How many indexes on a table

Rather than spending hours messing around trying to work it out, it'll be worth some hours of your time taking the course. Far too often, developers are on the road with wild ideas about what is right or wrong. Often I notice a kind of over-index anxiety. In the end, it is always about managing risks like "too slow queries" or "not to harm the workload with blocking issues. If you need this particular order of data, then you have to create and maintain them.

Another question is: what is the implication of not having a particular index. So a plan that shows many key lookup executes as very expensive really is not that expensive. And the query optimized switches from key lookup to scan far too soon again, when your data is in memory. So a single column key that is selective is not that bad. And: consider leaving out frequently updated columns from the include list of indexes on the understanding that the key lookup really is not that expensive.

Hi Joe, whenever I see that sort of overhead stated, the assumption is as I mentioned in the blog post, that the row is being updated with a lookup by the primary key. That's far from always being the case. As for single column indexes, I see people create many of those, and they're almost always unused. In that case, they really are just overhead. For example, while it might be helpful to have an index on CustomerID in an Orders table and I'd always start with one there to support the foreign key , invariably that's not a great index.

When adding another two covering indexes, we are doing about 4 times the original amount of writes. There are some discrepancies in the amount of writes, but this is due to the fact that to execute some of the queries we needed to spill to TEMPDB.

This gave a larger amount of writes than the amount of indexes increased. After multiple tests we can see that we will need 4 times the amount of writes purely for the indexes. When inserting data, we have seen that while inserting into a heap table we have an average of about 1 second, when adding a clustered index this increased to an average of seconds.

When adding 1 covering index this increased to seconds, and with two additional covering indexes the amount of time exploded to a whopping 45 — 50 seconds to insert the same workload.

After inserting When adding the clustered index, this amount stays exactly the same. When adding 1 covering index, this doubled, which means we are now keeping 2 copies of the data inside the memory. When adding the 2 additional covering indexes, we see that we are keeping the same data 4 times inside our memory.

We should careful when adding additional indexes. We want to be able to get all items out of our cache, which will be in nanoseconds instead of milliseconds when retrieving data from disk. So we have to keep in mind that every index that we add might take additional space inside your cache, removing other objects out of your cache and slowing them down. Also see dba. Add a comment. Active Oldest Votes. Your load profile is the most important factor in answering this question.

How do you know you have too many indexes? Improve this answer. Community Bot 1. Nick Chammas Nick Chammas Nilesh Thakkar 5 5 bronze badges. May I suggest to change the two occurences of " to " to " too ", since I can't edit them as my edit would need to change 6 characters minimum? Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. If you thought that primary keys have to be clustered indexes, think again. It is interesting that SQL Server did not recognize that there is already a covering clustered index and use that one.

Before we added the primary key constraint, it was possible and permissible to add new customers with the same customer IDs as existing customers. Go ahead, try it! Now that the PK is in place, though, that is no longer possible. Although there can be only one primary key, there can be other keys, if other combinations of columns are truly unique.

Creating them uses similar syntax:. Primary keys are necessary to make a table conform to relational theory. In practice, they are highly useful as are unique keys for referential integrity and a good way to get the database to check your assumptions about incoming data. By default, SQL Server creates a clustered index when you create a new table with a primary key:. While a primary key needs to be backed by an index to implement the constraint, the index does not need to be clustered, as we saw above.

Furthermore, the goals of primary keys and clustered indexes may not be the same. Fundamentally, a primary key constraint enables SQL Server to maintain the important property that a table may not have duplicate rows. In fact, unique constraints do exactly the same thing. Because they are backed by indexes, keys are also helpful for searches, since. On the other hand, clustered indexes can provide a performance advantage when reading the table in index order. This allows SQL Server to better use read ahead reads, which are asymptotically faster than page-by-page reads.

Also, a clustered index does not require uniqueness. If two or more rows have the same clustered index key, a uniqueifier is added to ensure that all rows in the index are unique. The point here is to carefully consider which arrangement is best for a new table. Consult with business users about how the table will be used. Remember that most reporting is sequential in nature. Choose your indexing accordingly, then test it.

Use real workloads and see if actual usage is still a good match for the indexing scheme. If not, adjust it to suit. Sometimes, a message will be included with the execution plan that an index is missing. For example, if I remove the indexes from the Customer table and try a search by CustomerID, the resulting plan looks like this:. The text in green, above, is just such a message. Basically, SQL Server is saying that if there were an index on the CustomerID column, the cost of the overall query could be reduced by That would reduce the cost to almost nothing.

Instead of a table scan, it could use an index seek operation. The question then becomes, should you always implement a missing index? Is this a once-a-year query that runs in 10 minutes without the index?

Perhaps you can leave that missing index alone. Is it a query that gets executed thousands of times a second from a busy e-commerce server? Probably you should implement the recommendation! You need to think it through and understand the usage patterns and the cost of an index before you do anything.

Come to think about it…. There is actually advice out in the wild stating that you should just index every column in your table so that no execution plan will ever have a missing index. Is this good advice? Once again, it depends.

Data warehouse databases often have a calendar table. Such a table is static. Often the primary key and clustered index is an integer or date column with the date matching the other columns in the row. This table never or rarely changes.