I have a table where Estate Agents can post jobs online.
Generally we expect 2000 entries per month, after a year that 24'000 entries!
Would this considerably slow the database down?
Should I export the data to a file if its older that a year?
If so how would I maintain data integrity
No, 24000 entries in a table is nowadays not considered a large amount of data at all. Of course I am make the assumption that your database is something like SQL Server, MySQL etc.
You would need to ensure that the table had indexes assigned to the relevant fields, e.g. the identity column or any column used regularly in WHERE clauses, as this would ensure that data could still be accessed quickly.
You should also definitely consider a back up schedule regardless of database size.
There's an old no-longer-on-topic question that is probably littered with useful information for you, and will at least serve as a starting point for researching and learning about database performance.
To be blunt... In the realm of "large volumes of data" 2,000 records per month is statistically indistinguishable from 0 records per month. You're not talking about a lot of data. So, unless there are some serious design problems with your database(s) and/or your application(s), you should be fine.
But the fact that you asked the question indicates that you don't know if you have any of these problems. So hopefully this will give you a good place to start. There's no magic bullet. There's no single thing you can do that will always make your database perform better. It depends a lot on how you use the data (how it's organized, whether it's more read-heavy or write-heavy, etc.) as to how you'd optimize it.
(Indeed, you'll want to explicitly avoid the mentality of "magic bullets" in this case. For example, I once worked with someone who was convinced that "adding indexes is how you improve database performance" because he was taught that at some impressionable point in his career. It's... not unilaterally true. And over-indexing or poorly-indexing can lead to dramatic performance problems in a database.)
Does the table have any indexes or a primary key? 24000 records is not much data but it doesn't cost anything to use indexes (correctly) to increase performance.
What is the table structure and which columns are you most likely to query the table on?
Related
We have a mid-size SQL Server based application that has no indexes defined. Not even on the the identity columns. I suggested to our moderately expensive application consultant that perhaps we might get better performance (particularly as our database grows) by creating some indexes on appropriate fields, and he said:
"Indexes will significantly impact other areas of the application and customers should not create them under any circumstances."
Anybody ever heard of anything like this? Are there ever circumstances where one should not create any indexes? I can see nothing special about this app - it's got int identity columns, then lots of string columns, bunch of relational tables but nothing special or weird that I can see.
Thanks!
[EDIT: the identity columns are not using "identity specification", they seem to be set by the program, looking at the database with Management Studio, I can find NO indexes...]
FOLLOWUP: At a conference I asked the CEO (and chief architect) of the company producing this product about this, his response was that they felt for small to midsize deployments, the overhead associated with maintaining indexes would have more of a negative to overall user experience (the application does a lot of writes) than the benefits of the indexes would offset, but for large databases, they do create indexes. The tech support guy was just overzealous and very unhelpful with his answer. Mystery solved.
Hire me and I'll create the indexes for you. 14 years' Sybase/SQL Server experience tells me to create those !darn! indexes. Unless your table has less than 500 records each.
My idea is that an index hash node is roughly sized to 1000.
The other thing you need to look out for is whether your consultant has normalized the tables. Perhaps, the table has 500 fields/columns, containing more than one conceptual entity or a whole dozen of conceptual entities. And that could be why he is nervous about creating indexes, because if there are 12 conceptual entities in the table there would be at least 12 set of indexes - in which case, he is absolutely true - under no circumstances ... blah blah.
However, if he indeed does have 500 columns or detectably multiple conceptual entities per table - he is a very very lousy data design engineer. In all my years working with more experienced data engineers, our tables rarely exceed 20 columns. 5 on the low side, 10 on the average. Sometimes for performance' sake we do allow mixing two entities in a table, or horizontalizing row occurrences into columns of a table.
When you look at the table design you can with an untrained eye see Product, Project, BuildSheet, FloorPlan, Equipment, etc records all rolled into one long row. You cannot mix all these entities together into one table.
That is the only reason I know why he could advise you against having indexes. If he is doing that, you should know that he is fraudulently representing his data design skills to your company and you should immediately drop him from your weekly contractual expenses.
OK, after reading larry's post - I agree with him too.
There is such a thing as over-indexing, especially in INSERT and UPDATE heavy applications with very large tables. So the answer to the question in your title is yes, it can sometimes be a bad idea to add indexes.
That's quite a different question from the one you ask in the body of your question, which is "Is it ever normal to have NO indexes in a SQL Server database". The answer is that unless you're using the database as a "write-only" system, in which data is added but only read after being bulk extracted and transformed into a another data store, it's exceedingly unusual not to have some indexes in the database.
Your consultant's statement is odd enough to make me believe that you may have left some important information out of your description. If not, I'd say he's nuts.
Do you have the disk space to spare? I've seen cases where the indexes weighed more than the table.
However, No indexes exist whatsoever! There can't be a case for that except for when all read operations need the entire table.
Columns with key constraints will have an implicit index on them anyway. So if you're always selecting by the primary key, then there's no point adding more indexes. If you're selecting by other criteria, then it makes sense to add indexes on those columns that you're querying on.
It also depends on how insert-heavy your data is. If you're inserting more often than you're querying, then the overhead of keeping the indexes up to date can make your inserts slower.
But to say you "should not create [indexes] under any circumstances" is a bit much.
What I would recommend is that you run the SQL Server Profiler tool with some your queries. This tool will recommend which indexes to add that will have the biggest effect on performance.
In most run-of-the-mill applications, the impact of indexes on insertion performance is a bit of non-issue. You're usually better off creating the index and if insertion performance drops dramatically (which it probably won't) you can try something else. Obviously there are some exceptions, where you should be more careful, like tables that are used for logging for instance.
As mentioned, disk space can be an issue.
Creating irrelevant indexes (e.g. duplicates) will also waste microseconds and occasionally result in a bad query execution plan.
The other problem I've seen is with strangely code third-party applications that generate parts of the database at runtime, and can delete or choke on indexes that they don't know about.
In the vast majority of cases though, a carefully chosen index will only be a benefit.
Not having indexes on id columns sounds really unusual and I would find any justification for not including them to smell very fishy.
You should be aware that if you are doing a high volume of commits to the database, adding more indexes will affect the speed of insertion, but no index on id? Wow.
It would be good to get better justification of exactly how adding extra indexes might cause problems though.
the more indexes you have the slower data inserts and modifications will be. Make sure that you add indexes when appropriate and write queries that can take advantage of those indexes, also if the selectivity leve of your index is low, it will not be used effectively
I would say that if your server is having troubles with CPU time, indexes could be a solution. If you are querying tables without indexes, the server will need a lot more resources and if tables are having millions of records, it can become a serious problem. I recently cooled down a CPU from 80-90% all the time to 10-20% just by putting the right indexes.
If using MS SQL, you could check the activity monitor to see what queries are expensive and create indexes based on the where clauses or joins.
Then at the recent expensive queries:
You can then right click and check the complete query!
For a few different reasons one of my projects is hosted on a shared hosting server
and developed in asp.Net/C# with access databases (Not a choice so don't laugh at this limitation, it's not from me).
Most of my queries are on the last few records of the databases they are querying.
My question is in 2 parts:
1- Is the order of the records in the database only visual or is there an actual difference internally. More specifically, the reason I ask is that the way it is currently designed all records (for all databases in this project) are ordered by a row identifying key (which is an auto number field) ascending but since over 80% of my queries will be querying fields that should be towards the end of the table would it increase the query performance if I set the table to showing the most recent record at the top instead of at the end?
2- Are there any other performance tuning that can be done to help with access tables?
"Access" and "performance" is an euphemism but the database type wasn't a choice
and so far it hasn't proven to be a big problem but if I can help the performance
I would sure like to do whatever I can.
Thanks.
Edit:
No, I'm not currently experiencing issues with my current setup, just trying to look forward and optimize everything.
Yes, I do have indexes and have a primary key (automatically indexes) on the unique record identifier for each of my tables. I definitely should have mentioned that.
You're all saying the same thing, I'm already doing all that can be done for access performance. I'll give the question "accepted answer" to the one that was the fastest to answer.
Thanks everyone.
As far as I know...
1 - That change would just be visual. There'd be no impact.
2 - Make sure your fields are indexed. If the fields you are querying on are unique, then make sure you make the fields a unique key.
Yes there is an actual order to the records in the database. Setting the defaults on the table preference isn't going to change that.
I would ensure there are indexes on all your where clause columns. This is a rule of thumb. It would rarely be optimal, but you would have to do workload testing against different database setups to prove the most optimal solution.
I work daily with legacy access system that can be reasonably fast with concurrent users, but only for smallish number of users.
You can use indexes on the fields you search for (aren't you already?).
http://www.google.com.br/search?q=microsoft+access+indexes
The order is most likely not the problem. Besides, I don't think you can really change it in Access anyway.
What is important is how you are accessing those records. Are you accessing them directly by the record ID? Whatever criteria you use to find the data you need, you should have an appropriate index defined.
By default, there will only be an index on the primary key column, so if you're using any other column (or combination of columns), you should create one or more indexes.
Don't just create an index on every column though. More indexes means Access will need to maintain them all when a new record is inserted or updated, which makes it slower.
Here's one article about indexes in Access.
Have a look at the field or fields you're using to query your data and make sure you have an index on those fields. If it's the same as SQL server you won't need to include the primary key in the index (assuming it's clustering on this) as it's included by default.
If you're running queries on a small sub-set of fields you could get your index to be a 'covering' index by including all the fields required, there's a space trade-off here, so I really only recommend it for 5 fields or less, depending on your requirements.
Are you actually experiencing a performance problem now or is this just a general optimization question? Also from your post it sounds like you are talking about a db with 1 table, is that accurate? If you are already experiencing a problem and you are dealing with concurrent access, some answers might be:
1) indexing fields used in where clauses (mentioned already)
2) Splitting tables. For example, if only 80% of your table rows are not accessed (as implied in your question), create an archive table for older records. Or, if the bulk of your performance hits are from reads (complicated reports) and you don't want to impinge on performance for people adding records, create a separate reporting table structure and query off of that.
3) If this is a reporting scenario, all queries are similar or the same, concurrency is somewhat high (very relative number given Access) and the data is not extremely volatile, consider persisting the data to a file that can be periodically updated, thus offloading the querying workload from the Access engine.
In regard to table order, Jet/ACE writes the actual table date in PK order. If you want a different order, change the PK.
But this oughtn't be a significant issue.
Indexes on the fields other than the PK that you sort on should make sorting pretty fast. I have apps with 100s of thousands of records that return subsets of data in non-PK sorted order more-or-less instantaneously.
I think you're engaging in "premature optimization," worrying about something before you actually have an issue.
The only circumstances in which I think you'd have a performance problem is if you had a table of 100s of thousands of records and you were trying to present the whole thing to the end user. That would be a phenomenally user-hostile thing to do, so I don't think it's something you should be worrying about.
If it really is a concern, then you should consider changing your PK from the Autonumber to a natural key (though that can be problematic, given real-world data and the prohibition on non-Null fields in compound unique indexes).
I've got a couple of things to add that I didn't notice being mentioned here, at least not explicitly:
Field Length, create your fields as large as you'll need them but don't go over - for instance, if you have a number field and the value will never be over 1000 (for the sake of argument) then don't type it as a Long Integer, something smaller like Integer would be more appropriate, or use a single instead of a double for decimal numbers, etc. By the same token, if you have a text field that won't have more than 50 chars, don't set it up for 255, etc, etc. Sounds obvious, but it's done, often times with the idea that "I might need that space in the future" and your app suffers in the mean time.
Not to beat the indexing thing to death...but, tables that you're joining together in your queries should have relationships established, this will create indexes on the foreign keys which greatly increases the performance of table joins (NOTE: Double check any foreign keys to make sure they did indeed get indexed, I've seen cases where they haven't been - so apparently a relationship doesn't explicitly mean that the proper indexes have been created)
Apparently compacting your DB regularly can help performance as well, this reduces internal fragmentation of the file and can speed things up that way.
Access actually has a Performance Analyzer, under tools Analyze > Performance, it might be worth running it on your tables & queries at least to see what it comes up with. The table analyzer (available from the same menu) can help you split out tables with alot of redundant data, obviously, use with caution - but it's could be helpful.
This link has a bunch of stuff on access performance optimization on pretty much all aspects of the database, tables, queries, forms, etc - it'd be worth checking out for sure.
http://office.microsoft.com/en-us/access/hp051874531033.aspx
To understand the answers here it is useful to consider how access works, in an un-indexed table there is unlikely to be any value in organising the data so that recently accessed records are at the end. Indeed by the virtue of the fact that Access / the JET engine is an ISAM database it's the other way around. (http://en.wikipedia.org/wiki/ISAM) That's rather moot however as I would never suggest putting frequently accessed values at the top of a table, it is best as others have said to rely on useful indexes.
I work in a company that uses single table Access database for its outbound cms, which I moved to a SQL server based system. There's a data list table (not normalized) and a calls table. This has about one update per second currently. All call outcomes along with date, time, and agent id are stored in the calls table. Agents have a predefined set of records that they will call each day (this comprises records from various data lists sorted to give an even spread throughout their set). Note a data list record is called once per day.
In order to ensure speed, live updates to this system are stored in a duplicate of the calls table fields in the data list table. These are then copied to the calls table in a batch process at the end of the day.
The reason for this is not obviously the speed at which a new record could be added to the calls table live, but when the user app is closed/opened and loads the user's data set again I need to check which records have not been called today - I would need to run a stored proc on the server that picked the last most call from the calls table and check if its calldate didn't match today's date. I believe a more expensive query than checking if a field in the data list table is NULL.
With this setup I only run the expensive query at the end of each day.
There are many pitfalls in this design, the main limitation is my inexperience. This is my first SQL server system. It's pretty critical, and I had to ensure it would work and I could easily dump data back to access db during a live failure. It has worked for 11 months now (and no live failure, less downtime than the old system).
I have created pretty well normalized databases for other things (with far fewer users), but I'm hesitant to implement this for the calling database.
Specifically, I would like to know your thoughts on whether the duplication of the calls fields in the data list table is necessary in my current setup or whether I should be able to use the calls table. Please try and answer this from my perspective. I know you DBAs may be cringing!
Redesigning an already working Database may become the major flaw here. Rather try to optimize what you have got running currently instead if starting from scratch. Think of indices, referential integrity, key assigning methods, proper usage of joins and the like.
In fact, have a look here:
Database development mistakes made by application developers
This outlines some very useful pointers.
The thing the "Normalisation Nazis" out there forget is that database design typically has two stages, the "Logical Design" and the "Physical Design". The logical design is for normalisation, and the physical design is for "now lets get the thing working", considering among other things the benefits of normalisation vs. the benefits of breaking nomalisation.
The classic example is an Order table and an Order-Detail table and the Order header table has "total price" where that value was derived from the Order-Detail and related tables. Having total price on Order in this case still make sense, but it breaks normalisation.
A normalised database is meant to give your database high maintainability and flexibility. But optimising for performance is one of the considerations that physical design considers. Look at reporting databases for example. And don't get me started about storing time-series data.
Ask yourself, has my maintainability or flexibility been significantly hindered by this decision? Does it cause me lots of code changes or data redesign when I change something? If not, and you're happy that your design is working as required, then I wouldn't worry.
I think whether to normalize it depends on how much you can do, and what may be needed.
For example, as Ian mentioned, it has been working for so long, is there some features they want to add that will impact the database schema?
If not, then just leave it as it is, but, if you need to add new features that change the database, you may want to see about normalizing it at that point.
You wouldn't need to call a stored procedure, you should be able to use a select statement to get the max(id) by the user id, or the max(id) in the table, depending on what you need to do.
Before deciding to normalize, or to make any major architectural changes, first look at why you are doing it. If you are doing it just because you think it needs to be done, then stop, and see if there is anything else you can do, perhaps add unit tests, so you can get some times for how long operations take. Numbers are good before making major changes, to see if there is any real benefit.
I would ask you to be a little more clear about the specific dilemma you face. If your system has worked so well for 11 months, what makes you think it needs any change?
I'm not sure you are aware of the fact that "Database design fundamentals" might relate to "logical database design fundamentals" as well as "physical database design fundamentals", nor whether you are aware of the difference.
Logical database design fundamentals should not (and actually cannot) be "sacrificed" for speed precisely because speed is only determined by physical design choices, the prime desision factor in which is precisely speed and performance.
Are there any hard limits on the number of rows in a table in a sql server table? I am under the impression the only limit is based around physical storage.
At what point does performance significantly degrade, if at all, on tables with and without an index. Are there any common practicies for very large tables?
To give a little domain knowledge, we are considering usage of an Audit table which will log changes to fields for all tables in a database and are wondering what types of walls we might run up against.
You are correct that the number of rows is limited by your available storage.
It is hard to give any numbers as it very much depends on your server hardware, configuration, and how efficient your queries are.
For example, a simple select statement will run faster and show less degradation than a Full Text or Proximity search as the number of rows grows.
BrianV is correct. It's hard to give a rule because it varies drastically based on how you will use the table, how it's indexed, the actual columns in the table, etc.
As to common practices... for very large tables you might consider partitioning. This could be especially useful if you find that for your log you typically only care about changes in the last 1 month (or 1 day, 1 week, 1 year, whatever). You could then archive off older portions of the data so that it's available if absolutely needed, but won't be in the way since you will almost never actually need it.
Another thing to consider is to have a separate change log table for each of your actual tables if you aren't already planning to do that. Using a single log table makes it VERY difficult to work with. You usually have to log the information in a free-form text field which is difficult to query and process against. Also, it's difficult to look at data if you have a row for each column that has been changed because you have to do a lot of joins to look at changes that occur at the same time side by side.
In addition to all the above, which are great reccomendations I thought I would give a bit more context on the index/performance point.
As mentioned above, it is not possible to give a performance number as depending on the quality and number of your indexes the performance will differ. It is also dependent on what operations you want to optimize. Do you need to optimize inserts? or are you more concerned about query response?
If you are truly concerned about insert speed, partitioning, as well a VERY careful index consideration is going to be key.
The separate table reccomendation of Tom H is also a good idea.
With audit tables another approach is to archive the data once a month (or week depending on how much data you put in it) or so. That way if you need to recreate some recent changes with the fresh data, it can be done against smaller tables and thus more quickly (recovering from audit tables is almost always an urgent task I've found!). But you still have the data avialable in case you ever need to go back farther in time.
I want to maintain last ten years of stock market data in a single table. Certain analysis need only data of the last one month data. When I do this short term analysis it takes a long time to complete the operation.
To overcome this I created another table to hold current year data alone. When I perform the analysis from this table it 20 times faster than the previous one.
Now my question is:
Is this the right way to have a separate table for this kind of problem. (Or we use separate database instead of table)
If I have separate table Is there any way to update the secondary table automatically.
Or we can use anything like dematerialized view or something like that to gain performance.
Note: I'm using Postgresql database.
You want table partitioning. This will automatically split the data between multiple tables, and will in general work much better than doing it by hand.
I'm working on near the exact same issue.
Table partitioning is definitely the way to go here. I would segment by more than year though, it would give you a greater degree of control. Just set up your partitions and then constrain them by months (or some other date). In your postgresql.conf you'll need to turn constraint_exclusion=on to really get the benefit. The additional benefit here is that you can only index the exact tables you really want to pull information from. If you're batch importing large amounts of data into this table, you may get slightly better results a Rule vs a Trigger and for partitioning, I find rules easier to maintain. But for smaller transactions, triggers are much faster. The postgresql manual has a great section on partitioning via inheritance.
I'm not sure about PostgreSQL, but I can confirm that you are on the right track. When dealing with large data volumes partitioning data into multiple tables and then using some kind of query generator to build your queries is absolutely the right way to go. This approach is well established in Data Warehousing, and specifically in your case stock market data.
However, I'm curious why do you need to update your historical data? If you're dealing with stock splits, it's common to implement that using a seperate multiplier table that is used in conjunction with the raw historical data to give an accurate price/share.
it is perfectly sensible to use separate table for historical records. It's much more problematic with separate database, as it's not simple to write cross-database queries
automatic updates - it's a tool for cronjob
you can use partial indexes for such things - they do wonderful job
Frankly, you should check your execution plans and try fixing your queries or indexing before taking more radical steps.
Indexing comes at very little cost (unless you do a lot of insertions) and your existing code will be faster (if you index properly) without modifying it.
Other measures such as partioning come after that...