Why can't I simply add an index that includes all columns?

I have a table in SQL Server database which I want to be able to search and retrieve data from as fast as possible. I don't care about how long time it takes to insert into the table, I am only interested in the speed at which I can get data.

The problem is the table is accessed with 20 or more different types of queries. This makes it a tedious task to add an index specially designed for each query. I'm considering instead simply adding an index that includes ALL columns of the table. It's not something you would normally do in "good" database design, so I'm assuming there is some good reason why I shouldn't do it.

Can anyone tell me why I shouldn't do this?

UPDATE: I forgot to mention, I also don't care about the size of my database. It's OK that it means my database size will grow larger than it needed to


First of all, an index in SQL Server can only have at most 900 bytes in its index entry. That alone makes it impossible to have an index with all columns.

Most of all: such an index makes no sense at all. What are you trying to achieve??

Consider this: if you have an index on (LastName, FirstName, Street, City), that index will not be able to be used to speed up queries on

  • FirstName alone
  • City
  • Street

That index would be useful for searches on

  • (LastName), or
  • (LastName, FirstName), or
  • (LastName, FirstName, Street), or
  • (LastName, FirstName, Street, City)

but really nothing else - certainly not if you search for just Street or just City!

The order of the columns in your index makes quite a difference, and the query optimizer can't just use any column somewhere in the middle of an index for lookups.

Consider your phone book: it's order probably by LastName, FirstName, maybe Street. So does that indexing help you find all "Joe's" in your city? All people living on "Main Street" ?? No - you can lookup by LastName first - then you get more specific inside that set of data. Just having an index over everything doesn't help speed up searching for all columns at all.

If you want to be able to search by Street - you need to add a separate index on (Street) (and possibly another column or two that make sense).

If you want to be able to search by Occupation or whatever else - you need another specific index for that.

Just because your column exists in an index doesn't mean that'll speed up all searches for that column!

The main rule is: use as few indices as possible - too many indices can be even worse for a system than having no indices at all.... build your system, monitor its performance, and find those queries that cost the most - then optimize these, e.g. by adding indices.

Don't just blindly index every column just because you can - this is a guarantee for lousy system performance - any index also requires maintenance and upkeep, so the more indices you have, the more your INSERT, UPDATE and DELETE operations will suffer (get slower) since all those indices need to be updated.

You are having a fundamental misunderstanding how indexes work.

Read this explanation "how multi-column indexes work".

The next question you might have is why not creating one index per column--but that's also a dead-end if you try to reach top select performance.

You might feel that it is a tedious task, but I would say it's a required task to index carefully. Sloppy indexing strikes back, as in this example.

Note: I am strongly convinced that proper indexing pays off and I know that many people are having the very same questions you have. That's why I'm writing a the a free book about it. The links above refer the pages that might help you to answer your question. However, you might also want to read it from the beginning.

I'm considering instead simply adding an index that includes ALL columns of the table.

This is always a bad idea. Indexes in database is not some sort of pixie dust that works magically. You have to analyze your queries and according to what and how is being queried - append indexes.

It is not as simple as "add everything to index and have a nap"

...if you add an index that contains all columns, and a query was actually able to use that index, it would scan it in the order of the primary key. Which means hitting nearly every record. Average search time would be O(n/2).. the same as hitting the actual database.

You need to read a bit lot about indexes.

It might help if you consider an index on a table to be a bit like a Dictionary in C#.

var nameIndex = new Dictionary<String, List<int>>();

That means that the name column is indexed, and will return a list of primary keys.

var nameOccupationIndex = new Dictionary<String, List<Dictionary<String, List<int>>>>();

That means that the name column + occupation columns are indexed. Now imagine the index contained 10 different columns, nested so far deep it contains every single row in your table.

This isn't exactly how it works mind you. But it should give you an idea of how indexes could work if implemented in C#. What you need to do is create indexes based on one or two keys that are queried on extensively, so that the index is more useful than scanning the entire table.

If this is a data warehouse type operation where queries are highly optimized for READ queries, and if you have 20 ways of dissecting the data, e.g.

WHERE clause involves..

 Q1: status, type, customer
 Q2: price, customer, band
 Q3: sale_month, band, type, status
 Q4: customer

And you absolutely have plenty of fast storage space to burn, then by all means create an index for EVERY single column, separately. So a 20-column table will have 20 indexes, one for each individual column. I could probably say to ignore bit columns or low cardinality columns, but since we're going so far, why bother (with that admonition). They will just sit there and churn the WRITE time, but if you don't care about that part of the picture, then we're all good.

Analyze your 20 queries, and if you have hot queries (the hottest ones) that still won't go any faster, plan it using SSMS (press Ctrl-L) with one query in the query window. It will tell you what index can help that queries - just create it; create them all, fully remembering that this adds again to the write cost, backup file size, db maintenance time etc.

1) size, an index essentially builds a copy of the data in that column some easily searchable structure, like a binary tree (I don't know SQL Server specifcs). 2) You mentioned speed, index structures are slower to add to.

That index would just be identical to your table (possibly sorted in another order). It won't speed up your queries.

Need Your Help

Syntax Highlighting with Pygments is failing via Liquid Templates String Error

python markdown jekyll liquid pygments

I'm using Jekyll to convert my markdown and Pygments for syntax highlighting.