Optimise SQL Query with SUM and Case - sql

Question

I have the following query which takes more than 1 mn to return data:
SELECT extract(HOUR
FROM date) AS HOUR,
SUM(CASE
WHEN country_name = France THEN atdelay
ELSE 0
END) AS France,
SUM(CASE
WHEN country_name = USA THEN atdelay
ELSE 0
END) AS USA,
SUM(CASE
WHEN country_name = China THEN atdelay
ELSE 0
END) AS China,
SUM(CASE
WHEN country_name = Brezil THEN atdelay
ELSE 0
END) AS Brazil,
SUM(CASE
WHEN country_name = Argentine THEN atdelay
ELSE 0
END) AS Argentine,
SUM(CASE
WHEN country_name = Equator THEN atdelay
ELSE 0
END) AS Equator,
SUM(CASE
WHEN country_name = Maroc THEN atdelay
ELSE 0
END) AS Maroc,
SUM(CASE
WHEN country_name = Egypt THEN atdelay
ELSE 0
END) AS Egypt
FROM
(SELECT *
FROM Contry
WHERE (TO_CHAR(entrydate, 'YYYY-MM-DD')::DATE) >= '2021-01-01'
AND (TO_CHAR(entrydate, 'YYYY-MM-DD')::DATE) <= '2021-01-31'
AND code IS NOT NULL) AS A
GROUP BY HOUR
ORDER BY HOUR ASC;
My table is structured like so:
+---------------------+---------------+------+-----+-------------------+-----------------------------+
| Field | Type | Null | Key | Default | Extra |
+---------------------+---------------+------+-----+-------------------+-----------------------------+
| id | bigint(20) | NO | PRI | NULL | auto_increment |
| country_name | varchar(30) | YES | MUL | NULL | |
| date | timestamp | NO | MUL | CURRENT_TIMESTAMP | on update CURRENT_TIMESTAMP |
| entrydate | timestamp | NO | | NULL | |
| keyword_count | int(11) | YES | | NULL | |
| all_impressions | int(11) | YES | | NULL | |
| all_clicks | int(11) | YES | | NULL | |
| all_ctr | float | YES | | NULL | |
| all_positions | float | YES | | NULL | |
+---------------------+---------------+------+-----+-------------------+-----------------------------+
The current table size is closing in on 50 million rows.
How can I make this faster?
I'm hoping there is another query or table optimisation I can do - alternatively I could pre-aggregate the data but I'd rather avoid that.

Answer 1

(Your table definition doesn't look like you are really using Postgres, but as you tagged your question with Postgres I'll answer it nevertheless)
One obvious attempt would be to create an index on entrydate, then change your WHERE clause so it can make use of that. When it comes to timestamp columns and a range condition it's usually better to use the "next day" as the upper limit together with < instead of <=
WHERE entrydate >= date '2021-01-01'
AND entrydate < date '2021-02-01'
AND code IS NOT NULL
If the condition AND code IS NOT NULL removes many rows in addition to the date range, you can created a partial index.
create index on country (entrydate)
where code IS NOT NULL;
However, when a large part of the rows qualifies for code is not null the additional filter won't help very much.
Not performance related, but the conditional aggregation can be written in a bit more compact way using the filter clause:
sum(atdelay) filter (where country_name = 'France') as france