WebJul 5, 2024 · Data ingested into a time series table ultimately ends up in chunks, its final resting place. Chunks can be managed (resized, dropped, etc) from the command line. Dropping chunks to purge old data is much more efficient than the usual alternatives. But, the true elegance of TimescaleDB lies in the fact that it is a PostgreSQL extension. WebJun 9, 2024 · SELECT * FROM timescaledb_information.compressed_chunk_stats; You will then see a list of chunks with their statuses: compression status and how much space is taken up by uncompressed and compressed data in bytes. If you don’t have the need to store data for a long period of time, you can delete out-of-date data to free up even more space.
Timescale Documentation About hypertables
WebSep 24, 2024 · TimescaleDB version (output of \dx in psql): [1.7.3] Installation method: ["using Docker"] Describe the bug i'm trying to drop chunks from a hypertable under some schema(not public). the hyper table has a continuous_aggregates view: SELECT drop_chunks(interval '2 days', 'tpadataaccess.tpa_tie') i get the following response: WebShows a list of the chunks that were dropped in the same style as the show_chunks function. Chunks are defined by a certain start ... drop_chunks -----_timescaledb_internal._hyper_3_5_chunk _timescaledb_internal._hyper_3_6_chunk _timescaledb_internal._hyper_3_7_chunk _timescaledb_internal._hyper_3_8_chunk … hotels near 4 yawkey way boston ma 02215
时空数据库实践(含 纽约TAXI数据透视分析) - PostGIS + TimescaleDB …
WebAll sizes are reported in bytes. If the function is executed on a distributed hypertable, it returns disk space usage information as a separate row per node. The access node is not … WebJul 9, 2024 · The show_chunks expects a regclass, which depending on your current search path means you need to schema qualify the table.. The following should work: SELECT … WebWith hypertables, Timescale makes it easy to improve insert and query performance by partitioning time-series data on its time parameter. Behind the scenes, the database … lily 10 hours