Job Templates
These templates show how to call lakelogic-driver in major orchestrators.
Update paths, credentials, and schedules to match your environment.
State & Scheduling Notes
- Use your orchestrator for schedules, retries, and alerting.
- Set
--window last_successto pick up where the prior run left off (uses run log tables). - Add
--summary-pathto emit a per-run JSON summary that you can archive or parse into metrics. - Add
--summary-tablewith--summary-backendto write run summaries into a table for dashboards (Spark, Snowflake, BigQuery, DuckDB, SQLite). - Add
--metrics-pathfor a lightweight metrics payload or--metrics-backend statsdfor real-time monitoring. - Use
--metrics-backend prometheusto expose a/metricsendpoint for scraping. - Use
--continue-on-errorif you want a best-effort run that reports all failures in one pass.
Airflow
File: examples/job_templates/airflow_dag.py
Prefect
File: examples/job_templates/prefect_flow.py
Dagster
File: examples/job_templates/dagster_job.py
Databricks Jobs
File: examples/job_templates/databricks_job.json
Azure Synapse Pipelines
File: examples/job_templates/synapse_pipeline.json
Microsoft Fabric Pipelines
File: examples/job_templates/fabric_pipeline.json
Azure Data Factory
File: examples/job_templates/adf_pipeline.json
AWS Glue
File: examples/job_templates/aws_glue_job.py
AWS Step Functions
File: examples/job_templates/aws_step_functions.json