This is an R-Tree implementation using GiST for spherical objects like

spherical points and spherical circles with useful functions and operators.

It alsosupport the Block Range INdexing (BRIN) for large datasets.

It alsosupports the Block Range INdexing (BRIN) for large datasets.

NOTICE:

This version will work only with PostgreSQL version 10 and above.

of data blocks (<literal>pages</literal>) on physical storage in order to

organize data searches on ranges of summarized data that can be easily skipped

on the base of search filters (see <ulink

url="https://www.postgresql.org/docs/9.5/static/brin-intro.html"><citetitle>

url="https://www.postgresql.org/docs/current/brin-intro.html"><citetitle>

PostgreSQL documentation</citetitle></ulink> for further details on BRINs).

As a consequence, BRINs result to be really small indexes (up to 1000 times

than GiST ones), generally with lower a performance compared with a GiST one,

<![CDATA[CREATE INDEX test_pos_idx USING BRIN ON test (pos);]]>

</programlisting>

<para>

By default, BRINs summarize block of 128 pages. The lower numbers

of pages are specified, the higher granularity is reached during

the searches, and performance's gap between GiST indexes and BRINs

is lower (consider that BRINs size increases as well). Different

summarizations can be used with the following command:

By default, BRINs summarize blocks of 128 pages. The smaller the

number of pages specified, the higher the granularity in searches,

and the gap in performance between GiST indexes and BRINs will be

decreased. Note that the size of the BRINs increases as well.

Different summarizations can be specified with the following

command:

</para>

<programlisting>

<![CDATA[CREATE INDEX test_pos_idx USING BRIN ON test (pos) WITH (pages_per_range = 16);]]>