Introduction to Concurrency

What is concurrency?

Concurrency in terms of databases means allowing multiple users to access the data contained within a database at the same time. If concurrent access is not managed by the Database Management System (DBMS) so that simultaneous operations don't interfere with one another problems can occur when various transactions interleave, resulting in an inconsistent database.

Concurrency is achieved by the DBMS, which interleaves actions (reads/writes of DB objects) of various transactions. Each transaction must leave the database in a consistent state if the DB is consistent when the transaction begins. Concurrent execution of user programs is essential for good DBMS performance. Because disk accesses are frequent, and relatively slow, it is important to keep the CPU humming by working on several user programs concurrently. Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared

while account balance is being computed. DBM pretend they are using a single-user system.

Purpose of Concurrency Control

o To enforce Isolation (through mutual exclusion) among conflicting transactions. o To preserve database consistency through consistency preserving execution of

transactions.

o  To resolve read-write and write-write conflicts.

Example: In concurrent execution environment if T1 conflicts with T2 over a data item A, then the existing concurrency control decides if T1 or T2 should get the A and if the other transaction is rolled-back or waits.

Timestamp based concurrency control algorithm

Timestamp

A monotonically increasing variable (integer) indicating the age of an operation or a transaction. A larger timestamp value indicates a more recent event or operation.

Timestamp based algorithm uses timestamp to serialize the execution of concurrent transactions.

Basic Timestamp Ordering

1.  Transaction T issues a write_item(X) operation:

If read_TS(X) > TS(T) or if write_TS(X) > TS(T), then an younger transaction has already read the data item so abort and roll-back T and reject the operation.

If the condition in part (a) does not exist, then execute write_item(X) of T and set write_TS(X) to TS(T).

2.  Transaction T issues a read_item(X) operation:

If write_TS(X) > TS(T), then an younger transaction has already written to the data item so abort and roll-back T and reject the operation.

If write_TS(X)  TS(T), then execute read_item(X) of T and set read_TS(X) to the larger of TS(T) and the current read_TS(X).

Strict Timestamp Ordering

1.  Transaction T issues a write_item(X) operation:

If TS(T) > read_TS(X), then delay T read X has terminated (committed or aborted).

2.  Transaction T issues a read_item(X) operation:

If TS(T) > write_TS(X), then delay T until the transaction read X has terminated (committed or aborted).

Multiversion concurrency control techniques

o       This approach maintains a number of versions of a data item and allocates the right version to a read operation of a transaction. Thus unlike other mechanisms a read operation in this mechanism is never rejected.

o       Side effect:

§     Significantly more storage (RAM and disk) is required to maintain multiple versions. To check unlimited growth of versions, a garbage collection is run when some criteria is satisfiedThis approach maintains a number of versions of a data item and allocates the right version to a read operation of a transaction.

^§        Thus unlike other mechanisms a read operation in this mechanism is never rejected.

Multiversion technique based on timestamp ordering

Assume X1, X2, …, Xn are the version of a transactions. With each Xi a read_TS (read timestamp) and a write_TS (write

timestamp) are associated.

read_TS(Xi): The read timestamp of Xi is the largest of all the timestamps of transactions that have successfully read version Xi.

write_TS(Xi):  The write timestamp of Xi that wrote the value of version Xi.

A new version of Xi is created only by a write operation.

To ensure serializability, the following two rules are used.

1. . If transaction T issues write_item (X) and version i of X has the highest write_TS(Xi) of all versions of X that is also less than or equal to TS(T), and read _TS(Xi) > TS(T), then abort and roll-back T; otherwise create a new version Xi and read_TS(X) = write_TS(Xj) = TS(T).

2. If transaction T issues read_item (X), find the version i of X that has the highest write_TS(Xi) of all versions of X that is also less than or equal to TS(T), then return the value of Xi to T, and set the value of read _TS(Xi) to the largest of TS(T) and the current read_TS(Xi).

Rule 2 guarantees that a read will never be rejected.

Multiversion Two-Phase Locking Using Certify Locks

Concept

o       Allow a transactionX whileT’ it toiswritereadlockedby a data conflicting transaction T

o       This is accomplished by maintaining two versions of each data item X where one version must always have been written by some committed transaction. This

means a write operation always creates a new version of X. Multiversion Two-Phase Locking Using Certify Locks

ⁿ        Steps

1.     X is the committed version of a data item.

2.     T creates a second version X’ after obt

3.     Other transactions continue to read X.

4. T is ready to commit so it obtains a certify lock on X’.

5.     The committed version X becomes X’.

6.     T releases its certify lock on X’, which

Compatibility tables for basic 2pl and 2pl with certify locks:-

Note:

In multiversion 2PL read and write operations from conflicting transactions can be processed concurrently.

This improves concurrency but it may delay transaction commit because of obtaining certify locks on all its writes. It avoids cascading abort but like strict two phase locking scheme conflicting transactions may get deadlocked.

Validation (Optimistic) Concurrency Control Schemes

In this technique only at the time of commit serializability is checked and transactions are aborted in case of non-serializable schedules.

Three phases:

1.     Read phase

2.     Validation phase

3.     Write phase

1. Read phase:

A transaction can read values of committed data items. However, updates are applied only to local copies (versions) of the data items (in database cache).

2.Validation phase: Serializability is checked before transactions write their updates to the database.

o       This phase for Ti checks that, for each transaction Tj that is either committed or is in its validation phase, one of the following conditions holds:

^§        Tj completes its write phase before Ti starts its read phase.

^§        Ti starts its write phase after Tj completes its write phase, and the read_set of Ti has no items in common with the write_set of Tj

^§        Both the read_set and write_set of Ti have no items in common with the write_set of Tj, and Tj completes its read phase.

^§        When validating Ti, the first condition is checked first for each transaction Tj, since (1) is the simplest condition to check. If (1) is false then (2) is checked and if (2) is false then (3 ) is checked. If none of these conditions holds, the validation fails and Ti is aborted.

3.Write phase: On a successful validation transacti otherwise, transactions are restarted.