Optimization on large tables - sql

Question

I have the following query that joins two large tables. I am trying to join on patient_id and records that are not older than 30 days.
select * from
chairs c
join data id
on c.patient_id = id.patient_id
and to_date(c.from_date, 'YYYYMMDD') - to_date(id.from_date, 'YYYYMMDD') >= 0
and to_date (c.from_date, 'YYYYMMDD') - to_date(id.from_date, 'YYYYMMDD') < 30
Currently, this query takes 2 hours to run. What indexes can I create on these tables for this query to run faster.

Answer 1

I will take a shot in the dark, because as others said it depends on what the table structure, indices, and the output of the planner is.
The most obvious thing here is that as long as it is possible, you want to represent dates as some date datatype instead of strings. That is the first and most important change you should make here. No index can save you if you transform strings. Because very likely, the problem is not the patient_id, it's your date calculation.
Other than that, forcing hash joins on the patient_id and then doing the filtering could help if for some reason the planner decided to do nested loops for that condition. But that is for after you fixed your date representation AND you still have a problem AND you see that the planner does nested loops on that attribute.

Answer 2

Some observations if you are stuck with string fields for the dates:
YYYYMMDD date strings are ordered and can be used for <,> and =.
Building strings from the data in chairs to use to JOIN on data will make good use of an index like one on data for patient_id, from_date.
So my suggestion would be to write expressions that build the date strings you want to use in the JOIN. Or to put it another way: do not transform the child table data from a string to something else.
Example expression that takes 30 days off a string date and returns a string date:
select to_char(to_date('20200112', 'YYYYMMDD') - INTERVAL '30 DAYS','YYYYMMDD')
Untested:
select * from
chairs c
join data id
on c.patient_id = id.patient_id
and id.from_date between to_char(to_date(c.from_date, 'YYYYMMDD') - INTERVAL '30 DAYS','YYYYMMDD')
and c.from_date

Answer 3

For this query:
select *
from chairs c join data
id
on c.patient_id = id.patient_id and
to_date(c.from_date, 'YYYYMMDD') - to_date(id.from_date, 'YYYYMMDD') >= 0 and
to_date (c.from_date, 'YYYYMMDD') - to_date(id.from_date, 'YYYYMMDD') < 30;
You should start with indexes on (patient_id, from_date) -- you can put them in both tables.
The date comparisons are problematic. Storing the values as actual dates can help. But it is not a 100% solution because comparison operations are still needed.
Depending on what you are actually trying to accomplish there might be other ways of writing the query. I might encourage you to ask a new question, providing sample data, desired results, and a clear explanation of what you really want. For instance, this query is likely to return a lot of rows. And that just takes time as well.

Answer 4

Your query have a non SERGABLE predicate because it uses functions that are iteratively executed. You need to discard such functions and replace them by a direct access to the columns. As an exemple :
SELECT *
FROM chairs AS c
JOIN data AS id
ON c.patient_id = id.patient_id
AND c.from_date BETWEEN id.from_date AND id.from_date + INTERVAL '1 day'
Will run faster with those two indexes :
CREATE X_SQLpro_001 ON chairs (patient_id, from_date);
CREATE X_SQLpro_002 ON data (patient_id, from_date) ;
Also try to avoid
SELECT *
And list only the necessary columns