Let’s dive into concurrency and coordination in distributed systems.
Concurrency is the ability of a system to execute multiple tasks simultaneously or in an overlapping manner. In a distributed system, different nodes can execute different tasks at the same time, leading to concurrent execution.
Coordination, on the other hand, is the management of these concurrent tasks or operations to ensure consistency, correctness, and safety. It involves synchronizing the activities of multiple processes to ensure they work together correctly and efficiently.
Let’s consider an example of a distributed system that uses a MapReduce pattern. This pattern involves dividing a large task into smaller subtasks that can be executed in parallel across multiple nodes.
Map Phase (Concurrency): The input data is divided into chunks, and the map function is applied to each chunk in parallel. This is an example of concurrency, as multiple map operations are being executed simultaneously on different nodes.
Reduce Phase (Coordination): The output of the map phase is shuffled and sorted so that all values associated with the same key are grouped together. The reduce function is then applied to each group of values. This is an example of coordination, as the system needs to ensure that all map operations have completed before starting the reduce operations.
Another example is a leader-based replication system. In this system, one node is elected as the leader, and the rest of the nodes are followers.
Write Operations (Concurrency): All write operations are sent to the leader. The leader writes the data to its local storage and then sends the data to all followers. This is an example of concurrency, as the leader and all followers are writing the data simultaneously.
Read Operations (Coordination): Read operations can be handled by any node. If a follower receives a read operation, it first needs to check with the leader to ensure it has the most up-to-date data. This is an example of coordination, as the follower needs to synchronize with the leader before it can complete the read operation.
These examples illustrate how concurrency and coordination work together in distributed systems to enable efficient and correct execution of tasks.