Time stamp Ordering

In Database Management Systems (DBMS), ensuring that multiple users can access and update data at the same time without errors is very important. This process is called concurrency control. One of the popular techniques used for concurrency control is Timestamp Ordering (TO).

Timestamp ordering ensures that transactions (operations like read, write, update) are executed in the same order in which they were initiated, based on the timestamps assigned to them. This method avoids conflicts such as dirty reads, lost updates, or inconsistent results.

Understanding the Concept of Timestamp

• A timestamp is simply a unique identifier assigned to every transaction when it starts.
• Usually, this timestamp is based on the system’s clock or a counter that increases whenever a new transaction begins.
• For example:
  • Transaction T1 starts at time 101 → Timestamp = 101
  • Transaction T2 starts at time 105 → Timestamp = 105

Here, the DBMS ensures that T1’s operations are executed before T2’s, because T1 is older.

Timestamp Ordering Protocol

The timestamp ordering protocol ensures that all transactions are executed according to their timestamp order. It does this by maintaining two important values for each data item (say X):

1. Read Timestamp (RTS(X)): The largest timestamp of a transaction that successfully read X.
2. Write Timestamp (WTS(X)): The largest timestamp of a transaction that successfully wrote X.

When a transaction tries to read or write a data item, the DBMS checks these timestamps to decide whether the operation can proceed, be delayed, or be aborted.

Rules of Timestamp Ordering

Let’s break down the two main cases:

1. Read Operation (Read(X))

Suppose transaction Ti wants to read data item X:

• If TS(Ti) < WTS(X) → AbortTi.
  • Reason: A newer transaction has already written to X. Allowing an older one to read would create inconsistency.
• Otherwise, allow the read and update:
  RTS(X) = max(RTS(X), TS(Ti)).

2. Write Operation (Write(X))

Suppose transaction Ti wants to write on X:

• If TS(Ti) < RTS(X) → AbortTi.
  • Reason: A newer transaction has already read X. Writing now would invalidate that read.
• If TS(Ti) < WTS(X) → AbortTi.
  • Reason: A newer transaction has already written to X.
• Otherwise, allow the write and set:
  WTS(X) = TS(Ti).

Example of Timestamp Ordering

Let’s take an example with two transactions:

• T1 (TS = 5)
• T2 (TS = 10)

Initially, RTS(X) = 0, WTS(X) = 0.

1. T1 reads X
   • TS(T1) = 5, WTS(X) = 0 → Allowed
   • Update RTS(X) = 5
2. T2 writes X
   • TS(T2) = 10, RTS(X) = 5 → Allowed
   • Update WTS(X) = 10
3. T1 tries to write X
   • TS(T1) = 5, WTS(X) = 10 → Not allowed
   • T1 is aborted (since a newer transaction already wrote on X).

This ensures the order of execution is consistent with timestamps.

Advantages of Timestamp Ordering

1. Deadlock-Free: Since decisions are based on timestamps, there is no waiting, which eliminates the risk of deadlocks.
2. Simple to Implement: The rules are straightforward, making it easier to manage concurrency.
3. Fair Scheduling: Older transactions are always given priority, ensuring fairness.

Disadvantages of Timestamp Ordering

1. High Abort Rate: Transactions may be aborted frequently if conflicts are high.
2. Starvation of Long Transactions: Older transactions may get aborted multiple times if newer ones keep conflicting.
3. Storage Overhead: The system must maintain RTS and WTS for every data item.

Variants of Timestamp Ordering

To improve efficiency, different versions of timestamp ordering exist:

1. Basic Timestamp Ordering (BTO): Uses the simple rules explained above.
2. Strict Timestamp Ordering: Delays writes until all conflicting reads are finished, ensuring recoverability.
3. Multiversion Timestamp Ordering (MVTO): Maintains multiple versions of data items, so read operations don’t block writes. This reduces aborts.

Conclusion

Timestamp Ordering in DBMS is a powerful concurrency control technique that ensures transactions are executed in a serializable and consistent manner. By assigning timestamps and maintaining read/write history, DBMS can prevent conflicts without using locks, making it deadlock-free. However, frequent aborts and potential starvation are its drawbacks.

In practice, timestamp ordering is often combined with other methods like multiversion concurrency control to achieve better performance in real-world systems.