MySQL performance issue on multiple select inside each other - mysql

Question

Below you can see my query is a big query running over a big table if you consider 200,000 data big but it loads over 10 sec to load I want to get expert help to optimize the query: any suggestion would be highly appreciated.
SELECT mt5_users.Name AS Name,
Test2.Login AS SLogin,
(
SELECT COUNT(Test.Order)
FROM (
SELECT *
FROM (
SELECT MAX(`Order`) AS `Order`,
SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(DISTINCT Time SEPARATOR ","), ",", 1), ",", -1) AS OPEN_TIME,
SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(DISTINCT Time SEPARATOR ","), ",", 2), ",", -1) AS CLOSE_TIME,
MAX(Profit) AS Profit,
MAX(Storage) AS Storage,
MAX(Login) AS Login,
MAX(Action) AS Action,
MAX(Entry) AS Entry
FROM `mt5_deals_2020`
WHERE Time BETWEEN "2020-09-01" AND "2020-10-01"
AND Entry IN ("0",
"1")
GROUP BY PositionID) AS Main
WHERE OPEN_TIME != CLOSE_TIME) As Test
WHERE Login = SLogin
AND Test.Entry <> "0"
AND Test.CLOSE_TIME BETWEEN "2020-09-01" AND "2020-10-01"
AND TIMESTAMPDIFF(MINUTE,Test.OPEN_TIME,Test.CLOSE_TIME) <= "5"
AND Test.Action <= 1 ) AS Scalp,
SUM(Test2.Profit+Test2.Storage) AS Profit,
(
SELECT COUNT(mt5_deals_2020.order)
FROM mt5_deals_2020
WHERE Login = SLogin
AND mt5_deals_2020.Time BETWEEN "2020-09-01" AND "2020-10-01"
AND mt5_deals_2020.Action <= 1
AND mt5_deals_2020.Entry <> "0" ) AS Trades,
(
SELECT SUM(mt5_deals_2020.Profit+mt5_deals_2020.Storage)
FROM mt5_deals_2020
WHERE Login = SLogin
AND mt5_deals_2020.Time BETWEEN "2020-09-01" AND "2020-10-01"
AND mt5_deals_2020.Entry <> "0"
AND mt5_deals_2020.Action <= 1 ) AS PL
FROM (
SELECT *
FROM (
SELECT MAX(`Order`) AS `Order`,
SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(DISTINCT Time SEPARATOR ","), ",", 1), ",", -1) AS OPEN_TIME,
SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(DISTINCT Time SEPARATOR ","), ",", 2), ",", -1) AS CLOSE_TIME,
MAX(Profit) AS Profit,
MAX(Storage) AS Storage,
MAX(Login) AS Login,
MAX(Action) AS Action,
MAX(Entry) AS Entry
FROM `mt5_deals_2020`
WHERE Time BETWEEN "2020-09-01" AND "2020-10-01"
AND Entry IN ("0",
"1")
GROUP BY PositionID) AS Main1
WHERE OPEN_TIME != CLOSE_TIME) As Test2
LEFT JOIN mt5_users
ON Test2.Login = mt5_users.Login
WHERE mt5_users.Group IN ("KUVVARSTUSD",
"real\\KUV3VARSIUSD",
"real\\KUVVARPLUSD",
"real\\KUVVARGOUSD",
"real\\KUVVARGOEUR"
)
AND Test2.CLOSE_TIME BETWEEN "2020-09-01" AND "2020-10-01"
AND TIMESTAMPDIFF(MINUTE,Test2.OPEN_TIME,Test2.CLOSE_TIME) <= "5"
AND Test2.Action <= 1
GROUP BY Test2.Login
I need the time difference of an opening and closing order with some other data so on inside selects what I do is just that.
Explain result added:

Answer 1

First, let's simplify
SELECT COUNT(Test.Order)
FROM
(
SELECT *
FROM
(
SELECT ...
FROM `mt5_deals_2020`
WHERE Time BETWEEN "2020-09-01" AND "2020-10-01"
AND Entry IN ("0", "1")
GROUP BY PositionID
) AS Main
WHERE OPEN_TIME != CLOSE_TIME
) As Test
WHERE Login = SLogin
AND Test.Entry <> "0"
AND ...
to
SELECT COUNT(*)
FROM
(
SELECT ...
FROM `mt5_deals_2020`
WHERE Time BETWEEN "2020-09-01" AND "2020-10-01"
AND Entry IN ("0", "1")
GROUP BY PositionID
) AS Main
WHERE OPEN_TIME != CLOSE_TIME
HAVING Login = SLogin
AND Test.Entry <> "0"
AND ...
Notes:
COUNT(x) tests x for being NOT NULL; I suspect that is irrelevant.
HAVING is like WHERE but it can reference expressions, such as aggregates like SUM().
Your formulation has a SELECT *, which involves creating a big(?) temp table with all the 'columns'. Mine avoids that.
SUBSTRING_INDEX is messy. Consider redesigning the schema so that you don't need to use it.
What are the possible values of Entry and Action? There may be a better way to do the tests on those. For example if Entry can be only 0 or 1, it is better to say mt5_deals_2020.Entry = 1, thereby opening the door for an index.
Potential bug:
Time BETWEEN "2020-09-01" AND "2020-10-01"
If Time is a DATE, then that includes the first of October. (Please provide SHOW CREATE TABLE.) I prefer the following:
Time >= "2020-09-01"
AND Time < "2020-09-01" + INTERVAL 1 MONTH
mt5_users might benefit from this composite, covering, index:
INDEX(Login, Group, Name) -- in this order
After doing some of those, come back for more discussion if you like.