Transaction Schedule

If two transactions are running concurrently, the database system will interleave the actions (read, write, commit, abort) of the transactions. The result is a schedule of the transactions.

Let's take a simple example with two transactions, T1 and T2.

• Transaction T1: Read(A), Write(A), Read(B), Write(B)

• Transaction T2: Read(C), Write(C), Read(D), Write(D)

A possible schedule for these transactions might be:

• Schedule S: Read(A)-T1, Write(A)-T1, Read(C)-T2, Write(C)-T2, Read(B)-T1, Write(B)-T1, Read(D)-T2, Write(D)-T2

In the above schedule, operations of T1 and T2 are interleaved.

Schedules are vital in understanding the concurrent execution of transactions. There are two types of schedules:

1. Serial schedule: In this schedule, transactions are ordered one after the other. If there are 'n' transactions, there will be 'n!' possible serial schedules. Though this type of schedule is simple and ensures database consistency, it may not provide sufficient concurrency.

2. Concurrent schedule: In this schedule, operations from a set of transactions are interleaved. While the concurrent schedule improves performance by allowing transactions to run in parallel, it increases the complexity of ensuring the ACID properties.

It's also important to note the concept of conflict and conflict-serializability in the context of schedules. Two operations are said to be in conflict if they belong to different transactions, operate on the same data item, and at least one of them is a write operation. A schedule is conflict-serializable if it can be transformed into a serial schedule by swapping non-conflicting operations.

In practice, the goal of a database system is to allow as much concurrency as possible, while ensuring that the execution of concurrent transactions yields consistent and correct results. The transaction scheduler in a DBMS is responsible for creating a schedule that maintains the appropriate balance between performance and correctness.

Serial Schedule

A serial schedule in the context of database systems refers to a sequence of transactions that are executed one after the other. In a serial schedule, each transaction in the sequence is executed to completion before the execution of the next transaction in the sequence begins.

For example, let's consider two transactions T1 and T2.

T1:

• Read(A)

• Write(A)

• Read(B)

• Write(B)

T2:

• Read(X)

• Write(X)

• Read(Y)

• Write(Y)

A serial schedule for these two transactions would look like this:

• Serial Schedule 1 (T1 followed by T2): Read(A)-T1, Write(A)-T1, Read(B)-T1, Write(B)-T1, Read(X)-T2, Write(X)-T2, Read(Y)-T2, Write(Y)-T2

• OR

• Serial Schedule 2 (T2 followed by T1): Read(X)-T2, Write(X)-T2, Read(Y)-T2, Write(Y)-T2, Read(A)-T1, Write(A)-T1, Read(B)-T1, Write(B)-T1

These two schedules are examples of serial schedules. In both cases, one transaction is executed entirely before the second transaction starts.

Serial schedules are straightforward to manage and maintain database consistency because each transaction is completed before the next one begins, thus there's no risk of conflicts. However, they don't make full use of the concurrency capabilities of modern multi-core processors and can lead to suboptimal performance in systems where many transactions are being executed concurrently.

In practice, many database systems use a combination of serial and concurrent transaction scheduling, with transaction isolation techniques used to ensure the consistency of the database.

Concurrent Schedule

A concurrent schedule in the context of database systems refers to a sequence of operations from multiple transactions where the operations are interleaved. In other words, instead of executing all operations of one transaction before moving to the next (as in a serial schedule), operations from different transactions are executed in an interleaved manner.

Concurrent scheduling is widely used in database systems to improve performance. By allowing multiple transactions to execute concurrently, the system can make better use of processing power and IO capabilities, resulting in more efficient overall system performance.

Let's take an example of two transactions T1 and T2:

Transaction T1:

• Read(A)

• Write(A)

• Read(B)

• Write(B)

Transaction T2:

• Read(X)

• Write(X)

• Read(Y)

• Write(Y)

A concurrent schedule for these transactions could be:

• Concurrent Schedule: Read(A)-T1, Read(X)-T2, Write(A)-T1, Write(X)-T2, Read(B)-T1, Read(Y)-T2, Write(B)-T1, Write(Y)-T2

In this schedule, the operations from T1 and T2 are interleaved.

While concurrent schedules can lead to increased performance, they can also cause problems if not managed correctly, such as read-write and write-write conflicts. That's why it's important to manage concurrency control using different techniques such as two-phase locking, timestamp ordering, etc.

It's also essential to ensure that a concurrent schedule is conflict-serializable. This means that it should be equivalent to some serial schedule (in terms of the final state of the database) for the same set of transactions, to maintain database consistency. If a concurrent schedule is conflict-serializable, it is considered correct, as it maintains the consistency of the database just like a serial schedule would.