On 19/5/25 17:38, Moreno Andreo wrote:
On 19/05/25 14:41, Achilleas Mantzios wrote:
On 5/19/25 09:14, Moreno Andreo wrote:
On 16/05/25 21:33, Achilleas Mantzios wrote:
On 16/5/25 18:45, Moreno Andreo wrote:
Hi,
we are moving our old binary data approach, moving them from
bytea fields in a table to external storage (making database
smaller and related operations faster and smarter).
In short, we have a job that runs in background and copies data
from the table to an external file and then sets the bytea field
to NULL.
(UPDATE tbl SET blob = NULL, ref = 'path/to/file' WHERE id = <uuid>)
This results, at the end of the operations, to a table that's less
than one tenth in size.
We have a multi-tenant architecture (100s of schemas with
identical architecture, all inheriting from public) and we are
performing the task on one table per schema.
So? toasted data are kept on separate TOAST tables, unless those
bytea cols are selected, you won't even touch them. I cannot
understand what you are trying to achieve here.
Years ago, when I made the mistake to go for a coffee and let my
developers "improvise" , the result was a design similar to what
you are trying to achieve. Years after, I am seriously considering
moving those data back to PostgreSQL.
The "related operations" I was talking about are backups and
database maintenance when needed, cluster/replica management, etc.
With a smaller database size they would be easier in timing and
effort, right?
Ok, but you'll lose replica functionality for those blobs, which
means you don't care about them, correct me if I am wrong.
I'm not saying I don't care about them, the opposite, they are
protected with Object Versioning and soft deletion, this should assure
a good protection against e.g. ransomware, if someone manages to get
in there (and if this happens, we'll have bigger troubles than this).
PostgreSQL has become very popular because of ppl who care about their data.
We are mostly talking about costs, here. To give things their names,
I'm moving bytea contents (85% of total data) to files into Google
Cloud Storage buckets, that has a fraction of the cost of the disks
holding my database (on GCE, to be clear ).
May I ask the size of the bytea data (uncompressed) ?.
single records vary from 150k to 80 MB, the grand total is more than
8,5 TB in a circa 10 TB data footprint
This data is not accessed frequently (just by the owner when he
needs to do it), so no need to keep it on expensive hardware.
I've already read in these years that keeping many big bytea fields
in databases is not recommended, but might have misunderstood this.
Ok, I assume those are unimportant data, but let me ask, what is the
longevity or expected legitimacy of those ? I haven't worked with
those just reading :
https://cloud.google.com/storage/pricing?_gl=1*1b25r8o*_up*MQ..&gclid=CjwKCAjwravBBhBjEiwAIr30VKfaOJytxmk7J29vjG4rBBkk2EUimPU5zPibST73nm3XRL2h0O9SxRoCaogQAvD_BwE&gclsrc=aw.ds#storage-pricing
would you choose e.g. "*Anywhere Cache storage" ?
*
Absolutely not, this is *not* unimportant data, and we are using
Standard Storage, for 0,02$/GB/month + operations, that compared to a
0.17$/GB/month of an SSD or even more for the Hyperdisks we are using,
is a good price drop.
How about hosting your data in your own storage and spend 0$/GB/month ?
**
Another way would have been to move these tables to a different
tablespace, in cheaper storage, but it still would have been 3 times
the buckets cost.
can you actually mount those Cloud Storage Buckets under a supported
FS in linux and just move them to tablespaces backed by this storage ?
Never tried, I mounted this via FUSE and had some simple operations in
the past, but not sure it can handle database operations in terms of
I/O bandwidth
Why are you considering to get data back to database tables?
Because now if we need to migrate from cloud to on-premise, or just
upgrade or move the specific server which holds those data I will
have an extra headache. Also this is a single point of failure, or
best case a cause for fragmented technology introduced just for the
sake of keeping things out of the DB.
This is managed as an hierarchical disk structure, so the calling
server may be literally everywhere, it just needs an account (or a
service account) to get in there ,
and you are locked in a proprietary solution. and at their mercy of any
future increases in cost.
The problem is: this is generating BIG table bloat, as you may
imagine.
Running a VACUUM FULL on an ex-22GB table on a standalone test
server is almost immediate.
If I had only one server, I'll process a table a time, with a
nightly script, and issue a VACUUM FULL to tables that have
already been processed.
But I'm in a logical replication architecture (we are using a
multimaster system called pgEdge, but I don't think it will make
big difference, since it's based on logical replication), and I'm
building a test cluster.
So you use PgEdge , but you wanna lose all the benefits of
multi-master , since your binary data won't be replicated ...
I don't think I need it to be replicated, since this data cannot be
"edited", so either it's there or it's been deleted. Buckets have
protections for data deletions or events like ransomware attacks and
such.
Also multi-master was an absolute requirement one year ago because
of a project we were building, but it has been abandoned and now a
simple logical replication would be enough, but let's do one thing a
time.
Multi-master is cool, you can configure your pooler / clients to take
advantage of this for full load balanced architecture, but if not a
strict requirement , you can live without it, as so many of us, and
employ other means of load balancing the reads.
That's what we are doing, it's a really cool feature, but I
experienced (maybe because it uses old pglogical extension) that the
replication is a bit fragile, especially when dealing with those bytea
fields (when I ingest big loads, say 25-30 GB or more), it happened to
break replication, and recreating a replica from scratch with "normal
size" tables is not a big deal, since it can be achieved
automatically, because they normally fit in shared memory and can be
transferred by the replicator, but you can imagine what would be the
effort and the downtime necessary to create a base backup, transfer it
to the replica, build the DB and restart a 10-TB database (ATM we are
running with a 2-node cluster).
Break this in batches, use modern techniques for robust data loading, in
smaller transactions, if you have to.
I've been instructed to issue VACUUM FULL on both nodes, nightly,
but before proceeding I read on docs that VACUUM FULL can disrupt
logical replication, so I'm a bit concerned on how to proceed.
Rows are cleared one a time (one transaction, one row, to keep
errors to the record that issued them)
Mind if you shared the specific doc ?
Obviously I can't find it from a quick search, I'll search deeper, I
don't think it went off a dream :-).
PgEdge is based on the old pg_logical, the old 2ndQuadrant
extension, not the native logical replication we have since pgsql
10. But I might be mistaken.
Don't know about this, it keeps running on latest pg versions (we
are about to upgrade to 17.4, if I'm not wrong), but I'll ask
I read about extensions like pg_squeeze, but I wonder if they are
still not dangerous for replication.
What's pgEdge take on that, I mean the bytea thing you are trying
to achieve here.
They are positive, it's they that suggested to do VACUUM FULL on
both nodes... I'm quite new to replication, so I'm searching some
advise here.
As I told you, pgEdge logical replication (old 2ndquadrant BDR) !=
native logical replication. You may look here :
https://github.com/pgEdge/spock
If multi-master is not a must you could convert to vanilla
postgresql and focus on standard physical and logical replication.
No, multimaster is cool, but as I said, the project has been
discontinued and it's not a must anymore. This is the first step,
actually. We are planning to return to plain PostgreSQL, or CloudSQL
for PostgreSQL, using logical replication (that seems the most
reliable of the two). We created a test case for both the options, and
they seem to be OK for now, even if I have still to do adequate stress
tests. And when I'll do the migration, I'd like to be migrating plain
data only and leave blobs where they are.
as you wish. But this design has inherent data infra fragmentation as
you understand.
Personally I like to let the DB take care of the data, and I take care
of the DB, not a plethora of extra systems that we need to keep
connected and consistent.
Thanks for your help.
Moreno.-
