I have a table with 20 or so columns. I have approximately 7 non-clustered indexes in that table on the columns that users filter by more often. The active records (those that the users see on their screen) are no more than 700-800. Twice a day a batch job runs and inserts a few records in that table - maybe 30 - 100 - and may update the existing ones as well.
I have noticed that the indexes need rebuilding EVERY time that the batch operation completes. Their fragmentation level doesnt go from 0-1% step by step to say 50%. I have noticed that they go from 0-1% to approx. 99% after the batch operation completes. A zillion of selects can happen on this table between batch operations but i dont think that matters.
Is this normal? i dont think it is. what do you think its the problem here? The indexed columns are mostly strings and floats.
A few changes could easily change fragmentation levels.
An insert on a page can cause a page split
Rows can overflow
Rows can be moved (forward pointers)
You'll have quite wide rows too so your data density (rows per page) is lower. DML on existing rows will cause fragmentation quite quickly if the DML is distributed across many pages
Related
I have a table with 281,433 records in it, ranging from March 2010 to the current date (Sept 2014). It's a transaction table which consists of records that determine stock which is currently in and out of the warehouse.
When making picks from the warehouse, the system needs to look over every transaction from a particular customer that was ever made (based on the AccountListID field, which determines the customer, a customer might on average have about 300 records in the table). This happens 2-3 times per request from the particular .NET application when a picking run is done.
There are times when the database seemingly locks out. Some requests complete no bother, within about 3 seconds. Others hang for 'up to 4 minutes' according to the end users.
My guess is with 4-5 requests at the same time all looking at this one transaction table things are getting locked up.
I'm thinking about partitioning this table so that the primary transaction table only contains record from the last 2 years. The end user has agreed that any records past this date are unnecessary.
But I can't just delete them, they're used elsewhere in the system. I have indexes already in place and they make a massive difference (going from >30 seconds to <2, on the accountlistid field). It seems partitioning is the next step.
1) Am I going down the right route as a solution to my 'locking' problem?
2) When moving a set of records (e.g. records where the field DateTimeCheckedIn is more than 2 years old) is this a manual process or does partitioning automatically do this?
Partitioning shouldn't be necessary on a table with fewer than 300,000 rows, unless each record is really big. If a record is occupying more than 4k bytes, then you have 300,000 pages (2,400,000,000 bytes) and that is getting larger.
Indexes are usually the solution for something like this. Taking more than a second to return 300 records in an indexed database seems like a long time (unless the records are really big and the network overhead adds to the time). Your table and index should both fit into memory. Check your memory configuration.
The next question is about the application code. If it uses cursors, then these might be the culprit by locking rows under certain circumstances. For read-only cursors, "FAST_FORWARD" or "FORWARD READ_ONLY" should be fast. It is possible that if the application code is locking all the historical records, then you might get contention. After all, this would occur when two records (for different) customers are on the same data page. The solution is to not lock the historical records as you read them. Or, to avoid using cursors all together.
I don't think partitioning will be necessary here. You can probably fix this with a well-placed index: I'm thinking a single index covering (in order) company, part number, and quantity. Or, if it's an old server, possibly just add ram. Finally, since this is reading a lot of older data for transactions, where individual transactions themselves are likely never (or at most very rarely) updated once written, you might do better with a READ UNCOMMITTED isolation level for this query.
We have a very large table that was partitioned into monthly tables. We have no autovacuum parameters set in the postgresql.conf file, so it's on by default with default parameters.
The past months tables table_201404, table_201403 do not get written to or updated/deleted once they are passed, they are only read from for historical data. Why is it that we are noticing autovacuum processes running on these tables? Is it because they are part of a main partition and PostgreSQL is seeing those tables as one?
We are toying with the idea of setting autovacuum_enabled to off for these past tables, but I wanted to consult the wisdom of Stackoverflow first.
Thanks all...
Even read-only tables need to be vacuumed for wrap-around once every 2 billion transactions, and under the default settings are vacuumed for wrap-around once every 150 million transactions.
The transaction IDs stored with each row are 32 bits, so they wrap around eventually. To prevent this from causing problems, any very old transactionID has to be replaced with a magic value meaning "Older than all other IDs". So the table has to be scanned to do that replacement. If the table never changes, eventually every transaction ID will be replaced with the magic value and conceptually that table no longer needs to be scanned. But that fact is not stored anywhere, so the table still needs to be scanned every now then so that the system can observe that they are all still OK. Fortunately the scan is done in sequentially and only needs to read, not write, so it should be fairly efficient.
It is possible that the whole thing will be redone in 9.5 so that tables like that would no longer need to be scanned.
I'm writing several hundred or potentially several thousand rows into a set of tables at a time, each of which is heavily indexed both internally and via indexed views.
Generally, the inserts are occurring where the rows inserted will be adjacent in the index.
I expect these inserts to be expensive, but they are really slow. I think part of the performance issue is that the indexes are being updated with each individual INSERT.
Is there a way to tell SQL Server to hold off on updating the indexes until I am finished with my batch of inserts so the index trees will only need to be updated once?
These are executed as separate statements due to needing to show the user a progress bar during save and log any individual issues, but are all coming from the same connection in C#. I can place them in a transaction if needed, though I'd prefer not to.
You are paying the cost of adding those rows to the index one way or another. Not updating the index during the insert would cause an issue with accuracy of concurrent statements - any query on that table that used any of the indexes would not "see" the new rows!
If speed is of the essence, and downtime after the insert isn't a major concern, you can:
Disable non-clustered indexes on the target table
Inert
Rebuild non-clustered indexes
You probably should clarify some more about your table:
How wide is the table?
How many indexes?
How wide are the indexes?
If you have 20 indexes and each index has 5 fields, you are really updating 100 extra fields per row which can get expensive quickly.
Let’s say you have a table with about 5 million records and a nvarchar(max) column populated with large text data. You want to set this column to NULL if SomeOtherColumn = 1 in the fastest possible way.
The brute force UPDATE does not work very well here because it will create large implicit transaction and take forever.
Doing updates in small batches of 50K records at a time works but it’s still taking 47 hours to complete on beefy 32 core/64GB server.
Is there any way to do this update faster? Are there any magic query hints / table options that sacrifices something else (like concurrency) in exchange for speed?
NOTE: Creating temp table or temp column is not an option because this nvarchar(max) column involves lots of data and so consumes lots of space!
PS: Yes, SomeOtherColumn is already indexed.
From everything I can see it does not look like your problems are related to indexes.
The key seems to be in the fact that your nvarchar(max) field contains "lots" of data. Think about what SQL has to do in order to perform this update.
Since the column you are updating is likely more than 8000 characters it is stored off-page, which implies additional effort in reading this column when it is not NULL.
When you run a batch of 50000 updates SQL has to place this in an implicit transaction in order to make it possible to roll back in case of any problems. In order to roll back it has to store the original value of the column in the transaction log.
Assuming (for simplicity sake) that each column contains on average 10,000 bytes of data, that means 50,000 rows will contain around 500MB of data, which has to be stored temporarily (in simple recovery mode) or permanently (in full recovery mode).
There is no way to disable the logs as it will compromise the database integrity.
I ran a quick test on my dog slow desktop, and running batches of even 10,000 becomes prohibitively slow, but bringing the size down to 1000 rows, which implies a temporary log size of around 10MB, worked just nicely.
I loaded a table with 350,000 rows and marked 50,000 of them for update. This completed in around 4 minutes, and since it scales linearly you should be able to update your entire 5Million rows on my dog slow desktop in around 6 hours on my 1 processor 2GB desktop, so I would expect something much better on your beefy server backed by SAN or something.
You may want to run your update statement as a select, selecting only the primary key and the large nvarchar column, and ensure this runs as fast as you expect.
Of course the bottleneck may be other users locking things or contention on your storage or memory on the server, but since you did not mention other users I will assume you have the DB in single user mode for this.
As an optimization you should ensure that the transaction logs are on a different physical disk /disk group than the data to minimize seek times.
Hopefully you already dropped any indexes on the column you are setting to null, including full text indexes. As said before, turning off transactions and the log file temporarily would do the trick. Backing up your data will usually truncate your log files too.
You could set the database recovery mode to Simple to reduce logging, BUT do not do this without considering the full implications for a production environment.
What indexes are in place on the table? Given that batch updates of approx. 50,000 rows take so long, I would say you require an index.
Have you tried placing an index or statistics on someOtherColumn?
This really helped me. I went from 2 hours to 20 minutes with this.
/* I'm using database recovery mode to Simple */
/* Update table statistics */
set transaction isolation level read uncommitted
/* Your 50k update, just to have a measures of the time it will take */
set transaction isolation level READ COMMITTED
In my experience, working in MSSQL 2005, moving everyday (automatically) 4 Million 46-byte-records (no nvarchar(max) though) from one table in a database to another table in a different database takes around 20 minutes in a QuadCore 8GB, 2Ghz server and it doesn't hurt application performance. By moving I mean INSERT INTO SELECT and then DELETE. The CPU usage never goes over 30 %, even when the table being deleted has 28M records and it constantly makes around 4K insert per minute but no updates. Well, that's my case, it may vary depending on your server load.
READ UNCOMMITTED
"Specifies that statements (your updates) can read rows that have been modified by other transactions but not yet committed." In my case, the records are readonly.
I don't know what rg-tsql means but here you'll find info about transaction isolation levels in MSSQL.
Try indexing 'SomeOtherColumn'...50K records should update in a snap. If there is already an index in place see if the index needs to be reorganized and that statistics have been collected for it.
If you are running a production environment with not enough space to duplicate all your tables, I believe that you are looking for trouble sooner or later.
If you provide some info about the number of rows with SomeOtherColumn=1, perhaps we can think another way, but I suggest:
0) Backup your table
1) Index the flag column
2) Set the table option to "no log tranctions" ... if posible
3) write a stored procedure to run the updates
Using SQL Server 2005. This is something I've noticed while doing some performance analysis.
I have a large table with about 100 million rows. I'm comparing the performance of different indexes on the table, to see what the most optimal is for my test scenario which is doing about 10,000 inserts on that table, among other things on other tables. While my test is running, I'm capturing an SQL Profiler trace which I load in to an SQL table when the test has finished so I can analyse the stats.
The first test run after recreating a different set of indexes on the table is very noticeably slower than subsequent runs - typically about 10-15 times slower for the inserts on this table on the first run after the index creation.
Each time, I clear the data and execution plan cache before the test.
What I want to know, is the reason for this initial poorer performance with a newly created set of indexes?
Is there a way I can monitor what is happening to cause this for the first run?
One possibility is that the default fill factor of zero is coming in to play.
This means that there's 'no room' in the index to accommodate your inserts. When you insert, a page split in the index is needed, which adds some empty space to store the new index information. As you carry out more inserts, more space is created in the index. After a while the rate of splitting will go down, because your inserts are hitting pages that are not fully filled, so splits are not needed. An insert requiring page splits is more expensive than one that doesn't.
You can set the fill factor when you create the index. Its a classic trade off between space used and performance of different operations.
I'm going go include a link to some Sybase ASE docs, 'cos they are nicely written and mostly applicable to SQL Server too.
Just to clarify:
1) You build an index on a table with 100m pre-existing rows.
2) You insert 10k rows into the table
3) You insert another 10k rows into the table
Step 3 is 10x faster than step 2?
What kind of index is the new index - not clustered, right? Because inserts on a clustered index will cause very different behavior. In addition, is there any significant difference in the profile of the 2 inserts, because depending on the clustered index, they will have different behavior. Typically, it should either have no clustered index or be clustered on an increasing key.