Re: Seeking Suggestions for Best Practices: Archiving and Migrating Historical Data in PostgreSQL

Hmm... that was a few years ago, back when v12 was new. It took about a
month (mainly because they didn't want me running exports during "office
hours").

There were 120 INSERT & SELECT (no UPDATE or DELETE) tables, so I was able
to add indices on date columns, create by-month views. (We migrated the
dozen or so *relatively* small UPDATE tables on cut-over day. On that same
day, I migrated the current month and the previous month's data in those
120 tables.

I made separate cron jobs to:
- export views from Oracle into COPY-style tab-separated flat files,
- lz4-compress views that had finished exporting, and
- scp files that were finished compressing, to an AWS EC2 VM.

These jobs pipelined, so there was always a job exporting, always a job
ready to compress tsv files, and another job ready to scp the lz4 files.
When there was nothing for a step to do, the job would sleep for a couple
of minutes, then check if there was more work to do.

On the AWS EC2 VM, a different cron job waited for files to finish
transferring, then loaded them into the correct table. Just like with the
source host jobs, the "load" job would sleep a bit and then check for more
work. I manually applied Indices.

The AWS RDS PG12 database was about 4TB. Snapshots were handled by AWS.
If this had been one of my on-prem systems, I'd have used pgbackrest.
(pgbackrest is impressively fast: takes good advantage of PG's 1GB file
max, and globs "small" files into one big file.)

On Fri, May 30, 2025 at 12:15 PM Andy Hartman <hartman60home(at)gmail(dot)com>
wrote:

> what was the duration start to finish of the migration of the 6tb of data.
> then what do you use for a quick backup after archived PG data
>
> Thanks.
>
> On Fri, May 30, 2025 at 11:29 AM Ron Johnson <ronljohnsonjr(at)gmail(dot)com>
> wrote:
>
>> On Fri, May 30, 2025 at 3:51 AM Motog Plus <mplus7535(at)gmail(dot)com> wrote:
>>
>>> Hi Team,
>>>
>>> We are currently planning a data archival initiative for our production
>>> PostgreSQL databases and would appreciate suggestions or insights from the
>>> community regarding best practices and proven approaches.
>>>
>>> **Scenario:**
>>> - We have a few large tables (several hundred million rows) where we
>>> want to archive historical data (e.g., older than 1 year).
>>> - The archived data should be moved to a separate PostgreSQL database
>>> (on a same or different server).
>>> - Our goals are: efficient data movement, minimal downtime, and safe
>>> deletion from the source after successful archival.
>>>
>>> - PostgreSQL version: 15.12
>>> - Both source and target databases are PostgreSQL.
>>>
>>> We explored using `COPY TO` and `COPY FROM` with CSV files, uploaded to
>>> a SharePoint or similar storage system. However, our infrastructure team
>>> raised concerns around the computational load of large CSV processing and
>>> potential security implications with file transfers.
>>>
>>> We’d like to understand:
>>> - What approaches have worked well for you in practice?
>>>
>>
>> This is how I migrated 6TB of data from an Oracle database to Postgresql,
>> and then implemented quarterly archiving of the PG database:
>> - COPY FROM (SELECT * FROM live_table WHERE date_fld in
>> some_manageable_date_range) TO STDOUT.
>> - Compress
>> - scp
>> - COPY TO archive_table.
>> - Index
>> - DELETE FROM live_table WHERE date_fld in some_manageable_date_range
>> (This I only did in the PG archive process
>>
>> (Naturally, the Oracle migration used Oracle-specific commands.)
>>
>> - Are there specific tools or strategies you’d recommend for ongoing
>>> archival?
>>>
>>
>> I write generic bash loops to which you pass an array that contains the
>> table name, PK, date column and date range.
>>
>> Given a list of tables, it did the COPY FROM, lz4 and scp. Once that
>> finished successfully, another script dropped archive indices on the
>> current table, COPY TO and CREATE INDEX statements. A third script did the
>> deletes.
>>
>> This works even when the live database tables are all connected via FK.
>> You just need to carefully order the tables in your script.
>>
>>
>>> - Any performance or consistency issues we should watch out for?
>>>
>>
>> My rules for scripting are "bite-sized pieces" and "check those return
>> codes!".
>>
>>
>>> Your insights or any relevant documentation/pointers would be immensely
>>> helpful.
>>>
>>
>> Index support uber alles. When deleting from a table which relies on a
>> foreign key link to a table which _does_ have a date field, don't hesitate
>> to join on that table.
>>
>> And DELETE of bite-sized chunks is faster than people give it credit for.
>>
>> --
>> Death to <Redacted>, and butter sauce.
>> Don't boil me, I'm still alive.
>> <Redacted> lobster!
>>
>

--
Death to <Redacted>, and butter sauce.
Don't boil me, I'm still alive.
<Redacted> lobster!