I was wondering if there is any difference between order of grouping in GROUP BY a, b and GROUP BY b, a (I know the final result is the same). If so, would it affect the query's speed?
A group by clause just defines the unique combination of field(s) which would be considered a group. There is no meaning to the order these fields are stated.
It does matter if you have multiple-column indexes. You should define the GROUP BY columns in the order of the index.
So, if you have an index for (a,b) then you should use GROUP BY a, b and MySQL is able to take full advantage of the index.
See example
Related
How looks like an optimal MySQL index for this query:
select a,b,c from t where a=1 and b=2 order by c
The optimal index is: t(a, b, c) or t(b, a, c).
The first two columns of the index will be used for the where clause. The third column can then be used for the order by.
I have a question about optimizing sql queries with multiple index.
Imagine I have a table "TEST" with fields "A, B, C, D, E, F".
In my code (php), I use the following "WHERE" query :
Select (..) from TEST WHERE a = 'x' and B = 'y'
Select (..) from TEST WHERE a = 'x' and B = 'y' and F = 'z'
Select (..) from TEST WHERE a = 'x' and B = 'y' and (D = 'w' or F = 'z')
what is the best approach to get the best speed when running queries?
3 multiple Index like (A, B), (A, B, F) and (A, B, D, F)?
Or A single multiple index (A, B, D, F)?
I would tend to say that the 3 index would be best even if the space of index in the database will be larger.
In my problem, I search the best execution time not the space.
The database being of a reasonable size.
Multiple-column indexes:
MySQL can use multiple-column indexes for queries that test all the columns in the index, or queries that test just the first column, the first two columns, the first three columns, and so on. If you specify the columns in the right order in the index definition, a single composite index can speed up several kinds of queries on the same table.
In other words, it is a waste of space an computing power to define an index that covers the same first N columns as another index and in the same order.
The best way to exam the index is to practice. Use "explain" in mysql, it will give you a query plan and tell you which index to use. In addition, it will give you an estimate time for your query to run. Here is an example
explain select * from TEST WHERE a = 'x' and B = 'y'
It is hard to give definitive answers without experiments.
BUT: ordinarily an index like (A,B,D) is considered to be superfluous if you have an index on (A,B,D,F). So, in my opinion you only need the one multicolumn index.
There is one other consideration. If your table has a lot of columns and a lot of rows and your SELECT list has a small subset of those columns, you might consider including those columns in your index. For example, if your query says SELECT D,F,G,H FROM ... you should try creating an index on
(A,B,D,F,G,H)
as it will allow the query to be satisfied from the index without having to refer back to the rows of the table. This can sometimes help performance a great deal.
It's hard to explain well, but generally you should use as few indexes as you can get away with, using as many columns of the common queries as you can, with the most commonly queried columns first.
In your example WHERE clauses, A and B are always included. These should thus be part of an index. If A is more commonly used in a search then list that first, if B is more commonly used then list that first. MySQL can partially use the index as long as each column (seen from the left) in the index is used in the WHERE clause. So if you have an index ( A, B, C ) then WHERE ( A = .. AND B = .. AND Z = .. ) can still use that index to narrow down the search. If you have a WHERE ( B = .. AND Z = .. ) clause then A isn't part of the search condition and it can't be used for that index.
You want the single multiple column index A, B, D, F OR A, B, F, D (only one of these at a time can be used), but which depends mostly on the number of times D or F are queried for, and the distribution of data. Say if most of the values in D are 0 but one in a hundred values are 1 then that column would have a poor key distribution and thus putting the index on that column wouldn't be all that useful.
The optimiser can use a composite index for where conditions that follow the order of the index with no gaps:
An index on (A,B,F) will cover the first two queries.
The last query is a bit trickier, because of the OR. I think only the A and B conditions will be covered by (A,B,F) but using a separate index (D) or index (F) may speed up the query depending on the cardinality of the rows.
I think an index on (A,B,D,F) can only be used for the A and B conditions on all three queries. Not the F condition on query two, because the D value in the index can be anything and not the D and F conditions because of the OR.
You may have to add hints to the query to get the optimiser to use the best index and you can see which indexes are being used by running an EXPLAIN ... on the query.
Also, adding indexes slows down DML statements and can cause locking issues, so it's best to avoid over-indexing where possible.
I have a reasonably big table (>10.000 rows) which is going to grow much bigger fast. On this table I run the following query:
SELECT *, MAX(a) FROM table GROUP BY b, c, d
Currently EXPLAIN tells me that there are no keys, no possible keys and it's "Using temporary; Using filesort". What would the best key be for such a table?
What about composite key b+c+d+a?
Btw, SELECT * makes no sense in case when you have GROUP BY
A primary index on field b,c,d would be nice if applicable.
In that case you just do a
SELECT * FROM table1
group by <insert PRIMARY KEY here>
If not put an index on b,c,d.
And maybe on a, depends on the performance.
If b,c,d are always used in unison, use a composite index on all three.
Very important! Always declare a primary key. Without it performance on InnoDB will suck.
To elaborate on #zerkms, you only need to put those columns in the group by clause that completely define the rows that you are selecting.
If you select * that may be OK, but than the max(a) is not needed and neither is the group by.
Also note that the max(a) may come from a different row than the rest of the fields.
The only use case that does make sense is:
select t1.*, count(*) as occurrence from t1
inner join t2 on (t1.id = t2.manytoone_id)
group by t1.id
Where t1.id is the PK.
I think you need to rethink that query.
Ask a new question explaining what you want with the real code.
And make sure to ask how to make the outcomedeterminate, so that all values shown are functionally dependent on the group by clause.
In the end what worked was a modification to the query as follows:
SELECT b, c, d, e, f, MAX(a) FROM table GROUP BY b, c, d
And creating an index on (b, c, d, e, f).
Thanks a lot for your help: the tips here were very useful.
I have a table with 5 columns,say - A(Primary key), B, C, D and E.
This table has almost 150k rows and there are no indices on this table. As expected the select queries are very slow.
These queries are generated by the user search requests so he can enter values in any of the fields (B, C, D and E) and these are 'IN' kind of queries. I am not sure what should be the good indexing strategy here - having indexes on each of these columns or have them in some combinations.
Selectivity of each of these columns is the same (around 50).
Any help would be appreciated.
Are you running the same query regardless of what the user gives you? In that case, that query should tell you what indexes to use.
For example, if your query might look like
SELECT * FROM mytable WHERE
B IN (...) AND
C IN (...) AND
D IN (...) AND
E IN (...)
In this case, where you restrict on all columns, a combined index with all five columns would probably be ok.
Otherwise, create one index per column, or combine columns that you always restrict on together in separate indexes.
Remember that if you have a combined index on e.g. B and C, then a query that does not restrict on B will not use that combined index.
if you can group two columns in one index that would okay. Having an index on each column is not so bad as long as you don't query Cartesian product like cross join. But better not too ..
I have a MyISAM table with almost 1 billion records, with say, three fields: a, b and c.
The table has a btree multi-field index on columns a, b and c in that order. Analyzing the index shows that the cardinalities for the fields in that index are:
a: 112 (int)
b: 2694 (int)
c: 936426795 (datetime)
Which means that there are around 100 different values for a, around 20 different values for b, and for each combination of a and b, a whole lot of values of c.
I want to perform a query over a specific value of a, and a range over c. Something like
select a, b, c from mytable where a=4 and c >= "2011-01-01 00:00:00" and c < "2011-01-02 00:00:00"
Getting the query explained shows me that it will indeed use the index, but I don't know if it will use only the first field of the index and then scan over the rest of the table, or if it will be smart enough to apply the third field index, for each value of b, which would be the same as executing 20 different queries, one for each different value of b.
Anybody who knows the internal working of mysql indices can answer this question?
Edit: I'm not asking whether or not I can have mysql to use the index over only a and c. I know how btrees work, and I know that you can only use it over a, a and b, or a and b and c. I would like to know if the mysql optimizer is smart enough to apply the index over all the values in b so it can use the a+b+c index, considering that the cardinality of b is extremely small.
Consider an even simpler example. A table with two columns: a and b, and the index has cardinality 1 over a and 10000000 over b. Mysql should be smart enough to know that there's only one value of a, therefore this index is equivalent to an index only over b, and should use this index when performing queries only over b.
MySQL Reference Manual :: How MySQL Uses Indexes
If the table has a multiple-column index, any leftmost prefix of the
index can be used by the optimizer to find rows. For example, if you
have a three-column index on (col1, col2, col3), you have indexed
search capabilities on (col1), (col1, col2), and (col1, col2, col3).
MySQL cannot use an index if the columns do not form a leftmost prefix of the index.
a,c is not a leftmost prefix of the index a,b,c so the index cannot be used to resolve the search on c.
The question makes sense from the point of view that some database engines are smart enough to scan the index rather than scanning the table. (And they allow "data" to be stored in the index for this exact reason.) Scanning the index will be faster than joining the index to the base data, then limiting (excluding) returned rows based on the where clause.
It would make sense that only the rows in the index that meet the where condition (on columns in the index) are joined. Particularly if you are running a large key cache...
It would appear this doesn't happen in MySQL which is disappointing.
Therefore no.
Below are some facts related with B-TREE index usage by mysql and one example to understand this logic.
a) If any table has approx. 75% same data then index will not be used instead mysql will do table scan.
b) Normally mysql use only single index per table.
c) Index ordering methodology: Mysql will use index as per their order.
For example there is an combined index on a, b and c field idx_a_b_c(a,b,c)
i. select a, b, c from mytable where a=4
This query will use index as 'a' column is first in index order.
ii. select a, b, c from mytable where a=4 and b=5
This query will use combined index on a & b as these column are continue in index order.
iii. select a, b, c from mytable where a=4 and b=5 and c >= "2011-01-01 00:00:00"
This query will use combined index on a, b & c as these column are continue in index order.
iv. select a, b, c from mytable where c >= "2011-01-01 00:00:00"
This query will not use index as mysql consider index from left most corner and column c is not a left most column in index.
v. select a, b, c from mytable where a=4 and c >= "2011-01-01 00:00:00" and c < "2011-01-02 00:00:00"
This query will use only index on 'a' column but not of 'c' column as continuity is breaking here from left side. So this query will use index on a column and then scan table for column c for corresponding rows as per filter on column a.