ّ am trying to insert multiple records got from the join table to another table user_to_property. In the user_to_property table user_to_property_id is primary, not null it is not autoincrementing. So I am trying to add user_to_property_id manually by an increment of 1.
WITH selectedData AS
( -- selection of the data that needs to be inserted
SELECT t2.user_id as userId
FROM property_lines t1
INNER JOIN user t2 ON t1.account_id = t2.account_id
)
INSERT INTO user_to_property (user_to_property_id, user_id, property_id, created_date)
VALUES ((SELECT MAX( user_to_property_id )+1 FROM user_to_property),(SELECT
selectedData.userId
FROM selectedData),3,now());
The above query gives me the below error:
ERROR: more than one row returned by a subquery used as an expression
How to insert multiple records to a table from the join of other tables? where the user_to_property table contains a unique record for the same user-id and property_id there should be only 1 record.
Typically for Insert you use either values or select. The structure values( select...) often (generally?) just causes more trouble than it worth, and it is never necessary. You can always select a constant or an expression. In this case convert to just select. For generating your ID get the max value from your table and then just add the row_number that you are inserting: (see demo)
insert into user_to_property(user_to_property_id
, user_id
, property_id
, created
)
with start_with(current_max_id) as
( select max(user_to_property_id) from user_to_property )
select current_max_id + id_incr, user_id, 3, now()
from (
select t2.user_id, row_number() over() id_incr
from property_lines t1
join users t2 on t1.account_id = t2.account_id
) js
join start_with on true;
A couple notes:
DO NOT use user for table name, or any other object name. It is a
documented reserved word by both Postgres and SQL standard (and has
been since Postgres v7.1 and the SQL 92 Standard at lest).
You really should create another column or change the column type
user_to_property_id to auto-generated. Using Max()+1, or
anything based on that idea, is a virtual guarantee you will generate
duplicate keys. Much to the amusement of users and developers alike.
What happens in an MVCC when 2 users run the query concurrently.
I have two query by union all and insert into temp table.
Query 1
select *
from (
select a.id as id, a.name as name from a
union all
select b.id as id, b.name as name from b
)
Query 2
drop table if exists temporary;
create temp table temporary as
select id as id, name as name
from a;
insert into temporary
select id as id, name as name
from b;
select * from temp;
Please tell me which one is better for performance?
I would expect the second option to have better performance, at least at the the database level. Both versions require doing a full table scan of both the a and b tables. But the first version would create an unnecessary intermediate table, used only for the purpose of the insert.
The only potential issue with doing two separate inserts is latency, i.e. the time it might take some process to get to and from the database. If you are worried about this, then you can limit to one insert statement:
INSERT INTO temporary (id, name)
SELECT id, name FROM a
UNION ALL
SELECT id, name FROM b;
This would just require one trip to the database.
I think use union all is the better performance way, not sure, you can try it your self. In tab run of SQL application alway show time to run. I take a snapshot in oracle; mysql and sql sv have the same tool to see it
click here to see image
I have a table in a PostgreSQL 8.3.8 database, which has no keys/constraints on it, and has multiple rows with exactly the same values.
I would like to remove all duplicates and keep only 1 copy of each row.
There is one column in particular (named "key") which may be used to identify duplicates, i.e. there should only exist one entry for each distinct "key".
How can I do this? (Ideally, with a single SQL command.)
Speed is not a problem in this case (there are only a few rows).
A faster solution is
DELETE FROM dups a USING (
SELECT MIN(ctid) as ctid, key
FROM dups
GROUP BY key HAVING COUNT(*) > 1
) b
WHERE a.key = b.key
AND a.ctid <> b.ctid
DELETE FROM dupes a
WHERE a.ctid <> (SELECT min(b.ctid)
FROM dupes b
WHERE a.key = b.key);
This is fast and concise:
DELETE FROM dupes T1
USING dupes T2
WHERE T1.ctid < T2.ctid -- delete the older versions
AND T1.key = T2.key; -- add more columns if needed
See also my answer at How to delete duplicate rows without unique identifier which includes more information.
EXISTS is simple and among the fastest for most data distributions:
DELETE FROM dupes d
WHERE EXISTS (
SELECT FROM dupes
WHERE key = d.key
AND ctid < d.ctid
);
From each set of duplicate rows (defined by identical key), this keeps the one row with the minimum ctid.
Result is identical to the currently accepted answer by a_horse. Just faster, because EXISTS can stop evaluating as soon as the first offending row is found, while the alternative with min() has to consider all rows per group to compute the minimum. Speed is of no concern to this question, but why not take it?
You may want to add a UNIQUE constraint after cleaning up, to prevent duplicates from creeping back in:
ALTER TABLE dupes ADD CONSTRAINT constraint_name_here UNIQUE (key);
About the system column ctid:
Is the system column “ctid” legitimate for identifying rows to delete?
If there is any other column defined UNIQUE NOT NULL column in the table (like a PRIMARY KEY) then, by all means, use it instead of ctid.
If key can be NULL and you only want one of those, too, use IS NOT DISTINCT FROM instead of =. See:
How do I (or can I) SELECT DISTINCT on multiple columns?
As that's slower, you might instead run the above query as is, and this in addition:
DELETE FROM dupes d
WHERE key IS NULL
AND EXISTS (
SELECT FROM dupes
WHERE key IS NULL
AND ctid < d.ctid
);
And consider:
Create unique constraint with null columns
For small tables, indexes generally do not help performance. And we need not look further.
For big tables and few duplicates, an existing index on (key) can help (a lot).
For mostly duplicates, an index may add more cost than benefit, as it has to be kept up to date concurrently. Finding duplicates without index becomes faster anyway because there are so many and EXISTS only needs to find one. But consider a completely different approach if you can afford it (i.e. concurrent access allows it): Write the few surviving rows to a new table. That also removes table (and index) bloat in the process. See:
How to delete duplicate entries?
I tried this:
DELETE FROM tablename
WHERE id IN (SELECT id
FROM (SELECT id,
ROW_NUMBER() OVER (partition BY column1, column2, column3 ORDER BY id) AS rnum
FROM tablename) t
WHERE t.rnum > 1);
provided by Postgres wiki:
https://wiki.postgresql.org/wiki/Deleting_duplicates
I would use a temporary table:
create table tab_temp as
select distinct f1, f2, f3, fn
from tab;
Then, delete tab and rename tab_temp into tab.
I had to create my own version. Version written by #a_horse_with_no_name is way too slow on my table (21M rows). And #rapimo simply doesn't delete dups.
Here is what I use on PostgreSQL 9.5
DELETE FROM your_table
WHERE ctid IN (
SELECT unnest(array_remove(all_ctids, actid))
FROM (
SELECT
min(b.ctid) AS actid,
array_agg(ctid) AS all_ctids
FROM your_table b
GROUP BY key1, key2, key3, key4
HAVING count(*) > 1) c);
Another approach (works only if you have any unique field like id in your table) to find all unique ids by columns and remove other ids that are not in unique list
DELETE
FROM users
WHERE users.id NOT IN (SELECT DISTINCT ON (username, email) id FROM users);
Postgresql has windows function, you can use rank() to archive your goal, sample:
WITH ranked as (
SELECT
id, column1,
"rank" () OVER (
PARTITION BY column1
order by column1 asc
) AS r
FROM
table1
)
delete from table1 t1
using ranked
where t1.id = ranked.id and ranked.r > 1
Here is another solution, that worked for me.
delete from table_name a using table_name b
where a.id < b.id
and a.column1 = b.column1;
How about:
WITH
u AS (SELECT DISTINCT * FROM your_table),
x AS (DELETE FROM your_table)
INSERT INTO your_table SELECT * FROM u;
I had been concerned about execution order, would the DELETE happen before the SELECT DISTINCT, but it works fine for me.
And has the added bonus of not needing any knowledge about the table structure.
Here is a solution using PARTITION BY and the virtual ctid column, which is works like a primary key, at least within a single session:
DELETE FROM dups
USING (
SELECT
ctid,
(
ctid != min(ctid) OVER (PARTITION BY key_column1, key_column2 [...])
) AS is_duplicate
FROM dups
) dups_find_duplicates
WHERE dups.ctid == dups_find_duplicates.ctid
AND dups_find_duplicates.is_duplicate
A subquery is used to mark all rows as duplicates or not, based on whether they share the same "key columns", but not the same ctid, as the "first" one found in the "partition" of rows sharing the same keys.
In other words, "first" is defined as:
min(ctid) OVER (PARTITION BY key_column1, key_column2 [...])
Then, all rows where is_duplicate is true are deleted by their ctid.
From the documentation, ctid represents (emphasis mine):
The physical location of the row version within its table. Note that although the ctid can be used to locate the row version very quickly, a row's ctid will change if it is updated or moved by VACUUM FULL. Therefore ctid is useless as a long-term row identifier. A primary key should be used to identify logical rows.
well, none of this solution would work if the id is duplicated which is my use case, then the solution is simple:
myTable:
id name
0 value
0 value
0 value
1 value1
1 value1
create dedupMyTable as select distinct * from myTable;
delete from myTable;
insert into myTable select * from dedupMyTable;
select * from myTable;
id name
0 value
1 value1
well you shouldn't have duplicates id into your table unless it doesn't have PK constraints or simply doesn't support it such as Hive/data lake tables
Better pay attention when loading your data to avoid dups over ID's
DELETE FROM tracking_order
WHERE
mvd_id IN (---column you need to remove duplicate
SELECT
mvd_id
FROM (
SELECT
mvd_id,thoi_gian_gui,
ROW_NUMBER() OVER (
PARTITION BY mvd_id
ORDER BY thoi_gian_gui desc) AS row_num
FROM
tracking_order
) s_alias
WHERE row_num > 1)
AND thoi_gian_gui in ( --column you used to compare to delete duplicates, eg last update time
SELECT
thoi_gian_gui
FROM (
SELECT
thoi_gian_gui,
ROW_NUMBER() OVER (
PARTITION BY mvd_id
ORDER BY thoi_gian_gui desc) AS row_num
FROM
tracking_order
) s_alias
WHERE row_num > 1)
My code, I remove all duplicates 7800445 row and keep only 1 copy of each row with 7 min 28 secs.
enter image description here
This worked well for me. I had a table, terms, that contained duplicate values. Ran a query to populate a temp table with all of the duplicate rows. Then I ran the a delete statement with those ids in the temp table. value is the column that contained the duplicates.
CREATE TEMP TABLE dupids AS
select id from (
select value, id, row_number()
over (partition by value order by value)
as rownum from terms
) tmp
where rownum >= 2;
delete from [table] where id in (select id from dupids)
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 am using postgresql. I have a table with about 10 million of records. I need to update a column of the table say 'a' using a sequence. This column needs to be updated in the order of another column say 'b'. So, for any two records r1 and r2, if value of 'a' for r1 is less than value of 'a' for r2 then value of 'b' for r1 must be less than value of 'b' for r2.
I am using something like this:
UPDATE table
SET col1 = nextval('myseq')
WHERE key IN (SELECT key
FROM table
ORDER BY col2);
key is the primary key of the table.
But it is taking too much time. Can anyone help me in doing it in optimized way.
Thanks
Try something like:
UPDATE table t
SET col1 = t2.new_col1
FROM (SELECT t2.key, nextval('myseq') as new_col1
FROM table t2
ORDER BY t2.col2) t2
WHERE t1.key = t2.key;
Or better something like:
UPDATE table t
SET col1 = t2.new_col1
FROM (SELECT t2.key,
row_number() OVER (ORDER BY t2.col2) as new_col1
FROM table t2) t2
WHERE t1.key = t2.key;
Don't use update at all.
Use a SELECT INTO like this:
SELECT *, nextval('myseq') AS col1
INTO new_table
FROM
(
SELECT *
FROM table
ORDER BY key
) AS sorted
Then replace the old table with the new. You'll have to recreate all your indexes and reinforce your primary keys.
Postgres doesn't replace each row it updates, it adds a second entry for the row and deprecates the old one. So if you're doing millions of updates it will make access extremely slow. Replacing the whole table is usually your best option.