Author: Jack Maguire

The node manager is a class that is designed to help derived job queens with their boring book-keeping. This classes is designed such that you have one of these per every node in your job digraph. Under the hood, the node manager is has the following elements:

Results to keep

There is a 2-dimensional sorted vector of results. Each row of the array is called a partition. The user (job queen developer) specifies how many job results they want for each parition.

When reporting a result, the user declares which partition the result should go in. Once the result is sorted into its correct partition, the last (worst) element of that parition will be removed if there are more elements than the user specified.

The user can access these results either using results_to_keep(), which creates a 1-dimensional representation of the 2D vector, or get_nth_job_result_id(), which returns the ResultID for the nth element. get_nth_job_result_id() is prefered over results_to_keep() because the former allows the node manager to keep accepting new results while the latter freezes the result vector to prevent iterator invalidation.

Results to discard

When a job result is removed from the 2-dimensional vector of results to keep, it is added to a std::list of job results to discard. The derived queen can access this list using append_job_results_that_should_be_discarded().

Counters for various job submission states

The node manager keeps track of:

  • The number of jobs that have been submitted for this node.

  • The next local job id to be submitted

  • The number of results received.*

*There is also built-in functionality to stop submitting jobs for a DAG node early once enough results come in. This is handled by the "result_threshold" arguments in the constructor.

Derived classes

Two derived classes have been created to make the interface simpler:


This class only creates 1 parition, so the 2-dimensional vector is basically a 1-dimensional vector. The interface to this class is designed such that you never need to specify a partition argument.


This class allows for multiple partitions, but it requires that the paritions have symmetric requirements. The number of results to keep is divided enevly among the paritions. Same is true for the result threshold. This allows for a modestly more user-friendly constructor, but none of the other methods are changed.

See Also