I am using citext
in PostgreSQL
for all text column types. I wonder about citext
performance.
I performed simple WHERE
statement benchmarks over text columns that have a b-tree index, but I couldn't see any differences in terms of query cost.
For example:
Select * From table_text where a = '1';
Select * From table_citext where a= '1';
These queries have identical query costs.
As far as I understand, citext
stores the string as it is without converting it to lower case. So when a value is used in the WHERE
clause, it uses the lower
function for every comparison in each node of the b-tree index (I used a b-tree index).
If this is as I say, this should have caused performance problems, but it hasn't.
How does PostgreSQL achieve this?
How does PostgreSQL store citext
column values in a b-tree index?
citext
is stored as it is input, without any conversion to lower case. This also holds for storage as b-tree index keys.
The magic happens in the comparison function for citext
:
/*
* citextcmp()
* Internal comparison function for citext strings.
* Returns int32 negative, zero, or positive.
*/
static int32
citextcmp(text *left, text *right, Oid collid)
{
char *lcstr,
*rcstr;
int32 result;
/*
* We must do our str_tolower calls with DEFAULT_COLLATION_OID, not the
* input collation as you might expect. This is so that the behavior of
* citext's equality and hashing functions is not collation-dependent. We
* should change this once the core infrastructure is able to cope with
* collation-dependent equality and hashing functions.
*/
lcstr = str_tolower(VARDATA_ANY(left), VARSIZE_ANY_EXHDR(left), DEFAULT_COLLATION_OID);
rcstr = str_tolower(VARDATA_ANY(right), VARSIZE_ANY_EXHDR(right), DEFAULT_COLLATION_OID);
result = varstr_cmp(lcstr, strlen(lcstr),
rcstr, strlen(rcstr),
collid);
pfree(lcstr);
pfree(rcstr);
return result;
}
So yes, this should incur some overhead. How expensive it is will also depend on the default collation of the database.
I'll demonstrate this using a query without an index. I am using the German collation:
SHOW lc_collate;
lc_collate
------------
de_DE.utf8
(1 row)
First using text
:
CREATE TABLE large_text(t text NOT NULL);
INSERT INTO large_text
SELECT i||'text'
FROM generate_series(1, 1000000) AS i;
VACUUM (FREEZE, ANALYZE) large_text;
\timing on
SELECT * FROM large_text WHERE t = TEXT 'mama';
t
---
(0 rows)
Time: 79.862 ms
Now the same experiment with citext
:
CREATE TABLE large_citext(t citext NOT NULL);
INSERT INTO large_citext
SELECT i||'text'
FROM generate_series(1, 1000000) AS i;
VACUUM (FREEZE, ANALYZE) large_citext;
\timing on
SELECT * FROM large_citext WHERE t = CITEXT 'mama';
t
---
(0 rows)
Time: 567.739 ms
So citext
is about seven times slower.
But don't forget that each of these experiments performed a sequential scan with a million comparisons.
If you use an index, the difference will not be noticeable:
CREATE INDEX ON large_text (t);
Time: 5443.993 ms (00:05.444)
SELECT * FROM large_text WHERE t = CITEXT 'mama';
t
---
(0 rows)
Time: 1.867 ms
CREATE INDEX ON large_citext (t);
Time: 28009.904 ms (00:28.010)
SELECT * FROM large_citext WHERE t = CITEXT 'mama';
t
---
(0 rows)
Time: 1.988 ms
You see that CREATE INDEX
takes much longer for the citext
columns (it has to perform a lot of comparisons), but the queries take about the same time.
The reason is that you need only few comparisons if you use an index scan: for each of the 2-3 index blocks you access you perform a binary search, and you may have to re-check the table row found in the case of a bitmap index scan.