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Lecture

ACID and Transaction Schedules

In course

CS-422: Database systems

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and und ...

Description

This lecture covers the concepts of transactions, ACID properties, schedules, and locking protocols in database systems. It explains the definition of transactions, the importance of atomicity, consistency, isolation, and durability. The instructor discusses the execution of transactions in parallel, the role of schedules in database management systems, and examples of interleaving schedules. Additionally, the lecture explores anomalies that can occur with interleaved execution, such as reading uncommitted data and overwriting uncommitted data. Conflict serializable schedules and the use of precedence graphs to determine conflict serializability are also explained.

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Instructor

Anastasia Ailamaki

Official source

Ontological neighbourhood

Computer engineering

High-performance computing: Distributed computing

Related concepts (32)

Isolation (database systems)

In database systems, isolation determines how transaction integrity is visible to other users and systems. A lower isolation level increases the ability of many users to access the same data at the same time, but increases the number of concurrency effects (such as dirty reads or lost updates) users might encounter. Conversely, a higher isolation level reduces the types of concurrency effects that users may encounter, but requires more system resources and increases the chances that one transaction will block another.

Schedule (computer science)

In the fields of databases and transaction processing (transaction management), a schedule (or history) of a system is an abstract model to describe execution of transactions running in the system. Often it is a list of operations (actions) ordered by time, performed by a set of transactions that are executed together in the system. If the order in time between certain operations is not determined by the system, then a partial order is used.

Commitment ordering

Commitment ordering (CO) is a class of interoperable serializability techniques in concurrency control of databases, transaction processing, and related applications. It allows optimistic (non-blocking) implementations. With the proliferation of multi-core processors, CO has also been increasingly utilized in concurrent programming, transactional memory, and software transactional memory (STM) to achieve serializability optimistically. CO is also the name of the resulting transaction schedule (history) property, defined in 1988 with the name dynamic atomicity.

Precedence graph

A precedence graph, also named conflict graph and serializability graph, is used in the context of concurrency control in databases. The precedence graph for a schedule S contains: A node for each committed transaction in S An arc from Ti to Tj if an action of Ti precedes and conflicts with one of Tj's actions. That is the actions belong to different transactions, at least one of the actions is a write operation, and the actions access the same object (read or write). A precedence graph of the schedule D, with 3 transactions.

Two-phase locking

In databases and transaction processing, two-phase locking (2PL) is a concurrency control method that guarantees serializability. It is also the name of the resulting set of database transaction schedules (histories). The protocol uses locks, applied by a transaction to data, which may block (interpreted as signals to stop) other transactions from accessing the same data during the transaction's life. By the 2PL protocol, locks are applied and removed in two phases: Expanding phase: locks are acquired and no locks are released.

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