zio.stm

Wraps array of TRef and adds methods for convenience.

A transactional queue that can only be dequeued.

A transactional queue that can only be enqueued.

A THub is a transactional message hub. Publishers can publish messages to the hub and subscribers can subscribe to take messages from the hub.

Transactional map implemented on top of TRef and TArray. Resolves conflicts via chaining.

A TPriorityQueue contains values of type A that an Ordering is defined on. Unlike a TQueue, take returns the highest priority value (the value that is first in the specified ordering) as opposed to the first value offered to the queue. The ordering that elements with the same priority will be taken from the queue is not guaranteed.

A TQueue is a transactional queue. Offerors can offer values to the queue and takers can take values from the queue.

A TReentrantLock is a reentrant read/write lock. Multiple readers may all concurrently acquire read locks. Only one writer is allowed to acquire a write lock at any given time. Read locks may be upgraded into write locks. A fiber that has a write lock may acquire other write locks or read locks.

The two primary methods of this structure are readLock, which acquires a read lock in a scoped context, and writeLock, which acquires a write lock in a scoped context.

Although located in the STM package, there is no need for locks within STM transactions. However, this lock can be quite useful in effectful code, to provide consistent read/write access to mutable state; and being in STM allows this structure to be composed into more complicated concurrent structures that are consumed from effectful code.

A TRef is a purely functional description of a mutable reference that can be modified as part of a transactional effect. The fundamental operations of a TRef are set and get. set transactionally sets the reference to a new value. get gets the current value of the reference.

NOTE: While TRef provides the transactional equivalent of a mutable reference, the value inside the TRef should be immutable. For performance reasons TRef is implemented in terms of compare and swap operations rather than synchronization. These operations are not safe for mutable values that do not support concurrent access.

A TSemaphore is a semaphore that can be composed transactionally. Because of the extremely high performance of ZIO's implementation of software transactional memory TSemaphore can support both controlling access to some resource on a standalone basis as well as composing with other STM data structures to solve more advanced concurrency problems.

For basic use cases, the most idiomatic way to work with a semaphore is to use the withPermit operator, which acquires a permit before executing some ZIO effect and release the permit immediately afterward. The permit is guaranteed to be released immediately after the effect completes execution, whether by success, failure, or interruption. Attempting to acquire a permit when a sufficient number of permits are not available will semantically block until permits become available without blocking any underlying operating system threads. If you want to acquire more than one permit at a time you can use withPermits, which allows specifying a number of permits to acquire. You can also use withPermitScoped or withPermitsScoped to acquire and release permits within the context of a scoped effect for composing with other resources.

For more advanced concurrency problems you can use the acquire and release operators directly, or their variants acquireN and releaseN, all of which return STM transactions. Thus, they can be composed to form larger STM transactions, for example acquiring permits from two different semaphores transactionally and later releasing them transactionally to safely synchronize on access to two different mutable variables.

Transactional set implemented on top of TMap.

STM[E, A] represents an effect that can be performed transactionally, resulting in a failure E or a value A.

def transfer(receiver: TRef[Int],
             sender: TRef[Int], much: Int): UIO[Int] =
 STM.atomically {
   for {
     balance <- sender.get
     _       <- STM.check(balance >= much)
     _       <- receiver.update(_ + much)
     _       <- sender.update(_ - much)
     newAmnt <- receiver.get
   } yield newAmnt
 }

 val action: UIO[Int] =
   for {
     t <- STM.atomically(TRef.make(0).zip(TRef.make(20000)))
     (receiver, sender) = t
     balance <- transfer(receiver, sender, 1000)
   } yield balance

Software Transactional Memory is a technique which allows composition of arbitrary atomic operations. It is the software analog of transactions in database systems.

The API is lifted directly from the Haskell package Control.Concurrent.STM although the implementation does not resemble the Haskell one at all. http://hackage.haskell.org/package/stm-2.5.0.0/docs/Control-Concurrent-STM.html

STM in Haskell was introduced in: Composable memory transactions, by Tim Harris, Simon Marlow, Simon Peyton Jones, and Maurice Herlihy, in ACM Conference on Principles and Practice of Parallel Programming 2005. https://www.microsoft.com/en-us/research/publication/composable-memory-transactions/

See also: Lock Free Data Structures using STMs in Haskell, by Anthony Discolo, Tim Harris, Simon Marlow, Simon Peyton Jones, Satnam Singh) FLOPS 2006: Eighth International Symposium on Functional and Logic Programming, Fuji Susono, JAPAN, April 2006 https://www.microsoft.com/en-us/research/publication/lock-free-data-structures-using-stms-in-haskell/