Postgresql – Most efficient way of updating table from another – Postgres

postgresqlpostgresql-9.6

I need to populate a foreign key column based on the contents of another table, and both methods I've tried are prohibitively slow.

I have the below tables (some columns omitted):

              Table "public.interface_events"
           Column           |  Type   |     Modifiers
----------------------------+---------+--------------------
 device_id                  | integer | not null
 interface_id               | integer |

Foreign-key constraints:
    "interface_events_device_id_fkey" FOREIGN KEY (device_id) REFERENCES device(id) ON UPDATE CASCADE ON DELETE RESTRICT
    "interface_events_interface_id_fkey" FOREIGN KEY (interface_id) REFERENCES interface(id) ON UPDATE CASCADE ON DELETE RESTRICT

                                       Table "public.device"
        Column        |         Type          |                      Modifiers
----------------------+-----------------------+-----------------------------------------------------
 id                   | integer               | not null default nextval('device_id_seq'::regclass)
 interface_id         | integer               | not null

Indexes:
    "device_pkey" PRIMARY KEY, btree (id)
    "device_interface_id_idx" btree (interface_id)

Foreign-key constraints:
    "device_interface_id_fkey" FOREIGN KEY (interface_id) REFERENCES interface(id) ON UPDATE CASCADE ON DELETE RESTRICT

Column interface_id in table interface_events needs updating from table device, so currently I have:

UPDATE interface_events SET interface_id = device.interface_id 
FROM device 
WHERE device.id = interface_events.device_id

I should point out that the relationship between device and interface_events is one to many, so there may be thousands of events per device. Is the UPDATE FROM method suitable in this situation? I'd earlier tried:

UPDATE interface_events SET interface_id = (SELECT device.interface_id FROM device WHERE device.id = interface_events.device_id);

But that took forever also.

There are 30 million rows in table interface_events, 32,000 in table device.

The update running currently (using the FROM syntax) has been active for 21 hours, although this is on a low spec test machine (2 x 3G cores, 3G RAM, spindle disk – it's disk I/O that's killing it, constant 99%).

It occures to me as I write I should have applied the foreign key constaint after the update, since I know it's integrity will be ok thanks to the column I'm copying from already being constrained, so I guess this question is more about the best query to use?

Best Answer

The fastest way will probably be to create a new table based on a join of the existing tables, create indexes and foreign keys constraints, and then drop the old "interface_events" and rename the new table into place. Views and foreign keys into this table can complicate this.

create interface_events_temp as 
    select interface_events.*, device.interface_id from interface_events 
        join device on (device.id = interface_events.device_id)

But the interface_events.* notation relies on interface_id not already existing in interface_events. Since it already exists, you would have to list out all columns in interface_events except for interface_id.

Related Solutions

Postgresql – Postgres multiple joins slow query, how to store default child record

You write:

Each customer can have multiple sites, but only one should be displayed in this list.

Yet, your query retrieves all rows. That would be a point to optimize. But you also do not define which site is to be picked.

Either way, it does not matter much here. Your EXPLAIN shows only 5026 rows for the site scan (5018 for the customer scan). So hardly any customer actually has more than one site. Did you ANALYZE your tables before running EXPLAIN?

From the numbers I see in your EXPLAIN, indexes will give you nothing for this query. Sequential table scans will be the fastest possible way. Half a second is rather slow for 5000 rows, though. Maybe your database needs some general performance tuning?

Maybe the query itself is faster, but "half a second" includes network transfer? EXPLAIN ANALYZE would tell us more.

If this query is your bottleneck, I would suggest you implement a materialized view.

After you provided more information I find that my diagnosis pretty much holds.

The query itself needs 27 ms. Not much of a problem there. "Half a second" was the kind of misunderstanding I had suspected. The slow part is the network transfer (plus ssh encoding / decoding, possibly rendering). You should only retrieve 100 rows, that would solve most of it, even if it means to execute the whole query every time.

If you go the route with a materialized view like I proposed you could add a serial number without gaps to the table plus index on it - by adding a column row_number() OVER (<your sort citeria here>) AS mv_id.

Then you can query:

SELECT *
FROM   materialized_view
WHERE  mv_id >= 2700
AND    mv_id <  2800;

This will perform very fast. LIMIT / OFFSET cannot compete, that needs to compute the whole table before it can sort and pick 100 rows.

pgAdmin timing

When you execute a query from the query tool, the message pane shows something like:

Total query runtime: 62 ms.

And the status line shows the same time. I quote pgAdmin help about that:

The status line will show how long the last query took to complete. If a dataset was returned, not only the elapsed time for server execution is displayed, but also the time to retrieve the data from the server to the Data Output page.

If you want to see the time on the server you need to use SQL EXPLAIN ANALYZE or the built in Shift + F7keyboard shortcut or Query -> Explain analyze. Then, at the bottom of the explain output you get something like this:

Total runtime: 0.269 ms

Postgresql – Improve performance on concurrent UPDATEs for a timestamp column in Postgres

Would a different kind of column be faster? For example an integer

No. timestamp and timestamptz are just unsigned 64-bit integers internally anyway.

Is there some way to not lock the column?

It doesn't lock the column. It takes weak table lock that doesn't really block anything except DDL, and takes a row level lock on the row you're updating.

There is no way to prevent the row level lock. It exists because without it behaviour and ordering concurrent updates would be undefined. We don't like undefined behaviour in RDBMSs.

It only blocks concurrent updates of the same row anyway.

Any other tips to improve this?

Not with the detail provided. There's likely a better way to do what you're trying to do, but it'll probably involve taking a few steps back and looking for a different strategy for solving the underlying problem.

In the specific case of cache invalidation I think you might want to look into LISTEN and NOTIFY. Again though, there just isn't enough info here to go on.

Best Answer

Related Solutions

Postgresql – Postgres multiple joins slow query, how to store default child record

pgAdmin timing

Postgresql – Improve performance on concurrent UPDATEs for a timestamp column in Postgres

Related Question