How to Approach Two-Phase Commit Assignments in Rust

Grasp the Functional and Pedagogical Goals

Most distributed assignments like the one you've been given aim to test more than just your coding ability:

• Functional goal: Implement a working two-phase commit protocol between a coordinator and participants.
• Pedagogical goals: Understand Rust’s ownership model, concurrency paradigm, and how it can help build safer systems; gain exposure to implementing distributed protocols.

These goals tell you that the assignment isn't just about "making it work" — it’s about learning how to work within Rust's ecosystem, using channels and enums correctly, and writing modular, fault-aware distributed code.

Dissect the System Architecture

The assignment you're working on includes:

• A coordinator process that manages the protocol.
• Multiple participants that may commit or abort operations.
• Multiple clients issuing requests to the coordinator.
• Communication via IPC channels.
• A checker system that analyzes commit logs.

Before writing anything, sketch a system diagram showing how messages flow between these components and what states each actor (participant/coordinator) can be in.

Know the Skeleton You’re Given

Such assignments often provide partial code scaffolding. In this case:

• src/main.rs: Where the coordinator spawns other processes.
• src/client.rs, src/participant.rs, src/coordinator.rs: Contain protocol logic for each entity.
• src/message.rs: Where your message formats are defined — this file is crucial.
• src/checker.rs: Already built, evaluates correctness. Using its expected message types is essential.

Spend your first hour reading and annotating each of these files. Your design should align with what the checker expects.

Phase-Wise Strategy to Implement a Rust-Based 2PC Assignment

Now that you're grounded in the requirements, let’s break down how to implement such a system in phases.

Phase 1: Building the Coordinator Logic

Design the State Machine

A coordinator in 2PC follows a deterministic protocol:

1. Receive request from a client.
2. Send a "prepare" message to all participants.
3. Collect votes (commit/abort).
4. Send "commit" or "abort" to participants.
5. Log the outcome.

Design a clear state machine or flow diagram for this. Implement logic so that only after receiving all votes does the coordinator move to the commit/abort decision.

Handle IPC and Process Management

Using the ipc-channel crate, establish channels to communicate with participants and clients. The main process should spawn children (using Rust’s Command module), passing correct arguments like --mode client, --mode participant, and shared --ipc_path.

The IPC setup typically follows this order:

• Parent opens an IpcOneShotServer.
• Child connects using IpcSender/IpcReceiver.
• Exchange a ready handshake before full message traffic.

You must carefully synchronize channel setup to avoid deadlocks or broken pipes.

Log Every Decision for Post-Mortem Analysis

Make use of src/oplog.rs to write commit/abort logs. Your implementation must ensure:

• Each transaction has a clear log entry.
• Log writing is atomic and durable (though crash recovery isn’t mandatory unless you go for extra credit).
• The format aligns with what the checker expects.

Phase 2: Implementing Clients and Participants

Clients Should Be Stateless and Concurrency-Aware

Each client issues multiple operation IDs to the coordinator. Design clients to:

• Generate a unique operation ID (UUID or incremental).
• Send it to the coordinator via IPC.
• Wait for a result (commit/abort).
• Optionally log or print the result.

If multiple clients run concurrently, spawn threads inside client.rs and guard shared resources with Mutex or Arc.

Participants Must Handle Success, Failure, and Silence

Each participant votes either "commit" or "abort" in phase one. To simulate realistic scenarios:

• Implement a probability-based success rate (e.g., 95% success).
• If a participant “fails,” simply don’t respond (simulate a timeout).
• If a participant chooses abort, it must be deterministic for that transaction.

Use Rust enums for Vote::Commit, Vote::Abort, and Vote::NoResponse. Ensure participant.rs handles phase-one messages, logs its vote, and waits for phase-two instructions.

Phase 3: Error Handling, Testing, and Debugging

Use Logging and Tracing Extensively

Use the macros:

• trace!("Processing request {:?}", request_id);
• info!("Participant voted commit");
• debug!("Timeout waiting for vote from {:?}", participant_id);

Initialize the logger at the start using stderrlog and expose verbosity via command-line args. Proper logs will save you hours of debugging time.

Simulate Real-World Failures

The assignment requires you to simulate both:

• Send failure (-S flag): Drop or delay messages.
• Operation failure (-s flag): Randomize participant behavior.

In participant.rs, write a wrapper around the send() function to simulate dropped messages. You may use something like:

• if rand::thread_rng().gen_bool(send_success_rate) { sender.send(message)?; }

Ensure your code is modular so this feature can be toggled easily with flags.

Run the Checker Frequently

Don’t wait until the night before to test with --mode check. Run the checker every time you make a logic change. Check:

• Were logs written in the correct format?
• Did all participants agree with the coordinator?
• Are there any missing logs?

Make sure your commit and abort logs are symmetric and complete.

Beyond Implementation: Optimization, Report Writing, and Extra Credit

Assignments of this complexity often ask for a short report. This is your opportunity to reflect and gain points beyond the code.

Analyze Your Performance

Measure the performance under different settings:

• Vary number of clients and participants.
• Compare outcomes with 90% vs. 95% success rates.
• Time the phases.

Use Rust’s Instant::now() to calculate durations.

Tabulate your findings:

Document Design Decisions

In your report, mention:

• Why you used Arc<Mutex<T>> for shared states.
• How you chose to serialize messages.
• How logging consistency was enforced.

You can even attach flow diagrams of your coordinator and participant logic.

Tackle Extra Credit (If You Have Time)

If you’ve nailed the basic 2PC:

• Implement a recovery protocol: store vote phase info and allow rejoining.
• Use an actual fault-tolerant logging mechanism like commitlog.
• Handle coordinator failure with timeout-based leader election (advanced).

These features are not trivial but are great resume builders if done right.

Final Thoughts: Key Takeaways for Students

Assignments like the Rust-based 2PC project are foundational experiences for future systems developers. They force you to think about:

• Safety vs. performance: Rust won’t let you shoot yourself in the foot, but it also demands design upfront.
• Concurrency and isolation: You can't just spawn threads and hope for the best. You need Mutexes, Arcs, and deterministic behavior.
• Protocol correctness: Every log, every message, and every vote needs to follow the 2PC rules — or the checker will catch you.

Here’s what to keep in mind as you approach similar distributed programming assignments:

• Start by understanding the roles of each process.
• Use skeleton code as a roadmap, not a crutch.
• Write modular, testable code with IPC and enums.
• Simulate failures early and test extensively.
• Run the checker often, not just at the end.

Once you’ve completed this kind of project, you’ll have a strong grasp of distributed protocols, message-passing concurrency, and how Rust enforces correctness at compile time. And that’s a powerful combination in modern software engineering.