Chapter: Fundamentals of Database Systems - Transaction Processing, Concurrency Control, and Recovery - Concurrency Control Techniques

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Concurrency Control Techniques

In this chapter we discuss a number of concurrency control techniques that are used to ensure the noninterference or isolation property of concurrently executing transactions.

Chapter 22

Concurrency Control Techniques


 

In this chapter we discuss a number of concurrency control techniques that are used to ensure the noninterference or isolation property of concurrently executing transactions. Most of these techniques ensure serializability of schedules—which we defined in Section 21.5—using concurrency control protocols (sets of rules) that guarantee serializability. One important set of protocols—known as two-phase locking protocols— employ the technique of locking data items to prevent multiple transactions from accessing the items concurrently; a number of locking protocols are described in Sections 22.1 and 22.3.2. Locking protocols are used in most commercial DBMSs. Another set of concurrency control protocols use timestamps. A timestamp is a unique identifier for each transaction, generated by the system. Timestamps values are generated in the same order as the transaction start times. Concurrency control protocols that use timestamp ordering to ensure serializability are introduced in Section 22.2. In Section 22.3 we discuss multiversion concurrency control protocols that use multiple versions of a data item. One multiversion protocol extends timestamp order to multiversion timestamp ordering (Section 22.3.1), and another extends two-phase locking (Section 22.3.2). In Section 22.4 we present a protocol based on the concept of validation or certification of a transaction after it executes its operations; these are sometimes called optimistic protocols, and also assume that multiple versions of a data item can exist.

 

Another factor that affects concurrency control is the granularity of the data items—that is, what portion of the database a data item represents. An item can be as small as a single attribute (field) value or as large as a disk block, or even a whole file or the entire database. We discuss granularity of items and a multiple granularity concurrency control protocol, which is an extension of two-phase locking, in Section 22.5. In Section 22.6 we describe concurrency control issues that arise when indexes are used to process transactions, and in Section 22.7 we discuss some additional concurrency control concepts. Section 22.8 summarizes the chapter.

 

It is sufficient to read Sections 22.1, 22.5, 22.6, and 22.7, and possibly 22.3.2, if your main interest is an introduction to the concurrency control techniques that are based on locking, which are used most often in practice. The other techniques are mainly of theoretical interest.


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