I have a table with close to a billion records, and need to query it with HAVING. It's very slow (about 15 minutes on decent hardware). How to speed it up?
SELECT ((mean - 3.0E-4)/(stddev/sqrt(N))) as t, ttest.strategyid, mean, stddev, N,
kurtosis, strategies.strategyId
FROM ttest,strategies
WHERE ttest.strategyid=strategies.id AND dataset=3 AND patternclassid="1"
AND exitclassid="1" AND N>= 300 HAVING t>=1.8
I think the problem is t cannot be indexed because it needs to be computed. I cannot add it as a column because the '3.0E-4' will vary per query.
Table:
create table ttest (
strategyid bigint,
patternclassid integer not null,
exitclassid integer not null,
dataset integer not null,
N integer,
mean double,
stddev double,
skewness double,
kurtosis double,
primary key (strategyid, dataset)
);
create index ti3 on ttest (mean);
create index ti4 on ttest (dataset,patternclassid,exitclassid,N);
create table strategies (
id bigint ,
strategyId varchar(500),
primary key(id),
unique key(strategyId)
);
explain select.. :
id
select_type
table
partitions
type
possible_keys
key
key_len
ref
rows
filtered
Extra
1
SIMPLE
ttest
NULL
range
PRIMARY,ti4
ti4
17
NULL
1910344
100.00
Using index condition; Using MRR
1
SIMPLE
strategies
NULL
eq_ref
PRIMARY
PRIMARY
8
Jellyfish_test.ttest.strategyid
1
100.00
Using where
The query needs to reformulated and an index needs to be added.
Plan A:
SELECT ((tt.mean - 3.0E-4)/(tt.stddev/sqrt(tt.N))) as t,
tt.strategyid, tt.mean, tt.stddev, tt.N, tt.kurtosis,
s.strategyId
FROM ttest AS tt
JOIN strategies AS s ON tt.strategyid = s.id
WHERE tt.dataset = 3
AND tt.patternclassid = 1
AND tt.exitclassid = 1
AND tt.N >= 300
AND ((tt.mean - 3.0E-4)/(tt.stddev/sqrt(tt.N))) >= 1.8
and a 'composite' and 'covering' index on test. Replace your ti4 with this (to make it 'covering'):
INDEX(dataset, patternclassid, exitclassid, -- any order
N, strategyid) -- in this order
Plan B:
SELECT ((tt.mean - 3.0E-4)/(tt.stddev/sqrt(tt.N))) as t,
tt.strategyid, tt.mean, tt.stddev, tt.N, tt.kurtosis,
( SELECT s.strategyId
FROM strategies AS s
WHERE s.id = tt.strategyid = s.id
) AS strategyId
FROM ttest AS tt
WHERE tt.dataset = 3
AND tt.patternclassid = 1
AND tt.exitclassid = 1
AND tt.N >= 300
AND ((tt.mean - 3.0E-4)/(tt.stddev/sqrt(tt.N))) >= 1.8
With the same index.
Unfortunately the expression for t needs to be repeated. By moving it from HAVING to WHERE, avoids gathering unwanted rows, only to end up throwing them away. Maybe the optimizer will do that automatically. Please provide EXPLAIN SELECT ... to see.
Also, it is unclear whether one of the two formulations will run faster than the other.
To be honest, I've never seen HAVING being used like this; for 20+ years I've assumed it can only be used in GROUP BY situations!
Anyway, IMHO you don't need it here, as Rick James points out, you can put it all in the WHERE.
Rewriting it a bit I end up with:
SELECT ((t.mean - 3.0E-4)/(t.stddev/sqrt(t.N))) as t,
t.strategyid,
t.mean,
t.stddev,
t.N,
t.kurtosis,
s.strategyId
FROM ttest t,
JOIN strategies s
ON s.id = t.strategyid =
WHERE t.dataset=3
AND t.patternclassid="1"
AND t.exitclassid="1"
AND t.N>= 300
AND ((t.mean - 3.0E-4)/(t.stddev/sqrt(t.N))) >= 1.8
Most of that we can indeed foresee a reasonable index. The problem remains with the last calculation:
AND ((t.mean - 3.0E-4)/(t.stddev/sqrt(t.N))) >= 1.8
However, before we go to that: how many rows are there if you ignore this 'formula'? 100? 200? If so, indexing as foreseen in Rick James' answer should be sufficient IMHO.
If it's 1000's or many more than the question becomes: how much of those are thrown out by the formula? 1%? 50% 99%? If it's on the low side then again, indexing as proposed by Rick James will do. If however you only need to keep a few you may want to further optimize this and index accordingly.
From your explanation I understand that 3.0E-4 is variable so we can't include it in the index.. so we'll need to extract the parts we can:
If my algebra isn't failing me you can play with the formula like this:
AND ((t.mean - 3.0E-4) / (t.stddev / sqrt(t.N))) >= 1.8
AND ((t.mean - 3.0E-4) ) >= 1.8 * (t.stddev / sqrt(t.N))
AND t.mean - 3.0E-4 >= (1.8 * (t.stddev / sqrt(t.N)))
AND - 3.0E-4 >= (1.8 * (t.stddev / sqrt(t.N))) - t.mean
So the query becomes:
SELECT ((t.mean - 3.0E-4)/(t.stddev/sqrt(t.N))) as t,
t.strategyid,
t.mean,
t.stddev,
t.N,
t.kurtosis,
s.strategyId
FROM ttest t,
JOIN strategies s
ON s.id = t.strategyid =
WHERE t.dataset=3
AND t.patternclassid="1"
AND t.exitclassid="1"
AND t.N>= 300
AND (1.8 * (t.stddev / sqrt(t.N))) - t.mean <= -3.0E-4
I'm not familiar with mysql but glancing the documentation it should be possible to include 'generated columns' in the index. So, we'll do exactly that with (1.8 * (t.stddev / sqrt(t.N)) - t.mean).
Your indexed fields thus become:
dataset, paternclassid, exitclassid, N, (1.8 * (t.stddev / sqrt(t.N))) - t.mean)
Note that the system will have to calculate this value for each and every row on insert (and possibly update) you do on the table. However, once there (and indexed) it should make the query quite a bit faster.
Related
I have got a SQL query that I tried to optimize and I could reduce through various means the time from over 5 seconds to about 1.3 seconds, but no further. I was wondering if anyone would be able to suggest further improvements.
The Explain diagram shows a full scan:
explain diagram
The Explain table will give you more details:
explain tabular
The query is simplified and shown below - just for reference, I'm using MySQL 5.6
select * from (
select
#row_num := if(#yacht_id = yacht_id and #charter_type = charter_type and #start_base_id = start_base_id and #end_base_id = end_base_id, #row_num +1, 1) as row_number,
#yacht_id := yacht_id as yacht_id,
#charter_type := charter_type as charter_type,
#start_base_id := start_base_id as start_base_id,
#end_base_id := end_base_id as end_base_id,
model, offer_type, instant, rating, reviews, loa, berths, cabins, currency, list_price, list_price_per_day,
discount, client_price, client_price_per_day, days, date_from, date_to, start_base_city, end_base_city, start_base_country, end_base_country,
service_binary, product_id, ext_yacht_id, main_image_url
from (
select
offer.yacht_id, offer.charter_type, yacht.model, offer.offer_type, offer.instant, yacht.rating, yacht.reviews, yacht.loa,
yacht.berths, yacht.cabins, offer.currency, offer.list_price, offer.list_price_per_day,
offer.discount, offer.client_price, offer.client_price_per_day, offer.days, date_from, date_to,
offer.start_base_city, offer.end_base_city, offer.start_base_country, offer.end_base_country,
offer.service_binary, offer.product_id, offer.start_base_id, offer.end_base_id,
yacht.ext_yacht_id, yacht.main_image_url
from website_offer as offer
join website_yacht as yacht
on offer.yacht_id = yacht.yacht_id,
(select #yacht_id:='') as init
where date_from > CURDATE()
and date_to <= CURDATE() + INTERVAL 3 MONTH
and days = 7
order by offer.yacht_id, charter_type, start_base_id, end_base_id, list_price_per_day asc, discount desc
) as filtered_offers
) as offers
where row_number=1;
Thanks,
goppi
UPDATE
I had to abandon some performance improvements and replaced the original select with the new one. The select query is actually dynamically built by the backend based on which filter criteria are set. As such the where clause of the most inner select can expland quite a lot. However, this is the default select if no filter is set and is the version that takes significantly longer than 1 sec.
explain in text form - doesn't come out pretty as I couldn't figure out how to format a table, but here it is:
1 PRIMARY ref <auto_key0> <auto_key0> 9 const 10
2 DERIVED ALL 385967
3 DERIVED system 1 Using filesort
3 DERIVED offer ref idx_yachtid,idx_search,idx_dates idx_dates 5 const 385967 Using index condition; Using where
3 DERIVED yacht eq_ref PRIMARY,id_UNIQUE PRIMARY 4 yachtcharter.offer.yacht_id 1
4 DERIVED No tables used
Sub selects are never great,
You should sign up here: https://www.eversql.com/
Run that and it will give you all the right indexes and optimsiations you need for this query.
There's still some optimization you can use. Considering the subquery returns 5000 rows only you could use an index for it.
First rephrase the predicate as:
select *
from website_offer
where date_from >= CURDATE() + INTERVAL 1 DAY -- rephrased here
and date(date_to) <= CURDATE() + INTERVAL 3 MONTH
and days = 7
order by yacht_id, charter_type, list_price_per_day asc, discount desc
limit 5000
Then, if you add the following index the performance could improve:
create index ix1 on website_offer (days, date_from, date_to);
I have the following query which takes about 28 seconds on my machine. I would like to optimize it and know if there is any way to make it faster by creating some indexes.
select rr1.person_id as person_id, rr1.t1_value, rr2.t0_value
from (select r1.person_id, avg(r1.avg_normalized_value1) as t1_value
from (select ma1.person_id, mn1.store_name, avg(mn1.normalized_value) as avg_normalized_value1
from matrix_report1 ma1, matrix_normalized_notes mn1
where ma1.final_value = 1
and (mn1.normalized_value != 0.2
and mn1.normalized_value != 0.0 )
and ma1.user_id = mn1.user_id
and ma1.request_id = mn1.request_id
and ma1.request_id = 4 group by ma1.person_id, mn1.store_name) r1
group by r1.person_id) rr1
,(select r2.person_id, avg(r2.avg_normalized_value) as t0_value
from (select ma.person_id, mn.store_name, avg(mn.normalized_value) as avg_normalized_value
from matrix_report1 ma, matrix_normalized_notes mn
where ma.final_value = 0 and (mn.normalized_value != 0.2 and mn.normalized_value != 0.0 )
and ma.user_id = mn.user_id
and ma.request_id = mn.request_id
and ma.request_id = 4
group by ma.person_id, mn.store_name) r2
group by r2.person_id) rr2
where rr1.person_id = rr2.person_id
Basically, it aggregates data depending on the request_id and final_value (0 or 1). Is there a way to simplify it for optimization? And it would be nice to know which columns should be indexed. I created an index on user_id and request_id, but it doesn't help much.
There are about 4907424 rows on matrix_report1 and 335740 rows on matrix_normalized_notes table. These tables will grow as we have more requests.
First, the others are right about knowing better how to format your samples. Also, trying to explain in plain language what you are trying to do is also a benefit. With sample data and sample result expectations is even better.
However, that said, I think it can be significantly simplified. Your queries are almost completely identical with the exception of the one field of "final_value" = 1 or 0 respectively. Since each query will result in 1 record per "person_id", you can just do the average based on a CASE/WHEN AND remove the rest.
To help optimize the query, your matrix_report1 table should have an index on ( request_id, final_value, user_id ). Your matrix_normalized_notes table should have an index on ( request_id, user_id, store_name, normalized_value ).
Since your outer query is doing the average based on an per stores averages, you do need to keep it nested. The following should help.
SELECT
r1.person_id,
avg(r1.ANV1) as t1_value,
avg(r1.ANV0) as t0_value
from
( select
ma1.person_id,
mn1.store_name,
avg( case when ma1.final_value = 1
then mn1.normalized_value end ) as ANV1,
avg( case when ma1.final_value = 0
then mn1.normalized_value end ) as ANV0
from
matrix_report1 ma1
JOIN matrix_normalized_notes mn1
ON ma1.request_id = mn1.request_id
AND ma1.user_id = mn1.user_id
AND NOT mn1.normalized_value in ( 0.0, 0.2 )
where
ma1.request_id = 4
AND ma1.final_Value in ( 0, 1 )
group by
ma1.person_id,
mn1.store_name) r1
group by
r1.person_id
Notice the inner query is pulling all transactions for the final value as either a zero OR one. But then, the AVG is based on a case/when of the respective value for the normalized value. When the condition is NOT the 1 or 0 respectively, the result is NULL and is thus not considered when the average is computed.
So at this point, it is grouped on a per-person basis already with each store and Avg1 and Avg0 already set. Now, roll these values up directly per person regardless of the store. Again, NULL values should not be considered as part of the average computation. So, if Store "A" doesn't have a value in the Avg1, it should not skew the results. Similarly if Store "B" doesnt have a value in Avg0 result.
I've a table with 50 columns. I defined one index (not unique) with the following 6 columns:
rdsr_id (int),
StartOfXrayIrradiation (datetime),
PatientsBirthDate (date),
DeviceObserverUID (varchar(100)),
IdentifiedProtocolShort (varchar(50)),
RedundantEntryFromDoseSummary (tinyint(1))
The table is called report and has around 20'000 rows and is growing. When running the following query, the result shows that only 4 keys of the index are used.
EXPLAIN EXTENDED SELECT r.PatientID, r.StartOfXrayIrradiation, MeanCTDIvol_in_mGy
FROM report r
INNER JOIN ct_irradiation_events e ON r.rdsr_id = e.rdsr_id
INNER JOIN patient_age_categories a ON ( DATEDIFF( r.StartOfXrayIrradiation, r.PatientsBirthDate ) <= a.max_age_days
AND DATEDIFF( r.StartOfXrayIrradiation, r.PatientsBirthDate ) >= a.min_age_days
AND a.description = 'Erwachsene' )
WHERE MeanCTDIvol_in_mGy IS NOT NULL
AND r.DeviceObserverUID = '2.25'
AND r.IdentifiedProtocolShort = 'XXXXX'
AND r.RedundantEntryFromDoseSummary =0
AND e.CTAcquisitionType != 'Constant Angle Acquisition'
AND DATEDIFF( r.StartOfXrayIrradiation, '2013-01-06' ) >=0
AND DATEDIFF( r.StartOfXrayIrradiation, '2014-03-06' ) <=0;
result for table report:
> id: 1
> select_type: SIMPLE
> table: r
> type: ref
> possible_keys: TimelineHistogramQueries
> key: TimelineHistogramQueries
> key_len: 4
> ref: rdsr.e.rdsr_id
> rows: 1
> filtered: 100.00
> Extra: Using where
So I guess the columns IdentifiedProtocolShort and RedundantEntryFromDoseSummary are not used? The result of the query are 1400 rows. When removing the two columns from the WHERE clause, 9500 rows are found. BTW: I did run "ANALYZE TABLE report" after creating the index, if that matters...
Why are not all keys of the index used? Should I change my index?
Assuming that your TimelineHistogramQueries key is a compound key over the six columns that you list in that order, then the key_len value of 4 (bytes) does indeed indicate that only the rdsr_id column is being used from the index: this is supported by the ref value of rdsr.e.rdsr_id.
You ask why IdentifiedProtocolShort and RedundantEntryFromDoseSummary (columns 5 and 6 in the index) are not being used. As documented under Multiple-Column Indexes:
MySQL cannot use the index to perform lookups if the columns do not form a leftmost prefix of the index.
If you do not require the columns of this index to be in their current order for any other query, you could merely reorder the columns; otherwise, you may need to define a second index.
Depends on what you want out of your query. Leave out patient ID and DOB from your first query if you are interested to see on which dates e.g. your patients had an x-ray, etc. Unless you are running your analysis by age. You are confusing the system by trying to index it all.
Create a table like this:
CREATE TABLE test ( a INT(10), b char(10));
add two indexes:
alter table test add key aa (a), add key bb (b);
insert some rows:
insert into test values (132,'logi');
insert into test values (322,'koko');
insert into test values (32,'kola');
etc...
You can test with a little number of rows BUT in my application i will have a hundred million of rows so what i am going to ask makes sense:
So, let's say that i want to execute two queries:
1) explain select * from test where b like "frif%";
2) explain select * from test where a like "32%";
The first uses the index bb since b is a char, while the second doesn't use the index aa since a is just an INT (and i treat it like a char!).
How can i make the second query execute as the first and search for numbers like "some_number%" and make that a query of range type and not ALL (as explain shows).
If you are treating the number as a character string, then store it that way. It sounds like the number is a code of some sort. Although consisting of numbers, it is really just the name of something (such as an account number).
If the number is fixed length, say 5, then you can do:
where a >= 32000 and a < 33000;
You could extend this idea for different lengths:
where a >= 32 and a < 33 or
a >= 320 and a < 330 or
a >= 3200 and a < 3300 or
a >= 30000 and a < 33000
*Hey everyone, I am working on a query and am unsure how to make it process as quickly as possible and with as little redundancy as possible. I am really hoping someone there can help me come up with a good way of doing this.
Thanks in advance for the help!*
Okay, so here is what I have as best I can explain it. I have simplified the tables and math to just get across what I am trying to understand.
Basically I have a smallish table that never changes and will always only have 50k records like this:
Values_Table
ID Value1 Value2
1 2 7
2 2 7.2
3 3 7.5
4 33 10
….50000 44 17.2
And a couple tables that constantly change and are rather large, eg a potential of up to 5 million records:
Flags_Table
Index Flag1 Type
1 0 0
2 0 1
3 1 0
4 1 1
….5,000,000 1 1
Users_Table
Index Name ASSOCIATED_ID
1 John 1
2 John 1
3 Paul 3
4 Paul 3
….5,000,000 Richard 2
I need to tie all 3 tables together. The most results that are likely to ever be returned from the small table is somewhere in the neighborhood of 100 results. The large tables are joined on the index and these are then joined to the Values_Table ON Values_Table.ID = Users_Table.ASSOCIATED_ID …. That part is easy enough.
Where it gets tricky for me is that I need to return, as quickly as possible, a list limited to 10 results where value1 and value2 are mathematically operated on to return a new_ value where that new_value is less than 10 and the result is sorted by that new_value and any other where statements I need can be applied to the flags. I do need to be able to move along the limit. EG LIMIT 0,10 / 11,10 / 21,10 etc...
In a subsequent (or the same if possible) query I need to get the top 10 count of all types that matched that criteria before the limit was applied.
So for example I want to join all of these and return anything where Value1 + Value2 < 10 AND I also need the count.
So what I want is:
Index Name Flag1 New_Value
1 John 0 9
2 John 0 9
5000000 Richard 1 9.2
The second response would be:
ID (not index) Count
1 2
2 1
I tried this a few ways and ultimately came up with the following somewhat ugly query:
SELECT INDEX, NAME, Flag1, (Value1 * some_variable + Value2) as New_Value
FROM Values_Table
JOIN Users_Table ON ASSOCIATED_ID = ID
JOIN Flags_Table ON Flags_Table.Index = Users_Table.Index
WHERE (Value1 * some_variable + Value1) < 10
ORDER BY New_Value
LIMIT 0,10
And then for the count:
SELECT ID, COUNT(TYPE) as Count, (Value1 * some_variable + Value2) as New_Value
FROM Values_Table
JOIN Users_Table ON ASSOCIATED_ID = ID
JOIN Flags_Table ON Flags_Table.Index = Users_Table.Index
WHERE (Value1 * some_variable + Value1) < 10
GROUP BY TYPE
ORDER BY New_Value
LIMIT 0,10
Being able to filter on the different flags and such in my WHERE clause is important; that may sound stupid to comment on but I mention that because from what I could see a quicker method would have been to use the HAVING statement but I don't believe that will work in certain instance depending on what I want to use my WHERE clause to filter against.
And when filtering using the flags table :
SELECT INDEX, NAME, Flag1, (Value1 * some_variable + Value2) as New_Value
FROM Values_Table
JOIN Users_Table ON ASSOCIATED_ID = ID
JOIN Flags_Table ON Flags_Table.Index = Users_Table.Index
WHERE (Value1 * some_variable + Value1) < 10 AND Flag1 = 0
ORDER BY New_Value
LIMIT 0,10
...filtered count:
SELECT ID, COUNT(TYPE) as Count, (Value1 * some_variable + Value2) as New_Value
FROM Values_Table
JOIN Users_Table ON ASSOCIATED_ID = ID
JOIN Flags_Table ON Flags_Table.Index = Users_Table.Index
WHERE (Value1 * some_variable + Value1) < 10 AND Flag1 = 0
GROUP BY TYPE
ORDER BY New_Value
LIMIT 0,10
That works fine but has to run the math multiple times for each row, and I get the nagging feeling that it is also running the math multiple times on the same row in the Values_table table. My thought was that I should just get only the valid responses from the Values_table first and then join those to the other tables to cut down on the processing; with how SQL optimizes things though I wasn't sure if it might not already be doing that. I know I could use a HAVING clause to only run the math once if I did it that way but I am uncertain how I would then best join things.
My questions are:
Can I avoid running that math twice and still make the query work
(or I suppose if there is a good way
to make the first one work as well
that would be great)
What is the fastest way to do this
as this is something that will
be running very often.
It seems like this should be painfully simple but I am just missing something stupid.
I contemplated pulling into a temp table then joining that table to itself but that seems like I would trade math for iterations against the table and still end up slow.
Thank you all for your help in this and please let me know if I need to clarify anything here!
** To clarify on a question, I can't use a 3rd column with the values pre-calculated because in reality the math is much more complex then addition, I just simplified it for illustration's sake.
Do you have a benchmark query to compare against? Usually it doesn't work to try to outsmart the optimizer. If you have acceptable performance from a starting query, then you can see where extra work is being expended (indicated by disk reads, cache consumption, etc.) and focus on that.
Avoid the temptation to break it into pieces and solve those. That's an antipattern. That includes temp tables especially.
Redundant math is usually ok - what hurts is disk activity. I've never seen a query that needed CPU work reduction on pure calculations.
Gather your results and put them in a temp table
SELECT * into TempTable FROM (SELECT INDEX, NAME, Type, ID, Flag1, (Value1 + Value2) as New_Value
FROM Values_Table
JOIN Users_Table ON ASSOCIATED_ID = ID
JOIN Flags_Table ON Flags_Table.Index = Users_Table.Index
WHERE New_Value < 10)
ORDER BY New_Value
LIMIT 0,10
Return Result for First Query
SELECT INDEX, NAME, Flag1, New_Value
FROM TempTable
Return Results for count of Types
Select ID, Count(Type)
FROM TempTable
GROUP BY TYPE
Is there any chance that you can add a third column to the values_table with the pre-calculated value? Even if the result of your calculation is dependent on other variables, you could run the calculation for the whole table but only when those variables change.