The Cost of try-catch Blocks Without an Exception
6.1 Exceptions
In this section, we examine the cost of exceptions and consider ways to avoid that cost. First, we look at the costs associated with try-catch blocks, which are the structures you need to handle exceptions. Then, we go on to optimizing the use of exceptions.6.1.1 The Cost of try-catch Blocks Without an Exception
try-catch blocks generally use no extra time if no exception is thrown, although some VMs may impose a slight penalty. The following test determines whether a VM imposes any significant overhead for try-catch blocks when the catch block is not entered. The test runs the same code twice, once with the try-catch entered for every loop iteration and again with just one try-catch wrapping the loop. Because were testing the VM and not the compiler, you must ensure that your compiler has not optimized the test away; use an old JDK version to compile it if necessary. To determine that the test has not been optimized away by the compiler, you need to compile the code, then decompile it: package tuning.exception; public class TryCatchTimeTest { public static void mainString[] args { int REPEAT = args.length == 0 ? 10000000 : Integer.parseIntargs[0]; Object[] xyz = {new Integer3, new Integer10101, new Integer67}; boolean res; long time = System.currentTimeMillis ; res = try_catch_in_loopREPEAT, xyz; System.out.printlntry catch in loop took + System.currentTimeMillis - time; time = System.currentTimeMillis ; res = try_catch_not_in_loopREPEAT, xyz; System.out.printlntry catch not in loop took + System.currentTimeMillis - time; Repeat the two tests several more times in this method for consistency checking ... } public static boolean try_catch_not_in_loopint repeat, Object[] o { Integer i[] = new Integer[3]; try { for int j = repeat; j 0; j-- { i[0] = Integer o[j+12]; i[1] = Integer o[j2]; i[2] = Integer o[j+22]; } return false; } catch Exception e {return true;} } - 136 - public static boolean try_catch_in_loopint repeat, Object[] o { Integer i[] = new Integer[3]; for int j = repeat; j 0; j-- { try { i[0] = Integer o[j+12]; i[1] = Integer o[j2]; i[2] = Integer o[j+22]; } catch Exception e {return true;} } return false; } } Running this test in various VMs results in a 10 increase in the time taken by the looped try- catch test relative to the nonlooped test for some VMs. See Table 6-1 . Table 6-1, Extra Cost of the Looped try-catch Test Relative to the Nonlooped try-catch Test VM 1.2 1.2 no JIT 1.3 HotSpot1.0 1.1.6
Increase in time ~10 None ~10 ~10 None6.1.2 The Cost of try-catch Blocks with an Exception
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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