What is Copy-on-write?

Copy-on-write
     Copy-on-write (sometimes referred to as "COW") is an optimization strategy used in computer programming. The fundamental idea is that if multiple callers ask for resources which are initially indistinguishable, you can give them pointers to the same resource. This function can be maintained until a caller tries to modify its "copy" of the resource, at which point a true private copy is created to prevent the changes becoming visible to everyone else. All of this happens transparently to the callers. The primary advantage is that if a caller never makes any modifications, no private copy need ever be created.

 

Copy-on-write in virtual memory
     Copy-on-write finds its main use in virtual memory operating systems; when a process creates a copy of itself, the pages in memory that might be modified by either the process or its copy are marked copy-on-write. When one process modifies the memory, the operating system's kernel intercepts the operation and copies the memory so that changes in one process's memory are not visible to the other.
     Another use is in the calloc function. This can be implemented by having a page of physical memory filled with zeroes. When the memory is allocated, the pages returned all refer to the page of zeroes and are all marked as copy-on-write. This way, the amount of physical memory allocated for the process does not increase until data is written. This is typically only done for larger allocations.
     Copy-on-write can be implemented by telling the MMU that certain pages in the process's address space are read-only. When data is written to these pages, the MMU raises an exception which is handled by the kernel, which allocates new space in physical memory and makes the page being written to correspond to that new location in physical memory.
     One major advantage of COW is the ability to use memory sparsely. Because the usage of physical memory only increases as data is stored in it, very efficient hash tables can be implemented which only use little more physical memory than is necessary to store the objects they contain. However, such programs run the risk of running out of virtual address space -- virtual pages unused by the hash table cannot be used by other parts of the program. The main problem with COW at the kernel level is the complexity it adds, but the concerns are similar to those raised by more basic virtual memory concerns such as swapping pages to disk; when the kernel writes to pages, it must copy them if they are marked copy-on-write.

     

Other applications of copy-on-write
     COW is also used outside the kernel, in library, application and system code. The string class provided by the C++ standard library, for example, was specifically designed to allow copy-on-write implementations. One hazard of COW in these contexts arises in multithreaded code, where the additional locking required for objects in different threads to safely share the same representation can easily outweigh the benefits of the approach.
     The COW concept is also used in virtualization/emulation software such as Bochs, QEMU, and UML for virtual disk storage. This allows a great reduction in required disk space when multiple VMs can be based on the same hard disk image, as well as increased performance as disk reads can be cached in RAM and subsequent reads served to other VMs out of the cache.
     The COW concept is also used in maintenance of instant snapshot on database servers like Microsoft SQL Server 2005. Instant snapshots preserve a static view of a database by storing a pre-modification copy of data when underlaying data are updated. Instant snapshots are used for testing uses or moment-dependent reports and should not be used to replace backups.
     COW may also be used as the underlying mechanism for snapshots provided by logical volume management and Microsoft Volume Shadow Copy Service.
     The copy-on-write technique can be used to emulate a read-write storage on media that require wear levelling or are physically Write Once Read Many.