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4de5a8dd7c
hive-c0re hand-rolled four traversals over a graph it doesn't own, because `Graph` exposed only `node()` and `nodes()`. They are generic — nothing in them knows what a hyperhive DAG is — so they move to `hive-jobq` and core delegates. `Graph` gains `root_of`, `descendants`, `roots`, `is_settled` and `first_error`; they reuse the private `is_descendant` the crate already had for its dep-scope rule. `subtree` gets faster on the way: core walked every node's whole parent chain to the root for every node in the graph, where `is_descendant` stops as soon as it sees the ancestor. `first_error` deliberately looks for the first `Failed` descendant that *carries* an error rather than the first `Failed` one. A node that rolled its failure up from a child holds no error of its own and sorts before that child, so the simpler version reports `None` for the common case and the dashboard loses the reason. The distinction has its own test. `dag_is_terminal` is deleted rather than moved: it was already a plain `state.is_terminal()` read, and its three call sites now ask the graph. |
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| src | ||
| Cargo.toml | ||
| README.md | ||
hive-jobq
A persistent job-DAG scheduler, extracted from hive-c0re's in-tree job_queue
as a domain-agnostic library. It schedules a single persistent graph of
nodes over named resources; it knows nothing about containers, rebuilds, or any
hyperhive type — the node payload N and resource name R are both generic, so
the caller supplies its own domain.
When to use it
Reach for this crate whenever you need to run a DAG of interdependent work items under bounded, named concurrency — the hive-c0re rebuild/lifecycle queue is the first consumer, but nothing here is specific to it. The caller defines the node kinds, wires deps, and supplies a runner; the scheduler decides what can start.
Model
One persistent graph for the whole system, not a DAG per job. Enqueuing inserts a self-contained sub-DAG and returns the new node ids; the scheduler runs a continuous loop, starting every node whose deps are satisfied:
- Resource deps are named counting semaphores over a caller-chosen type
R— e.g.build-slot(capacity N),agent/<name>(capacity 1), or any unconfigured name (capacity 1, created on use). A node acquires all its resource deps atomically at start (all-or-nothing) — no hold-and-wait, so no deadlock. - Node deps wait on another node per
DepWhen:AfterOkneeds success (a failed dep cancels the dependent),AfterAnyonly needs terminal.
A node carries two independent axes: its Deps (ordering + resource needs) and
its parent (structural grouping). The parent chain, not the node edges, is
what the scheduler consults for resource re-entrancy: a resource unit is held
for the acquiring node plus its whole parent subtree, and a descendant needing
a resource an ancestor already holds re-uses that grant (a re-entrant borrow,
one branch at a time) rather than taking a fresh unit.
A NodeId is opaque, stable, and monotonic (safe to persist). The scheduler is
single-threaded — it owns the resource table and mutates it directly.
Shape
Graph<N, R>— the persistent node store.insertmints ids and validates dep/parent references;set_stateis the single state-transition choke point (and where each node's lifecycle timestamps —started_at/finished_at,DateTime<Utc>— are stamped).Node<N, R>—{ id, parent, payload, deps, state, started_at, finished_at, error }. All fields public; derives serde for persistence + the wire.Scheduler<N, R>— drives the graph:settle()starts every ready node (acquiring resources atomically),complete(id, outcome)reports a finished node's result and rolls terminality up the parent chain, releasing grants once a subtree is done.Outcome::{Done, Failed(String)}— the failure reason ridesFailedonto the node'serror.ResourceTable<R>— per-name capacities; unconfigured names default to capacity 1.
See the crate-root and scheduler module //! docs for the full borrow/release
model.