129

I had to write a simple query where I go looking for people's name that start with a B or a D :

SELECT s.name 
FROM spelers s 
WHERE s.name LIKE 'B%' OR s.name LIKE 'D%'
ORDER BY 1

I was wondering if there is a way to rewrite this to become more performant. So I can avoid or and / or like?

3
  • Why are you trying to rewrite? Performance? Neatness? Is s.name indexed? Jan 15, 2012 at 11:29
  • I want to write for performance, s.name is not indexed. Jan 15, 2012 at 11:36
  • 10
    Well as you are searching without leading wild cards and not selecting any additional columns an index on name could be useful here if you care about performance. Jan 15, 2012 at 11:39

8 Answers 8

213

Pattern matching operators

  • LIKE (~~) is simple and fast but limited in its capabilities.
    ILIKE (~~*) the case insensitive variant.

  • ~ (regular expression match) is powerful but more complex and may be slow for anything more than basic expressions.
    ~* is the case insensitive variant.

  • SIMILAR TO is just pointless. A peculiar blend of LIKE and regular expressions. I never use it. See below.

All of the above can use a trigram index. See below.
For left-anchored patterns also a B-tree index using COLLATE "C" or the operator class text_pattern_ops. See below.

Basics about pattern matching in the manual.

Related operators

  • ^@ is "starts with" operator (for prefix matching), equivalent to the starts_with() function.
    Added with Postgres 11, can use an SP-GiST index. Since Postgres 15 also a B-tree index using a "C" collation. See below.

  • % is the "similarity" operator, provided by the additional module pg_trgm. See below.

  • @@ is the text search operator. See below.

Your query

... is pretty much the optimum. Syntax won't get much shorter, query won't get much faster:

SELECT name FROM spelers
WHERE  name LIKE 'B%' OR name LIKE 'D%'
ORDER  BY 1;

Or equivalent (slightly more expensive):

... WHERE name ~ '^B' OR name LIKE '^D'

A bit shorter, but can't use an index:

... WHERE name LIKE ANY ('{B%,D%}')
... WHERE name ~ ANY ('{^B,^D}')

A regular expression with branches shortens the syntax some more:

... WHERE name ~ '^(B|D).*'

Or a character class (only for the case with a single character):

... WHERE name ~ '^[BD].*'

For bigger tables, index support improves performance by orders of magnitude.

In Postgres 11 or later the new ^@ is more convenient as we can use the unadorned prefix directly - and fast when supported with an SP-GiST index:

... WHERE name ^@ 'B' OR name ^@ 'D'

Or:

... WHERE name ^@ ANY ('{B,D}')

In Postgres 15, the first variant can also use a B-tree index using COLLATE "C".

db<>fiddle here

Index

If concerned with performance, create an index like this for bigger tables to support left-anchored search patterns (matching from the start of the string):

CREATE INDEX spelers_name_special_idx ON spelers (name COLLATE "C");

Requires per-column collation support added with Postgres 9.1.

See:

In DBs running with the "C" locale (not typical), a plain B-tree index does the job.

In older versions (or still today), you can use the special operator class text_pattern_ops for the same purpose:

CREATE INDEX spelers_name_special_idx ON spelers (name text_pattern_ops);

SIMILAR TO or regular expressions with basic left-anchored expressions can use this index, too. But not with branches (B|D) or character classes [BD]. And no index currently supports LIKE ANY.

Trigram matching

Trigram matches or text search use special GIN or GiST indexes.

Beginning with Postgres 9.1 you can install the additional module pg_trgm to provide index support for any LIKE / ILIKE pattern (and simple regexp patterns with ~ / ~*) using a GIN or GiST index.

Details, example and links:

pg_trgm provides additional operators like:

  • % - the "similarity" operator
  • <% (commutator: %>) - the "word_similarity" operator in Postgres 9.6 or later
  • <<% (commutator: %>>) - the "strict_word_similarity" operator in Postgres 11 or later

Text search

Is a special type of pattern matching with separate infrastructure and index types. It uses dictionaries and stemming and is a great tool to find words in documents, especially for natural languages.

Prefix matching is also supported:

As well as phrase search since Postgres 9.6:

Consider the introduction in the manual and the overview of operators and functions.

Additional tools for fuzzy string matching

The additional module fuzzystrmatch offers some more options, but performance is generally inferior to all of the above.

In particular, various implementations of the levenshtein() function may be instrumental.

Why are regular expressions (~) always faster than SIMILAR TO?

SIMILAR TO expressions are rewritten into regular expressions internally. For every SIMILAR TO expression, there is at least one faster regular expression (saving the overhead of rewriting the expression). There is no performance gain in using SIMILAR TO ever.

Simple expressions that can make do with LIKE (~~) are faster with LIKE anyway.

SIMILAR TO is only supported in PostgreSQL because it ended up in early drafts of the SQL standard. They still haven't gotten rid of it. But there are plans to remove it and include regexp matches instead - or so I heard.

EXPLAIN ANALYZE reveals it. Just try with any table yourself!

EXPLAIN ANALYZE SELECT * FROM spelers WHERE name SIMILAR TO 'B%';

Reveals:

...  
Seq Scan on spelers  (cost= ...  
  Filter: (name ~ '^(?:B.*)$'::text)

SIMILAR TO has been rewritten with a regular expression (~).

15
  • The OP doesn't have an index on name but do you happen to know, if they did, would their original query involve 2 range seeks and similar a scan? Jan 15, 2012 at 11:43
  • 2
    @MartinSmith: A quick test with EXPLAIN ANALYZE shows 2 bitmap index scans. Multiple bitmap index scans can be combined rather quickly. Jan 15, 2012 at 11:46
  • Thanks. So would there be any milage with replacing the OR with UNION ALL or replacing name LIKE 'B%' with name >= 'B' AND name <'C' in Postgres? Jan 15, 2012 at 11:59
  • 1
    @MartinSmith: UNION won't but, yes, combining the ranges into one WHERE clause will speed up the query. I have added more to my answer. Of course, you have to take your locale into account. Locale-aware search is always slower. Jan 15, 2012 at 12:29
  • 2
    @a_horse_with_no_name: I expect not. The new capabilities of pg_tgrm with GIN indexes are a treat for generic text search. A search anchored at the start is already faster than that. Jan 17, 2012 at 22:44
13

How about adding a column to the table. Depending on your actual requirements:

person_name_start_with_B_or_D (Boolean)

person_name_start_with_char CHAR(1)

person_name_start_with VARCHAR(30)

PostgreSQL doesn't support computed columns in base tables a la SQL Server but the new column can be maintained via trigger. Obviously, this new column would be indexed.

Alternatively, an index on an expression would give you the same, cheaper. E.g.:

CREATE INDEX spelers_name_initial_idx ON spelers (left(name, 1)); 

Queries that match the expression in their conditions can utilize this index.

This way, the performance hit is taken when the data is created or amended, so may only be appropriate for a low activity environment (i.e. much fewer writes than reads).

0
8

You could try

SELECT s.name
FROM   spelers s
WHERE  s.name SIMILAR TO '(B|D)%' 
ORDER  BY s.name

I've no idea whether or not either the above or your original expression are sargable in Postgres though.

If you create the suggested index would also be interested to hear how this compares with the other options.

SELECT name
FROM   spelers
WHERE  name >= 'B' AND name < 'C'
UNION ALL
SELECT name
FROM   spelers
WHERE  name >= 'D' AND name < 'E'
ORDER  BY name
1
  • 1
    It worked and I got a cost of 1.19 where I had 1.25. Thanks ! Jan 15, 2012 at 11:41
2

What I have done in the past, faced with a similar performance issue, is to increment the ASCII character of the last letter, and do a BETWEEN. You then get the best performance, for a subset of the LIKE functionality. Of course, it only works in certain situations, but for ultra-large datasets where you're searching on a name for instance, it makes performance go from abysmal to acceptable.

2

Very old question, but I found another fast solution to this problem:

SELECT s.name 
FROM spelers s 
WHERE ascii(s.name) in (ascii('B'),ascii('D'))
ORDER BY 1

Since function ascii() looks only at first character of the string.

1
  • 1
    Does this use an index on (name)? Nov 25, 2017 at 12:56
2

For checking of initials, I often use casting to "char" (with the double quotes). It's not portable, but very fast. Internally, it simply detoasts the text and returns the first character, and "char" comparison operations are very fast because the type is 1-byte fixed length:

SELECT s.name 
FROM spelers s 
WHERE s.name::"char" =ANY( ARRAY[ "char" 'B', 'D' ] )
ORDER BY 1

Note that casting to "char" is faster than the ascii() slution by @Sole021, but it is not UTF8 compatible (or any other encoding for that matter), returning simply the first byte, so should only be used in cases where the comparison is against plain old 7-bit ASCII characters.

1

There are two methods not mentioned yet for dealing with such cases:

  1. partial (or partitioned - if created for full range manually) index - most useful when only a subset of data is required (for example during some maintenance or temporary for some reporting):

    CREATE INDEX ON spelers WHERE name LIKE 'B%'
    
  2. partitioning the table itself (using the first character as partitioning key) - this technique is especially worth considering in PostgreSQL 10+ (less painful partitioning) and 11+ (partition pruning during query execution).

Moreover, if the data in a table is sorted, one can benefit from using BRIN index (over the first character).

-4

Probably faster to do a single character comparison:

SUBSTR(s.name,1,1)='B' OR SUBSTR(s.name,1,1)='D'
1
  • 1
    Not really. column LIKE 'B%' will be more efficient than using substring function on the column. Jan 13, 2016 at 15:55

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.