I know this might be redundant but I have had the same query running for almost 3 days and before I kill it, I would like to get a community sanity check.
DELETE
FROM mytble
WHERE ogc_fid NOT IN
(SELECT MAX(dup.ogc_fid)
FROM mytble As dup
GROUP BY dup.id)
mytble is the name of the table, ogc_fid is the name of the unique id field and id is the name of the field that I want to be the unique id. There are 41 million records in the table and indexes are built and everything so I am still a bit concerned about why its taking so long to complete. Any thoughts on this?
If I understood correctly, you want to delete all the records for which a record with the same dup_id
(but with a higher ogc_fid) exists. And keep only those with the highest ogc_fid.
-- DELETE -- uncomment this line and comment the next line if proven innocent.
SELECT COUNT(*)
FROM mytble mt
WHERE EXISTS (
SELECT *
FROM mytble nx
WHERE nx.dup_id = mt.dup_id -- there exists a row with the same dup_id
AND nx.ogc_fid > mt.ogc_fid -- , ... but with a higher ogc_fid
);
With an index on dup_id (and maybe on ogc_id) this should run maybe a few minutes for 41M records.
UPDATE: if no indexes exist, you could speed up the above queries by first creating an index:
CREATE UNIQUE INDEX sinterklaas ON mytble (dup_id, ogc_id);
Would be nice if you provided explain output, but what you're doing might be faster when done like this (again, I'd look up explain):
DELETE FROM mytable d
USING mytable m
LEFT JOIN (SELECT max(ogc_fid) AS f FROM mytble GROUP BY id) AS q ON m.ogc_fid=q.f
WHERE d.ogc_fid=m.ogc_fid AND q.f IS NULL;
Related
I am using PostgreSQL v 11.6. I've read a lot of questions asking about how to optimize queries which are using DISTINCT. Mine is not that different, but despite the other questions where the people usually want's to keep the other part of the query and just somehow make DISTINCT ON faster, I am willing to rewrite the query with the sole purpose to make it as performent as possible. The current query is this:
SELECT DISTINCT s.name FROM app.source AS s
INNER JOIN app.index_value iv ON iv.source_id = s.id
INNER JOIN app.index i ON i.id = iv.index_id
INNER JOIN app.namespace AS ns ON i.namespace_id=ns.id
WHERE (SELECT TRUE FROM UNNEST(Array['Default']::CITEXT[]) AS nss WHERE ns.name ILIKE nss LIMIT 1)
ORDER BY s.name;
The app.source table contains about 800 records. The other tables are under 5000 recrods tops, but the app.index_value contains 35_420_354 (about 35 million records) which I guess causes the overall slow execution of the query.
The EXPLAIN ANALYZE returns this:
I think that all relevent indexes are in place (maybe there can be made some small optimization) but I think that in order to get significant improvements in the time execution I need a better logic for the query.
The current execution time on a decent machine is 35~38 seconds.
Your query is not using DISTINCT ON. It is merely using DISTINCT which is quite a different thing.
SELECT DISTINCT is indeed often an indicator for a oorly written query, because DISTINCT is used to remove duplicates and it is often the case tat the query creates those duplicates itself. The same is true for your query. You simply want all names where certain entries exist. So, use EXISTS (or IN for that matter).
EXISTS
SELECT s.name
FROM app.source AS s
WHERE EXISTS
(
SELECT NULL
FROM app.index_value iv
JOIN app.index i ON i.id = iv.index_id
JOIN app.namespace AS ns ON i.namespace_id = ns.id
WHERE iv.source_id = s.id
AND (SELECT TRUE FROM UNNEST(Array['Default']::CITEXT[]) AS nss WHERE ns.name ILIKE nss LIMIT 1)
)
ORDER BY s.name;
IN
SELECT s.name
FROM app.source AS s
WHERE s.id IN
(
SELECT iv.source_id
FROM app.index_value iv
JOIN app.index i ON i.id = iv.index_id
JOIN app.namespace AS ns ON i.namespace_id = ns.id
WHERE (SELECT TRUE FROM UNNEST(Array['Default']::CITEXT[]) AS nss WHERE ns.name ILIKE nss LIMIT 1)
)
ORDER BY s.name;
Thus we avoid creating an unnecessarily large intermediate result.
Update 1
From the database side we can support queries with appropriate indexes. The only criteria used in your query that limits selected rows is the array lookup, though. This is probably slow, because the DBMS cannot use database indexes here as far as I know. And depending on the array content we can end up with zero app.namespace rows, few rows, many rows or even all rows. The DBMS cannot even make proper assumptions on know how many. From there we'll retrieve the related index and index_value rows. Again, these can be all or none. The DBMS could use indexes here or not. If it used indexes this would be very fast on small sets of rows and extremely slow on large data sets. And if it used full table scans and joined these via hash joins for instance, this would be the fastest approach for many rows and rather slow on few rows.
You can create indexes and see whether they get used or not. I suggest:
create index idx1 on app.index (namespace_id, id);
create index idx2 on app.index_value (index_id, source_id);
create index idx3 on app.source (id, name);
Update 2
I am not versed with arrays. But t looks like you want to check if a matching condition exists. So again EXISTS might be a tad more appropriate:
WHERE EXISTS
(
SELECT NULL
FROM UNNEST(Array['Default']::CITEXT[]) AS nss
WHERE ns.name ILIKE nss
)
Update 3
One more idea (I feel stupid now to have missed that): For each source we just look up whether there is at least one match. So maybe the DBMS starts with the source table and goes from that table to the next. For this we'd use the following indexes:
create index idx4 on index_value (source_id, index_id);
create index idx5 on index (id, namespace_id);
create index idx6 on namespace (id, name);
Just add them to your database and see what happens. You can always drop indexes again when you see the DBMS doesn't use them.
i was trying to get the id and the number from table with condition of number isn't in the id.
select id,number from tmp_t where number not in (select id from tmp_t)
Have tried the query and it's taking soooo looonggg... like almost 40 minutes and i got disconnected from server.
So what should i do? the data is around 500K rows..
So i wanted to show "here you go the id and the number, which the number didn't exist in the id."
Because i tried to insert the number, but the number is a FK and depending on the ID, so i wanted to know the id and the number, that's why i'm using not in.
Maybe someone know? Btw im using Postgresql-13
You can write it with NOT EXISTS instead, although these queries will have different results if any value of id is NULL (in which case, NOT IN probably yields not the answer you want, so NOT EXISTS is better from that perspective as well.)
select id,number from tmp_t where not exists
(select 1 from tmp_t a where a.id=tmp_t.number);
But your formulation is also efficient as long as work_mem is large enough.
Typically NOT EXISTS is faster (and doesn't suffer from surprises if NULL values are involved):
select t1.id, t1.number
from tmp_t t1
where not exists (select *
from tmp_t t2
where t2.id = t1.number)
I have something like this. With this part of code I detect if a vehicle stopped at least 5 minutes.
And works but, with a large amount of data, it starts to be slow.
I did a lot of tests and I'm sure that my problem is in the not exists block.
My table:
CREATE TABLE public.messages
(
id bigint PRIMARY KEY DEFAULT nextval('messages_id_seq'::regclass),
messagedate timestamp with time zone NOT NULL,
vehicleid integer NOT NULL,
driverid integer NOT NULL,
speedeffective double precision NOT NULL,
-- ... few nonsense properties
)
WITH (
OIDS=FALSE
);
ALTER TABLE public.messages OWNER TO postgres;
CREATE INDEX idx_messages_1 ON public.messages
USING btree (vehicleid, messagedate);
And my query:
SELECT
*
FROM
messages m
WHERE
m.speedeffective > 0
and m.next_speedeffective = 0
and not exists( -- my problem
select id
from messages
where
vehicleid = m.vehicleid
and speedeffective > 5 -- I forgot this condition
and messagedate > m.messagedate
and messagedate <= m.messagedate + interval '5 minutes'
)
I can't figure out how to build the condition in a more performant way.
Edit DAY2:
I added a previous table like this to use in the second table:
WITH messagesx as (
SELECT
vehicleid,
messagedate
FROM
messages
WHERE
speedeffective > 5
)
and now works better. I think that I'm missing a little detail.
Typically, a 'NOT EXISTS' will slow down your query as it requires a full scan of the table for each of the outer rows. Try to incorporate the same functionality within a join (I'm trying to rewrite the query here, without knowing the table, so I might make a mistake here):
SELECT
*
FROM
messages m1
LEFT JOIN
messages m2
ON m1.vehicleid = m2.vehicleid AND m1.messagedate < m2.messagedate AND m1.messagedate <= m2.messagedate+interval '5 minutes'
WHERE
speedeffective > 0
and next_speedeffective = 0
and m2.vehicleid IS NULL
Take note that the NOT EXISTS is rewritten as the non-hit of the join condition.
Based on this answer: https://stackoverflow.com/a/36445233/5000827
and reading about NOT IN, NOT EXISTS and LEFT JOIN (where join is NULL)
For PostgreSQL, NOT EXISTS and LEFT JOIN are anti-join and works at the same way. (This is the reason why the #CountZukula answer's result is almost the same than mine)
The problem was on the kind of operation: Nest or Hash.
So, based on this: https://www.postgresql.org/docs/9.6/static/routine-vacuuming.html
PostgreSQL's VACUUM command has to process each table on a regular basis for several reasons:
To recover or reuse disk space occupied by updated or deleted rows.
To update data statistics used by the PostgreSQL query planner.
To update the visibility map, which speeds up index-only scans.
To protect against loss of very old data due to transaction ID wraparound or multixact ID wraparound.
I made a VACUUM ANALYZE to messages table and the same query works way fast.
So, with the VACUUM PostgreSQL can decide better.
I don't understand why the following doesn't fail. How does the subquery have access to a column from a different table at the higher level?
drop table if exists temp_a;
create temp table temp_a as
(
select 1 as col_a
);
drop table if exists temp_b;
create temp table temp_b as
(
select 2 as col_b
);
select col_a from temp_a where col_a in (select col_a from temp_b);
/*why doesn't this fail?*/
The following fail, as I would expect them to.
select col_a from temp_b;
/*ERROR: column "col_a" does not exist*/
select * from temp_a cross join (select col_a from temp_b) as sq;
/*ERROR: column "col_a" does not exist
*HINT: There is a column named "col_a" in table "temp_a", but it cannot be referenced from this part of the query.*/
I know about the LATERAL keyword (link, link) but I'm not using LATERAL here. Also, this query succeeds even in pre-9.3 versions of Postgres (when the LATERAL keyword was introduced.)
Here's a sqlfiddle: http://sqlfiddle.com/#!10/09f62/5/0
Thank you for any insights.
Although this feature might be confusing, without it, several types of queries would be more difficult, slower, or impossible to write in sql. This feature is called a "correlated subquery" and the correlation can serve a similar function as a join.
For example: Consider this statement
select first_name, last_name from users u
where exists (select * from orders o where o.user_id=u.user_id)
Now this query will get the names of all the users who have ever placed an order. Now, I know, you can get that info using a join to the orders table, but you'd also have to use a "distinct", which would internally require a sort and would likely perform a tad worse than this query. You could also produce a similar query with a group by.
Here's a better example that's pretty practical, and not just for performance reasons. Suppose you want to delete all users who have no orders and no tickets.
delete from users u where
not exists (select * from orders o where o.user_d = u.user_id)
and not exists (select * from tickets t where t.user_id=u.ticket_id)
One very important thing to note is that you should fully qualify or alias your table names when doing this or you might wind up with a typo that completely messes up the query and silently "just works" while returning bad data.
The following is an example of what NOT to do.
select * from users
where exists (select * from product where last_updated_by=user_id)
This looks just fine until you look at the tables and realize that the table "product" has no "last_updated_by" field and the user table does, which returns the wrong data. Add the alias and the query will fail because no "last_updated_by" column exists in product.
I hope this has given you some examples that show you how to use this feature. I use them all the time in update and delete statements (as well as in selects-- but I find an absolute need for them in updates and deletes often)
I have a table in my database and I want for each row in my table to have an unique id and to have the rows named sequently.
For example: I have 10 rows, each has an id - starting from 0, ending at 9. When I remove a row from a table, lets say - row number 5, there occurs a "hole". And afterwards I add more data, but the "hole" is still there.
It is important for me to know exact number of rows and to have at every row data in order to access my table arbitrarily.
There is a way in sqlite to do it? Or do I have to manually manage removing and adding of data?
Thank you in advance,
Ilya.
It may be worth considering whether you really want to do this. Primary keys usually should not change through the lifetime of the row, and you can always find the total number of rows by running:
SELECT COUNT(*) FROM table_name;
That said, the following trigger should "roll down" every ID number whenever a delete creates a hole:
CREATE TRIGGER sequentialize_ids AFTER DELETE ON table_name FOR EACH ROW
BEGIN
UPDATE table_name SET id=id-1 WHERE id > OLD.id;
END;
I tested this on a sample database and it appears to work as advertised. If you have the following table:
id name
1 First
2 Second
3 Third
4 Fourth
And delete where id=2, afterwards the table will be:
id name
1 First
2 Third
3 Fourth
This trigger can take a long time and has very poor scaling properties (it takes longer for each row you delete and each remaining row in the table). On my computer, deleting 15 rows at the beginning of a 1000 row table took 0.26 seconds, but this will certainly be longer on an iPhone.
I strongly suggest that you re-think your design. In my opinion your asking yourself for troubles in the future (e.g. if you create another table and want to have some relations between the tables).
If you want to know the number of rows just use:
SELECT count(*) FROM table_name;
If you want to access rows in the order of id, just define this field using PRIMARY KEY constraint:
CREATE TABLE test (
id INTEGER PRIMARY KEY,
...
);
and get rows using ORDER BY clause with ASC or DESC:
SELECT * FROM table_name ORDER BY id ASC;
Sqlite creates an index for the primary key field, so this query is fast.
I think that you would be interested in reading about LIMIT and OFFSET clauses.
The best source of information is the SQLite documentation.
If you don't want to take Stephen Jennings's very clever but performance-killing approach, just query a little differently. Instead of:
SELECT * FROM mytable WHERE id = ?
Do:
SELECT * FROM mytable ORDER BY id LIMIT 1 OFFSET ?
Note that OFFSET is zero-based, so you may need to subtract 1 from the variable you're indexing in with.
If you want to reclaim deleted row ids the VACUUM command or pragma may be what you seek,
http://www.sqlite.org/faq.html#q12
http://www.sqlite.org/lang_vacuum.html
http://www.sqlite.org/pragma.html#pragma_auto_vacuum