`nexyron.snapshot_materialized_list`

Generic Description

nexyron.snapshot_materialized_list lists cached materialized feature snapshot artifacts.

CALL nexyron.procedures()
YIELD name, description, parameters, output_columns
WHERE name = 'nexyron.snapshot_materialized_list'
RETURN name, description, parameters, output_columns

Abstraction-platform runtime procedures build, materialize, refresh, inspect, and execute artifacts derived from registered abstraction contracts.

Consumer-Level Explanation

This procedure is the main way to discover which feature snapshots have been materialized, which ASOF point they represent, how many rows they contain, and whether the current feature definitions make them stale.

Parameters

• This procedure takes no explicit parameters.

Output Columns

• name: Snapshot definition name.
• scenario: Optional scenario used during materialization.
• row_count: Cached row count.
• requested_at_ms: ASOF timestamp requested during materialization, or null for non-ASOF materialization.
• requested_system_at_ms: Optional dual-time system cutoff.
• materialized_at_ms: Wall-clock time when the artifact was built.
• refresh_required: true when the current feature set or feature versions no longer match the cached artifact.

Example Contract Prerequisite

The executable Cypher blocks on this page query nexyron.procedures() so they work in an empty database and stay synchronized with the live procedure registry. A direct CALL nexyron.snapshot_materialized_list(...) requires the named abstraction contracts, artifacts, features, snapshots, datasets, models, or policies referenced by that call to exist first; otherwise the runtime correctly fails with an unknown-contract error rather than inventing state.

Conceptual Explanation

This procedure stays inside the same Cypher, semantic-contract, and artifact runtime as the rest of Nexyron. That matters because catalog visibility, materialization state, freshness, and dependency shape are part of the same database contract rather than hidden external service state.

Automatic daily feature snapshots use names prefixed with __auto_feature_snapshot__. Backend abstraction and feature generation registers the automatic snapshot contract from the finalized active feature set. Manual snapshot backfills are capped at 30 materialization points as well. Automatic materializations outside that active 30-day window are pruned by service retention maintenance through nexyron.snapshot_materialized_drop, including their stream-backed feature history points.

More Detailed Explanation

In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with YIELD and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven abstraction procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.

Advanced Example

CALL nexyron.procedures()
YIELD name, parameters, output_columns
WHERE name = 'nexyron.snapshot_materialized_list'
RETURN name,
       [p IN parameters | p.name] AS parameter_names,
       output_columns
ORDER BY name

Real Use Cases

• Build or refresh quarter-specific training artifacts close to the graph so analysts can inspect the exact rows, labels, and split behavior before promoting a model.
• Audit artifact freshness, dependency shape, and rebuild backlog when a late membership backfill or facility schedule correction invalidates downstream abstraction assets.
• Find missing automatic daily ASOF snapshots by comparing expected daily requested_at_ms values with the rows returned by this procedure.

Real Limitations And Tradeoffs

• This procedure exposes or drives abstraction-platform runtime state. It does not replace the need for well-defined upstream features, snapshots, datasets, models, or policies.

• When artifacts are stale, the correctness question is usually upstream contract quality first, not only refresh mechanics.

• Listing artifacts is not a retention guarantee. The service can remove old automatic artifacts outside the active window while preserving manual artifacts and currently expected automatic days.