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I have been searching good information about index benchmarking on PostgreSQL and found nothing really good.
I need to understand how PostgreSQL behaves while handling a huge amount of records.
Let's say 2000M records on a single non-partitioned table.
Theoretically, b-trees are O(log(n)) for reads and writes but in practicality
I think that's kind of an ideal scenario not considering things like HUGE indexes not fitting entirely in memory (swapping?) and maybe other things I am not seeing at this point.
There are no JOIN operations, which is fine, but note this is not an analytical database and response times below 150ms (less the better) are required. All searches are expected to be done using indexes, of course. Where we have 2-3 indexes:
UUID PK index
timestamp index
VARCHAR(20) index (non unique but high cardinality)
My concern is how writes and reads will perform once the table reach it's expected top capacity (2500M records)
... so specific questions might be:
May "adding more iron" achieve reasonable performance in such scenario?
NOTE this is non-clustered DB so this is vertical scaling.
What would be the main sources of time consumption either for reads and writes?
What would be the amount of records on a table that we can consider "too much" for this standard setup on PostgreSql (no cluster, no partitions, no sharding)?
I know this amount of records suggests taking some alternative (sharding, partitioning, etc) but this question is about learning and understanding PostgreSQL capabilities more than other thing.
There should be no performance degradation inserting into or selecting from a table, even if it is large. The expense of index access grows with the logarithm of the table size, but the base of the logarithm is large, and the index shouldn't have a depth of the index cannot be more than 5 or 6. The upper levels of the index are probably cached, so you end up with a handful of blocks read when accessing a single table row per index scan. Note that you don't have to cache the whole index.
My two questions are:
Can I use clustered indexes to speed
up bulk inserts in big tables?
Can I then still efficiently use
foreign key relationships if my
IDENTITY column is not the clustered
index anymore?
To elaborate, I have a database with a couple of very big (between 100-1000 mln rows) tables containing company data. Typically there is data about 20-40 companies in such a table, each as their own "chunk" marked by "CompanyIdentifier" (INT). Also, every company has about 20 departments, each with their own "subchunk" marked by "DepartmentIdentifier" (INT).
It frequently happens that a whole "chunk" or "subchunk" is added or removed from the table. My first thought was to use Table Partitioning on those chunks, but since I am using SQL Server 2008 Standard Edition I am not entitled to it. Still, most queries I have are executed on a "chunk" or "subchunk" rather than on the table as a whole.
I have been working to optimize these tables for the following functions:
Queries that are run on subchunks
"Benchmarking" queries that are run on the table as a whole
Inserting/removing big chunks of data.
For 1) and 2) I haven't encountered a lot of problems. I have created several indexes on key fields (also containing CompanyIdentifier and DepartmentIdentifier where useful) and the queries are running fine.
But for 3) I have struggled to find a good solution.
My first strategy was to always disable indexes, bulk insert a big chunk and rebuild indexes. This was very fast in the beginning, but now that there are a lot of companies in the database, it takes a very long time to rebuild the index each time.
At the moment my strategy has changed to just leaving the index on while inserting, since this seems to be faster now. But I want to optimize the insert speed even further.
I seem to have noticed that by adding a clustered index defined on CompanyIdentifier + DepartmentIdentifier, the loading of new "chunks" into the table is faster. Before I had abandoned this strategy in favour of adding a clustered index on an IDENTITY column, as several articles pointed out to me that the clustered index is contained in all other indexes and so the clustered index should be as small as possible. But now I am thinking of reviving this old strategy to speed up the inserts. My question, would this be wise, or will I suffer performance hits in other areas? And will this really speed up my inserts or is that just my imagination?
I am also not sure whether in my case an IDENTITY column is really needed. I would like to be able to establish foreign key relationships with other tables, but can I also use something like a CompanyIdentifier+DepartmentIdentifier+[uniquifier] scheme for that? Or does it have to be a table-wide, fragmented IDENTITY number?
Thanks a lot for any suggestions or explanations.
Well, I've put it to the test, and putting a clustered index on the two "chunk-defining" columns increases the performance of my table.
Inserting a chunk is now relatively fast compared to the situation where I had a clustered IDENTITY key, and about as fast as when I did not have any clustered index. Deleting a chunk is faster than with or without clustered index.
I think the fact that all the records I want to delete or insert are guaranteed to be all together on a certain part of the harddisk makes the tables faster - it would seem logical to me.
Update: After a year of experience with this design I can say that for this approach to work, it is necessary to schedule regular rebuilding of all the indexes (we do it once a week). Otherwise, the indexes become fragmented very soon and performance is lost. Nevertheless, we are in a process of migration to a new database design with partitioned tables, which is basically better in every way - except for the Enterprise Server license cost, but we've already forgotten about it by now. At least I have.
A clustered index is a physical index, a physical data structure, a row order. If you insert in the middle of the clustered index, the data will be physically inserted in the middle of the present data. I imagine a serious performance issue in this case. I only know this from theory, because if I do this in practice, it will be a mistake according to my theoretical knowledge.
Therefore, I only use (and advise the use) of clustered indexes on fields that are always, physically, inserted at the end, preserving the order.
A clustered index can be placed on a datetime field which marks the moment of insertion or something like that, because physically they will be ordered after appending a row. Identity is a good clustered index also, but not always relevant for querying.
In your solution you place a [uniquifier] field, but why do this when you can put an identity that will do just that? It will be unique, physically ordered, small (for foreign keys in other tables means smaller index), and in some cases faster.
Can't you try this, experiment? I have a similar situation here, where I have 4 billion rows, constantly more are inserting (up to 100 per second), the table has no primary key and no clustered index, so the propositions in this topic are VERY interesting for me too.
Can I use clustered indexes to speed up bulk inserts in big tables?
Never! Imagine another million rows that you need to put in that table and have them physically ordered it is a colossal loss in performance in the long run.
Can I then still efficiently use foreign key relationships if my IDENTITY column is not the clustered index anymore?
Absolutely. By the way, clustered index is no silver bullet and may be slower than your ordinary index.
Have a look at the System.Data.SqlClient.SqlBulkCopy API. Given your requirements to write signficant numbers of rows in and out of the database, it might be what you need?
Bulk copy streams the data into the table in a single operation then performs the index check once. I use it to copy 500,000 rows in and out of a database table and it's performance is an order of magnitude better than any other technique I've tried, assuming that your application can be structured to take use of the API?
i've been playing around with some etl stuff the last little bit. i went through jsut regularly inserting into the table, then removing and readding indexes before and after the insert, tried merge statements, then i finally tried ssis. I'm sold on ssis. Just yesterday i managed to cut an etl process (~24 million records, ~6gb) from ~1-1 1/2 hours per run to ~24 minutes, jsut by letting ssis handle the inserts.
i believe with advanced services you should be able to use ssis.
(Given you have already chosen the Answer and given yourself the points, this is provided as a free service, a charitable act !)
A little knowledge is a dangerous thing. There are many issues to be considered; and they must be considered together. Taking any one issue and examining it in isolation is a very fragmented way to go about administering a database: you will forever be finding some new truth and changing eveything you thought before. Before launching into it, please read this ▶question/answer◀ for context.
Do not forget, these days anyone with a keyboard and a modem can get their "papers" published. Some of them work for MS, evangelising the latest "enhancement"; others publish glowing reports of features they have never used, or used only once, in one context, but they publish that it works in every context. (Look at Spence's answer: he is enthusiastic and "sold" but under scrutiny, the statements are false; he is not a bad person, just typical of the masses in the MS world and how they operate; how they publish.)
Note: I use the term MicroSofties to describe those people who believe in the gatesian notion that any unqualified person can administer a database; and that MS will fix everything. It is not intended as an insult, more as an endearment, because of the belief in magic, and the suspension of the laws of physics.
Clustered Indices
Were designed for Relational databases, by real engineers (Sybase, before MS acquired the code) who have more brains than all of MS put together. Relational databases have Relational Keys, not Idiot keys. These are multi-column keys, that automatically distribute the data, and therefore the insert load, eg. inserting Invoices for various Companies all the time (although not in our discussed case of "chunks").
if you have good Relational keys, CIs provide Range Queries (your (1) & (2) ), and other advantages, that NCIs simply do not have.
Starting off with Id columns, before modelling and normalising the data, severely hinders the modelling and normalisation processes.
If you have an Idiot database, then you will have more indices than not. The contents of many MS databases are not "relational", they are commonly just unnormalised filing systems, with way more indices than a Normalised database would have. Therefore there is a big push, a lot of MS "enhancements" to try and give these abortions a bit of speed. Fix the symptom but don't go anywhere near the problem that caused the symptom.
In SQL 2005 and again in 2008 MS has screwed around with CIs, and the result is they are now better in some ways, but worse in other ways; the universality of CIs has been lost.
It is not correct that NCIs carry the CI (the CI is the basic single storage structure; the NCIs are secondary, and dependent on the CI; that's why when you re-create a CI, all the NCIs are automatically re-created). The NCIs carry the CI Key at the leaf level.
Microsoft has its problems, which change with the major releases (but are not eliminated):
and in MS this is not efficiently done, so the NCI index size is large; in enterprise DBMS when this is efficiently done, this is not a consideration.
In the MS world, therefore, it is only half true, that the CI key should be as short as possible. If you understand that the consideration is the size of NCIs, and if you are willing to incur that expense, it return for a table that is very fast due to a carefully constructed CI, then that is the best option.
The common advice that the CI should be theIdiot column is totally and completely wrong. The worst canditate fo a CI key is a monotonically increasing value (IDENTITY, DATETIME, etc). WHy ? because you have guaranteed that all concurrent inserts will fight for the current insert location, the last page on the index.
The real purpose of Partitioning (Which MS provided 10 years after the Enterprise vendors) is to spread this load. Sure, they then have to provide a method of allocating the Partitions, on guess what, nothing but a Relational Key; but to start with, now the Idiot key is spread across 32 or 64 Partitions, providing better concurrency.
the CI must be Unique. Relational dbs demand Unique keys, so that is a no-brainer.
But for the amateurs who have poured non-relational contents into the database, if they do not know this rule, but they know that the CI spreads the data (a little knowledge is a dangerous thing), they keep their Idiot key in a NCI (good) but they create the CI on an almost-but-not-quite Unique Key. Deadly. CI's must be Unique, that is a design demand. Duplicate (remember we are talking CI Key here) rows are off-page, located in Overflow pages, and the (then) last page; and constitute a method of badly fragmenting the Page Chain.
Update, since this point is being questioned elsewhere. I have already stated the MS keeps changing the methods without fixing the problem.
The MS Online manual, with their pretty pictures (not technical diagrams) tells us that In 2008, they have replaced (substitued one for another) Overflow Pages, with the adorable "Uniqueifier".
That totally satisfies the MicroSofties. Non-Unique CIs are not a problem. It is handled by magic. Case closed.
But there is no logic or completeness to the statements, and qualified people will ask the obvious questions: where is this "Uniqueifier" located ? On every row, or just the rows needing "Uniqueifying". DBBC PAGE shows it is on every row. So MS has just added a 4-byte secret column (including handling overhead) to every row, instead of a few Overflow Pages for the non-unique rows only. That's MS idea of engineering.
End Update
Anyway, the point remains, that Non-Unique CIs have a substantial overhead (now more than before) and should be avoided. you would be better off adding a 1- or 2-byte column yourself, to force uniqueness.
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Therefore, unchanged from the beginning (1984), the best candidate for a CI is a multi-column unique Relational key (I cannot say that yours is for sure, but it certainly looks like it).
And put any monotonically increasing keys (IDENTITY, DATETIME) in an NCI.
Remember also that the CI is a single storage structure, which eliminates the (otherwise) Heap; the CI B-Tree is married to the rows at the Leaf level; the Leaf Level entry is the row. That guarantees one less read on every access.
So it is not possible, that a NCI+Heap can be faster than a CI. Anther common myth in the MS world that defies the laws of physics: navigating a B-Tree and writing to the one place you are already in, has got to be faster than additionally writing the row to a separate storage structure. But MicroSofties do believe in magic, they've suspended the laws of physics.
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There are many other features you need to learn and use, I will mention at least FILLFACTOR and RESERVEPAGEGAP, to give this post a bit of completeness. Do not use these features until you understand them. All performance features have a cost that you need to understand and accept.
CIs are also self-trimming at both the Page and Extent level, there is no wasted space. PageSplits are something to monitor for (Random inserts only), and that is easily modulated by FILLFACTOR and RESERVEPAGEGAP.
And read the SO site for Clustered Indices, but keep in mind all the above, esp. the first two paras.
Your Specific Case
By all means, get rid of your surrogate keys (Idiot columns), and replace them with true natural Relational keys. Surrogates are always an additional key and index; that is a price that should not be forgotten or taken lightly.
CompanyIdentifier+DepartmentIdentifier+[uniquiefier] is exactly what I am talking about. Now notice that they are already INTs, and very fast, so it is very silly to add a NUMERIC(10,0) Idiot Key. Use a 1- or 2-byte column toforce Uniqueness.
If you get this right, you may not need a Partition licence.
The CompanyIdentifier+DepartmentIdentifier+[uniquifier] is the perfect candidate (not knowing anything about your db other than that which you have posted) for a CI, in the context that you perform mass delete/insert periodically. Detailed above.
Contrary to what others have stated, this is a good thing, and does not fragment the CI. Lets' say ou have 20 Companies, and you delete 1, which constitutes 5% of the data. That entire PageChain which was reasonably contiguous, is now relegated to the FreePageChain, contiguous and intact. To be precise, you have a single point of fragmentation, but not fragmentation in the sense of the normal use of the word. And guess what, if you turn around and perform a mass insert, where do you think that data will go ? That's right the exact same physical location as the Deleted rows. And the FreePageChain moves to the PageChain, extent and page at a time.
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but what is alarming is that you did not know about the demand for CI to be Unique. Sad that the MicroSofties write rubbish, but not why/what each simplistic rule is based on; not the core information. The exact symptom of non-unique CIs is, the table will be very fast immediately after DROP/CREATE CI, and then slow down over time. An good Unique CI will hold its speed, and it would take a year to slow down (2 years on my large, active banking dbs).
4 hours is a very long time for 1 Billion rows (I can recreate a CI on 16 billion rows with a 6-column key in 3 minutes on an enterprise platform). But in any case, that means you have to schedule it as regular weekly or demand maintenance.
why aren't you using the WITH SORTED_DATA option ? Wasn't your data sorted, before the drop ? This option rewrites the CI Non-leaf pages but not the leaf pages (containing the rows). It can only do that if it is confident that the data was sorted. Not using this option rewrites every page, in physical order.
Now, please be kind. Before you ask me twenty questions, read up a little and understand all the issues I have defined here.
I have an app, which cycles through a huge number of records in a database table and performs a number of SQL and .Net operations on records within that database (currently I am using Castle.ActiveRecord on PostgreSQL).
I added some basic btree indexes on a couple of the feilds, and as you would expect, the performance of the SQL operations increased substantially. Wanting to make the most of dbms performance I want to make some better educated choices about what I should index on all my projects.
I understand that there is a detrement to performance when doing inserts (as the database needs to update the index, as well as the data), but what suggestions and best practices should I consider with creating database indexes? How do I best select the feilds/combination of fields for a set of database indexes (rules of thumb)?
Also, how do I best select which index to use as a clustered index? And when it comes to the access method, under what conditions should I use a btree over a hash or a gist or a gin (what are they anyway?).
Some of my rules of thumb:
Index ALL primary keys (I think most RDBMS do this when the table is created).
Index ALL foreign key columns.
Create more indexes ONLY if:
Queries are slow.
You know the data volume is going to increase significantly.
Run statistics when populating a lot of data in tables.
If a query is slow, look at the execution plan and:
If the query for a table only uses a few columns, put all those columns into an index, then you can help the RDBMS to only use the index.
Don't waste resources indexing tiny tables (hundreds of records).
Index multiple columns in order from high cardinality to less. This means: first index the columns with more distinct values, followed by columns with fewer distinct values.
If a query needs to access more than 10% of the data, a full scan is normally better than an index.
Here's a slightly simplistic overview: it's certainly true that there is an overhead to data modifications due to the presence of indexes, but you ought to consider the relative number of reads and writes to the data. In general the number of reads is far higher than the number of writes, and you should take that into account when defining an indexing strategy.
When it comes to which columns to index I'v e always felt that the designer ought to know the business well enough to be able to take a very good first pass at which columns are likely to benefit. Other then that it really comes down to feedback from the programmers, full-scale testing, and system monitoring (preferably with extensive internal metrics on performance to capture long-running operations),
As #David Aldridge mentioned, the majority of databases perform many more reads than they do writes and in addition, appropriate indexes will often be utilised even when performing INSERTS (to determine the correct place to INSERT).
The critical indexes under an unknown production workload are often hard to guess/estimate, and a set of indexes should not be viewed as set once and forget. Indexes should be monitored and altered with changing workloads (that new killer report, for instance).
Nothing beats profiling; if you guess your indexes, you will often miss the really important ones.
As a general rule, if I have little idea how the database will be queried, then I will create indexes on all Foriegn Keys, profile under a workload (think UAT release) and remove those that are not being used, as well as creating important missing indexes.
Also, make sure that a scheduled index maintenance plan is also created.
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.
I'm working on a project with a rather large Oracle database (although my question applies equally well to other databases). We have a web interface which allows users to search on almost any possible combination of fields.
To make these searches go fast, we're adding indexes to the fields and combinations of fields on which we believe users will commonly search. However, since we don't really know how our customers will use this software, it's hard to tell which indexes to create.
Space isn't a concern; we have a 4 terabyte RAID drive of which we are using only a small fraction. However, I'm worried about the possible performance penalties of having too many indexes. Because those indexes need to be updated every time a row is added, deleted, or modified, I imagine it'd be a bad idea to have dozens of indexes on a single table.
So how many indexes is considered too many? 10? 25? 50? Or should I just cover the really, really common and obvious cases and ignore everything else?
It depends on the operations that occur on the table.
If there's lots of SELECTs and very few changes, index all you like.... these will (potentially) speed the SELECT statements up.
If the table is heavily hit by UPDATEs, INSERTs + DELETEs ... these will be very slow with lots of indexes since they all need to be modified each time one of these operations takes place
Having said that, you can clearly add a lot of pointless indexes to a table that won't do anything. Adding B-Tree indexes to a column with 2 distinct values will be pointless since it doesn't add anything in terms of looking the data up. The more unique the values in a column, the more it will benefit from an index.
I usually proceed like this.
Get a log of the real queries run on the data on a typical day.
Add indexes so the most important queries hit the indexes in their execution plan.
Try to avoid indexing fields that have a lot of updates or inserts
After a few indexes, get a new log and repeat.
As with all any optimization, I stop when the requested performance is reached (this obviously implies that point 0. would be getting specific performance requirements).
Everyone else has been giving you great advice. I have an added suggestion for you as you move forward. At some point you have to make a decision as to your best indexing strategy. In the end though, the best PLANNED indexing strategy can still end up creating indexes that don't end up getting used. One strategy that lets you find indexes that aren't used is to monitor index usage. You do this as follows:-
alter index my_index_name monitoring usage;
You can then monitor whether the index is used or not from that point forward by querying v$object_usage. Information on this can be found in the Oracle® Database Administrator's Guide.
Just remember that if you have a warehousing strategy of dropping indexes before updating a table, then recreating them, you will have to set the index up for monitoring again, and you'll lose any monitoring history for that index.
In data warehousing it is very common to have a high number of indexes. I have worked with fact tables having two hundred columns and 190 of them indexed.
Although there is an overhead to this it must be understood in the context that in a data warehouse we generally only insert a row once, we never update it, but it can then participate in thousands of SELECT queries which might benefit from indexing on any of the columns.
For maximum flexibility a data warehouse generally uses single column bitmap indexes except on high cardinality columns, where (compressed) btree indexes can be used.
The overhead on index maintenance is mostly associated with the expense of writing to a great many blocks and the block splits as new rows are added with values that are "in the middle" of existing value ranges for that column. This can be mitigated by partitioning and having the new data loads aligned with the partitioning scheme, and by using direct path inserts.
To address your question more directly, I think it is probably fine to index the obvious at first, but do not be afraid of adding more indexes on if the queries against the table would benefit.
In a paraphrase of Einstein about simplicity, add as many indexes as you need and no more.
Seriously, however, every index you add requires maintenance whenever data is added to the table. On tables that are primarily read only, lots of indexes are a good thing. On tables that are highly dynamic, fewer is better.
My advice is to cover the common and obvious cases and then, as you encounter issues where you need more speed in getting data from specific tables, evaluate and add indices at that point.
Also, it's a good idea to re-evaluate your indexing schemes every few months, just to see if there is anything new that needs indexing or any indices that you've created that aren't being used for anything and should be gotten rid of.
In addition to the points everyone else has raised, the Cost Based Optimizer incurs a cost when creating a plan for an SQL statement if there are more indexes because there are more combinations for it to consider. You can reduce this by correctly using bind variables so that SQL statements stay in the SQL cache. Oracle can then do a soft parse and re-use the plan it found last time.
As always, nothing is simple. If there are skewed columns and histograms involved then this can be a bad idea.
In our web applications we tend to limit the combinations of searches that we allow. Otherwise you would have to test literally every combination for performance to ensure you did not have a lurking problem that someone will find one day. We have also implemented resource limits to stop this causing issues elsewhere in the application should something go wrong.
I made some simple tests on my real project and real MySql database. I already answered in this topic: What is the cost of indexing multiple db columns?
But I think it will be better if I quote it here:
I made some simple tests using my real
project and real MySql database.
My results are: adding average index
(1-3 columns in an index) to a table -
makes inserts slower by 2.1%. So, if
you add 20 indexes, your inserts will
be slower by 40-50%. But your selects
will be 10-100 times faster.
So is it ok to add many indexes? - It
depends :) I gave you my results - You
decide!
Ultimately how many indexes you need depend on the behavior of your applications that ride on top of your database server.
In general the more inserting you do the more painful your indexes become. Each time you do an insert, all the indexes that include that table have to be updated.
Now if your application has a decent amount of reading, or even more so if it's almost all reading, then indexes are the way to go as there will be major performance improvements for very little cost.
There's no static answer in my opinion, this sort of thing falls under 'performance tuning'.
It could be that everything your app does is looked up by a primary key, or it could be the oposite in that queries are done over unristricted combinations of fields and any one in particular could be used at any given time.
Beyond just indexing, there's reogranizing your DB to include calculated search fields, splitting tables, etc - it's really dependant on your load shapes and query parameters, how much/what data 'really' needs to be retruend by a query.
If your entire DB is fronted by stored-procedure facades turning becomes a bit easier, as you don't have to wory about every ad-hoc query. Or you may have a deep understanding of the kind of queries that will hit your DB, and can limit the tuning to those.
For SQL Server I've found the Database Engine Tuning advisor usefull - you set up 'typical' workloads and it can make recommendations about adding/removing indexes and statistics. I'm sure other DBs have similar tools, either 'offical' or third party.
This really is a more theoretical questions than practical. Indexes impact on your performance depends on the hardware you have, the version of Oracle, index types, etc. Yesterday I heard Oracle announced a dedicated storage, made by HP, which is supposed to perform 10 times faster with 11g database.
As for your case, there can be several solutions:
1. Have a large amount of indexes (>20) and rebuild them daily (nightly). This would be especially useful if the table gets thousands of updates/deletes daily.
2. Partition your table (if that applies your data model).
3. Use a separate table for new/updated data, and run a nightly process which combines the data together. This would require a change in your application logic.
4. Switch to IOT (index organized table), if your data support this.
Of course there might be many more solutions for such case. My first suggestion to you, would be to clone the DB to a development environment, and run some stress testing against it.
An index imposes a cost when the underlying table is updated. An index provides a benefit when it is used to spped up a query. For each index, you need to balance the cost against the benefit. How much slower does the query run without the index? How much of a benefit is running faster? Can you or your users tolerate the slow speed when the index is missing?
Can you tolerate the additional time it takes to complete an update?
You need to compare costs and benefits. That's particular to your situation. There's no magic number of indexes that passes the threshold of "too many".
There's also the cost of the space needed to store the index, but you've said that in your situation that's not an issue. The same is true in most situations, given how cheap disk space has become.
If you do mostly reads (and few updates) then there's really no reason not to index everything you'll need to index. If you update often, then you may need to be cautious on how many indexes you have. There's no hard number, but you'll notice when things start to slow down. Make sure your clustered index is the one that makes the most sense based on the data.
One thing you may consider is building indexes to target a standard combination of searches. If column1 is commonly searched, and column2 is often used with it, and column3 is sometimes used with column2 and column1, then an index on column1, column2, and column3 in that order can be used for any of those three circumstances, though it is only one index that has to be maintained.
How many columns are there?
I have always been told to make single-column indexes, not multi-column indexes. So no more indexes than the amount of columns, IMHO.
What it really comes down to is, don't add an index unless you know (and this often means gathering usage statistics) that it will be used far more often than it's updated.
Any index that doesn't meet that criteria will cost you more to rebuild than the performance penalty of not having it in the odd case it got used.
Sql server gives you some good tools that let you see which indexes are actually being used.
This article, http://www.mssqltips.com/tip.asp?tip=1239, gives you some queries that let you get a better insight into how much an index is used, as opposed to how much it is updated.
It is totally based on the columns which are being used in Where Clause.
And as the Thumb of Rule, we must have indexes on Foreign Key Columns to avoid DEADLOCKS.
AWR report should analyze periodically to understand the need of indexes.