Question

Suppose an RPC request is of the form "Increment the value of field X of disk block \(\mathrm{N}\) by \(10 \%\)." Specify a mechanism to be used by the executing server to guarantee that an arriving request is executed exactly once, even if the server crashes while in the middle of the operation. Assume that individual disk block writes are either complete or else the block is unchanged. You may also assume that some designated "undo log" blocks are available. Your mechanism should include how the RPC server is to behave at restart.

Short answer

Use an undo log and a commit log and re-execute incomplete operations after a crash.

Step-by-step solution

- Prepare the Undo Log

Before making any changes to the disk block \(\text{N}\), write the current value of block \(\text{N}\) to a designated undo log block. This ensures that the server can restore the block to its original state if a crash occurs during the operation.

- Modify the Disk Block

Increment the value of field X of disk block \(\text{N}\) by 10%. Perform the write operation on the disk block knowing an undo log is in place.

- Commit the Changes

Once the disk block \(\text{N}\) has been successfully modified, mark the operation as complete in a designated log (separate from the undo log). This helps the server to identify which operations were finished before a potential crash.

- Handle Server Crashes

If the server crashes and restarts, it should check the designated log. If the operation was not marked as complete (i.e., the operation is not in the log), the server should use the undo log to revert the disk block \(\text{N}\) to its previous state, ensuring consistency.

- Re-execute Incomplete Requests

After ensuring the previous state is consistent by potentially reverting changes using the undo log, the server should re-execute the RPC request from the beginning, following the previous steps (preparing undo log, modifying block, committing changes).

Key concepts

RPC (Remote Procedure Call)

Remote Procedure Call (RPC) is a protocol that allows one program to request a service or action to be executed by another program located on a different computer in a network. The program initiating the call sends a request to the remote host machine, which processes the request and sends back the result. In the context of our exercise, the server receives an RPC request to increment a field value in a disk block. Understanding RPC is essential as it is the foundation of how the request is communicated and executed across distributed systems.

Key benefits of RPC include:

• Transparency: Acts like a local procedure call despite being remote.
• Efficiency: Suitable for distributed systems connectivity.
• Modularity: Enables separation of services into discrete units.

With RPC, we focus on creating a seamless and efficient method for interaction between different system components, which is crucial for our exercise on executing requests exactly once.

Undo Logging

Undo logging is a technique used to ensure data consistency and recoverability in case of a system crash. Before modifying any data, the current state of that data is written to a log. If a crash happens during the operation, this log can be used to 'undo' the changes, restoring the data to its previous state.

In our exercise, undo logging steps include:

• Writing the current value of the block to the undo log before making changes.
• Proceeding with the requested updates knowing we can revert if needed.

In the event of a crash, the undo log is crucial for ensuring that incomplete operations do not leave the data in an inconsistent state. By rolling back to the previous state, undo logging helps maintain stability and reliability in the system.

Exactly-Once Semantics

Exactly-once semantics guarantees that a particular operation, such as an RPC request, is executed precisely one time. This is challenging in distributed systems, especially when considering server crashes and retries.

To achieve exactly-once semantics, our exercise uses a combination of undo logging and a designated log to track completed operations. The main points include:

• Logging the initial state of data before changes begin.
• Logging the completion of the operation.

In case of a server crash, these logs are referenced to decide whether an operation needs to be reverted or re-executed. This mechanism ensures that all operations are executed once and only once, promoting data consistency and system reliability.

Server Crash Recovery

Server crash recovery is the process of restoring system operations and ensuring data consistency after a failure or crash. In our exercise, maintaining an undo log and a designated completion log helps streamline recovery.

Upon restart, the server checks:

• The completion log to identify finished operations.
• The undo log to revert any incomplete changes.

After ensuring the state is consistent, incomplete requests are re-executed from the start. This approach helps the system handle crashes gracefully, minimizing data loss and ensuring high availability.

Data Consistency

Data consistency ensures that a system reflects the accurate and correct state of data at any given time, even in the face of concurrent operations or crashes. It is a critical aspect of distributed systems.

In the context of our exercise, the techniques used ensure consistent data:

• Undo logging to revert to previous states if needed.
• Marking completed operations in a designated log.

By using these concepts, the system ensures that data remains accurate and intact, preventing anomalies and ensuring trust in the operations. Consistent data forms the backbone of reliable distributed systems, essential for maintaining system integrity.