I want to calculate with an alias in sqlite (Example is modified from http://www.sqlitetutorial.net):
if i do it like this, i get the error message "no such column: tracks_count"
SELECT albumid,
title,
(
SELECT count(trackid)
FROM tracks
WHERE tracks.AlbumId = albums.AlbumId
)
tracks_count, tracks_count * album_nr
FROM albums
ORDER BY tracks_count DESC;
if i do it like this, i get zero for the mulitplication
SELECT albumid,
title,
(
SELECT count(trackid)
FROM tracks
WHERE tracks.AlbumId = albums.AlbumId
)
tracks_count, "tracks_count" * album_nr
FROM albums
ORDER BY tracks_count DESC;
Table data for the example:
table albums
table tracks
You don't even need a subquery here:
SELECT
a.albumid,
a.title,
COUNT(t.albumid) AS tracks_count,
COUNT(t.albumid) * a.album_nr AS other_count
FROM albums a
LEFT JOIN tracks t
ON a.albumid = t.albumid
GROUP BY
a.albumid,
a.title;
If you wanted to make your current approach work, then the problem you are having is that you are referring to the tracks_count alias in the same select in which it was defined. This isn't allowed, because the alias may not have even been computed yet. But, I would recommend using the answer I gave above.
Related
I am trying to get a list of most used tags for posts on a website on a given day. I currently have this query:
SELECT posts.pdate, tags.tag, count(posts.pid) as post_count
FROM posts, tags
WHERE posts.pid = tags.pid
GROUP BY posts.pdate, tags.tag
ORDER BY posts.pdate;
This provides me with each distinct tag, along with the date they are used on as well as how many posts used them, returning me with this:
2020-09-10|CMPUT291|1
2020-09-10|computing|1
2020-09-10|database|2
2020-09-10|frequentTag1|2
2020-09-10|relational|2
2020-09-10|sql|1
2020-09-10|tieTag1|2
2020-09-11|Database|1
2020-09-11|data|1
2020-09-11|relational|1
2020-09-11|sql|1
2020-09-13|Database|1
2020-09-13|Sql language|1
2020-09-13|access|1
2020-09-13|frequentTag3|2
2020-09-13|query|3
2020-09-13|relational|3
2020-09-13|sql|1
2020-09-17|Database|1
2020-09-17|frequentTag3|3
2020-09-17|query|1
2020-09-17|relational|1
2020-09-17|sql|1
2020-09-17|sql language|1
2020-09-20|RELATIONAL|1
2020-09-20|database|1
2020-09-20|query|1
2020-09-20|sql language|1
2020-09-25|database|1
2020-09-25|sql language|1
2020-09-30|boring|2
2020-09-30|extra tag|1
2020-09-30|fun|3
2020-09-30|just here|1
2020-09-30|more tag|1
2020-09-30|sleep|3
2020-09-30|tag tag|1
2020-09-30|tag test|1
2020-09-30|test tag|1
But, I now need to make it only give me the rows that have the max (or all of them with max in case of a tie) for each date.
I WANT to be able to use MAX(count(posts.pid)) but I know that doesn't work so I need to find an alternative.
I should get a final result of this:
2020-09-10|database|2
2020-09-10|frequentTag1|2
2020-09-10|relational|2
2020-09-10|tieTag1|2
2020-09-11|Database|1
2020-09-11|data|1
2020-09-11|relational|1
2020-09-11|sql|1
2020-09-13|query|3
2020-09-13|relational|3
2020-09-17|frequentTag3|3
2020-09-20|RELATIONAL|1
2020-09-20|database|1
2020-09-20|query|1
2020-09-20|sql language|1
2020-09-25|database|1
2020-09-25|sql language|1
2020-09-30|fun|3
2020-09-30|sleep|3
Any help would be greatly appreciated.
APPLICABLE SCHEMA:
create table posts (
pid char(4),
pdate date,
title text,
body text,
poster char(4),
primary key (pid),
foreign key (poster) references users
);
create table tags (
pid char(4),
tag text,
primary key (pid,tag),
foreign key (pid) references posts
);
You can use RANK() window function:
SELECT pdate, tag, post_count
FROM (
SELECT p.pdate,
t.tag,
COUNT(*) post_count,
RANK() OVER (PARTITION BY p.pdate ORDER BY COUNT(*) DESC) rnk
FROM posts p INNER JOIN tags t
ON p.pid = t.pid
GROUP BY p.pdate, t.tag
)
WHERE rnk = 1
ORDER BY pdate, tag;
You should use a proper JOIN with an ON clause instead of that outdated syntax with the WHERE clause.
I have a query that I run in PostgreSQL like this:
select
c_count, count(*) as custdist
from (
select
c_custkey,
count(o_orderkey)
from
customer left outer join orders on
c_custkey = o_custkey
and o_comment not like '%special%requests%'
group by
c_custkey
)as c_orders (c_custkey, c_count)
group by
c_count
order by
custdist desc,
c_count desc;
And I wanted to run it on SQLite, but I got this error: Error: near" (": syntax error. Maybe he doesn't recognize this as c_orders (c_custkey, c_count).
Is there any way to rewrite this query to execute in SQLite?
SQLite does not allow redefining/renaming columns for an nested, aliased query. You can do that with a WITH clause (i.e. Common Table Expression; CTE). Or you can add aliases to the nested query columns directly using AS keyword.
Interesting that this is exactly how the outer query columns are named. Just use the same pattern for the nested query. I don't use PostgreSQL, but why not add aliases directly on each column and complicate it by using different syntax for each part of the query?
select
c_count, count(*) as custdist
from (
select
c_custkey,
count(o_orderkey) AS c_count
from
customer left outer join orders on
c_custkey = o_custkey
and o_comment not like '%special%requests%'
group by
c_custkey
) AS c_orders
group by
c_count
order by
custdist desc,
c_count desc;
I'm trying to use values from an apex_t_numbers collection in a SELECT query as WITH subquery:
atn_cur_ids := apex_string.split_numbers(arg_v_ids, ':');
-- So if arg_v_ids := '1:2:3', then atn_cur_ids := apex_t_numbers(1, 2, 3)
with t_cur_ids as (
select * as id from table(atn_cur_ids);
)
select text from t_texts
join t_cur_ids on t_texts.id = t_cur_ids.id
And here's the problem - apex_t_numbers is a table of number, not of record type with named fields. Oracle SQL doesn't allow to give aliases to a * even if it has only one single "anonymous" column.
A possible solution could be a function that both
receives * and
returns value per row
But I am aware of only one that can get a * and return something - count(*), and it doesn't meet the second requirement.
Alright, found a solution. It could be done with column_value as a name of column:
with t_cur_ids as (
select column_value as id from table(atn_cur_ids);
)
select text from t_texts
join t_cur_ids on t_texts.id = t_cur_ids.id
here is my query
select *
from table
where id in ( select string_agg(CAST(id as varchar), '","') FROM table)
string_agg() is completely useless and unnecessary for that:
select *
from table_one
where id in (select id FROM other_table)
I assume you are doing that for two different tables, otherwise that would be a very expensive way of writing: select * from table where id is not null
As a training exercise I'm working on a fictional SQLite database resembling League of Legends, and I need to perform a left outer join to get a table of all players and if they have skins that are not called 'Classic', return those too.
I currently have this query:
SELECT * FROM players
LEFT OUTER JOIN (SELECT * FROM playerchampions WHERE NOT championskin = 'Classic')
ON name = playername
Which returns what I am looking for, but also a lot of columns I don't want (player experience, player IP, player RP, playername in the playerchampions table. The code for the two tables is as following:
CREATE TABLE players (
name TEXT PRIMARY KEY,
experience INTEGER,
currencyip INTEGER,
currencyrp INTEGER
);
CREATE TABLE playerchampions (
playername TEXT REFERENCES players ( name ) ON UPDATE CASCADE,
championname TEXT REFERENCES champions ( name ) ON UPDATE CASCADE,
championskin TEXT REFERENCES skins ( skinname ) ON UPDATE CASCADE,
PRIMARY KEY ( playername, championname, championskin )
);
As I said, the query executes, but I can't use SELECT players.name, playerchampions.championname, playerchampions.championskin as the playerchampions columns are not given their proper table name when returned.
How do I fix this?
Try using aliases:
SELECT p.name, c.championskin FROM players p LEFT OUTER JOIN (SELECT pc.playername playername, pc.championskin championskin FROM playerchampions pc WHERE NOT pc.championskin = 'Classic') c ON p.name = c.playername;
Not sure if its exactly what you need, but it will get you closer...
SELECT * FROM players p LEFT OUTER JOIN playerchampions pc ON (p.name = pc.playername) WHERE NOT pc.championskin = 'Classic'