Atomicity (database systems)
In database systems, atomicity (or atomicness; from Greek atomos, undividable) is one of the ACID transaction properties. An atomic transaction is an indivisible and irreducible series of database operations such that either all occur, or nothing occurs.[1] A guarantee of atomicity prevents updates to the database occurring only partially, which can cause greater problems than rejecting the whole series outright. As a consequence, the transaction cannot be observed to be in progress by another database client. At one moment in time, it has not yet happened, and at the next it has already occurred in whole (or nothing happened if the transaction was cancelled in progress).
An example of an atomic transaction is a monetary transfer from bank account A to account B. It consists of two operations, withdrawing the money from account A and saving it to account B. Performing these operations in an atomic transaction ensures that the database remains in a consistent state, that is, money is not lost nor created if either of those two operations fail.[2]
Orthogonality
Atomicity does not behave completely orthogonally with regard to the other ACID properties of the transactions. For example, isolation relies on atomicity to roll back changes in the event of isolation failures such as deadlock; consistency also relies on rollback in the event of a consistency-violation by an illegal transaction. Finally, atomicity itself relies on durability to ensure the atomicity of transactions even in the face of external failures.
As a result of this, failure to detect errors and roll back the enclosing transaction may cause failures of isolation and consistency.
Implementation
Typically, systems implement Atomicity by providing some mechanism to indicate which transactions have started and which finished; or by keeping a copy of the data before any changes occurred (read-copy-update). Several filesystems have developed methods for avoiding the need to keep multiple copies of data, using journaling (see journaling file system). Databases usually implement this using some form of logging/journaling to track changes. The system synchronizes the logs (often the metadata) as necessary once the actual changes have successfully taken place. Afterwards, crash recovery simply ignores incomplete entries. Although implementations vary depending on factors such as concurrency issues, the principle of atomicity — i.e. complete success or complete failure — remain.
Ultimately, any application-level implementation relies on operating-system functionality. At the file-system level, POSIX-compliant systems provide system calls such as open(2)
and flock(2)
that allow applications to atomically open or lock a file. At the process level, POSIX Threads provide adequate synchronization primitives.
The hardware level requires atomic operations such as Test-and-set, Fetch-and-add, Compare-and-swap, or Load-Link/Store-Conditional, together with memory barriers. Portable operating systems cannot simply block interrupts to implement synchronization, since hardware that lacks actual concurrent execution such as hyper-threading or multi-processing is now extremely rare.
In NoSQL data stores with eventual consistency, the atomicity is also weaker specified than in relational database systems, and exists only in rows (i.e. column families).[3]
See also
References
- ↑ "atomic operation". http://www.webopedia.com/: Webopedia. Retrieved 2011-03-23.
An operation during which a processor can simultaneously read a location and write it in the same bus operation. This prevents any other processor or I/O device from writing or reading memory until the operation is complete.
- ↑ Amsterdam, Jonathan. "Atomic File Transactions, Part 1 - O'Reilly Media". archive.oreilly.com. Retrieved 2016-02-28.
- ↑ Olivier Mallassi (2010-06-09). "Let's play with Cassandra… (Part 1/3)". http://blog.octo.com/en/: OCTO Talks!. Retrieved 2011-03-23.
Atomicity is also weaker than what we are used to in the relational world. Cassandra guarantees atomicity within a
ColumnFamily
so for all the columns of a row.