How to improve query speed in mysql query - mysql

Question

I'm trying to optimize my query speed as much as possible. A side problem is that I cannot see the exact query speed, because it is rounded to a whole second. The query does get the expected result and takes about 1 second. The final query should be extended even more and for this reason i am trying to improve it. How can this query be improved?
The database is constructed as an electricity utility company. The query should eventually calculate an invoice. I basically have 4 tables, APX price, powerdeals, powerload, eans_power.
APX price is an hourly price, powerload is a quarterly hour volume. First step is joining these two together for each quarter of an hour.
Second step is that I currently select the EAN that is indicated in the table eans_power.
Finally I will join the Powerdeals that currently consist only of a single line and indicates from which hour, until which hour and weekday from/until it should be applicable. It consist of an hourly volume and price. Currently it is only joined on the hours, but it will be extended to weekdays as well.
MYSQL Query:
SELECT l.DATE, l.PERIOD_FROM, a.PRICE, l.POWERLOAD,
SUM(a.PRICE*l.POWERLOAD), SUM(d.hourly_volume/4)
FROM timeseries.powerload l
INNER JOIN timeseries.apxprice a ON l.DATE = a.DATE
INNER JOIN contracts.eans_power c ON l.ean = c.ean
LEFT OUTER JOIN timeseries.powerdeals d ON d.period_from <= l.period_from
AND d.period_until >= l.period_until
WHERE l.PERIOD_FROM >= a.PERIOD_FROM
AND l.PERIOD_FROM < a.PERIOD_UNTIL
AND l.DATE >= '2018-01-01'
AND l.DATE <= '2018-12-31'
GROUP BY l.date
Explain:
1 SIMPLE c NULL system PRIMARY,ean NULL NULL NULL 1 100.00 Using temporary; Using filesort
1 SIMPLE l NULL ref EAN EAN 21 const 35481 11.11 Using index condition
1 SIMPLE d NULL ALL NULL NULL NULL NULL 1 100.00 Using where; Using join buffer (Block Nested Loop)
1 SIMPLE a NULL ref DATE DATE 4 timeseries.l.date 24 11.11 Using index condition
Create table queries:
apxprice
CREATE TABLE `apxprice` (
 `apx_id` int(11) NOT NULL AUTO_INCREMENT,
 `date` date DEFAULT NULL,
 `period_from` time DEFAULT NULL,
 `period_until` time DEFAULT NULL,
 `price` decimal(10,2) DEFAULT NULL,
 PRIMARY KEY (`apx_id`),
 KEY `DATE` (`date`,`period_from`,`period_until`)
) ENGINE=MyISAM AUTO_INCREMENT=29664 DEFAULT CHARSET=latin1
powerdeals
CREATE TABLE `powerdeals` (
 `deal_id` int(11) NOT NULL AUTO_INCREMENT,
 `date_deal` date NOT NULL,
 `start_date` date NOT NULL,
 `end_date` date NOT NULL,
 `weekday_from` int(11) NOT NULL,
 `weekday_until` int(11) NOT NULL,
 `period_from` time NOT NULL,
 `period_until` time NOT NULL,
 `hourly_volume` int(11) NOT NULL,
 `price` int(11) NOT NULL,
 `type_deal_id` int(11) NOT NULL,
 `contract_id` int(11) NOT NULL,
 PRIMARY KEY (`deal_id`)
) ENGINE=MyISAM AUTO_INCREMENT=2 DEFAULT CHARSET=latin1
powerload
CREATE TABLE `powerload` (
 `powerload_id` int(11) NOT NULL AUTO_INCREMENT,
 `ean` varchar(18) DEFAULT NULL,
 `date` date DEFAULT NULL,
 `period_from` time DEFAULT NULL,
 `period_until` time DEFAULT NULL,
 `powerload` int(11) DEFAULT NULL,
 PRIMARY KEY (`powerload_id`),
 KEY `EAN` (`ean`,`date`,`period_from`,`period_until`)
) ENGINE=MyISAM AUTO_INCREMENT=61039 DEFAULT CHARSET=latin1
eans_power
CREATE TABLE `eans_power` (
 `ean` char(19) NOT NULL,
 `contract_id` int(11) NOT NULL,
 `invoicing_id` int(11) NOT NULL,
 `street` varchar(255) NOT NULL,
 `number` int(11) NOT NULL,
 `affix` char(11) NOT NULL,
 `postal` char(6) NOT NULL,
 `city` varchar(255) NOT NULL,
 PRIMARY KEY (`ean`),
 KEY `ean` (`ean`,`contract_id`,`invoicing_id`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1
Sample data tables
apx_prices
apx_id,date,period_from,period_until,price
1,2016-01-01,00:00:00,01:00:00,23.86
2,2016-01-01,01:00:00,02:00:00,22.39
powerdeals
deal_id,date_deal,start_date,end_date,weekday_from,weekday_until,period_from,period_until,hourly_volume,price,type_deal_id,contract_id
1,2019-05-15,2018-01-01,2018-12-31,1,5,08:00:00,20:00:00,1000,50,3,1
powerload
powerload_id,ean,date,period_from,period_until,powerload
1,871688520000xxxxxx,2018-01-01,00:00:00,00:15:00,9
2,871688520000xxxxxx,2018-01-01,00:15:00,00:30:00,11
eans_power
ean,contract_id,invoicing_id,street,number,affix,postal,city
871688520000xxxxxx,1,1,road,14,postal,city
Result, without sum() and group by:
DATE,PERIOD_FROM,PRICE,POWERLOAD,a.PRICE*l.POWERLOAD,d.hourly_volume/4,
2018-01-01,00:00:00,27.20,9,244.80,NULL
2018-01-01,00:15:00,27.20,11,299.20,NULL
Result, with sum() and group by:
DATE, PERIOD_FROM, PRICE, POWERLOAD, SUM(a.PRICE*l.POWERLOAD), SUM(d.hourly_volume/4)
2018-01-01,08:00:00,26.33,21,46193.84,12250.0000
2018-01-02, 08:00:00,47.95,43,90623.98,12250.0000

Answer 1

Preliminary optimizations:
Use InnoDB, not MyISAM.
Use CHAR only for constant-lenght strings
Use consistent datatypes (see ean, for example)
For an alternative to using time-to-the-second, check out the Handler counts .
Because range tests (such as l.PERIOD_FROM >= a.PERIOD_FROM AND l.PERIOD_FROM < a.PERIOD_UNTIL) are essentially impossible to optimize, I recommend you expand the table to have one entry per hour (or 1 per quarter hour, if necessary). Looking up a row via a key is much faster than doing a scan of "ALL" the table. 9K rows for an entire year is trivial.
When you get past these recommendations (and the Comments), I will have more tips on optimizing the indexes, especially InnoDB's PRIMARY KEY.