Leader Election

In many distributed systems, there are tasks that should only be performed by a single node at a time to avoid inconsistency and conflicts. For example:

• In a database with leader-follower replication, only one node can be the leader responsible for handling writes.
• A scheduled job that runs every hour should only be executed by one worker in a cluster, not all of them.
• A service that manages a shared resource needs a single node to act as the arbiter.

Leader election is the process by which a group of nodes in a distributed system dynamically chooses one node to be the unique "leader" responsible for these special tasks.

Why is Leader Election Necessary?

Without a clear leader, you can run into several problems:

• Split-Brain: If two nodes both think they are the leader, they might both accept writes or perform actions, leading to data corruption and an inconsistent system state.
• Redundant Work: If all nodes try to perform the same scheduled job, it's a waste of resources and could have unintended side effects.

A leader election algorithm ensures that all nodes can agree on which one is the leader, even if nodes crash or the network is unreliable.

How Leader Election Works

A robust leader election process typically relies on a separate, highly available coordination service that provides a consensus mechanism. The most common tools for this are ZooKeeper and etcd.

Here's a common pattern for leader election using a service like ZooKeeper:

1. Attempt to Create an Ephemeral Node: All nodes in the cluster try to create the same, specific node in ZooKeeper (e.g., /election/leader). This node must be an ephemeral node, which means it will be automatically deleted by ZooKeeper if the client that created it disconnects or crashes.
2. The Winner Becomes the Leader: ZooKeeper guarantees that only one client can successfully create a node with a given path. The node that succeeds in creating the /election/leader node becomes the new leader.
3. Followers Watch the Node: All the other nodes that failed to create the node become followers. They then place a "watch" on the /election/leader node. This means ZooKeeper will notify them if the node is ever deleted.
4. Handling Leader Failure: The leader periodically sends a "heartbeat" to ZooKeeper to keep its session alive. If the leader node crashes or gets disconnected from the network, its session with ZooKeeper will time out, and ZooKeeper will automatically delete the ephemeral /election/leader node.
5. Triggering a New Election: When the /election/leader node is deleted, ZooKeeper sends a notification to all the follower nodes that were watching it. This notification signals that the leader is gone and triggers a new election. All the follower nodes go back to step 1 and try to create the node again.

Key Properties of this Approach

• Fault Tolerance: The use of heartbeats and ephemeral nodes ensures that the system can automatically detect and recover from a leader failure.
• Consistency: ZooKeeper's consensus protocol guarantees that there will only ever be one leader at a time, preventing a split-brain scenario.
• Simplicity for Clients: The application nodes themselves don't have to implement a complex consensus algorithm. They just need to use a standard ZooKeeper client library to interact with the ephemeral node.

Other Leader Election Strategies

While using a coordination service like ZooKeeper is the most common and robust approach, there are other methods:

• Using a Relational Database: You could use a table in a database with a unique constraint. All nodes try to insert a row with a specific primary key. The one that succeeds is the leader. This is generally not recommended as it can be slow and puts a heavy load on the database.
• Using a Distributed Lock Manager: Services like Redis can be used to acquire a distributed lock. The node that acquires the lock becomes the leader. This requires careful implementation to handle lock expiry and renewal correctly.

In a system design interview, you should not try to invent your own leader election algorithm. The problem is notoriously difficult to get right.

Instead, you should:

1. Identify the need for a leader: Recognize the parts of your system that require a single coordinator.
2. Propose using a standard, battle-tested tool: State that you would use a coordination service like ZooKeeper or etcd to handle the leader election process.

This demonstrates that you understand the problem, are aware of the standard industry solutions, and know not to reinvent the wheel for such a critical and complex piece of infrastructure.