dagster-rocky 1.19.0

Dagster integration for the Rocky SQL transformation engine

dagster-rocky

Dagster integration for the Rocky SQL transformation engine.

dagster-rocky wraps the rocky CLI as a Dagster ConfigurableResource and exposes Rocky-managed tables as materializable Dagster assets — complete with check results, lineage, drift detection and quality metrics surfaced as native Dagster events.

Install

uv add dagster-rocky

You'll also need the Rocky CLI on your $PATH: https://github.com/rocky-data/rocky/releases?q=engine

Quick start (component)

Add a defs.yaml next to your other Dagster definitions:

type: dagster_rocky.RockyComponent
attributes:
  binary_path: rocky
  config_path: config/rocky.toml
  models_dir: models

Dagster's component loader will:

1. Run rocky discover (and rocky compile, when models are present) and cache the result.
2. Build one subset-aware multi_asset per Rocky group, with declared row_count / column_match / freshness checks per table.
3. On materialization, shell out to rocky run --filter <key>=<value> for the selected subset and yield MaterializeResult + AssetCheckResult events with rich metadata.

Quick start (resource)

import dagster as dg
from dagster_rocky import RockyResource

rocky = RockyResource(
    binary_path="rocky",
    config_path="config/rocky.toml",
    timeout_seconds=3600,
)

defs = dg.Definitions(resources={"rocky": rocky})

Then in an asset:

@dg.asset
def acme_orders(rocky: RockyResource) -> dg.MaterializeResult:
    result = rocky.run(filter="tenant=acme")
    return dg.MaterializeResult(
        metadata={"tables_copied": result.tables_copied, "duration_ms": result.duration_ms},
    )

Public API

Symbol	Purpose
RockyResource	ConfigurableResource wrapping the Rocky CLI
RockyComponent	State-backed Dagster component that loads Rocky tables as assets
RockyDagsterTranslator	Subclass to customize asset key / group / tag mapping
RockyMetadataSet	Namespaced metadata (source_id, strategy, watermark, …)
load_rocky_assets()	Functional helper that returns AssetSpec for each Rocky table
emit_materializations() / emit_check_results()	Convert a RunResult into Dagster events
check_metadata()	Build a metadata mapping for a single Rocky CheckResult
cost_metadata_from_optimize()	Extract per-model cost recommendations from OptimizeResult
parse_rocky_output()	Auto-detect a Rocky JSON payload and return the matching Pydantic model

Documentation

• Dagster Integration docs — resource, component, translator, schedules, sensors, pipes, and more
• DEVELOPMENT.md — local setup, architecture, testing
• CHANGELOG.md — release notes

Related projects

• Rocky — the Rust SQL transformation engine
• Rocky VS Code extension — VS Code extension with LSP and AI features

License

Apache 2.0