Check Results

Two functions convert Rocky execution results into Dagster events that appear in the Dagster UI.

emit_materializations(result, translator?) -> list[AssetMaterialization]

Converts Rocky materializations into Dagster AssetMaterialization events.

Each materialization includes metadata:

• strategy — the materialization strategy used (e.g., incremental, full_refresh)
• duration_ms — how long the materialization took
• rows_copied — number of rows copied
• watermark — the new high watermark value

An optional translator can be passed to control asset key mapping, ensuring consistency with how assets were discovered via load_rocky_assets().

emit_check_results(result) -> list[AssetCheckResult]

Converts Rocky check results into Dagster AssetCheckResult events.

Handles all Rocky check types:

• row_count — validates source and target row counts match
• column_match — validates columns exist in both source and target
• freshness — validates data is within a staleness threshold
• null_rate — validates null rates are below a threshold
• custom — any user-defined check

All check metadata is propagated to the Dagster event for full observability.

Example

from dagster_rocky import RockyResource, emit_check_results, emit_materializations
import dagster as dg

@dg.asset
def replicate(context, rocky: RockyResource):
    result = rocky.run(filter="tenant=acme")

    for mat in emit_materializations(result):
        context.log_event(mat)

    for check in emit_check_results(result):
        context.log_event(check)

    return result.tables_copied

Both functions return lists, so you can also inspect or filter events before logging them:

mats = emit_materializations(result)
context.log.info(f"Emitting {len(mats)} materializations")
for mat in mats:
    context.log_event(mat)