PostgreSQL Disk Space – Releasing Disk Space Using DELETE or TRUNCATE

deletepostgresqltruncate

More than a week ago, I deleted all the rows in a postgresql table (not via truncate, instead with delete from ...). Select count (*) reveals table rows are now 0.

When I now run queries to query disk space, I still see the table taking up space. Specifically, all the indexes still exist and are taking up space. How do I get rid of them and release disk space? Secondly, why do they remain in the first place, when I've gotten rid of all the rows?

Here's the table's detailed description in case warranted:

                                      Table "public.links_photoobjectsubscription"
     Column     |           Type           |                                 Modifiers                                  
----------------+--------------------------+----------------------------------------------------------------------------
 id             | integer                  | not null default nextval('links_photoobjectsubscription_id_seq'::regclass)
 viewer_id      | integer                  | not null
 updated_at     | timestamp with time zone | not null
 seen           | boolean                  | not null
 type_of_object | character varying(15)    | not null
 which_photo_id | integer                  | 
 which_link_id  | integer                  | 
 which_group_id | integer                  | 
 which_salat_id | integer                  | 
Indexes:
    "links_photoobjectsubscription_pkey" PRIMARY KEY, btree (id)
    "links_photoobjectsubscription_seen" btree (seen)
    "links_photoobjectsubscription_updated_at" btree (updated_at)
    "links_photoobjectsubscription_viewer_id" btree (viewer_id)
    "links_photoobjectsubscription_which_photo_id" btree (which_photo_id)
Foreign-key constraints:
    "links_photoobjectsubscription_viewer_id_fkey" FOREIGN KEY (viewer_id) REFERENCES auth_user(id) DEFERRABLE INITIALLY DEFERRED
    "links_photoobjectsubscription_which_photo_id_fkey" FOREIGN KEY (which_photo_id) REFERENCES links_photo(id) DEFERRABLE INITIALLY DEFERRED
    "which_group_id_photoobjectsubscription" FOREIGN KEY (which_group_id) REFERENCES links_group(id) ON DELETE CASCADE
    "which_link_id_photoobjectsubscription" FOREIGN KEY (which_link_id) REFERENCES links_link(id) ON DELETE CASCADE
    "which_salat_id_photoobjectsubscription" FOREIGN KEY (which_salat_id) REFERENCES links_salatinvite(id) ON DELETE CASCADE

Best Answer

From the docs on VACUUM

There are two variants of VACUUM: standard VACUUM and VACUUM FULL. VACUUM FULL can reclaim more disk space but runs much more slowly. Also, the standard form of VACUUM can run in parallel with production database operations. (Commands such as SELECT, INSERT, UPDATE, and DELETE will continue to function normally, though you will not be able to modify the definition of a table with commands such as ALTER TABLE while it is being vacuumed.) VACUUM FULL requires exclusive lock on the table it is working on, and therefore cannot be done in parallel with other use of the table. Generally, therefore, administrators should strive to use standard VACUUM and avoid VACUUM FULL.

You essentially need to issue a command to rewrite the whole table (from the same doc),

Tip: Plain VACUUM may not be satisfactory when a table contains large numbers of dead row versions as a result of massive update or delete activity. If you have such a table and you need to reclaim the excess disk space it occupies, you will need to use VACUUM FULL, or alternatively CLUSTER or one of the table-rewriting variants of ALTER TABLE. These commands rewrite an entire new copy of the table and build new indexes for it. All these options require exclusive lock. Note that they also temporarily use extra disk space approximately equal to the size of the table, since the old copies of the table and indexes can't be released until the new ones are complete.

In the same document,

Tip: If you have a table whose entire contents are deleted on a periodic basis, consider doing it with TRUNCATE rather than using DELETE followed by VACUUM. TRUNCATE removes the entire content of the table immediately, without requiring a subsequent VACUUM or VACUUM FULL to reclaim the now-unused disk space. The disadvantage is that strict MVCC semantics are violated.

And, from the docs on TRUNCATE

TRUNCATE quickly removes all rows from a set of tables. It has the same effect as an unqualified DELETE on each table, but since it does not actually scan the tables it is faster. Furthermore, it reclaims disk space immediately, rather than requiring a subsequent VACUUM operation. This is most useful on large tables.

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

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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

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