Re: Millions of tables

On Tue, Sep 27, 2016 at 10:15 AM, Terry Schmitt <tschmitt(at)schmittworks(dot)com>
wrote:

>
>
> On Sun, Sep 25, 2016 at 7:50 PM, Greg Spiegelberg <gspiegelberg(at)gmail(dot)com>
> wrote:
>
>> Hey all,
>>
>> Obviously everyone who's been in PostgreSQL or almost any RDBMS for a
>> time has said not to have millions of tables. I too have long believed it
>> until recently.
>>
>> AWS d2.8xlarge instance with 9.5 is my test rig using XFS on EBS (io1)
>> for PGDATA. Over the weekend, I created 8M tables with 16M indexes on
>> those tables. Table creation initially took 0.018031 secs, average
>> 0.027467 and after tossing out outliers (qty 5) the maximum creation time
>> found was 0.66139 seconds. Total time 30 hours, 31 minutes and 8.435049
>> seconds. Tables were created by a single process. Do note that table
>> creation is done via plpgsql function as there are other housekeeping tasks
>> necessary though minimal.
>>
>> No system tuning but here is a list of PostgreSQL knobs and switches:
>> shared_buffers = 2GB
>> work_mem = 48 MB
>> max_stack_depth = 4 MB
>> synchronous_commit = off
>> effective_cache_size = 200 GB
>> pg_xlog is on it's own file system
>>
>> There are some still obvious problems. General DBA functions such as
>> VACUUM and ANALYZE should not be done. Each will run forever and cause
>> much grief. Backups are problematic in the traditional pg_dump and PITR
>> space. Large JOIN's by VIEW, SELECT or via table inheritance (I am abusing
>> it in my test case) are no-no's. A system or database crash could take
>> potentially hours to days to recover. There are likely other issues ahead.
>>
>> You may wonder, "why is Greg attempting such a thing?" I looked at
>> DynamoDB, BigTable, and Cassandra. I like Greenplum but, let's face it,
>> it's antiquated and don't get me started on "Hadoop". I looked at many
>> others and ultimately the recommended use of each vendor was to have one
>> table for all data. That overcomes the millions of tables problem, right?
>>
>> Problem with the "one big table" solution is I anticipate 1,200 trillion
>> records. Random access is expected and the customer expects <30ms reads
>> for a single record fetch.
>>
>> No data is loaded... yet Table and index creation only. I am interested
>> in the opinions of all including tests I may perform. If you had this
>> setup, what would you capture / analyze? I have a job running preparing
>> data. I did this on a much smaller scale (50k tables) and data load via
>> function allowed close to 6,000 records/second. The schema has been
>> simplified since and last test reach just over 20,000 records/second with
>> 300k tables.
>>
>> I'm not looking for alternatives yet but input to my test. Takers?
>>
>> I can't promise immediate feedback but will do my best to respond with
>> results.
>>
>> TIA,
>> -Greg
>>
>
> I have not seen any mention of transaction ID wraparound mentioned in this
> thread yet. With the numbers that you are looking at, I could see this as a
> major issue.
>
> T
>

Thank you Terry. You get the gold star. :) I was waiting for that to
come up.

Success means handling this condition. A whole database vacuum and
dump-restore is out of the question. Can a properly tuned autovacuum
prevent the situation?

-Greg