What are the disadvantages in using Garbage Collection? [closed]

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Most of the modern languages have built in garbage collection (GC). e.g. Java, .NET languages, Ruby, etc. Indeed GC simplifies application development in many ways.

I am interested to know the limitations / disadvantages of writing applications in GCed languages. Assuming GC implemenation is optimal, I am just wondering we may be limited by GC to take some o开发者_开发百科ptimization decisions.

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The main disadvantages to using a garbage collector, in my opinion, are:

1. Non-deterministic cleanup of resources. Sometimes, it is handy to say "I'm done with this, and I want it cleaned NOW". With a GC, this typically means forcing the GC to cleanup everything, or just wait until it's ready - both of which take away some control from you as a developer.

2. Potential performance issues which arise from non-deterministic operation of the GC. When the GC collects, it's common to see (small) hangs, etc. This can be particularly problematic for things such as real-time simulations or games.

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Take it from a C programmer ... it is about cost/benefit and appropriate use

The garbage collection algorithms such as tri-color/mark-and-sweep there is often significant latency between a resource being 'lost' and the physical resource being freed. In some runtimes the GC will actually pause execution of the program to perform garbage collection.

Being a long time C programmer, I can tell you:

a) Manual free() garbage collection is hard -- This is because there is usually a greater error rate in human placement of free() calls than GC algorithms.

b) Manual free() garbage collection costs time -- Does the time spent debugging outweigh the millisecond pauses of a GC? It may be beneficial to use garbage collection if you are writing a game than say an embedded kernel.

But, when you can't afford the runtime disadvantage (right resources, real-time constraints) then performing manual resource allocation is probably better. It may take time but can be 100% efficient.

Try and imagine an OS kernel written in Java? or on the .NET runtime with GC ... Just look at how much memory the JVM accumulates when running simple programs. I am aware that projects exist like this ... they just make me feel a bit sick.

Just bear in mind, my linux box does much the same things today with 3GB RAM than it did when it had 512MB ram years ago. The only difference is I have mono/jvm/firefox etc running. The business case for GC is clear, but it still makes me uncomfortable alot of the time.

Good books:

Dragon book (recent edition), Modern Compiler Implementation in C

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For .NET, there are two disadvantages that I can see.

1) People assume that the GC knows best, but that's not always the case. If you make certain types of allocations, you can cause yourself to experience some really nasty program deaths without direct invokation of the GC.

2) Objects larger than 85k go onto the LOH, or Large Object Heap. That heap is currently NEVER compacted, so again, your program can experience out-of-memory exceptions when really the LOH is not compacted enough for you to make another allocation.

Both of these bugs are shown in code that I posted in this question:

How do I get .NET to garbage collect aggressively?

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I am interested to know the limitations / disadvantages of writing applications in GCed languages. Assuming GC implemenation is optimal, I am just wondering we may be limited by GC to take some optimization decisions.

My belief is that automatic memory management imposes a glass ceiling on efficiency but I have no evidence to substantiate that. In particular, today's GC algorithms offer only high throughput or low latency but not both simultaneously. Production systems like .NET and the HotSpot JVM incur significant pauses precisely because they are optimized for throughput. Specialized GC algorithms like Staccato offer much lower latency but at the cost of much lower minimum mutator utilisation and, therefore, low throughput.

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If you are confident(good) about your memory management skills, there is no advantage.

The concept was introduced to minimize the time of development and due to lack of experts in programming who thoroughly understood memory.

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The biggest problem when it comes to performance (especially on or real-time systems) is, that your program may experience some unexpected delays when GC kicks in. However, modern GC try to avoid this and can be tuned for real time purposes.

Another obvious thing is that you cannot manage your memory by yourself (for instance, allocate on numa local memory), which you may need to do when you implement low-level software.

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It is almost impossible to make a non-GC memory manager work in a multi-CPU environment without requiring a lock to be acquired and released every time memory is allocated or freed. Each lock acquisition or release will require a CPU to coordinate its actions with other CPUs, and such coordination tends to be rather expensive. A garbage-collection-based system can allow many memory allocations to occur without requiring any locks or other inter-CPU coordination. This is a major advantage. The disadvantage is that many steps in garbage collection require that the CPU's coordinate their actions, and getting good performance generally requires that such steps be consolidated to a significant degree (there's not much benefit to eliminating the requirement of CPU coordination on each memory allocation if the CPUs have to coordinate before each step of garbage collection). Such consolidation will often cause all tasks in the system to pause for varying lengths of time during collection; in general, the longer the pauses one is willing to accept, the less total time will be needed for collection.

If processors were to return to a descriptor-based handle/pointer system (similar to what the 80286 used, though nowadays one wouldn't use 16-bit segments anymore), it would be possible for garbage collection to be done concurrently with other operations (if a handle was being used when the GC wanted to move it, the task using the handle would have to be frozen while the data was copied from its old address to its new one, but that shouldn't take long). Not sure if that will ever happen, though (Incidentally, if I had my druthers, an object reference would be 32 bits, and a pointer would be an object reference plus a 32-bit offset; I think it will be awhile before there's a need for over 2 billion objects, or for any object over 4 gigs. Despite Moore's Law, if an application would have over 2 billion objects, its performance would likely be improved by using fewer, larger, objects. If an application would need an object over 4 gigs, its performance would likely be improved by using more, smaller, objects.)

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Typically, garbage collection has certain disadvantages:

• Garbage collection consumes computing resources in deciding what memory is to be freed, reconstructing facts that may have been known to the programmer. The penalty for the convenience of not annotating object lifetime manually in the source code is overhead, often leading to decreased or uneven performance. Interaction with memory hierarchy effects can make this overhead intolerable in circumstances that are hard to predict or to detect in routine testing.
• The point when the garbage is actually collected can be unpredictable, resulting in stalls scattered throughout a session. Unpredictable stalls can be unacceptable in real-time environments such as device drivers, in transaction processing, or in interactive programs.
• Memory may leak despite the presence of a garbage collector, if references to unused objects are not themselves manually disposed of. This is described as a logical memory leak.[3] For example, recursive algorithms normally delay release of stack objects until after the final call has completed. Caching and memoizing, common optimization techniques, commonly lead to such logical leaks. The belief that garbage collection eliminates all leaks leads many programmers not to guard against creating such leaks.
• In virtual memory environments typical of modern desktop computers, it can be difficult for the garbage collector to notice when collection is needed, resulting in large amounts of accumulated garbage, a long, disruptive collection phase, and other programs' data swapped out.
• Perhaps the most significant problem is that programs that rely on garbage collectors often exhibit poor locality (interacting badly with cache and virtual memory systems), occupy more address space than the program actually uses at any one time, and touch otherwise idle pages. These may combine in a phenomenon called thrashing, in which a program spends more time copying data between various grades of storage than performing useful work. They may make it impossible for a programmer to reason about the performance effects of design choices, making performance tuning difficult. They can lead garbage-collecting programs to interfere with other programs competing for resources