Log message:
postgresql-timescaledb: updated to 2.17.2

2.17.2 (2024-11-06)

This release contains bug fixes since the 2.17.1 release. We recommend that you
upgrade at the next available opportunity.

Bugfixes

Fix "negative bitmapset member not allowed" and performance degradation
on queries to compressed tables with ORDER BY clause matching the order of the
compressed data
Use-after-free in vectorized grouping by segmentby columns

2.17.1 (2024-10-21)

This release contains performance improvements and bug fixes since the 2.17.0 \ 
release. We recommend that you upgrade at the next available opportunity.

Features

Add chunk skipping GUC
Bugfixes

Change log level used in compression
Fix collation for in-memory tuple filtering

2.17.0 (2024-10-08)

This release adds support for PostgreSQL 17, significantly improves the \ 
performance of continuous aggregate refreshes, and contains performance \ 
improvements for analytical queries and delete operations over compressed \ 
hypertables.
We recommend that you upgrade at the next available opportunity.

Highlighted features in TimescaleDB v2.17.0

Full PostgreSQL 17 support for all existing features. TimescaleDB v2.17 is \ 
available for PostgreSQL 14, 15, 16, and 17.

Significant performance improvements for continuous aggregate policies:
Continuous aggregate refresh is now using merge instead of deleting old \ 
materialized data and re-inserting. This update can decrease dramatically the \ 
amount of data that must be written on the continuous aggregate in the presence \ 
of a small number of changes, reduce the i/o cost of refreshing a continuous \ 
aggregate, and generate fewer Write-Ahead Logs (WAL). Overall, continuous \ 
aggregate policies will be more lightweight, use less system resources, and \ 
complete faster.

Increased performance for real-time analytical queries over compressed hypertables:
We are excited to introduce additional Single Instruction, Multiple Data (SIMD) \ 
vectorization optimization to our engine by supporting vectorized execution for \ 
queries that group by using the segment_by column(s) and aggregate using the \ 
basic aggregate functions (sum, count, avg, min, max).
Stay tuned for more to come in follow-up releases! Support for grouping
on additional columns, filtered aggregation,
vectorized expressions, and time_bucket is coming soon.

Improved performance of deletes on compressed hypertables when a large amount of \ 
data is affected.
This improvement speeds up operations that delete whole segments by skipping the \ 
decompression step. It is enabled for all deletes that filter by the segment_by \ 
column(s).

Log message:
*: replace CMAKE_ARGS with CMAKE_CONFIGURE_ARGS

Log message:
postgresql-timescaledb: updated to 2.16.1

2.16.1

This release contains bug fixes since the 2.16.0 release. We recommend that you \ 
upgrade at the next available opportunity.

Bugfixes

Fix untier_chunk for hypertables with foreign keys

Log message:
postgresql-timescaledb: updated to 2.16.0

2.16.0

This release contains significant performance improvements when working with \ 
compressed data, extended join
support in continuous aggregates, and the ability to define foreign keys from \ 
regular tables towards hypertables.
We recommend that you upgrade at the next available opportunity.

In TimescaleDB v2.16.0 we:

Introduce multiple performance focused optimizations for data manipulation \ 
operations (DML) over compressed chunks.
Improved upsert performance by more than 100x in some cases and more than 1000x \ 
in some update/delete scenarios.
Add the ability to define chunk skipping indexes on non-partitioning columns of \ 
compressed hypertables
TimescaleDB v2.16.0 extends chunk exclusion to use those skipping (sparse) \ 
indexes when queries filter on the relevant columns,
and prune chunks that do not include any relevant data for calculating the query \ 
response.
Offer new options for use cases that require foreign keys defined.
You can now add foreign keys from regular tables towards hypertables. We have \ 
also removed
some really annoying locks in the reverse direction that blocked access to \ 
referenced tables
while compression was running.
Extend Continuous Aggregates to support more types of analytical queries.
More types of joins are supported, additional equality operators on join clauses, and
support for joins between multiple regular tables.
Highlighted features in this release

Improved query performance through chunk exclusion on compressed hypertables.
You can now define chunk skipping indexes on compressed chunks for any column \ 
with one of the following
integer data types: smallint, int, bigint, serial, bigserial, date, timestamp, \ 
timestamptz.

After you call enable_chunk_skipping on a column, TimescaleDB tracks the min and \ 
max values for
that column. TimescaleDB uses that information to exclude chunks for queries \ 
that filter on that
column, and would not find any data in those chunks.

Improved upsert performance on compressed hypertables.
By using index scans to verify constraints during inserts on compressed chunks, \ 
TimescaleDB speeds
up some ON CONFLICT clauses by more than 100x.

Improved performance of updates, deletes, and inserts on compressed hypertables.
By filtering data while accessing the compressed data and before decompressing, \ 
TimescaleDB has
improved performance for updates and deletes on all types of compressed chunks, \ 
as well as inserts
into compressed chunks with unique constraints.

By signaling constraint violations without decompressing, or decompressing only \ 
when matching
records are found in the case of updates, deletes and upserts, TimescaleDB \ 
v2.16.0 speeds
up those operations more than 1000x in some update/delete scenarios, and 10x for \ 
upserts.

You can add foreign keys from regular tables to hypertables, with support for \ 
all types of cascading options.
This is useful for hypertables that partition using sequential IDs, and need to \ 
reference those IDs from other tables.

Lower locking requirements during compression for hypertables with foreign keys
Advanced foreign key handling removes the need for locking referenced tables \ 
when new chunks are compressed.
DML is no longer blocked on referenced tables while compression runs on a hypertable.

Improved support for queries on Continuous Aggregates
INNER/LEFT and LATERAL joins are now supported. Plus, you can now join with \ 
multiple regular tables,
and you can have more than one equality operator on join clauses.

PostgreSQL 13 support removal announcement

Following the deprecation announcement for PostgreSQL 13 in TimescaleDB v2.13,
PostgreSQL 13 is no longer supported in TimescaleDB v2.16.

The Currently supported PostgreSQL major versions are 14, 15 and 16.

Log message:
postgresql-timescaledb: updated to 2.15.3

2.15.3

Bugfixes

* Fix the handling of multiple unique indexes in a compressed INSERT.
* Fix the corresponding equivalence member not found error.
* Fix the leaks in the DML functions.
* Fix the error when acquiring a tuple lock on the OSM chunks on the replica.
* Fix ORDER BY/GROUP BY expression not found in targetlist on PG16

Log message:
postgresql-timescaledb: updated to 2.15.2

Release 2.15.2

Bugfixes

Fix sort pushdown for partially compressed chunks.
Fix removal of metadata function and update script.
Fix segfault in compress_chunk with a primary space partition.
Disallow hash partitioning on primary column.

Log message:
postgresql-timescaledb: updated to 2.15.1

2.15.1 (2024-05-28)

This release contains performance improvements and bug fixes since
the 2.15.0 release. Best practice is to upgrade at the next
available opportunity.

Log message:
postgresql-timescaledb: updated to 2.15.0

2.15.0

This release contains the performance improvements and bug fixes introduced since
TimescaleDB v2.14.2. Best practice is to upgrade at the next available opportunity.

Highlighted features in this release

Continuous Aggregate now supports time_bucket with origin and/or offset.
The following improvements have been introduced for hypertable compression:
Added planner support to check more kinds of WHERE conditions before decompression.
This reduces the number of rows that have to be decompressed.
You can now use minmax sparse indexes when you compress columns with btree indexes.
Make compression uses the defaults functions.
Vectorize filters in the WHERE clause contain text equality operators and LIKE \ 
expressions.