In create table wizard of PGAdmin 4 when you open the column type drop-down menu, there is a type named ltree_gist.
Knowing that GIST is probably the best index option to use upon ltree columns, I suspect that ltree_gist is just ltree with an index defined on it as it is reasonable to create a ltree type column with a GIST index in just one move. But looks like its not that!
Long story short, could someone please explain the difference between ltree and ltree_gist in PGAdmin4 interface?
I could not find anything in the documentation.
ltree_gist is an implementation detail that is used for the implementation of GiST index support for ltree values. It is used for storing index entries.
That type cannot be used in SQL or table definitions directly.
Related
The past two days I've been reading a lot about jsonb, full text search, gin index, trigram index and what not but I still can not find a definitive or at least a good enough answer on how to fastly search if a row of type JSONB contains certain string as a value. Since it's a search functionality the behavior should be like that of ILIKE
What I have is:
Table, lets call it app.table_1 which contains a lot of columns one of which is of type JSONB, so lets call it column_jsonb
The data inside column_jsonb will always be flatten (no nested objects, etc) but the keys can vary. An example of the data in the column with obfuscated values looks like this:
"{""Key1"": ""Value1"", ""Key2"": ""Value2"", ""Key3"": null, ""Key4"": ""Value4"", ""Key5"": ""Value5""}"
I have a GIN index for this column which doesn't seems to affect the search time significantly (I am testing with 20k records now which takes about 550ms). The indes looks like this:
CREATE INDEX ix_table_1_column_jsonb_gin
ON app.table_1 USING gin
(column_jsonb jsonb_path_ops)
TABLESPACE pg_default;
I am interested only in the VALUES and the way I am searching them now is this:
EXISTS(SELECT value FROM jsonb_each(column_jsonb) WHERE value::text ILIKE search_term)
Here search_term is variable coming from the front end with the string that the user is searching for
I have the following questions:
Is it possible to make the check faster without modifying the data model? I've read that trigram index might be usfeul for similar cases but at least for me it seems that converting jsonb to text and then checking will be slower and actually I am not sure if the trigram index will actually work if the column original type is JSONB and I explicitly cast each row to text? If I'm wroing I would really appreciate some explanation with example if possible.
Is there some JSONB function that I am not aware of which offers what I am searching for out of the box, I'm constrained to PostgreSQL v 11.9 so some new things coming with version 12 are not available for me.
If it's not possible to achieve significant improvement with the current data structure can you propose a way to restructure the data in column_jsonb maybe another column of some other type with data persisted in some other way, I don't know...
Thank you very much in advance!
If the data structure is flat, and you regularly need to search the values, and the values are all the same type, a traditional key/value table would seem more appropriate.
create table table1_options (
table1_id bigint not null references table1(id),
key text not null,
value text not null
);
create index table1_options_key on table1_options(key);
create index table1_options_value on table1_options(value);
select *
from table1_options
where value ilike 'some search%';
I've used simple B-Tree indexes, but you can use whatever you need to speed up your particular searches.
The downsides are that all values must have the same type (doesn't seem to be a problem here) and you need an extra table for each table. That last one can be mitigated somewhat with table inheritance.
According to pgAdmin 4 4.21 documentation » Creating or Modifying a Table »
Select gin to create a GIN index. A GIN index may improve performance when managing two-dimensional geometric data types and nearest-neighbor searches
We should create a Gin index for geometric column if we intend to use Nearest-neighbor searches, Which I do!
However, when defining Gin index it asks for Operator Class and there are two options there (jsonb_path_obs and gin_int_ops) but none of them works with Geometry type.
Could someone please tell me how to create a Gin index on a Geometry type column?
P.S by geometry I mean PostGIS's geometry column type
Please link to the thing you are quoting so we don't have to go searching for it.
That looks like a bug in the pgadmin4 docs. They seem to have the GIN and GiST labels reversed in those descriptions. GIN supports multiple keys better than GiST does, but doesn't support nearest-neighbor or spatial. You want a GiST index.
I'm trying to add a GIN index that includes a UUID in a Postgres 9.6 database. Technically it is a composite index, with composite GIN support coming from the btree_gin plugin.
I try to create the index with this statement:
CREATE EXTENSION btree_gin;
CREATE INDEX ix_tsv ON text_information USING GIN (client_id, text_search_vector);
but I get this error:
ERROR: data type uuid has no default operator class for access method "gin"
HINT: You must specify an operator class for the index or define a default operator class for the data type.
client_id is data type uuid and text_search_vector is a tsvector. I don't think the composite/btree_gin factor is actually relevant, as I get the same error trying to create the index on just client_id alone, but hopefully if there is a solution to this, it is one that will work with a composite index also.
I found PostgreSQL GIN index on array of uuid , which seems to suggest that it should be possible (if an array of UUIDs can be done, then surely an individual UUID can be done). However, the solution there was pretty opaque to me - it's not immediately obvious how to modify this solution to support a single UUID.
I would prefer a solution that doesn't involve casting the UUID to another type in the index or in another column, as I would rather not have to write specialized queries with casts in them (we are using django ORM to generate queries atm).
It is possible for GIN indexes. But not before Postgres 11, where it was added. The release notes:
Allow btree_gin to index bool, bpchar, name and uuid data types (Matheus Oliveira)
So the simple solution is to upgrade to Postgres 11. This should be good news for you:
April 9, 2019: Cloud SQL now supports PostgreSQL version 11.1 Beta
Or, in many cases you can alternatively use a GiST index, for which the same was introduced with Postgres 10, already. The release notes:
Add indexing support to btree_gist for the UUID data type (Paul Jungwirth)
Related:
How to use uuid with postgresql gist index type?
If neither is an option, you are back to what you wanted to avoid:
casting the uuid to another type in the index
You can create an expression index on a (consistent!) text representation or, theoretically, on two bigint columns derived from the uuid. But the first makes the index considerably bigger and slower and the second creates much more complication ...
The syntax of the cast is simple enough though: uuid::text. In an index expression that requires an extra set of parentheses. With the additional module btree_gin installed:
CREATE INDEX ix_uuid_tsv ON text_information USING GIN ((client_id::uuid), tsv);
Related:
Postgres using an index for one table but not another
What is the optimal data type for an MD5 field?
Would index lookup be noticeably faster with char vs varchar when all values are 36 chars
Or you could backport the feature from Postgres 11 - which is not an option with a hosted service like Google Cloud SQL for PostgreSQL as you mentioned in a comment. And I hardly see the use case where one would be skilled enough to implement the backport, but not to upgrade to Postgres 11.
We are trying to locate a performance problem and wondering if an index is being used.
We have a table with a composite key, "ID" and "Version", both integers.
We have a select that tries to find the max of "ID". (This is done via Entity framework if it makes a difference).
Will this use the index or will it do a table scan?
If the ID column is defined as the first part of a multi-column index, then DB2 will use that index to determine the MAX(). It will still probably try to use the index if you did a MAX(VERSION), but if you have a very large table, this may take quite a bit of processing.
You can confirm this using the explain facilities (link is for Linux/Unix/Windows 9.7).
I am a newbie in postgres. I have a column named host (string varchar2) in a table which has around 20 million rows. How do I use indexing to optimize my search to find particular host. Also, this column will be updated daily do I need to write trigger indexing at particular interval? If yes, how do I do that? (For Records I am using Ruby and Rails 3)
Assuming you're doing exact matches, you should just be able to create the index and leave it:
CREATE INDEX host_index ON table_name (host)
The query optimizer should just use that automatically.
You may wish to specify other options such as the collation to use.
See the PostgreSQL docs for CREATE INDEX for more information.
I'd suggest using BRIN Index since its introduction from PostgreSQL 9.5 rather than the conventional btree index.
For text search, it is recommended that you use GIN or GiST index types.
https://www.postgresql.org/docs/9.5/static/textsearch-indexes.html
Another possibility is that if you were only performing exact matching in the host column, i.e., no inequality comparisons (>, <) and partial matching (like, wildcard) involved, you may consider converting host to a hash integer to speed up the search significantly.