Managing Groups of Workers experimental

When managing a set of workers, a central actor often dispatches requests to a set of workers. For this purpose, the class actor_pool implements a lightweight abstraction for managing a set of workers using a dispatching policy. Unlike groups, pools usually own their workers.

Pools are created using the static member function make, which takes either one argument (the policy) or three (number of workers, factory function for workers, and dispatching policy). After construction, one can add new workers via messages of the form ('SYS', 'PUT', worker), remove workers with ('SYS', 'DELETE', worker), and retrieve the set of workers as vector<actor> via ('SYS', 'GET').

An actor pool takes ownership of its workers. When forced to quit, it sends an exit messages to all of its workers, forcing them to quit as well. The pool also monitors all of its workers.

Pools do not cache messages, but enqueue them directly in a workers mailbox. Consequently, a terminating worker loses all unprocessed messages. For more advanced caching strategies, such as reliable message delivery, users can implement their own dispatching policies.

Dispatching Policies

A dispatching policy is a functor with the following signature:

using uplock = upgrade_lock<detail::shared_spinlock>;
using policy = std::function<void (actor_system& sys,
                                   uplock& guard,
                                   const actor_vec& workers,
                                   mailbox_element_ptr& ptr,
                                   execution_unit* host)>;

The argument guard is a shared lock that can be upgraded for unique access if the policy includes a critical section. The second argument is a vector containing all workers managed by the pool. The argument ptr contains the full message as received by the pool. Finally, host is the current scheduler context that can be used to enqueue workers into the corresponding job queue.

The actor pool class comes with a set predefined policies, accessible via factory functions, for convenience.

actor_pool::policy actor_pool::round_robin();

This policy forwards incoming requests in a round-robin manner to workers. There is no guarantee that messages are consumed, i.e., work items are lost if the worker exits before processing all of its messages.

actor_pool::policy actor_pool::broadcast();

This policy forwards each message to all workers. Synchronous messages to the pool will be received by all workers, but the client will only recognize the first arriving response message—or error—and discard subsequent messages. Note that this is not caused by the policy itself, but a consequence of forwarding synchronous messages to more than one actor.

actor_pool::policy actor_pool::random();

This policy forwards incoming requests to one worker from the pool chosen uniformly at random. Analogous to round_robin, this policy does not cache or redispatch messages.

using join = function<void (T&, message&)>;
using split = function<void (vector<pair<actor, message>>&, message&)>;
template <class T>
static policy split_join(join jf, split sf = ..., T init = T());

This policy models split/join or scatter/gather work flows, where a work item is split into as many tasks as workers are available and then the individuals results are joined together before sending the full result back to the client.

The join function is responsible for “glueing” all result messages together to create a single result. The function is called with the result object (initialed using init) and the current result messages from a worker.

The first argument of a split function is a mapping from actors (workers) to tasks (messages). The second argument is the input message. The default split function is a broadcast dispatching, sending each worker the original request.