I am using PostgreSQL to compute empirical probability density functions for pairs of variables across all my data. I am trying to determine if/when it is more effective to index before computing the PDF. I run EXPLAIN CREATE INDEX like,
EXPLAIN CREATE INDEX AB ON xrootd ("F.mName", "F.mOpenTime");
CREATE INDEX AB ON xrootd ("F.mName", "F.mOpenTime");
But PSQL complains,
psql:sql/stats.sql:3: ERROR: syntax error at or near "INDEX"
LINE 2: EXPLAIN CREATE INDEX AB ON xrootd ("F.mName", "F.mOpenTime")...
Is there a better way of doing anything I am trying to do? At the very least, I would like to know if constructing the indexes is useful. I have a lot of variable and a lot of data, so speeding this up is crucial.
Checking the cost of CREATE INDEX would be able to tell me if make the index is too expensive for the gain of using it.
There is no EXPLAIN CREATE INDEX, as EXPLAIN only works for SELECTs and DML queries (INSERT/DELETE/UPDATE).
What you are probably looking for is called hypothetical indexes. There is a PostgreSQL extension for that: https://github.com/dalibo/hypopg
Related
I'm trying to build an index for a table with 1B of rows. 24 hours has passed and the query is still running:
CREATE INDEX idx1_table1b on table1b using HASH(column1).
Since column1 is often filtered with equality operator(=), I've chosen hash indexing to be the index type. The DB instance class I'm using is Serverless V2, ACU min-max:16-128, PostgreSQL 14.6.
Not sure if I missed anything in the configuration or statement, any help is appreciated, Thanks!
Found out the column has tons of duplicate value, which might be the cause why the hashing halted(or took a long time to build hash-index).
The solution to my problem is to use btree(which accommodates well duplicate values) and the indexed was built in minutes. The performance of using indexed column to perform join in a query is at milli-second performance.
I have an ltree column containing a tree with a depth of 3. I'm trying to write a query that can select all children at a specific depth (level 1 = get all parents, 2 = get all children, 3 = get all grandchildren). I know this is pretty straightforward with n_level:
SELECT path FROM hierarchies
WHERE
nlevel(path) = 1
LIMIT 1000;
I have 200,000 dummy records and it's pretty fast (~170 ms). However, this query uses a sequential scan. I think it'd be better to write it in a way that takes advantage of the ltree operators supported by the GiST index. Frustratingly, I can't seem to wrap my brain around them, and I haven't found a similar question on SO or DBA (besides this one on finding leaves)
Any advice is appreciated!
The only index that could support your query is a simple b-tree index on an expression.
create index on hierarchies((nlevel(path)))
Note however that it is quite possible for the planner to choose a sequential scan anyway, exemplary in the case the number of rows with level 1 is much more than other levels.
This below query I am using for a search:
I guess this current time is not bad but still I am searching for some kind of more optimizations. Also I saw in the analyze report this nested loop and nested loop joins shows the red. It would be great if I get an idea to reduce that. I was thinking to add index for search key. It would be great if I can get more suggestions to improve this. Here I have added the explain analyze result with 3 times execution, which ran in production
You could try to add ingredients.name or ingredients.code to an existing index or to create a new index so that more rows are filtered during ingredients index scan.
You should also try to avoid to use fonction on column name such as LOWER(ingredients.name) to make sure the right index is used.
it seems that my server won't use gin index.
I've created a new database with one table.
I've inserted one row as example.
I've loaded trigram extension and created gin index using trigrams
But when I check if the index works right I can see it doesn't
Any ideas?
SQL: http://pastebin.com/1yDQQA1Z
P.S. A day ago I've followed a tutorial about trigrams. Basically it was the same like my example above. The table had 2 columns, numeric(5, 0) and character varying (the one with gin trgm index). Query was with like operator using "%" and index was working (I could see Bitmap using in query explain), so I know, my server can use index (and its properly installed).
Thanks in advance.
Don't test on one row, it is meaningless.
Here's an excerpt of the documentation explaining why, in Examining Index Usage:
Use real data for experimentation. Using test data for setting up
indexes will tell you what indexes you need for the test data, but
that is all.
It is especially fatal to use very small test data sets. While
selecting 1000 out of 100000 rows could be a candidate for an index,
selecting 1 out of 100 rows will hardly be, because the 100 rows
probably fit within a single disk page, and there is no plan that can
beat sequentially fetching 1 disk page.
I've been working on a project at work and have come to the realization that I must invoke a function in several of the queries' WHERE clauses. The performance isn't terrible exactly, but I would love to improve it. So I looked at the docs for indexes which mentioned that:
An index field can be an expression computed from the values of one or more columns of the table row.
Awesome. So I tried creating an index:
CREATE INDEX idx_foo ON foo_table (stable_function(foo_column));
And received an error:
ERROR: functions in index expression must be marked IMMUTABLE
So then I read about Function Volatility Categories which had this to say about stable volatility:
In particular, it is safe to use an expression containing such a function in an index scan condition.
Based on the phrasing "index scan condition" I'm guessing it doesn't mean an actual index. So what does it mean? Is it possible to utilize a stable function in an index? Or do we have to go all the way and ensure this would work as an immutable function?
We're using Postgres v9.0.1.
An "index scan condition" is a search condition, and can use a volatile function, which will be called for each row processed. An index definition can only use a function if it is immutable -- that is, that function will always return the same value when called with any given set of arguments, and has no user-visible side effects. If you think about it a little, you should be able to see what kind of trouble you could get into if the function might return a different value than what it did when the index entry was created.
You might be tempted to lie to the database and declare a function as immutable which isn't really; but if you do, the database will probably do surprising things that you would rather it didn't.
9.0.1 has bugs for which fixes are available. Please upgrade to 9.0.somethingrecent.
http://www.postgresql.org/support/versioning/