Louisville KY 311
Public data
Louisville KY 311 data, published as Louisville KY 311 publishes it. Ingest delivers this data to a data warehouse you own as one table, and updates it on the schedule you choose. There is no code to write and nothing to install.
- 140,313rows as of September 2026
- About 3,600new rows a week
- 1 tablein your warehouse
What you get
| Table | Each row is |
|---|---|
featureserverfeatureserver | Louisville Metro (LOJIC) 311 service requests published in the metro_311_2026 ArcGIS FeatureServer layer, the current one-layer-per-calendar-year series. Measured 2026-09-16: 140,313 requests with requested_datetime 2026-01-01 through 2026-09-13. Each run re-reads the entire layer and loads with replace, so the destination mirrors the layer at read time, including later edits and any retractions; the paginated multi-request read of a live layer is not an atomic snapshot. Earlier calendar years are separate layers (metro_311_2022, metro_call_311_service_requests_2023, ...) and are not included, and nothing here claims retention beyond what the publisher keeps. ArcGIS native Date fields (requested_datetime, updated_datetime, closed_date) arrive as Unix epoch MILLISECONDS and are preserved as bigint; they are not timestamps. Rows are keyed on ObjectId, the layer's row id, because service_request_id is not unique in the layer: on 2026-09-16 one request appeared as two rows identical in every field but ObjectId. |
How it works
- Choose Louisville KY 311. The data is public, so there is nothing to sign in to.
- Pick where it goes. BigQuery, Snowflake, Databricks, Redshift and 10 more, in an account you own.
- Pick a schedule. Daily is the default, and weekly and monthly are there too.
- Ingest runs it from then on. If a run fails, your dashboard shows which table and why.
Questions
- Do I need an account with Louisville KY 311?
- No. The data is public, so there is nothing to sign up for and nothing to paste in.
- Which warehouses can Louisville KY 311 data go to?
- Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL and Snowflake, in an account you own.
- How fresh is the data?
- As fresh as your schedule: daily by default, or weekly or monthly. Schedules as often as every 15 minutes are on the Enterprise plan.
- Will running it again create duplicate rows?
- No. Each run replaces the table, so it never holds two copies of the same row.
- Do I need to write code?
- No. Ingest builds, runs and maintains the connector. Someone with access to your warehouse connects it once, following a short guide.
For your data team: technical reference
Connector louisville_311, version 0.1.0, a REST source, status beta, authentication none.
Vendor documentation: https://services1.arcgis.com/79kfd2K6fskCAkyg/arcgis/rest/services/metro_311_2026/FeatureServer/0
Configuration
No configuration required.
Resources
| Resource | Status | Plan | Write | Primary key | Overrides |
|---|---|---|---|---|---|
featureserverLouisville Metro (LOJIC) 311 service requests published in the metro_311_2026 ArcGIS FeatureServer layer, the current one-layer-per-calendar-year series. Measured 2026-09-16: 140,313 requests with requested_datetime 2026-01-01 through 2026-09-13. Each run re-reads the entire layer and loads with replace, so the destination mirrors the layer at read time, including later edits and any retractions; the paginated multi-request read of a live layer is not an atomic snapshot. Earlier calendar years are separate layers (metro_311_2022, metro_call_311_service_requests_2023, ...) and are not included, and nothing here claims retention beyond what the publisher keeps. ArcGIS native Date fields (requested_datetime, updated_datetime, closed_date) arrive as Unix epoch MILLISECONDS and are preserved as bigint; they are not timestamps. Rows are keyed on ObjectId, the layer's row id, because service_request_id is not unique in the layer: on 2026-09-16 one request appeared as two rows identical in every field but ObjectId. | beta | full | replace | ObjectId | - |
Where this lands, and what else connects
Setting up the destination is its own short guide, one per warehouse or lake: Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL, Snowflake.
Other sources Ingest connects for government teams: Abilene TX 311, Albany NY 311, Ann Arbor MI 311, Anne Arundel County MD 311, Auburn WA 311, Aurora IL 311.
- How Ingest reads a REST source
- Ingest for government teams
- The tables Ingest creates
- Every source Ingest connects
Get Louisville KY 311 data into your warehouse
Last updated .