eventordering

Event ordering in distributed systems concerns determining a sequence of events across processes that may not share a global clock. It distinguishes causal ordering (one event may cause another) from a total order that arranges all events linearly. Without synchronization, events can be concurrent and their ordering is undefined or inconsistent across nodes.

The canonical tools are Lamport's logical clocks and vector clocks. Lamport timestamps assign a monotonically increasing scalar to events and preserve the happens-before relation but do not capture causality precisely for concurrent events. Vector clocks attach a vector of counters per process, enabling detection of which events are causally related or concurrent.

To achieve a global or total order, systems use protocols like total order broadcast or consensus algorithms (Paxos, Raft). These provide a single sequence of delivered events or operations that all participating nodes agree on, enabling linearizability and consistent replication. Physical clocks can supplement logical clocks but require tight synchronization and still cannot perfectly determine causality in asynchronous networks.

Applications include database replication, distributed transactions, event streaming platforms, and distributed ledgers. Challenges include clock skew, message delays, concurrency, and scalability. A well-chosen ordering approach balances causality, complexity, and performance for the target system.