whether String s are already canonicalized. There is no guarantee that they are, although the compiler can canonicalize String s that are equal and are compiled in the same pass. The String.intern method canonicalizes strings in an internal table. This is supposed to be, and usually is, the same table used by strings canonicalized at compile time, but in some earlier JDK versions e.g., 1.0, it was not the same table. In any case, there is no particular reason to use the internal string table to canonicalize your strings unless you want to compare String s by identity see Section 5.5 . Using your own table gives you more control and allows you to inspect the table when necessary. To see the difference between identity and equality comparisons for String s, including the difference that String.intern makes, you can run the following class: public class Test { public static void mainString[] args { System.out.printlnargs[0]; see that we have the empty string should be true System.out.printlnargs[0].equals; should be false since they are not identical objects System.out.printlnargs[0] == ; should be true unless there are two internal string tables System.out.printlnargs[0].intern == ; } } This Test class, when run with the command line: java Test gives the output: true false true4.2.4.2 Changeable objects
Canonicalizing objects is best for read-only objects and can be troublesome for objects that change. If you canonicalize a changeable object and then change its state, then all objects that have a reference to the canonicalized object are still pointing to that object, but with the objects new state. For example, suppose you canonicalize a special Date value. If that object has its date value changed, all objects pointing to that Date object now see a different date value. This result may be desired, but more often it is a bug. If you want to canonicalize changeable objects, one technique to make it slightly safer is to wrap the object with another one, or use your own subclass. [5] Then all accesses and updates are controlled - 87 - by you. If the object is not supposed to be changed, you can throw an exception on any update method. Alternatively, if you want some objects to be canonicalized but with copy-on-write behavior, you can allow the updater to return a noncanonicalized copy of the canonical object. [5] Beware that using a subclass may break the superclass semantics. Note that it makes no sense to build a table of millions or even thousands of strings or other objects if the time taken to test for, access, and update objects in the table is longer than the time you are saving canonicalizing them.4.2.4.3 Weak references
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
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» Java 2 cpu=samples Profile Output
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» Optimizations Performed When Using the -O Option
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» 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
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» 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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