A deadlock situation can arise if all of the following four conditions hold simultaneously in a system:

  1. Mutual exclusion:
    at least one resource must be held in a non-shareable mode. Only one process can use the resource at any given instant of time.
  2. Hold and wait or resource holding:
    a process is currently holding at least one resource and requesting additional resources which are being held by other processes.
  3. No preemption:
    a resource can be released only voluntarily by the process holding it.
  4. Circular wait:
    a process must be waiting for a resource which is being held by another process, which in turn is waiting for the first process to release the resource. In general, there is a set of waiting processes, P = {P1, P2, …, PN}, such that P1 is waiting for a resource held by P2, P2 is waiting for a resource held by P3 and so on until PN is waiting for a resource held by P1.

These four conditions are known as the Coffman conditions from their first description in a 1971 article by Edward G. Coffman, Jr. Unfulfillment of any of these conditions is enough to preclude a deadlock from occurring.



ZAB Algorithm

ZAB is an atomic broadcast algorithm, which orders and executes concurrent requests in a sequential manner.

It consists of two modes:

  • Recovery: When the service starts or after a leader failure. Ends when a leader emerges and a quorum of servers have synchronized their state with the leader
  • Broadcast: The leader is the server that executes a broadcast by initiating the broadcast protocol. Once a leader has synchronized with a quorum of followers, it begins to broadcast messages

Important related links:


BASE involves step-by-step transformation of a transactional application into one that will be far more concurrent and less rigid, it stands for “Basically Available Soft-State Services with Eventual Consistency”

  • Basically Available: Fast response even if some replicas are slow or crashed
    • BASE paper describes: In data centers, partitioning faults are very rare and are mapped to crash failures by forcing the isolated machines to reboot
  • Soft-State Service: No durable memory
    • Can’t store any permanent data
    • Restarts in a “clean” state after a crash
    • To remember data, either replicate it in memory in enough copies to never lose all in any crash, or pass it to some other service that keeps “hard state”
  • Eventual Consistency: OK to send “optimistic” answers to the external client
    • Could use cached data (without checking for staleness)
    • Could guess at what the outcome of an update will be
    • Might skip locks, hoping that no conflicts will happen
    • Later, if needed, correct any inconsistencies in an offline clean up activity

ACID is a model for correct behavior of databases with the following properties:

  • Atomicity: Even if “transactions” have multiple operations, does them to completion (commit) or rolls back so that they leave no effect (abort)
  • Consistency: A transaction that runs on a correct database leaves it in a correct (“consistent”) state.
  • Isolation: It looks as if each transaction ran all by itself. Basically says “we’ll hide any concurrency”, it runs all its operation in a sequential manner
  • Durability: Once a transaction commits, updates can’t be lost or rolled back

Related article: CAP theorem

Consensus with paxos

Paxos is an algorithm to achieve consensus in asynchronous distributed system model. More about Paxos can be found unter:

Terms in Computer Science

A low-level object or operation from which higher-level, more complex objects and operations can be constructed. In graphics, primitives are basic elements, such as lines, curves, and polygons, which you can combine to create more complex graphical images. In programming, primitives are the basic operations supported by the programming language. A programmer combines these primitives to create more complex operations, which are packaged as functions, procedures, and methods. This definition is referred from