Linux kernel patches boost PG performance up to twice:
https://www.phoronix.com/news/MGLRU-Reaches-mm-stable
https://www.phoronix.com/news/MGLRU-Reaches-mm-stable
Phoronix
MGLRU Patches Merged To "mm-stable" Ahead Of Linux 6.1 - New Benchmarks Look Good
As further indication of MGLRU hopefully being mainlined for Linux 6.1 as planned, the Multi-Gen LRU patches have now been moved to Andrew Morton's mm-stable branch.
At what conference for the second year in a row was the author of this channel not invited to speak? :)
In short, about MERGE in just released Postgres 15:
https://twitter.com/samokhvalov/status/1580935490580058112
https://twitter.com/samokhvalov/status/1580935490580058112
Twitter
Two things MERGE lacks now:
- RETURNING clause to allow user to see what exactly was done and save on RTT
- WHEN NOT MATCHED BY [SOURCE|TARGET] to allow easy syncing with source - e.g., ETL
The former is postgresism, the latter is what SQL Server has (but…
- RETURNING clause to allow user to see what exactly was done and save on RTT
- WHEN NOT MATCHED BY [SOURCE|TARGET] to allow easy syncing with source - e.g., ETL
The former is postgresism, the latter is what SQL Server has (but…
Lads - check out our super serious (no) reel for Techcrunch Disrupt!
https://youtu.be/RxijVdlUBZk
Ps: no sound needed :)
https://youtu.be/RxijVdlUBZk
Ps: no sound needed :)
MySQL HeatWave Performance Comparison
- 11X faster than Redshift
- 9X faster than Snowflake
- 9X faster than BigQuery
- 3X faster than Synapse
https://www.oracle.com/mysql/heatwave/performance/
- 11X faster than Redshift
- 9X faster than Snowflake
- 9X faster than BigQuery
- 3X faster than Synapse
https://www.oracle.com/mysql/heatwave/performance/
Oracle
HeatWave MySQL Performance Comparisons
HeatWave MySQL on OCI outperforms top cloud databases.
A few PG hacks from Alibaba (thx to @olegkovalov)
1) PostgreSQL Graph Search Practices - 10 Billion-Scale Graph with Millisecond Response
https://www.alibabacloud.com/blog/postgresql-graph-search-practices---10-billion-scale-graph-with-millisecond-response_595039
2) Social Friend Relationship System Practice in PostgreSQL - Accelerating Queries of Positive and Negative Relationships
https://www.alibabacloud.com/blog/595043
1) PostgreSQL Graph Search Practices - 10 Billion-Scale Graph with Millisecond Response
https://www.alibabacloud.com/blog/postgresql-graph-search-practices---10-billion-scale-graph-with-millisecond-response_595039
2) Social Friend Relationship System Practice in PostgreSQL - Accelerating Queries of Positive and Negative Relationships
https://www.alibabacloud.com/blog/595043
Any of you in St. Petersburg now? Let me know, there is a surprise for you :)
https://postgresml.org/blog/postgresml-is-8x-faster-than-python-http-microservices/#why-latency-is-important
(thx to @olegkovalov)
(thx to @olegkovalov)
PostgresML
PostgresML is 8-40x faster than Python HTTP microservices – PostgresML
PostgresML's architecture gives it a huge performance advantage over traditional deployments when it comes to latency, throughput and memory utilization.
duckdb going mad...
UNION Type
UNION Type
CREATE TABLE messages(u UNION(num INT, error VARCHAR));FROM-first
INSERT INTO messages VALUES (42);
INSERT INTO messages VALUES ('oh my globs');
-- SELECT clause is optional, SELECT * is implied (if not included)BTW SQL standard already has special syntax for it:
FROM tbl;
-- first 5 rows of the table
FROM tbl LIMIT 5;
-- SELECT can be used after the FROM
FROM tbl SELECT l_orderkey;
-- insert all data from tbl1 into tbl2
INSERT INTO tbl2 FROM tbl1;
TABLE tbl;COLUMNS Expression
SELECT MIN(COLUMNS(*)), COUNT(*) from obs;List comprehension support
SELECT COLUMNS('val[0-9]+') from obs;
SELECT [x + 1 for x in [1, 2, 3]] AS l;
DuckDB
Announcing DuckDB 0.6.0
The DuckDB team is happy to announce the latest DuckDB version (0.6.0) has been released. This release of DuckDB is named “Oxyura” after the White-headed duck (Oxyura leucocephala) which is an endangered species native to Eurasia. To install the new version…
There will be no singularity
absolutely cursed…
Now in snowflake...
... and in dwh.dev and parsers.dev!
create table t (a int, b int, c int);
create view v as
select * exclude (a) rename (b as d, c as e) from t
;
... and in dwh.dev and parsers.dev!
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