Multiversion concurrency control

Multiversion concurrency control (MCC or MVCC), is a concurrency control method commonly used by database management systems to provide concurrent access to the database and in programming languages to implement transactional memory.^[1]

If someone is reading from a database at the same time as someone else is writing to it, it is possible that the reader will see a half-written or inconsistent piece of data. There are several ways of solving this problem, known as concurrency control methods. The simplest way is to make all readers wait until the writer is done, which is known as a lock. This can be very slow, so MVCC takes a different approach: each user connected to the database sees a snapshot of the database at a particular instant in time. Any changes made by a writer will not be seen by other users of the database until the changes have been completed (or, in database terms: until the transaction has been committed.)

When an MVCC database needs to update an item of data, it will not overwrite the old data with new data, but instead marks the old data as obsolete and adds the newer version elsewhere. Thus there are multiple versions stored, but only one is the latest. This allows readers to access the data that was there when they began reading, even if it was modified or deleted part way through by someone else. It also allows the database to avoid the overhead of filling in holes in memory or disk structures but requires (generally) the system to periodically sweep through and delete the old, obsolete data objects. For a document-oriented database it also allows the system to optimize documents by writing entire documents onto contiguous sections of disk—when updated, the entire document can be re-written rather than bits and pieces cut out or maintained in a linked, non-contiguous database structure.

MVCC provides point in time consistent views. Read transactions under MVCC typically use a timestamp or transaction ID to determine what state of the DB to read, and read these versions of the data. Read and write transactions are thus isolated from each other without any need for locking. Writes create a newer version, while concurrent reads access the older version.

Implementation

MVCC uses timestamps (TS), and incrementing transaction IDs, to achieve transactional consistency. MVCC ensures a transaction (T) never has to wait to Read a database object (P) by maintaining several versions of the object. Each version of object P has both a Read Timestamp (RTS) and a Write Timestamp (WTS) which lets a particular transaction T_i read the most recent version of the object which precedes the transaction's Read Timestamp RTS(T_i).

If transaction T_i wants to Write to object P, and there is also another transaction T_k happening to the same object, the Read Timestamp RTS(T_i) must precede the Read Timestamp RTS(T_k), i.e., RTS(T_i) < RTS(T_k), for the object Write Operation (WTS) to succeed. A Write cannot complete if there are other outstanding transactions with an earlier Read Timestamp (RTS) to the same object. Like standing in line at the store, you cannot complete your checkout transaction until those in front of you have completed theirs.

To restate; every object (P) has a Timestamp (TS), however if transaction T_i wants to Write to an object, and the transaction has a Timestamp (TS) that is earlier than the object's current Read Timestamp, TS(T_i) < RTS(P), then the transaction is aborted and restarted. (If you try to cut in line, to check out early, go to the back of that line.) Otherwise, T_i creates a new version of object P and sets the read/write timestamp TS of the new version to the timestamp of the transaction TS=TS(T_i).^[2]

The drawback to this system is the cost of storing multiple versions of objects in the database. On the other hand, reads are never blocked, which can be important for workloads mostly involving reading values from the database. MVCC is particularly adept at implementing true snapshot isolation, something which other methods of concurrency control frequently do either incompletely or with high performance costs.

Examples

Concurrent read-write

At Time = 1, the state of a database could be:

Time	Object 1	Object 2
0	"Foo" by T0	"Bar" by T0
1	"Hello" by T1

T0 wrote Object 1="Foo" and Object 2="Bar". After that T1 wrote Object 1="Hello" leaving Object 2 at its original value. The new value of Object 1 will supersede the value at 0 for all transactions that start after T1 commits at which point version 0 of Object 1 can be garbage collected.

If a long running transaction T2 starts a read operation of Object 2 and Object 1 after T1 committed and there is a concurrent update transaction T3 which deletes Object 2 and adds Object 3="Foo-Bar", the database state will look like at time 2:

Time	Object 1	Object 2	Object 3
0	"Foo" by T0	"Bar" by T0
1	"Hello" by T1
2		(deleted) by T3	"Foo-Bar" by T3

There is a new version as of time 2 of Object 2 which is marked as deleted and a new Object 3. Since T2 and T3 run concurrently T2 sees the version of the database before 2 i.e. before T3 committed writes, as such T2 reads Object 2="Bar" and Object 1="Hello". This is how multiversion concurrency control allows snapshot isolation reads without any locks.

History

Multiversion concurrency control is described in some detail in the 1981 paper "Concurrency Control in Distributed Database Systems"^[3] by Phil Bernstein and Nathan Goodman, then employed by the Computer Corporation of America. Bernstein and Goodman's paper cites a 1978 dissertation^[4] by David P. Reed which quite clearly describes MVCC and claims it as an original work.

The first shipping, commercial database software product featuring MVCC was Digital's VAX Rdb/ELN. The second was InterBase, both of which are still active, commercial products.

Version control systems

Any version control system that has the internal notion of a version (e.g. Subversion, Git, probably almost any current VCS with the notable exception of CVS) will provide explicit MVCC (you only ever access data by its version identifier).

Among the VCSs that don't provide MVCC at the repository level, most still work with the notion of a working copy, which is a file tree checked out from the repository, edited without using the VCS itself and checked in after the edit. This working copy provides MVCC while it is checked out.

References

↑ refs. Clojure. Retrieved on 2013-09-18.
↑ Ramakrishnan, R., & Gehrke, J. (2000). Database management systems. Osborne/McGraw-Hill.
↑ Bernstein, Philip A.; Goodman, Nathan (1981). "Concurrency Control in Distributed Database Systems". ACM Computing Surveys.
↑ Reed, David P. (September 21, 1978). "Naming and Synchronization in a Decentralized Computer System". MIT dissertation.