Waiting for 9.5 – Use abbreviated keys for faster sorting of text datums.

On 19th of January, Robert Haas committed patch:

Use abbreviated keys for faster sorting of text datums.
This commit extends the SortSupport infrastructure to allow operator
classes the option to provide abbreviated representations of Datums;
in the case of text, we abbreviate by taking the first few characters
of the strxfrm() blob.  If the abbreviated comparison is insufficent
to resolve the comparison, we fall back on the normal comparator.
This can be much faster than the old way of doing sorting if the
first few bytes of the string are usually sufficient to resolve the
There is the potential for a performance regression if all of the
strings to be sorted are identical for the first 8+ characters and
differ only in later positions; therefore, the SortSupport machinery
now provides an infrastructure to abort the use of abbreviation if
it appears that abbreviation is producing comparatively few distinct
keys.  HyperLogLog, a streaming cardinality estimator, is included in
this commit and used to make that determination for text.
Peter Geoghegan, reviewed by me.

Continue reading Waiting for 9.5 – Use abbreviated keys for faster sorting of text datums.

Waiting for 9.5 – BRIN: Block Range Indexes.

On 7th of November, Alvaro Herrera committed patch:

BRIN is a new index access method intended to accelerate scans of very
large tables, without the maintenance overhead of btrees or other
traditional indexes.  They work by maintaining "summary" data about
block ranges.  Bitmap index scans work by reading each summary tuple and
comparing them with the query quals; all pages in the range are returned
in a lossy TID bitmap if the quals are consistent with the values in the
summary tuple, otherwise not.  Normal index scans are not supported
because these indexes do not store TIDs.
As new tuples are added into the index, the summary information is
updated (if the block range in which the tuple is added is already
summarized) or not; in the latter case, a subsequent pass of VACUUM or
the brin_summarize_new_values() function will create the summary
For data types with natural 1-D sort orders, the summary info consists
of the maximum and the minimum values of each indexed column within each
page range.  This type of operator class we call "Minmax", and we
supply a bunch of them for most data types with B-tree opclasses.
Since the BRIN code is generalized, other approaches are possible for
things such as arrays, geometric types, ranges, etc; even for things
such as enum types we could do something different than minmax with
better results.  In this commit I only include minmax.
Catalog version bumped due to new builtin catalog entries.
There's more that could be done here, but this is a good step forwards.
Loosely based on ideas from Simon Riggs; code mostly by Álvaro Herrera,
with contribution by Heikki Linnakangas.
Patch reviewed by: Amit Kapila, Heikki Linnakangas, Robert Haas.
Testing help from Jeff Janes, Erik Rijkers, Emanuel Calvo.
  The research leading to these results has received funding from the
  European Union's Seventh Framework Programme (FP7/2007-2013) under
  grant agreement n° 318633.

Continue reading Waiting for 9.5 – BRIN: Block Range Indexes.

How to deal with timestamps?

Every now and then someone asks, on irc or mailing lists, some question which shows deep misunerstanding (or lack of understanding) of timestamps – especially the ones with time zones.

Since I got bitten by this before, let me describe what timestamps are, how to work with them, and what are the most common pitfalls that you can encounter.

Continue reading How to deal with timestamps?

Waiting for 9.4 – Introduce jsonb, a structured format for storing json.

Portuguese Brazil Version

On 23rd of March, Andrew Dunstan committed patch:

Introduce jsonb, a structured format for storing json.
The new format accepts exactly the same data as the json type. However, it is
stored in a format that does not require reparsing the orgiginal text in order
to process it, making it much more suitable for indexing and other operations.
Insignificant whitespace is discarded, and the order of object keys is not
preserved. Neither are duplicate object keys kept - the later value for a given
key is the only one stored.
The new type has all the functions and operators that the json type has,
with the exception of the json generation functions (to_json, json_agg etc.)
and with identical semantics. In addition, there are operator classes for
hash and btree indexing, and two classes for GIN indexing, that have no
equivalent in the json type.
This feature grew out of previous work by Oleg Bartunov and Teodor Sigaev, which
was intended to provide similar facilities to a nested hstore type, but which
in the end proved to have some significant compatibility issues.
Authors: Oleg Bartunov,  Teodor Sigaev, Peter Geoghegan and Andrew Dunstan.
Review: Andres Freund

Continue reading Waiting for 9.4 – Introduce jsonb, a structured format for storing json.

Waiting for 9.3 – Support indexing of regular-expression searches in contrib/pg_trgm.

On 9th of April, Tom Lane committed patch:

Support indexing of regular-expression searches in contrib/pg_trgm.
This works by extracting trigrams from the given regular expression,
in generally the same spirit as the previously-existing support for
LIKE searches, though of course the details are far more complicated.
Currently, only GIN indexes are supported.  We might be able to make
it work with GiST indexes later.
The implementation includes adding API functions to backend/regex/
to provide a view of the search NFA created from a regular expression.
These functions are meant to be generic enough to be supportable in
a standalone version of the regex library, should that ever happen.
Alexander Korotkov, reviewed by Heikki Linnakangas and Tom Lane

One day later Tom Lane added support for the same operations using GiST indexes (original patch was working only with GIN).

Continue reading Waiting for 9.3 – Support indexing of regular-expression searches in contrib/pg_trgm.

“= 123” vs. “= ‘depesz'”. What is faster?

There is this idea that normal form in databases require you to use integer, auto incrementing, primary keys.

The idea was discussed by many people, I will just point you to series of three blog posts on the subject by Josh Berkus ( part 1, 2 and 3, and reprise).

One of the points that proponents of surrogate keys (i.e. those based on integer and sequences) raise is that comparing integers is faster than comparing texts. So,

SELECT * FROM users WHERE id = 123

is faster than

SELECT * FROM users WHERE username = 'depesz'

Is it?

Continue reading “= 123" vs. “= ‘depesz'". What is faster?