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

Question

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

Answer 1

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.

Answer 2

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.

Answer 3

I think the questioner is asking

'why can't I make an index like':

create index index_name
on table_name
(
    *
)

The problems with that have been addressed.

But given it sounds like they are using MS sql server. It's useful to understand that you can include nonkey columns in an index so they the values of those columns are available for retrieval from the index, but not to be used as selection criteria :

create index index_name
on table_name
(
    foreign_key
)
include (a,b,c,d) -- every column except foreign key

I created two tables with a million identical rows

I indexed table A like this

create nonclustered index index_name_A
on A
(
    foreign_key -- this is a guid
)

and table B like this

create nonclustered index index_name_B
on B
(
    foreign_key -- this is a guid
)
include (id,a,b,c,d) -- ( every key except foreign key)

no surprise, table A was slightly faster to insert to.

but when I and ran these this queries

select * from A where foreign_key = @guid
select * from B where foreign_key = @guid

On table A, sql server didn't even use the index, it did a table scan, and complained about a missing index including id,a,b,c,d

On table B, the query was over 50 times faster with much less io

forcing the query on A to use the index didn't make it any faster

select * from A where foreign_key = @guid
select * from A with (index(index_name_A)) where foreign_key = @guid

Answer 4

...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.

Answer 5

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
 etc

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.

Answer 6

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"

Answer 7

I see only long and complicated answers here so I thought I should give the simplest answer possible.

You cannot add an entire table, or all its columns, to an index because that just duplicates the table.

In simple terms, an index is just another table with selected data ordered in the order you normally expect to query it in, and a pointer to the row on disk where the rest of the data lives.

So, a level of indirection exists. You have a partial copy of a table in an preordered manner (both on disk and in RAM, assuming the index is not fragmented), which is faster to query for the columns defined in the index only, while the rest of the columns can be fetched without having to scan the disk for them, because the index contains a reference to the correct position on disk where the rest of the data is for each row.

Answer 8

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.

Answer 9

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