I need to make queries such as
SELECT
Url, COUNT(*) AS requests, AVG(TS) AS avg_timeSpent
FROM
myTable
WHERE
Url LIKE '%/myController/%'
GROUP BY
Url
run as fast as possible.
The columns selected and grouped are almost always the same, being the difference, an extra column on the select and group by (the column tenantId)
What kind of index should I create to help me run this scenario?
Edit 1:
If I change my base query to '/myController/%' (note there's no % at the begging) would it be better?
This is a query that cannot be sped up with an index. The DBMS cannot know beforehand how many records will match the condition. It may be 100% or 0.001%. There is no clue for the DBMS to guess this. And access via an index only makes sense when a small percentage of rows gets selected.
Moreover, how can such an index be structured and useful? Think of a telephone book and you want to find all names that contain 'a' or 'rs' or 'ems' or whatever. How would you order the names in the book to find all these and all other thinkable letter combinations quickly? It simply cannot be done.
So the DBMS will read the whole table record for record, no matter whether you provide an index or not.
There may be one exception: With an index on URL and TS, you'd have both columns in the index. So the DBMS might decide to read the whole index rather than the whole table then. This may make sense for instance when the table has hundreds of columns or when the table is very fragmented or whatever. I don't know. A table is usually much easier to read sequentially than an index. You can still just try, of course. It doesn't really hurt to create an index. Either the DBMS uses it or not for a query.
Columnstore indexes can be quite fast at such tasks (aggregates on globals scans). But even they will have trouble handling a LIKE '%/mycontroler/%' predicate. I recommend you parse the URL once into an additional computed field that projects the extracted controller of your URL. But the truth is that looking at global time spent on a response URL reveals very little information. It will contain data since the beginning of time, long since obsolete by newer deployments, and not be able to capture recent trends. A filter based on time, say per hour or per day, now that is a very useful analysis. And such a filter can be excellently served by a columnstore, because of natural time order and segment elimination.
Based on your posted query you should have a index on Url column. In general columns which are involved in WHERE , HAVING, ORDER BY and JOIN ON condition should be indexed.
You should get the generated query plan for the said query and see where it's taking more time. Again based n the datatype of the Url column you may consider having a FULLTEXT index on that column
Related
I have a table on SQL Server with about 10 million rows. It has a nonclustered index ClearingInfo_idx which looks like:
I am running query which isn't using ClearingInfo_idx index and execution plan looks like this:
Can anyone explain why query optimizer chooses to scan clustered index ?
I think it suggests this index because you use a sharp search for the two columns immediate and clearingOrder_clearingOrderId. Those values are numbers, which were good to search. The column status is nvarchar which isn't the best for a search, and due to your search with in, SQL Server needs to search two of those values.
SQL Server would use the two number columns to get a faster result and searching in the status in the second round after the number of possible results is reduced due to the exact search on the two number columns.
Hopefully you get my opinion. :-) Otherwise, just ask again. :-)
As Luaan already pointed out, the likely reason the system prefers to scan the clustered index is because
you're asking for all fields to be returned (SELECT *), change this to fields that are present in the index ( = index fields + clustered index-fields) and you'll probably see it using just the index. If you'd need a couple of extra fields you can consider INCLUDEing those in the index.
the order of the index fields isn't very optimal. Additionally it might well be that the 'content' of the field isn't very helpful either. How many distinct values are present in the index-columns and how are they spread around? If you're WHERE covers 90% of the records there is very little reason to first create a (huge) list of keys and then go fetch those from the clustered index later on. Scanning the latter directly then makes much more sense.
Did you try the suggested index? Not sure what other queries run on the table, but for this particular query it seems like a valid replacement to me. If the replacement will satisfy the other queries is another question off course. Adding extra indexes might negatively impact your IUD operations and it will require more disk-space; there is no such thing as a free lunch =)
That said, if performance is an issue, have you considered a filtered index? (again, no such thing as a free lunch; it's all about priorities)
As I know, from the relational database theory, a select statement without an order by clause should be considered to have no particular order. But actually in SQL Server and Oracle (I've tested on those 2 platforms), if I query from a table without an order by clause multiple times, I always get the results in the same order. Does this behavior can be relied on? Anyone can help to explain a little?
No, that behavior cannot be relied on. The order is determined by the way the query planner has decided to build up the result set. simple queries like select * from foo_table are likely to be returned in the order they are stored on disk, which may be in primary key order or the order they were created, or some other random order. more complex queries, such as select * from foo where bar < 10 may instead be returned in order of a different column, based on an index read, or by the table order, for a table scan. even more elaborate queries, with multipe where conditions, group by clauses, unions, will be in whatever order the planner decides is most efficient to generate.
The order could even change between two identical queries just because of data that has changed between those queries. a "where" clause may be satisfied with an index scan in one query, but later inserts could make that condition less selective, and the planner could decide to perform a subsequent query using a table scan.
To put a finer point on it. RDBMS systems have the mandate to give you exactly what you asked for, as efficiently as possible. That efficiency can take many forms, including minimizing IO (both to disk as well as over the network to send data to you), minimizing CPU and keeping the size of its working set small (using methods that require minimal temporary storage).
without an ORDER BY clause, you will have not asked exactly for a particular order, and so the RDBMS will give you those rows in some order that (maybe) corresponds with some coincidental aspect of the query, based on whichever algorithm the RDBMS expects to produce the data the fastest.
If you care about efficiency, but not order, skip the ORDER BY clause. If you care about the order but not efficiency, use the ORDER BY clause.
Since you actually care about BOTH use ORDER BY and then carefully tune your query and database so that it is efficient.
No, you can't rely on getting the results back in the same order every time. I discovered that when working on a web page with a paged grid. When I went to the next page, and then back to the previous page, the previous page contained different records! I was totally mystified.
For predictable results, then, you should include an ORDER BY. Even then, if there are identical values in the specified columns there, you can get different results. You may have to ORDER BY fields that you didn't really think you needed, just to get a predictable result.
Tom Kyte has a pet peeve about this topic. For whatever reason, people are fascinated by this, and keep trying to come up with cases where you can rely upon a specific order without specifying ORDER BY. As others have stated, you can't. Here's another amusing thread on the topic on the AskTom website.
The Right Answer
This is a new answer added to correct the old one. I've got answer from Tom Kyte and I post it here:
If you want rows sorted YOU HAVE TO USE AN ORDER. No if, and, or buts about it. period. http://tkyte.blogspot.ru/2005/08/order-in-court.html You need order by on that IOT. Rows are sorted in leaf blocks, but leaf blocks are not stored sorted. fast full scan=unsorted rows.
https://twitter.com/oracleasktom/status/625318150590980097
https://twitter.com/oracleasktom/status/625316875338149888
The Wrong Answer
(Attention! The original answer on the question was placed below here only for the sake of the history. It's wrong answer. The right answer is placed above)
As Tom Kyte wrote in the article mentioned before:
You should think of a heap organized table as a big unordered
collection of rows. These rows will come out in a seemingly random
order, and depending on other options being used (parallel query,
different optimizer modes and so on), they may come out in a different
order with the same query. Do not ever count on the order of rows from
a query unless you have an ORDER BY statement on your query!
But note he only talks about heap-organized tables. But there is also index-orgainzed tables. In that case you can rely on order of the select without ORDER BY because order implicitly defined by primary key. It is true for Oracle.
For SQL Server clustered indexes (index-organized tables) created by default. There is also possibility for PostgreSQL store information aligning by index. More information can be found here
UPDATE:
I see, that there is voting down on my answer. So I would try to explain my point a little bit.
In the section Overview of Index-Organized Tables there is a phrase:
In an index-organized table, rows are stored in an index defined on the primary key for the table... Index-organized tables are useful when related pieces of data must be stored together or data must be physically stored in a specific order.
http://docs.oracle.com/cd/E25054_01/server.1111/e25789/indexiot.htm#CBBJEBIH
Because of index, all data is stored in specific order, I believe same is true for Pg.
http://www.postgresql.org/docs/9.2/static/sql-cluster.html
If you don't agree with me please give me a link on the documenation. I'll be happy to know that there is something to learn for me.
I have a private messaging system for my browser game. When I check most CPU time using queries I see that this table is the most CPU using one. I am not good with indexes, query time optimization. So I would like to get your optimization tips about this table.
Alright now I am going to show you table structure first:
structure image
Alright this following query reads how many unread messages does user have and this query is the most CPU using one since it reads at every page load:
SELECT COUNT([Id]) [Number]
FROM [MyTable]
WHERE [ReceiverUserId] = #1
AND [ReceiverReaded] = #2
AND [ReceiverDeleted] = #3
So what kind of indexes etc might improve my performance?
Why allow NULLs on those columns at all - either it's read or not. Just default to 0. Then index on Read/Deleted/ReceivedUser (in that order they will be "partitioned" if you need a lot of ALL READ access, alternatively, if most reads are just for a single user, put an index on ReceivedUser)
What you want to do is see your index be covering. In your case, you could put an index on ReceiverUserId and INCLUDE columns ReceiverReaded and ReceiverDeleted and it would be covering (for that query). In the execution plan, you should just see an index seek, since you have a single user.
You could capture the workload and then run it through the index tuning wizard in SQL Server and it would probably make pretty good suggestions. You need to interpret what it's telling you, of course.
You always want indexes on the fields you are searching for, so you would probably improve the query performance by adding indexes on [ReceiverUserId], [ReceiverReaded] and [ReceiverDeleted].
Of course the more columns you index, the slower your UPDATES and INSERTS will be.
A fairly simple rule of thumb in db optimization is to index any column that appears as part of a predicate in a WHERE clause or a JOIN. From your example these would include:
ReceiverUserId
ReceiverReaded
ReceiverDeleted
There are also a number of optimizer tools available that will "observe" your db and tell you what columns to index for best performance.
Different approach that may be viable for your application: don't query the messages table at all when the user isn't explicitly requesting any content, e.g. when he's not in the "messages" section of your game.
try extending your user table with integer valued columns indicating how many messages are there and how many are read already. Every time you modify the message table, you also modify the corresponding value in the user table.
This way you won't need to look through the whole table on every refresh. Note though, that the downturn of this method is some extra synchronization work on the programmer's part. If you've encapsulated the modification of the messages table (add message, read message, delete message) properly, this shouldn't be a problem.
Index your search fields (per #PaulStock's answer).
Change your tinyint fields to bit fields (default value = 0)
Does your body really need to be nvarchar(4000)? That's HUGE! Consider much shorter messages (such as nvarchar(300) or smaller -- for reference, Twitter is just 140.)
I have an sql server 2008 database along with 30000000000 records in one of its major tables. Now we are looking for the performance for our queries. We have done with all indexes. I found that we can split our database tables into multiple partitions, so that the data will be spread over multiple files, and it will increase the performance of the queries.
But unfortunatly this functionality is only available in the sql server enterprise edition, which is unaffordable for us.
Is there any way to opimize for the query performance? For example, the query
select * from mymajortable where date between '2000/10/10' and '2010/10/10'
takes around 15 min to retrieve around 10000 records.
A SELECT * will obviously be less efficiently served than a query that uses a covering index.
First step: examine the query plan and look for and table scans and the steps taking the most effort(%)
If you don’t already have an index on your ‘date’ column, you certainly need one (assuming sufficient selectivity). Try to reduce the columns in the select list, and if ‘sufficiently’ few, add these to the index as included columns (this can eliminate bookmark lookups into the clustered index and boost performance).
You could break your data up into separate tables (say by a date range) and combine via a view.
It is also very dependent on your hardware (# cores, RAM, I/O subsystem speed, network bandwidth)
Suggest you post your table and index definitions.
First always avoid Select * as that will cause the select to fetch all columns and if there is an index with just the columns you need you are fetching a lot of unnecessary data. Using only the exact columns you need to retrieve lets the server make better use of indexes.
Secondly, have a look on included columns for your indexes, that way often requested data can be included in the index to avoid having to fetch rows.
Third, you might try to use an int column for the date and convert the date into an int. Ints are usually more effective in range searches than dates, especially if you have time information to and if you can skip the time information the index will be smaller.
One more thing to check for is the Execution plan the server uses, you can see this in management studio if you enable show execution plan in the menu. It can indicate where the problem lies, you can see which indexes it tries to use and sometimes it will suggest new indexes to add.
It can also indicate other problems, Table Scan or Index Scan is bad as it indicates that it has to scan through the whole table or index while index seek is good.
It is a good source to understand how the server works.
If you add an index on date, you will probably speed up your query due to an index seek + key lookup instead of a clustered index scan, but if your filter on date will return too many records the index will not help you at all because the key lookup is executed for each result of the index seek. SQL server will then switch to a clustered index scan.
To get the best performance you need to create a covering index, that is, include all you columns you need in the "included columns" part of your index, but that will not help you if you use the select *
another issue with the select * approach is that you can't use the cache or the execution plans in an efficient way. If you really need all columns, make sure you specify all the columns instead of the *.
You should also fully quallify the object name to make sure your plan is reusable
you might consider creating an archive database, and move anything after, say, 10-20 years into the archive database. this should drastically speed up your primary production database but retains all of your historical data for reporting needs.
What type of queries are we talking about?
Is this a production table? If yes, look into normalizing a bit more and see if you cannot go a bit further as far as normalizing the DB.
If this is for reports, including a lot of Ad Hoc report queries, this screams data warehouse.
I would create a DW with seperate pre-processed reports which include all the calculation and aggregation you could expect.
I am a bit worried about a business model which involves dealing with BIG data but does not generate enough revenue or even attract enough venture investment to upgrade to enterprise.
Suppose I have a database table with two fields, "foo" and "bar". Neither of them are unique, but each of them are indexed. However, rather than being indexed together, they each have a separate index.
Now suppose I perform a query such as SELECT * FROM sometable WHERE foo='hello' AND bar='world'; My table a huge number of rows for which foo is 'hello' and a small number of rows for which bar is 'world'.
So the most efficient thing for the database server to do under the hood is use the bar index to find all fields where bar is 'world', then return only those rows for which foo is 'hello'. This is O(n) where n is the number of rows where bar is 'world'.
However, I imagine it's possible that the process would happen in reverse, where the fo index was used and the results searched. This would be O(m) where m is the number of rows where foo is 'hello'.
So is Oracle smart enough to search efficiently here? What about other databases? Or is there some way I can tell it in my query to search in the proper order? Perhaps by putting bar='world' first in the WHERE clause?
Oracle will almost certainly use the most selective index to drive the query, and you can check that with the explain plan.
Furthermore, Oracle can combine the use of both indexes in a couple of ways -- it can convert btree indexes to bitmaps and perform a bitmap ANd operation on them, or it can perform a hash join on the rowid's returned by the two indexes.
One important consideration here might be any correlation between the values being queried. If foo='hello' accounts for 80% of values in the table and bar='world' accounts for 10%, then Oracle is going to estimate that the query will return 0.8*0.1= 8% of the table rows. However this may not be correct - the query may actually return 10% of the rwos or even 0% of the rows depending on how correlated the values are. Now, depending on the distribution of those rows throughout the table it may not be efficient to use an index to find them. You may still need to access (say) 70% or the table blocks to retrieve the required rows (google for "clustering factor"), in which case Oracle is going to perform a ful table scan if it gets the estimation correct.
In 11g you can collect multicolumn statistics to help with this situation I believe. In 9i and 10g you can use dynamic sampling to get a very good estimation of the number of rows to be retrieved.
To get the execution plan do this:
explain plan for
SELECT *
FROM sometable
WHERE foo='hello' AND bar='world'
/
select * from table(dbms_xplan.display)
/
Contrast that with:
explain plan for
SELECT /*+ dynamic_sampling(4) */
*
FROM sometable
WHERE foo='hello' AND bar='world'
/
select * from table(dbms_xplan.display)
/
Eli,
In a comment you wrote:
Unfortunately, I have a table with lots of columns each with their own index. Users can query any combination of fields, so I can't efficiently create indexes on each field combination. But if I did only have two fields needing indexes, I'd completely agree with your suggestion to use two indexes. – Eli Courtwright (Sep 29 at 15:51)
This is actually rather crucial information. Sometimes programmers outsmart themselves when asking questions. They try to distill the question down to the seminal points but quite often over simplify and miss getting the best answer.
This scenario is precisely why bitmap indexes were invented -- to handle the times when unknown groups of columns would be used in a where clause.
Just in case someone says that BMIs are for low cardinality columns only and may not apply to your case. Low is probably not as small as you think. The only real issue is concurrency of DML to the table. Must be single threaded or rare for this to work.
Yes, you can give "hints" with the query to Oracle. These hints are disguised as comments ("/* HINT */") to the database and are mainly vendor specific. So one hint for one database will not work on an other database.
I would use index hints here, the first hint for the small table. See here.
On the other hand, if you often search over these two fields, why not create an index on these two? I do not have the right syntax, but it would be something like
CREATE INDEX IX_BAR_AND_FOO on sometable(bar,foo);
This way data retrieval should be pretty fast. And in case the concatenation is unique hten you simply create a unique index which should be lightning fast.
First off, I'll assume that you are talking about nice, normal, standard b*-tree indexes. The answer for bitmap indexes is radically different. And there are lots of options for various types of indexes in Oracle that may or may not change the answer.
At a minimum, if the optimizer is able to determine the selectivity of a particular condition, it will use the more selective index (i.e. the index on bar). But if you have skewed data (there are N values in the column bar but the selectivity of any particular value is substantially more or less than 1/N of the data), you would need to have a histogram on the column in order to tell the optimizer which values are more or less likely. And if you are using bind variables (as all good OLTP developers should), depending on the Oracle version, you may have issues with bind variable peeking.
Potentially, Oracle could even do an on the fly conversion of the two b*-tree indexes to bitmaps and combine the bitmaps in order to use both indexes to find the rows it needs to retrieve. But this is a rather unusual query plan, particularly if there are only two columns where one column is highly selective.
So is Oracle smart enough to search
efficiently here?
The simple answer is "probably". There are lots'o' very bright people at each of the database vendors working on optimizing the query optimizer, so it's probably doing things that you haven't even thought of. And if you update the statistics, it'll probably do even more.
I'm sure you can also have Oracle display a query plan so you can see exactly which index is used first.
The best approach would be to add foo to bar's index, or add bar to foo's index (or both). If foo's index also contains an index on bar, that additional indexing level will not affect the utility of the foo index in any current uses of that index, nor will it appreciably affect the performance of maintaining that index, but it will give the database additional information to work with in optimizing queries such as in the example.
It's better than that.
Index Seeks are always quicker than full table scans. So behind the scenes Oracle (and SQL server for that matter) will first locate the range of rows on both indices. It will then look at which range is shorter (seeing that it's an inner join), and it will iterate the shorter range to find the matches with the larger of the two.
You can provide hints as to which index to use. I'm not familiar with Oracle, but in Mysql you can use USE|IGNORE|FORCE_INDEX (see here for more details). For best performance though you should use a combined index.