cnmjbm

5 ms·

1.
by cnmjbm 6y ago
Before details of the benchmark is disclosed, whoever believes in this claim, it is not me.
2.
by cnmjbm 6y ago
Can someone educate me about which of the two approaches mentioned below is better, Snowflake's separated compute from storage or ElasticSearch's aggressive sharding? Thanks in advance!
3.
by cnmjbm 6y ago
Yeah. I knew that, but removing them afterwards seems "a big chunk of work" and never being a satisfactory solution, eg: [1] https://community.snowflake.com/s/question/0D50Z00007Ft37mSA... [2] https:&#x
4.
by cnmjbm 6y ago
Snowflake documentation notes "Snowflake supports defining and maintaining constraints, but does not enforce them.". So it is possible that Snowflake users can get inaccurate analytic results from accidentally duplicated data. How
5.
by cnmjbm 6y ago
I hope he's right this time :o) https://www.youtube.com/watch?v=KmXJSeMaoTY
6.
by cnmjbm 6y ago
The comment "...If you are doing streaming etc, you could end up with a lot more data..." is interesting. Can have more details? For the comment "If amazon us east is down...they need to explicitly copy eveything from east to
7.
by cnmjbm 6y ago
https://nattaylor.com/blog/2019/snowflake-internals/
8.
by cnmjbm 6y ago
The point that ML requires lots of compute on few bytes makes senses as ML performs mostly repetitive matrix operations, but doesn't a series of SQL queries on database data with a "star schema" also require lots of compute o
9.
Is GPU Database a Hype?
2 points by cnmjbm 6y ago|2 comments