This is my personal collection of SQL examples and proof-of-concept files, specifically focused on TimescaleDB features and capabilities. The repository features a diverse range of SQL files demonstrating time-series data handling, hypertables, continuous aggregates, and other TimescaleDB-specific functionality.
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Start TimescaleDB: Use the Docker setup to run TimescaleDB locally:
./run_timescale_docker.sh
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Load environment: Source the environment variables:
source .env -
Run any SQL snippet: Use the helper script to execute snippets:
./psql_cmd.sh <filename.sql>
Example:
./psql_cmd.sh sensors.sql
- TimescaleDB Docker: Uses
timescale/timescaledb-ha:pg17.4-ts2.21.3-all - Connection:
postgres://postgres:password@localhost:5432/postgres - No pager: All psql commands are configured to disable paging for better command-line experience
TimescaleDB Core Features: Files like hypertable_model.sql, caggs.sql, compression.sql, and retention.sql demonstrate the core TimescaleDB functionality including hypertables, continuous aggregates, compression policies, and data retention.
Time-Series Analytics: Files such as bollinger_bands.sql, correlation_matrix.sql, ohlcv.sql, and frequency.sql showcase advanced time-series analysis techniques using TimescaleDB's analytical functions.
Background Jobs & Automation: Examples like job.sql, jobs.sql, and various caggs files demonstrate TimescaleDB's background job system for automated data processing and maintenance.
Performance & Scale: Files like massive_distributed_inserts.sql, chunk_skipping.sql, and skip_scan_example.sql provide insights into TimescaleDB's performance optimization features.
- All SQL files are self-contained and can be executed independently
- Each file includes necessary setup and demonstrates specific TimescaleDB features
- Use
#file:run_timescale_docker.shreference for database connection in any new snippets - Focus on practical, real-world TimescaleDB use cases