TechGIG_Memory leaks in_java_webnair_26th_july_2012

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This presentation was presented on techGig 26th July 2012. Talks how we can catch Memory leaks

This presentation was presented on techGig 26th July 2012. Talks how we can catch Memory leaks

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  • 1. Memory Leaks in Java By:- Ashish Bhasin ashbhasin@yahoo.com
  • 2. Agenda • Introduction • Resolving Memory Leaks
  • 3. Then why are we here??? Memory Management is done by Java Introduction
  • 4. Memory Manager – Garbage collector (GC) • A key feature of memory management in Java is its garbage-collected heap – Garbage collector (GC) that comes with Java is a tracing collector, which determines which objects should be preserved in memory by tracing all objects reachable from a set of roots. – These reachable objects survive collections because they may be used in the course of program execution.
  • 5. Memory Manager – Garbage collector (GC)
  • 6. What is Memory Leak in Java ? Note :- When no more memory is remaining, an OutOfMemoryError alert will be thrown and generate an exception like this: Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at
  • 7. 7 What is memory leak in java? (Memory Map) Java Memory leak Allocated Reachable Live Handled by JVM
  • 8. 8 Why Memory Leak is BAD… • Memory-related issues affect execution speed and reliability of application.
  • 9. Causes of memory leaks in Java • The four typical causes of memory leaks in a Java program are: – Unknown or unwanted object references: These objects are no longer needed, but the garbage collector can not reclaim the memory because another object still refers to it. – Long-living (static) objects: These objects stay in the memory for the application's full lifetime. Objects tagged to the session may also have the same lifetime as the session, which is created per user and remains until the user logs out of the application. – Failure to clean up or free native system resources: Native system resources are resources allocated by a function external to Java, typically native code written in C or C++. Java Native Interface (JNI) APIs are used to embed native libraries/code into Java code. – Bugs in the JDK or third-party libraries: Bugs in various versions of the JDK or in the Abstract Window Toolkit and Swing packages can cause memory leaks.
  • 10. Types of Memory Leaks in Objects Lapsed Listener Object added to collection, not removed e.g. event listener, observer collection size can grow without bound iteration over “dead” objects degrades performance Lingerer Reference used transiently by long-term object Reference always reset on next use e.g. associations with menu items e.g. global action or service Limbo Reference pinned by long-running thread references on stack GC doesn’t do local liveness analysis
  • 11. Lapsed Listener – An Example (1/2) • Listeners are commonly used to specify event handlers for events that occur to the object. Some commonly used event types are: – GUI events: listener classes implementing java.util.EventListener interface for GUI events in AWT, Swing, and other GUI libraries. – Database connection events; listeners implement ConnectionEventListener interface in javax.sql. Note :- • The listener pattern, a specific class of the observer pattern, consists of a subject and an observer. • The listener pattern is widespread, it is error-prone and may cause memory leaks if not used properly.
  • 12. • Listener registration: object.addMyListener(n ewMyListener(...)); • unregistering the listener and allowing object to be garbage- collected.object.remov eMyListener(l); A typical large-scale application with a GUI and a database back end may use dozens of different types of listeners, all of which have to be unregistered to avoid memory leaks. Lapsed Listener – An Example (2/2)
  • 13. We will see how to catch Memory leaks Oops, Java has memory leaks Resolving Memory Leaks
  • 14. Resolving Memory Leaks • What to look in your program – Is My Program actually leaking Memory – Monitoring Process – Dump the heap – Analyze the heap
  • 15. Note • FIG 1 :- The graph below shows the memory usage in a healthy Java application that does not suffer from memory leaks, with the peak load occurring around 10 AM and application usage drastically decreasing at 5 PM. Naturally, the peak load on business applications often correlates with normal business hours. • FIG 2 :- let's suppose that we have a memory leak in the application. The primary characteristic of memory leaks is that memory requirements increase as a function of time, not as a function of the load. Let's see how the application would look after running for a few days with a memory leak and the same peak user loads reached around 10 AM every day: • There is one special case that should be noted here: a program that needs to be restarted periodically in order to prevent it from crashing with an OutOfMemoryError alert. Is My Program Leaking Memory?
  • 16. Monitoring Memory Leaks - Verbose GC log Monitoring using GC which shows that we might have leak in the program
  • 17. Monitoring Java Process
  • 18. Dump the Heap • Note – Before you dump heap, be sure to keep the following issues in mind: • Programs in the JVM should be paused for the duration of the heap dump, • Heap dumps are saved on disk, and the files might be fairly large.
  • 19. Tools to Analyze Heap Dump Fast leak Slow leak
  • 20. Analyzing the Heap Dump for Fast Memory Leaks • Analyzing the heap dump is done in order to: – Find objects that are "leaking" – Find the root cause of the memory leak
  • 21. Slow and Small Memory Leaks
  • 22. Profiling
  • 23. Profiling • What is Profiling? • What Profiling Tells You • What Profiling Is Not • Manual Profiling • Profiling Techniques Overview – Insertion – Sampling – Instrumented VM
  • 24. What is Profiling? • Profiling is measuring an application, specifically: – where is the time being spent? • This is “classical” profiling • which method takes the most time? • which method is called the most? – how is memory being used? • what kind of objects are being created? • this in especially applicable in OO, GC’ed environments
  • 25. What Profiling Tells You • Basic information: – How much time is spent in each method? (“flat” profiling) – How many objects of each type are allocated?
  • 26. What Profiling Tells You • Beyond the basics: – Program flow (“hierarchical” profiling) • do calls to method A cause method B to take too much time? – Per-line information • which line(s) in a given method are the most expensive? • Which methods created which objects? – Visualization aspects • Is it easy to use the profiler to get to the information you’re interested in?
  • 27. What Profiling Is Not • Profiling is measuring performance statistics on your particular application – regardless of the underlying platform • Benchmarking is measuring the performance of a particular platform – not a specific application • Optimization is an automatic technique that applies generic enhancements to speed up code – regardless of the application or platform
  • 28. Optimization • Even though optimization isn’t always enough, it’s a good place to start • Java is designed to be optimized by the JVM, not by the compiler – even though there are optimizing compilers • JIT compilers help • Sun’s next-generation JVM, HotSpot, offers: – generational garbage collection – improved, profiling native compiler
  • 29. Manual Profiling • You don’t absolutely need to have a profiling tool to profile your code… you could – build your own profiling tool • see Dr. Dobb’s Journal, March 1998 • Or Dr. Dobbs, Sept. 1999 – use very simple code-insertion techniques • System.out.println(System.getCurrentTimeMillis());
  • 30. Profiling Techniques Overview • Commercial profilers use one of three techniques for profiling programs: – insertion – sampling – instrumented virtual machine • Why is it important to understand how a profiler works? – each different technique has its own pros & cons – different profilers may give different results
  • 31. Insertion • Multiple flavours: – Source code insertion • profiling code goes in with the source • easy to do – Object code insertion • profiling code goes into the .o (C++) or .class (Java) files • can be done statically or dynamically • hard to do – modified class loader
  • 32. Insertion Pros & Cons • Insertion Pros: – can be used across a variety of platforms – accurate (in some ways) • can’t easily do memory profiling • Insertion Cons: – requires recompilation or relinking of the app – profiling code may affect performance • difficult to calculate exact impact
  • 33. Sampling • In sampling, the processor or VM is monitored and at regular intervals an interrupt executes and saves a “snapshot” of the processor state • This data is then compared with the program’s layout in memory to get an idea of where the program was at each sample
  • 34. Sampling Pros & Cons • Sampling Pros: – no modification of app is necessary • Sampling Cons: – a definite time/accuracy trade-off • a high sample rate is accurate, but takes a lot of time – more…
  • 35. Sampling Pros & Cons • Sampling Cons: – very small methods will almost always be missed • if a small method is called frequently and you have are unlucky, small but expensive methods may never show up – sampling cannot easily monitor memory usage
  • 36. Instrumented VM • Another way to collect information is to instrument the Java VM • Using this technique each and every VM instruction can be monitored – highly accurate
  • 37. Instrumented VM Pros&Cons • Pros: – The most accurate technique – Can monitor memory usage data as well as time data – Can easily be extended to allow remote profiling • Cons: – The instrumented VM is platform- specific
  • 38. Instrumented VMs • Java 2 (JDK 1.2 and higher) – information can be accessed through JVMPI – the Java Virtual Machine Profiling Interface • http://java.sun.com/products/jdk/1.3/docs/guide/jvmpi / • Microsoft JVM – uses a COM-based interface to provide profiling information • JProbe Profiler
  • 39. Common Bottlenecks • Although profiling can yield some surprises, often the bottlenecks are fairly obvious once the profiler points them out – excessive heap expansion – not using System.arraycopy() – using the “+” operator with String objects – using unbuffered I/O streams – excessive memory allocations – excessive calls to slow library methods
  • 40. Demo Time