Why does PostgresQL query performance drop over time, but restored when rebuilding index

Question

According to this page in the manual, indexes don't need to be maintained. However, we are running with a PostgresQL table that has a continuous rate of updates, deletes and inserts that over time (a few days) sees a significant query degradation. If we delete and recreate the index, query performance is restored.

We are using out of the box settings.
The table in our test is currently starting out empty and grows to half a million rows. It has a fairly large row (lots of text fields).

We are searching based of an index, not the primary key (I've confirmed the index is being used, at least under normal conditions)

The table is being used as a persistent store for a single process. Using PostgresQL on Windows with a Java client.

I'm willing to give up insert and update performance to keep up the query performance.

We are considering rearchitecting the application so that data is spread across various dynamic tables in a manner that allows us to drop and rebuild indexes periodically without impacting the application. However, as always, there is a time crunch to get this to work and I suspect we are missing something basic in our configuration or usage.

We have considered forcing vacuuming and rebuild to run at certain times, but I suspect the locking period for such an action would cause our query to block. This may be an option, but there are some real-time (windows of 3-5 seconds) implications that require other changes in our code.

Additional information: Table and index

CREATE TABLE icl_contacts
(
  id bigint NOT NULL,
  campaignfqname character varying(255) NOT NULL,
  currentstate character(16) NOT NULL,
  xmlscheduledtime character(23) NOT NULL,
...
25 or so other fields.  Most of them fixed or varying character fiel  
...
  CONSTRAINT icl_contacts_pkey PRIMARY KEY (id)
)
WITH (OIDS=FALSE);
ALTER TABLE icl_contacts OWNER TO postgres;

CREATE INDEX icl_contacts_idx
  ON icl_contacts
  USING btree
  (xmlscheduledtime, currentstate, campaignfqname);

Analyze:

Limit  (cost=0.00..3792.10 rows=750 width=32) (actual time=48.922..59.601 rows=750 loops=1)
  ->  Index Scan using icl_contacts_idx on icl_contacts  (cost=0.00..934580.47 rows=184841 width=32) (actual time=48.909..55.961 rows=750 loops=1)
        Index Cond: ((xmlscheduledtime < '2010-05-20T13:00:00.000'::bpchar) AND (currentstate = 'SCHEDULED'::bpchar) AND ((campaignfqname)::text = '.main.ee45692a-6113-43cb-9257-7b6bf65f0c3e'::text))

And, yes, I am aware there there are a variety of things we could do to normalize and improve the design of this table. Some of these options may be available to us.

My focus in this question is about understanding how PostgresQL is managing the index and query over time (understand why, not just fix). If it were to be done over or significantly refactored, there would be a lot of changes.

Solution 1

Auto vacuum should do the trick, provided you configured it for your desired performance.

Notes: VACUUM FULL: this will rebuild table statistics and reclaim loads of disk space. It locks the whole table.

VACUUM: this will rebuild table statistics and reclaim some disk space. It can be run in parallel with production system, but generates lots of IO which can impact performance.

ANALYZE: this will rebuild query planner statistics. This is triggered by VACUUM, but can be run on its own.

More detailed notes found here

Solution 2

This smells like index bloat to me. I'l refer you to this page

http://www.postgresql.org/docs/8.3/static/routine-reindex.html

which says at the bottom:

Also, for B-tree indexes a freshly-constructed index is somewhat faster to access than one that has been updated many times, because logically adjacent pages are usually also physically adjacent in a newly built index. (This consideration does not currently apply to non-B-tree indexes.) It might be worthwhile to reindex periodically just to improve access speed.

Which does seem to conflict with the page you referenced saying that indexes "don't require maintenance or tuning".

Have you tried "create index concurrently"?

Solution 3

As for performance, using strings for storing time and status info is quite a bottleneck. First of all, indexes on texts are extremely inefficient, comparing two times on the same day needs at least 11 comparison (in the format you used), however, using time type it can be reduced to simply one comparison. This also effects the size of the index, and a large index is hard to search over, and the db won't keep it in memory. Same considerations apply to the state column. If it represents a small set of states, you should use integer numbers mapped to states, this will reduce the nodes of the index - and the index size accordingly. Furthermore, this index will be useless even using theese built-in types if you don't specify the actual time in your query.

Solution 4

Is the '2010-05-20T13:00:00.000' value that xmlscheduledtime is being compared to, part of the SQL, or supplied as a parameter?

When planning how to run the query, saying that a field must be less than a supplied parameter with an as yet unknown value doesn't give PostgreSQL much to go on. It doesn't know whether that'll match nearly all the rows, or hardly any of the rows.

Reading about how the planner uses statistics helps tremendously when trying to figure out why your database is using the plans it is.

You might get better select performance by changing the order of fields in that complex index, or creating a new index, with the fields ordered (campaignfqname, currentstate, xmlscheduledtime) since then the index will take you straight to the campaign fq name and current state that you are interested in, and the index scan over the xmlscheduledtime range will all be rows you're after.

Solution 5

That's a textbook case. You should setup autovacuum to be a lot more aggressive.

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