2
votes

Running a query such as the following:

SELECT some_column FROM [myproject.mytable] LIMIT 1000

Over a dataset that is approximately 240 million rows (where the columns queryable size is less than 2GB) takes over 140 seconds to complete.

Is there something I can do to improve the tables query performance? Or am I missing something?

Edit:

Job id for reference: job__aamhffrd45gp6VEYDjQCK1JDH8

Edit 2:

Ive identified a pattern which is that it seems to be only the table that is currently being written to that is exceedingly slow, however this is still a large problem for me.

1
This is not normal, but a BQ engineer could verify. For that king of support, you will need to provide a job id. Also: It might be a network problem (transmitting 1000 results). Can you try the same query with LIMIT 10? - Felipe Hoffa
The limit did not seem to effect it at all (and I am trying from the Web ui currently) - I will post a job ID soon. - Ewan Walker
@EwanWalker try this SELECT some_column FROM [myproject.mytable] a JOIN (SELECT id FROM [myproject.mytable] ORDER BY id LIMIT 1000, 10) as b ON b.id = a.id - Alexander
@AlexanderGrebenshikov Unfortunately as this is a raw statistical table there are no IDs as there is no value to having one in such a data set (as far as I know being that it is non-relational data) - Ewan Walker
@AlexanderGrebenshikov he is using Google Bigquery and not MySQL. - Pentium10

1 Answers

0
votes

As of the time of posting this, I have been informed that Google knows of the issue and there is no ETA on a fix for the issue as of yet. This ended up being an issue on their end.