adsb-ingestion

name	adsb-ingestion
description	Set up real-time ADS-B aircraft position ingestion from adsb.lol: create tables, network rules, external access integrations, Python ingestion procedures, flight-matching enrichment, scheduled tasks, and optional historical backfill. Subskill of aviation-installer — must be invoked from the router, not independently. Use when: configuring ADS-B data pipeline as part of installation. Do NOT use for: standalone execution, flight schedules (use flight-schedules), derived analytics (use derived-analytics). Triggers: ADS-B ingestion, aircraft tracking setup, adsb.lol, realtime aircraft data.
depends_on	["aviation-installer","base-setup"]
metadata	{"author":"Snowflake SIT-IS","version":"1.0.0","category":"infrastructure"}

ADS-B Ingestion Setup

This subskill cannot be run independently. It must be invoked from the aviation-installer router after base-setup completes.

Creates all ADS-B ingestion infrastructure: network rules, external access integrations for adsb.lol and GitHub APIs, ADS-B tables, Python ingestion procedures (realtime + ETL + enrichment), aircraft metadata enrichment, historical backfill procedures, and the core task chain (TASK_INGEST_ADSB → TASK_ENRICH_ADSB).

Prerequisites

• base-setup completed (PROPERTIES_AIRPORT exists with 1 row)
• ACCOUNTADMIN role (required for CREATE INTEGRATION and CREATE NETWORK RULE)
• Variables from router: {TARGET_DB}, {SCHEMA}, {IATA}, {ICAO}, {WAREHOUSE}, {CENTER_LAT}, {CENTER_LON}, {BACKFILL_DAYS}, {GIT_REPO_STAGE_BASE}

Required Privileges

Privilege	Scope	Reason
CREATE NETWORK RULE	Database	Creates rules for adsb.lol and GitHub APIs
CREATE INTEGRATION	Account	Creates external access integrations
CREATE SECRET	Schema	Creates secrets for API keys
CREATE PROCEDURE	Schema	Creates 15+ ingestion/ETL procedures
CREATE TASK	Schema	Creates TASK_INGEST_ADSB and TASK_ENRICH_ADSB
EXECUTE TASK	Account	Enables task execution

Configuration

Parameter	Default	Description
API_URL	https://api.adsb.lol/v2/point/{LAT}/{LON}/27	ADS-B endpoint (27nm radius)
RADIUS_NM	27	Capture radius in nautical miles (~50km)
BACKFILL_DAYS	5	Days of historical ADS-B to backfill
TASK_SCHEDULE	CRON '30 1 * * * UTC'	Daily ingestion schedule

Friction Logging

Report all friction points (errors, warnings, workarounds, race conditions) back to the parent installer using the F1/F2/F3 format from .cortex/skills/logs/README.md. The parent writes the consolidated friction log. If executing standalone, write to .cortex/skills/logs/friction-log_{YYYY-MM-DD}_{HH-MM}.md.

Workflow

Read the references/ subfiles for complete SQL:

• references/01-network-rules-eai.md — Network rules and EAIs
• references/02-tables.md — All tables (ADSB_DATA, helpers, flight matching)
• references/03a-schedule-enrichment.md — PROC_ENRICH_ADSB_WITH_SCHEDULE (flight-schedule matching)
• references/03b-aircraft-meta-enrichment.md — PROC_ENRICH_AIRCRAFT_META + backfill + task
• references/04-ingestion-procedures.md — Realtime ingestion procedures
• references/05-tasks-and-dag.md — Task DAG definitions
• references/06a-backfill-infra.md — Backfill stage, tables
• references/06b-backfill-download.md — PROC_DOWNLOAD_TO_STAGE
• references/06c-backfill-extract.md — PROC_EXTRACT_TO_NDJSON
• references/06d-backfill-load-filter.md — PROC_LOAD_NDJSON_TO_INTERIM + PROC_FILTER_AND_INSERT_SQL
• references/06e-backfill-orchestrators.md — PROC_PROCESS_FROM_STAGE, PROC_BACKFILL_ADSB_HISTORY, PROC_START_BACKFILL_HISTORY
• references/06f-backfill-retry-cleanup.md — Retry wrappers, cleanup, tags, usage reference

Execute ALL SQL from each file. Do NOT skip or optimize away any queries.

Step 0: Set Query Tag

ALTER SESSION SET query_tag = '{"origin":"sf_sit-is-aviation","name":"oss-aviation-adsb-ingestion","version":{"major":1,"minor":0},"attributes":{"is_quickstart":1,"source":"sql"}}';

Step 1: Create Network Rules

Create 2 network rules in {TARGET_DB}.{SCHEMA}:

• {SCHEMA}_adsb_lol_rule — allows api.adsb.lol:443
• {SCHEMA}_github_rule — allows api.github.com, github.com, objects.githubusercontent.com, release-assets.githubusercontent.com

Step 2: Create External Access Integrations

Create 2 EAIs (account-level objects, require ACCOUNTADMIN):

• {EAI_ADSB_LOL} (e.g., AIRPORT_SAN_PUBLIC_ADSB_LOL_EAI) — for realtime position fetch
• {EAI_GITHUB} (e.g., AIRPORT_SAN_PUBLIC_GITHUB_EAI) — for historical ADS-B archive download

Note: EAI names are derived by replacing non-alphanumeric characters in {TARGET_DB}_{SCHEMA} with underscores.

Step 3: Create ADS-B Tables

Create core tables:

• HELPER_ADSB_LOL_RAW — raw JSON responses from adsb.lol (Bronze layer)
• HELPER_AIRCRAFT_META — aircraft type and description lookup (populated by enrichment procedure)
• ADSB_DATA — canonical ADS-B position records (Gold layer) with flight matching fields

Step 4: Create Staging Infrastructure

Create:

• ADSB_HISTORY_STAGE — internal stage for historical ADS-B TAR archives
• FF_AIRLINES_CSV — already created in base-setup (skip if exists)
• HELPER_ADSB_BACKFILL_STATUS — backfill tracking per-day status table
• HELPER_ADSB_HISTORY_INTERIM — interim table for raw JSON from backfill

Step 5: Create Ingestion Procedures

Create Python stored procedures:

• PROC_INGEST_ADSB_REALTIME() — fetches live positions from adsb.lol API, inserts into HELPER_ADSB_LOL_RAW
• PROC_ETL_ADSB_TO_DATA() — transforms Bronze → Gold (ADSB_DATA), deduplicates by icao24+timestamp
• PROC_DEDUP_ADSB_DATA(INT) — removes duplicate position records older than N days
• PROC_ADSB_INGEST_AND_ETL() — orchestrates PROC_INGEST_ADSB_REALTIME + PROC_ETL_ADSB_TO_DATA

Step 6: Create Flight Enrichment Procedures

Create procedures for matching ADS-B tracks to flight schedules:

• PROC_ENRICH_ADSB_WITH_SCHEDULE(INT) — matches ADSB_DATA tracks to FLIGHT_SCHEDULE by callsign, time, and O/D proximity; populates HELPER_FLIGHT_LEG, HELPER_FLIGHT_MATCH_CANDIDATES, HELPER_FLIGHT_MATCH_RESULT
• Helper tables: HELPER_FLIGHT_LEG, HELPER_FLIGHT_MATCH_CANDIDATES, HELPER_FLIGHT_MATCH_RESULT, HELPER_RECURRING_CALLSIGN_PRIOR

Step 7: Create Aircraft Metadata Procedures

• PROC_ENRICH_AIRCRAFT_META(INT, INT, INT) — Python procedure that fetches aircraft type/description from GitHub aircraft database, populates HELPER_AIRCRAFT_META
• PROC_BACKFILL_ADSB_AIRCRAFT_DESC(INT) — backfills description field on existing ADSB_DATA rows
• PROC_ENRICH_AIRCRAFT_META_AND_BACKFILL() — orchestrates both

Step 8: Create Historical Backfill Procedures

Python procedures for downloading globe_history archives from adsb.lol GitHub releases:

• PROC_DOWNLOAD_TO_STAGE(VARCHAR) — downloads TAR.GZ to ADSB_HISTORY_STAGE
• PROC_EXTRACT_TO_NDJSON(VARCHAR) — extracts NDJSON from TAR in stage
• PROC_LOAD_NDJSON_TO_INTERIM(VARCHAR) — loads NDJSON into HELPER_ADSB_HISTORY_INTERIM
• PROC_FILTER_AND_INSERT_SQL(VARCHAR) — filters to airport bbox and inserts into ADSB_DATA
• PROC_PROCESS_FROM_STAGE(VARCHAR) — orchestrates extract→load→filter for one day
• PROC_BACKFILL_ADSB_HISTORY() — main backfill loop, iterates over pending days
• PROC_RUN_BACKFILL_ONCE() — wrapper that runs backfill once then suspends TASK_ADSB_BACKFILL_ONCE
• PROC_RUN_BACKFILL_RETRY_UTC() — retry wrapper for failed days
• PROC_START_BACKFILL_HISTORY() — seeds HELPER_ADSB_BACKFILL_STATUS and creates/resumes TASK_ADSB_BACKFILL_ONCE
• PROC_START_BACKFILL_RETRY_UTC() — creates/resumes TASK_ADSB_BACKFILL_RETRY
• PROC_CLEANUP_STAGE(VARCHAR) — removes processed files from stage

Step 9: Create Monitoring and Audit Tables

• HELPER_INSTALL_AUDIT — installation record (already created in base-setup; insert row here if not done)
• HELPER_MONITOR_LAST_REFRESH — tracks last refresh timestamps per object
• HELPER_QA_COUNTS_DAILY — QA row counts per table per day
• HELPER_INGEST_AUDIT — per-run ingest audit log

Step 10: Create Core Tasks

CREATE TASK {TARGET_DB}.{SCHEMA}.TASK_INGEST_ADSB
  WAREHOUSE = {WAREHOUSE}
  SCHEDULE = 'USING CRON 30 1 * * * UTC'
  COMMENT = '{"origin":"sf_sit-is-aviation","name":"oss-aviation-adsb-ingestion","version":{"major":1,"minor":0},"attributes":{"is_quickstart":1,"source":"sql"}}'
  AS CALL {TARGET_DB}.{SCHEMA}.PROC_ADSB_INGEST_AND_ETL();

CREATE TASK {TARGET_DB}.{SCHEMA}.TASK_ENRICH_ADSB
  WAREHOUSE = {WAREHOUSE}
  COMMENT = '{"origin":"sf_sit-is-aviation","name":"oss-aviation-adsb-ingestion","version":{"major":1,"minor":0},"attributes":{"is_quickstart":1,"source":"sql"}}'
  AFTER {TARGET_DB}.{SCHEMA}.TASK_INGEST_ADSB
  AS CALL {TARGET_DB}.{SCHEMA}.PROC_ENRICH_ADSB_WITH_SCHEDULE(1);

CREATE TASK {TARGET_DB}.{SCHEMA}.TASK_ENRICH_AIRCRAFT_META
  WAREHOUSE = {WAREHOUSE}
  SCHEDULE = 'USING CRON 15 3 * * * UTC'
  COMMENT = '{"origin":"sf_sit-is-aviation","name":"oss-aviation-adsb-ingestion","version":{"major":1,"minor":0},"attributes":{"is_quickstart":1,"source":"sql"}}'
  AS CALL {TARGET_DB}.{SCHEMA}.PROC_ENRICH_AIRCRAFT_META_AND_BACKFILL();

Note: Do NOT resume tasks here. The router resumes all tasks together in Step 5 after all sub-skills complete.

Step 11: Verify

SELECT 'HELPER_ADSB_LOL_RAW' AS OBJ, COUNT(*) AS CNT FROM {TARGET_DB}.{SCHEMA}.HELPER_ADSB_LOL_RAW
UNION ALL SELECT 'ADSB_DATA', COUNT(*) FROM {TARGET_DB}.{SCHEMA}.ADSB_DATA
UNION ALL SELECT 'HELPER_AIRCRAFT_META', COUNT(*) FROM {TARGET_DB}.{SCHEMA}.HELPER_AIRCRAFT_META;

Expected: 0 rows (data arrives after tasks run). Verify objects exist by checking INFORMATION_SCHEMA.PROCEDURES.

Stopping Points

• After Step 2: Confirm all 2 EAIs exist (SHOW INTEGRATIONS LIKE '%{IATA}%')
• After Step 5: Test ingestion manually: CALL {TARGET_DB}.{SCHEMA}.PROC_INGEST_ADSB_REALTIME()
• After Step 10: Confirm tasks exist (SUSPENDED state expected): SHOW TASKS IN {TARGET_DB}.{SCHEMA}

Troubleshooting

Error	Cause	Fix
EAI creation fails	Insufficient privileges	ACCOUNTADMIN required; check role with SELECT CURRENT_ROLE()
PROC_INGEST_ADSB_REALTIME fails	EAI misconfigured	Test with CALL PROC_INGEST_ADSB_REALTIME() and check error
Python packages not installing	Anaconda agreement missing	Run CALL SYSTEM$ACCEPT_LEGAL_TERMS('ANACONDA') with ACCOUNTADMIN
No data after 10 min	Incorrect bounding box	Verify airport bounding box in PROPERTIES_AIRPORT; check API endpoint coverage
Backfill procedures missing	Package agreement	Python procedures require ANACONDA_PACKAGE_AGREEMENT on account

Return to Router

After completing all steps, return to the aviation-installer router. If an API key was provided, continue with flight-schedules. Otherwise, continue with derived-analytics.

Cleanup

Use the aviation-cleanup skill for automated tag-based teardown. Manual cleanup:

ALTER TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_INGEST_ADSB SUSPEND;
ALTER TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ENRICH_ADSB SUSPEND;
ALTER TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ENRICH_AIRCRAFT_META SUSPEND;
ALTER TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ADSB_BACKFILL_ONCE SUSPEND;
ALTER TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ADSB_BACKFILL_RETRY SUSPEND;

DROP TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_INGEST_ADSB;
DROP TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ENRICH_ADSB;
DROP TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ENRICH_AIRCRAFT_META;
DROP TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ADSB_BACKFILL_ONCE;
DROP TASK IF EXISTS {TARGET_DB}.{SCHEMA}.TASK_ADSB_BACKFILL_RETRY;
DROP TABLE IF EXISTS {TARGET_DB}.{SCHEMA}.ADSB_DATA;
DROP TABLE IF EXISTS {TARGET_DB}.{SCHEMA}.HELPER_ADSB_LOL_RAW;