I'm new to SQL Server, trying to optimize a procedure I received from ex-colleague (and I can't ask him).
At the final step, the procedure updates a large table using a MERGE statement. After that, it drops two nonclustered indexes and creates them again. What is the purpose of doing that? Aren't collected statistics for optimizer being recollected regularly? Is recreating indexes the only way to provide optimizer with fresh statistics?
Thanks
After that, it drops two nonclustered indexes and creates them again. What is the purpose
of doing that?
To organize them into less space without possibly page splits that may have happened during the merge. Generally it is NOT needed - like at all. It MAY make sense, but it is much better to actually analyze the index statistics about page splits before doing that unless you can be sure it is beneficial on every load.
Aren't collected statistics for optimizer being recollected regularly?
They are, but reoganizing the indices may make them more efficient. As data changes, data in index pages changes and when it overflows then a page is split. This leads to the index (nto the statistics on it) being unbalanced over time, which may lead to additional IO load.
Is recreating indexes the only way to provide optimizer with fresh statistics?
No. But you do not do it for statistics in the first place. You can just update the statistics if you want this. You do it to get an efficient index.
I have a table of a little over 1 billion rows of time-series data with fantastic insert performance but (sometimes) awful select performance.
Table tblTrendDetails (PK is ordered as shown):
PK TrendTime datetime
PK CavityId int
PK TrendValueId int
TrendValue real
The table is continuously pulling in new data and purging old data, so insert and delete performance needs to remain snappy.
When executing a query such as the following, performance is poor (30 sec):
SELECT *
FROM tblTrendDetails
WHERE TrendTime BETWEEN #inMinTime AND #inMaxTime
AND CavityId = #inCavityId
AND TrendValueId = #inTrendId
If I execute the same query again (with similar times, but any #inCavityId or #inTrendId), performance is very good (1 sec). Performance counters show that disk access is the culprit the first time the query is run.
Any recommendations regarding how to improve performance without (significantly) adversely affecting the insert or delete performance? Any suggestions (including completely changing the underlying database) are welcome.
The fact that subsequent queries of the same or similar data run much faster is probably due to SQL Server caching your data. That said, is it possible to speed this initial query up?
Verify the query plan:
My guess is that your query should result in an Index Seek rather than an Index Scan (or worse, a Table Scan). Please verify this using SET SHOWPLAN_TEXT ON; or a similar feature. Using between and = as your query does should really take advantage of the clustered index, though that's debatable.
Index Fragmentation:
It is possible that your clustered index (the primary key in this case) is quite fragmented after all of those inserts and deletes. I would probably check this with DBCC SHOWCONTIG (tblTrendDetails).
You can defrag the table's indexes with DBCC INDEXDEFRAG (MyDatabase, tblTrendDetails).
This may take some time, but will allow the table to remain accessible, and you can stop the operation without any nasty side-effects.
You might have to go further and use DBCC DBREINDEX (tblTrendDetails). This is an offline operation, though, so you should only do this when the table does not need to be accessed.
There are some differences described here: Microsoft SQL Server 2000 Index Defragmentation Best Practices.
Be aware that your transaction log can grow quite a bit from defragging a large table, and it can take a long time.
Partitioned Views:
If these do not remedy the situation (or fragmentation is not a problem), you may even wish to look to partitioned views, in which you create a bunch of underlying base tables for various ranges of records, then union them all up in a view (replacing your original table).
Better Stuff:
If performance of these selects is a real business need, you may be able to make the case for better hardware: faster drives, more memory, etc. If your drives are twice as fast, then this query will run in half the time, yeah? Also, this may not be workable for you, but I've simply found newer versions of SQL Server to truly be faster with more options and better to maintain. I'm glad to have moved most of my company's data to 2008R2. But I digress...
How can you determine if the performance gained on a SELECT by indexing a column will outweigh the performance loss on an INSERT in the same table? Is there a "tipping-point" in the size of the table when the index does more harm than good?
I have table in SQL Server 2008 with 2-3 million rows at any given time. Every time an insert is done on the table, a lookup is also done on the same table using two of its columns. I'm trying to determine if it would be beneficial to add indexes to the two columns used in the lookup.
Like everything else SQL-related, it depends:
What kind of fields are they? Varchar? Int? Datetime?
Are there other indexes on the table?
Will you need to include additional fields?
What's the clustered index?
How many rows are inserted/deleted in a transaction?
The only real way to know is to benchmark it. Put the index(es) in place and do frequent monitoring, or run a trace.
This depends on your workload and your requirements. Sometimes data is loaded once and read millions of times, but sometimes not all loaded data is ever read.
Sometimes reads or writes must complete in certain time.
case 1: If table is static and is queried heavily (eg: item table in Shopping Cart application) then indexes on the appropriate fields is highly beneficial.
case 2: If table is highly dynamic and not a lot of querying is done on a daily basis (eg: log tables used for auditing purposes) then indexes will slow down the writes.
If above two cases are the boundary cases, then to build indexes or not to build indexes on a table depends on which case above does the table in contention comes closest to.
If not leave it to the judgement of Query tuning advisor. Good luck.
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.
We have a very large table (> 77M records and growing) runing on SQL Server 2005 64bit Standard edition and we are seeing some performance issues. There are up to a hundred thousand records added daily.
Does anyone know if there is a limit to the number of records SQL server Standard edition can handle? Should be be considering moving to Enterprise edition or are there some tricks we can use?
Additional info:
The table in question is pretty flat (14 columns), there is a clustered index with 6 fields, and two other indexes on single fields.
We added a fourth index using 3 fields that were in a select in one problem query and did not see any difference in the estimated performance (the query is part of a process that has to run in the off hours so we don't have metrics yet). These fields are part of the clustered index.
Agreeing with Marc and Unkown above ... 6 indexes in the clustered index is way too many, especially on a table that has only 14 columns. You shouldn't have more than 3 or 4, if that, I would say 1 or maybe 2. You may know that the clustered index is the actual table on the disk so when a record is inserted, the database engine must sort it and place it in it's sorted organized place on the disk. Non clustered indexes are not, they are supporting lookup 'tables'. My VLDBs are laid out on the disk (CLUSTERED INDEX) according to the 1st point below.
Reduce your clustered index to 1 or 2. The best field choices are the IDENTITY (INT), if you have one, or a date field in which the fields are being added to the database, or some other field that is a natural sort of how your data is being added to the database. The point is you are trying to keep that data at the bottom of the table ... or have it laid out on the disk in the best (90%+) way that you'll read the records out. This makes it so that there is no reorganzing going on or that it's taking one and only one hit to get the data in the right place for the best read. Be sure to put the removed fields into non-clustered indexes so you don't lose the lookup efficacy. I have NEVER put more than 4 fields on my VLDBs. If you have fields that are being update frequently and they are included in your clustered index, OUCH, that's going to reorganize the record on the disk and cause COSTLY fragmentation.
Check the fillfactor on your indexes. The larger the fill factor number (100) the more full the data pages and index pages will be. In relation to how many records you have and how many records your are inserting you will change the fillfactor # (+ or -) of your non-clustered indexes to allow for the fill space when a record is inserted. If you change your clustered index to a sequential data field, then this won't matter as much on a clustered index. Rule of thumb (IMO), 60-70 fillfactor for high writes, 70-90 for medium writes, and 90-100 for high reads/low writes. By dropping your fillfactor to 70, will mean that for every 100 records on a page, 70 records are written, which will leave free space of 30 records for new or reorganized records. Eats up more space, but it sure beats having to DEFRAG every night (see 4 below)
Make sure the statistics exist on the table. If you want to sweep the database to create statistics using the "sp_createstats 'indexonly'", then SQL Server will create all the statistics on all the indexes that the engine has accumulated as requiring statistics. Don't leave off the 'indexonly' attribute though or you'll add statistics for every field, that would then not be good.
Check the table/indexes using DBCC SHOWCONTIG to see which indexes are getting fragmented the most. I won't go into the details here, just know that you need to do it. Then based on that information, change the fillfactor up or down in relation to the changes the indexes are experiencing change and how fast (over time).
Setup a job schedule that will do online (DBCC INDEXDEFRAG) or offline (DBCC DBREINDEX) on individual indexes to defrag them. Warning: don't do DBCC DBREINDEX on this large of a table without it being during maintenance time cause it will bring the apps down ... especially on the CLUSTERED INDEX. You've been warned. Test and test this part.
Use the execution plans to see what SCANS, and FAT PIPES exist and adjust the indexes, then defrag and rewrite stored procs to get rid of those hot spots. If you see a RED object in your execution plan, it's because there are not statistics on that field. That's bad. This step is more of the "art than the science".
On off peak times, run the UPDATE STATISTICS WITH FULLSCAN to give the query engine as much information about the data distributions as you can. Otherwise do the standard UPDATE STATISTICS (with standard 10% scan) on tables during the weeknights or more often as you see fit with your observerations to make sure the engine has more information about the data distributions to retrieve the data for efficiently.
Sorry this is so long, but it's extremely important. I've only give you here minimal information but will help a ton. There's some gut feelings and observations that go in to strategies used by these points that will require your time and testing.
No need to go to Enterprise edition. I did though in order to get the features spoken of earlier with partitioning. But I did ESPECIALLY to have much better mult-threading capabilities with searching and online DEFRAGING and maintenance ... In Enterprise edition, it is much much better and more friendly with VLDBs. Standard edition doesn't handle doing DBCC INDEXDEFRAG with online databases as well.
The first thing I'd look at is indexing. If you use the execution plan generator in Management Studio, you want to see index seeks or clustered index seeks. If you see scans, particularly table scans, you should look at indexing the columns you generally search on to see if that improves your performance.
You should certainly not need to move to Enterprise edition for this.
[there is a clustered index with 6 fields, and two other indexes on single fields.]
Without knowing any details about the fields, I would try to find a way to make the clustered index smaller.
With SQL Server, all the clustered-key fields will also be included in all the non-clustered indices (as a way to do the final lookup from non-clustered index to actual data page).
If you have six fields at 8 bytes each = 48 bytes, multiply that by two more indices times 77 million rows - and you're looking at a lot of wasted space which translates into a lot
of I/O operations (and thus degrades performance).
For the clustered index, it's absolutely CRUCIAL for it to be unique, stable, and as small as possible (preferably a single INT or such).
Marc
Do you really need to have access to all 77 million records in a single table?
For example, if you only need access to the last X months worth of data, then you could consider creating an archiving strategy. This could be used to relocate data to an archive table in order to reduce the volume of data and subsequently, query time on your 'hot' table.
This approach could be implemented in the standard edition.
If you do upgrade to the Enterprise edition you can make use of table partitioning. Again depending on your data structure this can offer significant performance improvements. Partitioning can also be used to implement the strategy previously mentioned but with less administrative overhead.
Here is an excellent White paper on table partitioning in SQL Server 2005
http://msdn.microsoft.com/en-us/library/ms345146.aspx
I hope what I have detailed is clear and understandable. Please do feel to contact me directly if you require further assistance.
Cheers,
http://msdn.microsoft.com/en-us/library/ms143432.aspx
You've got some room to grow.
As far as performance issues, that's a whole other question. Caching, sharding, normalizing, indexing, query tuning, app code tuning, and so on.
Standard should be able to handle it. I would look at indexing and the queries you use with the table. You want to structure things in such a way that your inserts don't cause too many index recalcs, but your queries can still take advantage of the index to limit lookups to a small portion of the table.
Beyond that, you might consider partitioning the table. This will allow you to divide the table into several logical groups. You can do it "behind-the-scenes", so it still appears in sql server as one table even though it stored separately, or you can do it manually (create a new 'archive' or yearly table and manually move over rows). Either way, only do it after you looked at the other options first, because if you don't get that right you'll still end up having to check every partition. Also: partitioning does require Enterprise Edition, so that's another reason to save this for a last resort.
In and of itself, 77M records is not a lot for SQL Server. How are you loading the 100,000 records? is that a batch load each day? or thru some sort of OLTP application? and is that the performance issue you are having, i.e adding the data? or is it the querying that giving you the most problems?
If you are adding 100K records at a time, and the records being added are forcing the cluster-index to re-org your table, that will kill your performance quickly. More details on the table structure, indexes and type of data inserted will help.
Also, the amount of ram and the speed of your disks will make a big difference, what are you running on?
maybe these are minor nits, but....
(1) relational databases don't have FIELDS... they have COLUMNS.
(2) IDENTITY columns usually mean the data isn't normalized (or the designer was lazy). Some combination of columns MUST be unique (and those columns make up the primary key)
(3) indexing on datetime columns is usually a bad idea; CLUSTERING on datetime columns is also usually a bad idea, especially an ever-increasing datetime column, as all the inserts are contending for the same physical space on disk. Clustering on datetime columns in a read-only table where that column is part of range restrictions is often a good idea (see how the ideas conflict? who said db design wasn't an art?!)
What type of disks do you have?
You might monitor some disk counters to see if requests are queuing.
You might move this table to another drive by putting it in another filegroup. You can also to the same with the indexes.
Initially I wanted to agree with Marc. The width of your clustered index seems suspect, as it will essentially be used as the key to perform lookups on all your records. The wider the clustered index, the slower the access, generally. And a six field clustered index feels really, really suspect.
Uniqueness is not required for a clustered index. In fact, the best candidates for fields that should be in the clustered index are ones that are not unique and used in joins. For example, in a Persons table where each Person belongs to one Group and you frequently join Persons to Groups, while accessing batches of people by group, Person.group_id would be an ideal candidate, for this particular use case.