I have a database that was recreated each night with about 10 columns and 1,000,000 rows. The data is completely deleted and re-inserted.
I have full text search on this table turned on and I rebuild it after each night.
Recently I noticed that my indexes get extremely fragmented by doing this. Is rebuilding my indexes after each insert the solution to this?
I'm trying to speed up my search and filtering of the data, should I just rebuild the indexes each night as well as the full text index?
Is the fragmentation really slowing me down that much?
I'm also open to other ways to improve performance on this table on a nightly basis if you have any suggestions.
Related
I have 4 lucene index with Hibernate-search. Each has 2 million document. Recently I need to add #Facet fields. But whole index rebuild time is too slow.
No, you have to rebuild the index.
The process of rebuilding the index does indeed take some time, but with some tuning you can speed it up significantly.
Since there are many situations in which you'll need to rebuild the index, it's worth spending a bit of time to investigate on how to make it fast enough to be acceptable: you will need this also in case of disaster recovery.
I have an Azure SQL Database that has proved pretty successful so far. It's about 20 months old, no maintenance done... but it has handled a lot. Some tables have millions of rows, and when querying on columns that are indexed, query response times are acceptable when using the web application that talks to it.
However, I read conflicting advice on rebuilding indexes.
This guy says there is no point in doing it: http://beyondrelational.com/modules/2/blogs/76/posts/15290/index-fragmentation-in-sql-azure.aspx
This guy says go ahead rebuild:
https://alexandrebrisebois.wordpress.com/2013/02/06/dont-forget-about-index-maintenance-on-windows-azure-sql-database/
I have run some rebuild index statements on some of the smaller tables storing a few thousand rows. Some of the fragmentation would drop by about 1/2... then if I run it a second time, it might go down by about
these rebuilds ran in about 2-10 seconds depending on size of table...
Then I ran an index that had the following fragmentation on a table that has about 2 million rows:
PK__tmp_ms_x__CDEC17C03A4CDB46 55.2335782060565
PK__tmp_ms_x__CDEC17C03A4CDB46 0
IX_this_is_my_fk_index 15.7538877620014
It took 33 minutes.
The result was
PK__tmp_ms_x__CDEC17C03A4CDB46 0.01
PK__tmp_ms_x__CDEC17C03A4CDB46 0
IX_this_is_my_fk_index 0
Questions:
Query speeds have not really changed since doing the above. Is this normal?
Given that there are many things I have no control over in SQL Azure, does it even make sense to Rebuild indexes?
BTW: I am not and never have been a DBA... just a developer
Rebuilding indexes will matter if the indexes are actually being used. If the index isnt being used for the query youre running, then you wont see a difference. If its only lightly being used, you'll see a minor difference if you run stats. If its being heavily used, you should see a good performance increase, most of the time. The other thing to note with Microsoft SQL is that index fragmentation is sometimes irrelevant. Usually when I'm choosing whether or not to rebuild an index, im looking at the page count combined with fragmentation. If im running a query and i'm having performance issues, and im using the index, and the index has more than 16000 pages, and the index is more than 50% fragmented, ill rebuild it. If the table is small or if I can use the online option, i will just go ahead and rebuild all of them at the same time..
Specifically for Azure, my opinion is that if you are trying to improve performance, its still a good step to take because its so easy, even if you cant be sure of the results. Whether or not its a shared service and whether or not you can control the hardware layer, reviewing the index fragmentation and rebuilding the indexes are something you have access to, so why not make use of it?
So I guess the short answer is yes, in certain situations.
What I would suggest, rather than manually reviewing indexes and rebuilding them, is set up a nightly or weekly job that runs when your db is least active. Have it go through all the tables and rebuild the indexes. You can also give it a set running time if you have lots of tables, and then make it "stateful" (you can use a table to retain progress info) so it remembers where it left off and resumes at the next scheduled run.
i am having recently came to know that sql server if i delete one column or modify it acquires space at backend so i need to reindex and shrink the database and i have done it and my datbase size reduced to
2.82 to 1.62
so its good like wise so now i am in a confusion
so in my mind many questions regarding this subject occurs pls help me about this one
1. So it is necessary to recreate indexes(refresh ) after particular interval
It is necessary to shrink database after particular time so performance will be up to date?
If above yes then what particular time should i refresh (Shrink) my database?
i am having no idea what should be done for disk spacing problem i am having 77000 records it takes 2.82gb dataspace which is not acceptable i am having two tables of that one only with one table nvarchar(max) so there should be minimum spaces to database can anyone help me on this one Thanks in advance
I am going to simplify things a little for you so you might want to read up about the things I talk about in my answer.
Two concepts you must understand. Allocated space vs free space. A database might be 2GB in size but it is only using 1GB so it has allocated 2GB with 1GB free space. When you shrink a database it removes the free space so free space should be about 0. Dont think smaller file size is faster. As you database grows it has to allocate space again. When you shrink the file and then it grows every so often it cannot allocate space in a contiguous fashion. This will create fragmentation of the files which slows you down even more.
With data files(.mdb) files this is not so bad but with the transaction log shrinking the log can lead to virtual log file fragmentation issues which can slow you down. So in a nutshell there is very little reason to shrink your database on a schedule. Go read about Virtual Log Files in SQL Server there are a lot of articles about it. This is a good article about shrink log files and why it is bad. Use it as a starting point.
Secondly indexes get fragmented over time. This will lead to bad performance of SELECT queries mainly but will also affect other queries. Thus you need to perform some index maintenance on the database. See this answer on how to defragment your indexes.
Update:
Well the time you rebuild indexes is not clear cut. Index rebuilds lock the index during the rebuild. Essentially they are offline for the duration. In your case it would be fast 77 000 rows is nothing for SQL server. So rebuilding the indexes will consume server resources. IF you have enterprise edition you can do online index rebuilding which will NOT lock the indexes but will consume more space.
So what you need to do is find a maintenance window. For example if your system is used from 8:00 till 17:00 you can schedule maintenance rebuilds after hours. Schedule this with SQL server agent. The script in the link can be automated to run.
Your database is not big. I have seen SQL server handle tables of 750GB without taking strain if the IO is split over several disks. The slowest part of any database server is not the CPU or the RAM but the IO pathways to the disks. This is a huge topic though. Back to your point you are storing data in NVARCHAR(MAX) fields. I assume this is large text. So after you shrink the database you see the size at 1,62GB which means that each row in your database is about 1,62/77 000 big or roughly 22Kb big. This seems reasonable. Export the table to a text file and check the size you will be suprised it will probably be larger than 1,62GB.
Feel free to ask more detail if required.
We currently have a SQL Agent Job that runs once a week to identify highly fragment indexes and rebuild them. For certain large indexes on large tables, this ends up causing the system to timeout, as the index is unavailable during the rebuild.
We have identified a strategy that should significantly reduce the fragmentation that occurs, but that won't be implemented for some time, and it doesn't cover everything.
We checked in to upgrading to the Enterprise edition, which allows for online index rebuilding. However, the cost is prohibitive for us at this point.
The indexes don't really change that much, so we can assume that they are static, at least for the most part.
I did envision a way that we could perhaps simulate the online index rebuilding. It could work as follows
For each of the large indexes identified, run a script to:
Check the fragmentation and proceed if it exceeds a certain threshold.
Create a new index, entitled CurrentIndex_TEMP.
Initiate a rebuild on the index.
Remove the temporary index.
It seems that once the temporary index has been built, it would be possible to rebuild the other index without causing any downtime, since SQL Server would have another index that would then be available to use on queries that would have otherwise used the other query.
Iterating through this for each index would hopefully minimize the increase in overall index size, as each temporary index would be removed before any other temporary indexes were created.
This strategy would also retain the historical data on the indexes. I had originally considered a strategy of first renaming the current index, then creating it again with the original name, and then removing the index that had been renamed. This, however, would result in a loss of history.
So, my question...
Is this a feasible strategy? Are there any significant problems I may run into? I understand that this will take some manual oversight from time to time, but I'm willing to accept that at this point.
Thanks for the help.
Any offline index rebuild with lock the table so you don't gain anything by creating a duplicated index.
With great effort your can simulate online index rebuilds. You have to rebuild all indexes on the table at once.
Create a copy of the table T with identical schema ("T_new")
Rename T to T_old
Create a view T defined as select * from T_old and set up INSTEAD OF DML triggers which perform all DML on both T_old and T_new
In a background job copy over batches from T_old to T_new using the MERGE statement
Finally, after the copy is completed, perform some renaming and dropping to make T_new the new T
This requires insanely high effort and good testing. But you can realize pretty much arbitrary schema changes with this online.
Hi all i'm completely new to maintenance tasks on SQL Server. I've set up a datawharehouse, that basically reads a load of xml files and imports this data into several tables using an SSIS. Now i've set indexes on the tables concerned and optimized my ssis. However i know that i should perform some maintenance tasks but i dont really know where to begin. We are talking about quite a bit of data, we are keeping data for up to 6 months and so far we have 3 months worth of data and the database is currently 147142.44 MB with roughly 57690230 rows in the main table. So it could easily double in size. Just wondering what your recommendations are?
While there is the usual index rebuild and statistics update which are part of normal maintenance, I would look at all of the currently long running queries and try to do some index tuning, before the data size grows. Resizing the database also forms part of a normal maintenance plan, if you can predict the growth and allocate enough space between maintenance runs then you can avoid the performance hit of space auto allocation (which will always happen at the worst possible time)