SQL Server Performance Tuning

How to Optimize Your Server's HardwareWhen it comes time to blame poor application performance on something, server hardware gets a disproportionate amount of blame. What is ironic, is that in most cases the hardware is not the main cause of the problem. In fact, server hardware plays a much smaller role than most people think when it comes to SQL Server-based application performance and scalability.
The reason for this is that most slow applications are slow because of poor up front design, not because of slow hardware. The reason hardware is often blamed is because performance problems often don't show themselves until after the application is rolled out. And since the application's design can't be changed at this time, about the only thing you can try to help boost performance is to throw hardware at it. While hardware can help, it usually doesn't fully resolve the problem, and this is why hardware is often blamed for slow performance. While hardware can sometimes be an issue, most likely it is not.
In order to prevent your server hardware from being a drag on your SQL Server-based application (which it can if it is inappropriately selected or configured), let's take a brief look at some of the most common hardware selection and tuning issues.
Selecting HardwareSelecting the optimum hardware for your SQL Server-based application depends on a variety of factors, such as the size of the database, the number of users, how the database is used (OLTP or OLAP), and others. While there is no sure-fire formula for sizing server hardware, the best way to get a feel for sizing is to test your application early in the development stage. Ah, testing is mentioned again. That's right. While many experienced DBAs can probably give you a good estimate on the optimum hardware you need, only through realistic testing will you know for sure what hardware is required to meet your application's needs.
When is comes to server hardware, here are some things to keep in mind:
CPU: Always purchase a server with the ability to expand its number of CPUs. For example, if testing indicates that a single CPU server will be adequate, purchase a server with at least room for two CPUs, even if you only use one of the slots. The same goes for larger servers with four or more CPUs. Always leave room for growth.
Memory: This is probably the most significant piece of hardware that affects SQL Server's performance. Ideally, your entire database should fit into RAM. Unfortunately, this is not often possible. At the very minimum, try to get enough RAM to hold the largest table you expect to have, and if you can afford it, get all the RAM your server can handle, which is often 2GB or more. There is no such thing as too much RAM.
I/O Subsystem: After RAM, the I/O subsystem is the most important piece of hardware to affect SQL Server's performance. At the very minimum, purchase hardware-based RAID for your databases. As a rule of thumb, you will to purchase more, smaller drives, not fewer, larger drives in your array. The more disks that are in an array, the faster I/O will be.
Network Connection: At the server, have at least one 100Mbs network card, and it should be connected to a switch. Ideally, you should have two network cards in the server connected to a switch in full-duplex mode.
Tuning the ServerEven the most expensive server hardware won't perform well if it is not configured and tuned correctly. I have seen many hardware-related performance problems caused as the result of not using Microsoft NT Server approved hardware and drivers. Some of these types of hardware performance-related issues are very difficult to trace and resolve. Ideally, ensure that you hardware, including NT, is correctly installed and configured by a competent technician. Then test your application under controlled conditions to test for potential performance issues before it is used in production.
Your operating system must also be configured correctly. This includes many things, too many to describe here. Just as with the hardware, ensure that the operating system is properly configured and tested before it is put into production.
For best performance on a server, SQL Server should be the only application running on the server, other than management utilities. Don't try to save a few bucks by putting your IIS or MTS server on the same server as SQL Server. Not only does this hurt SQL Server's performance, but it also makes it more difficult to performance tune and troubleshoot SQL Server.
How to Optimize SQL Server's Configuration Settings

Another common misconception about tuning SQL Server is that you must fine-tune its various configuration settings in order to get optimum performance. While there was some truth to this in earlier versions of SQL, this is no longer much of an issue, except on the very largest and busiest of servers.
For the most part, SQL Server is self-tuning. What does this mean? It means that SQL Server observes what is running on itself, and automatically makes internal adjustments which, for the most part, keep SQL Server running as optimally as possible given the tasks at hand and the given hardware.
When you perform performance testing on SQL Server, keep in mind that SQL Server can take some time before it adjusts itself optimally. In other words, the performance you get immediately after starting the SQL Server service, and the performance you get a couple of hours later after a typical workload has been running, can be different. Always perform your testing after SQL Server has had a chance to adjust itself to your workload.
There are 36 SQL Server configuration options that can be changed using either the Enterprise Manager or the sp_configure stored procedure. Unless you have a lot of experience tuning SQL Server, I don't recommend you change any of SQL Server's settings. As a novice, you may make a change that could in fact reduce performance. This is because when you change a setting, you are "hard-coding" the setting from then on. SQL Server has the ability to change its setting on the fly, based on the current workload. But once you "hard-code" a setting, you partially remove SQL Server's ability to self-tune itself.
If after serious consideration you feel that making a change to one or more SQL Server configuration settings can boost performance in your particular environment, then you will want to proceed slowly and cautiously. Before you make the setting change, you will first want to get a good baseline on the SQL Server's performance, under a typical workload, using a tool such as Performance Monitor (discussed later). Then make only one change at a time. Never make more than one change at a time, because if you do, you won't know which change, if any of them, made a difference.
Once the one change is made, again measure SQL Server's performance under the same workload to see if performance was actually boosted. If it wasn't, which will often be the case, then change back to the default setting. If there was a performance boost, then continue to check to see if the boost in performance continues under other workloads the server experiences over time. Your later testing may show that your change helps some workloads, but hinders others. This is why changing most configuration settings is not recommended.
In any event, if your application is suffering from a performance-related issue, the odds of a configuration change resolving it are quite low.
How to Optimize Your Application's Design

If you are using an n-tier design for your application, and who isn't for most large-scale applications these days, SQL Server is just one part of a larger application. And perhaps more important than you realize, how your implement your n-tier design affects your application's performance more than SQL Server itself. Unfortunately, SQL Server often gets more of the blame for poor performance than the application design, even when it is usually the application's design that is causing most of the performance problems. What I hope to do here is offer a few suggestions that may aide you in your application design, helping to prevent SQL Server from getting all the blame for poor performance. So let's start.
One of the first steps you must decide when designing an n-tier application is to select the logical and physical design. Of the two, the physical design is where most of the mistakes are made when it comes to performance. This is because this is where the theory (based on the logical design) has to be implemented in the real world. And just like anything else, you have many choices to make. And many of these choices don't lend themselves to scalability or high performance.
For example, do you want to implement a physical two-tier implementation with fat clients, a physical two-tier implementation with a fat server, a physical three-tier implementation, an Internet implementation, or some other implementation? Once you decide this question, then you must ask yourself, what development language will be used, what browser, will you use Microsoft Transaction Server (MTS), will you use Microsoft Message Queue Server (MSMQ), and on and on.
Each of these many decisions can and will affect performance and scalability. Because there are so many options, it is again important to test potential designs early in the design stage, using rapid prototyping, to see which implementation will best meet your user's needs.
More specifically, as you design your physical implementation, try to follow these general recommendations to help ensure scalability and optimal performance in your application:
Perform as many data-centered tasks as possible on SQL Server in the form of stored procedures. Avoid manipulating data at the presentation and business services tiers.
Don't maintain state (don't store data from the database) in the business services tier. Maintain state in the database as much as possible
Don't create complex or deep object hierarchies. The creation and use of complex classes or a large number of objects used to model complex business rules can be resource intensive and reduce the performance and scalability of your application. This is because the memory allocation when creating and freeing these objects is costly.
Consider designing the application to take advantage of database connection pooling and object pooling using Microsoft Transaction Server (MTS). MTS allows both database connections and objects to be pooled, greatly increasing the overall performance and scalability of your application.
If your application runs queries against SQL Server that by nature are long, design the application to be able to run queries asynchronously. This way, one query does not have to wait for the next before it can run. One way to build in this functionality into your n-tier application is to use the Microsoft Message Queue Server (MSMQ).
While following these suggestions won't guarantee a scalable and fast performing application, they are a good first start.
How to Optimize Your Database's DesignLike application design, database design is very critical to the scalability and performance of your SQL Server applications. And also like application design, if you don't do a good job in the first place, it is very hard and expensive to make changes after your application has gone into production. Here are some key things to keep in mind when designing SQL Server databases for scalability and performance.
As always, you will want to test your design as early as possible using realistic data. This means you will need to develop prototype databases with sample data, and test the design using the type of activity you expect to see in the database once production starts.
One of the first design decisions you must make is whether the database will be used for OLTP or OLAP. Notice that I said "or". One of the biggest mistakes you can make when designing a database is to try to meet the needs of both OLTP and OLAP. These two types of applications are mutually exclusive in you are interested in any sense of high performance and scalability.
OLTP databases are generally highly normalized, helping to reduce the amount of data that has to be stored. The less data you store, the less I/O SQL Server will have to perform, and the faster database access will be. Transactions are also kept as short as possible in order to reduce locking conflicts. And last of all, indexing is generally minimized to reduce the overhead of high levels of INSERTs, UPDATEs, and DELETEs.
OLAP databases, on the other hand, are highly de-normalized. In addition, transactions are not used, and because the database is read-only, record locking is not an issue. And of course, heavy indexing is used in order to meet the wide variety of reporting needs.
As you can see, OLTP and OLAP databases serve two completely different purposes, and it is virtually impossible to design a database to handle both needs. While OLAP database design is out of this book's scope, I do want to mention a couple of performance-related suggestions in regard to OLTP database design.
When you go through the normalization process when designing your OLTP databases, your initial goal should be to fully normalize it according to the three general principles of normalization. The next step is to perform some preliminary performance testing, especially if you foresee having to perform joins on four or more tables at a time. Be sure to test using realistic sample data.
If performance is acceptable, then don't worry about having to join four or more tables in a query. But if performance is not acceptable, then you may want to do some selective de-normalization of the tables involved in order to reduce the number of joins used in the query, and to speed performance.
It is much easier to catch a problem in the early database design stage, rather than after the finished application has been rolled out. De-normalization of tables after the application is complete is nearly impossible. One word of warning. Don't be tempted to de-normalize your database without thorough testing. It is very hard to deduce logically what de-normalization will do to performance. Only through realistic testing can you know for sure if de-normalization will gain you anything in regards to performance.
How to Optimize Your Application Code for SQL ServerAt some point during the development process you will have to begin coding your application to work with SQL Server. By this time, the application and database designs should have already been completed and tested for performance and scalability using rapid prototyping techniques.
How your code your application has a significant bearing on performance and scalability, just as the database design and the overall application design affect performance and scalability. Sometimes, something as simple as choosing one coding technique over another can make a significant different. Rarely is there only one way to code a task, but often there is only one way to code a task for optimum performance and scalability.What I want to do in this section is focus on some essential techniques that can affect the performance of your application and SQL Server.


How to Optimize Your Transact-SQL Code:

Transact-SQL, just like any programming language, offers more than one way to perform many tasks. And as you might imagine, some techniques offer better performance than others. In this section you will learn some of the "tricks-of-the-trade" when it comes to writing high performing Transact-SQL code.
Choose the Appropriate Data TypesWhile you might think that this topic should be under database design, I have decided to discuss it here because Transact-SQL is used to create the physical tables that were designed during the earlier database design stage.
Choosing the appropriate data types can affect how quickly SQL Server can SELECT, INSERT, UPDATE, and DELETE data, and choosing the most optimum data type is not always obvious. Here are some suggestions you should implement when creating physical SQL Server tables to help ensure optimum performance.
Always choose the smallest data type you need to hold the data you need to store in a column. For example, if all you are going to be storing in a column are the numbers 1 through 10, then the TINYINT data type is more appropriate that the INT data type. The same goes for CHAR and VARCHAR data types. Don't specify more characters for character columns that you need. This allows SQL Server to store more rows in its data and index pages, reducing the amount of I/O needed to read them. Also, it reduces the amount of data moved from the server to the client, reducing network traffic and latency.
If the text data in a column varies greatly in length, use a VARCHAR data type instead of a CHAR data type. Although the VARCHAR data type has slightly more overhead than the CHAR data type, the amount of space saved by using VARCHAR over CHAR on variable length columns can reduce I/O, improving overall SQL Server performance.
Don't use the NVARCHAR or NCHAR data types unless you need to store 16-bit character (Unicode) data. They take up twice as much space as VARCHAR or CHAR data types, increasing server I/O overhead.
If you need to store large strings of data, and they are less than 8,000 characters, use a VARCHAR data type instead of a TEXT data type. TEXT data types have extra overhead that drag down performance.
If you have a column that is designed to hold only numbers, use a numeric data type, such as INTEGER, instead of a VARCHAR or CHAR data type. Numeric data types generally require less space to hold the same numeric value as does a character data type. This helps to reduce the size of the columns, and can boost performance when the columns is searched (WHERE clause) or joined to another column.
Use Triggers Cautiously:

Triggers can be a powerful tool in Transact-SQL, but since they execute every time that a table is INSERTED, UPDATED, or DELETED (depending on how the trigger is created), they can produce a lot of overhead. Here's some tips on how to optimize trigger performance.
Keep the code in your triggers to the very minimum to reduce overhead. The more code that runs in the trigger, the slower each INSERT, UPDATE, and DELETE that fires it will be.
Don't use triggers to perform tasks that can be performed using more efficient techniques. For example, don't use a trigger to enforce referential integrity if SQL Server's built-referential integrity is available to accomplish your goal. The same goes if you have a choice between using a trigger or a CHECK constraint to enforce rules or defaults. You will generally want to choose a CHECK constraint as they are faster than using triggers when performing the same task.
Try to avoid rolling back triggers because of the overhead involved. Instead of letting the trigger find a problem and rollback a transaction, catch the error before it can get to the trigger (if possible based on your code). Catching an error early (before the trigger fires) consumes fewer server resources than letting the trigger roll back.
Don't Access More Data Than You Need:

While this suggestion may sound obvious, it must not be, because this is a common performance-related issue I find over and over again in many SQL Server-based applications. Here are some ideas on how to minimize the amount of data that is returned to the client.
Don't return more columns or rows of data to the client than absolutely necessary. This just increases disk I/O on the server and network traffic, both of which hurts performance. In SELECT statements, don't use SELECT * to return rows, always specify in your SELECT statement exactly which columns are needed to be returned for this particular query, and not a column more. In most cases, be sure to include a WHERE clause to reduce the number or rows sent to only those rows the clients needs to perform the task immediately at hand.
If your application allows users to run queries, but you are unable in your application to easily prevent users from returning hundreds, even thousands of unnecessary rows of data they don't need, consider using the TOP operator within the SELECT statement. This way, you can limit how may rows are returned, even if the user doesn't enter any criteria to help reduce the number or rows returned to the client.
Avoid Using Cursors:

Transact-SQL is designed to work best on result sets, not on individual records. That's where cursors come into play. They allow you to process individual records. The only problem with individual record processing is that it is slow. Ideally, for high-performing SQL Server-based applications, cursors should be avoided.
If you need to perform row-by-row operations, try to find another method to perform the task. Some options are to perform row-by-row tasks at the client instead of the server, using tempdb tables at the server, or using a correlated sub-query.
Unfortunately, these are not always possible, and you have to use a cursor. If you find it impossible to avoid using cursors in your applications, then perhaps one of these suggestions will help.
SQL Server offers you several different types of cursors, each with its different performance characteristics. Always select the cursor with the least amount of overhead that has the features you need to accomplish your goals. The most efficient cursor you can choose is the fast forward-only cursor.
When using a server-side cursor, always try to fetch as small a result set as possible. This includes fetching only those rows and columns the client needs immediately. The smaller the cursor, no matter what type of server-side cursor it is, the fewer resources it will use, and performance will benefit.
When you are done using a cursor, don't just CLOSE it, you must also DEALLOCATE it. Deallocation is required to free up the SQL Server resources used by the cursor. If you only CLOSE the cursor, locks are freed, but SQL Server resources are not. If you don't DEALLOCATE your cursors, the resources used by the cursor will stay allocated, degrading the performance of your server until they are released.
Use Joins Appropriately:

Table joins can be a big contributor of performance problems, especially if the joins include more than two tables, or if the tables are very large. Unfortunately, joins are a fact of life in relational databases. Because they are so common, you will need to take extra time to help ensure that your joins are as optimal as possible. Here are some tips to help.
If you have two or more tables that are frequently joined together, then the columns used for the joins should have an appropriate index. If the columns used for the joins are not naturally compact, then considering adding surrogate keys to the tables that are compact in order to reduce the size of the keys, thus decreasing read I/O during the join process, and increasing overall performance. You will learn more about indexing in the next section of this article.
For best performance, the columns used in joins should be of the same data types. And if possible, they should be numeric data types rather than character types.
Avoid joining tables based on columns with few unique values. If columns used for joining aren't mostly unique, then the SQL Server optimizer will perform a table scan for the join, even if an index exists on the columns. For best performance, joins should be done on columns that have unique indexes.
If you have to regularly join four or more tables to get the recordset you need, consider denormalizing the tables so that the number of joined tables is reduced. Often, by adding one or two columns from one table to another, joins can be reduced.
Encapsulate Your Code in Stored Procedures:

Virtually all of the Transact-SQL used in your SQL Server-based applications should be encapsulated in stored procedures, not run as dynamic SQL or scripts. This not only reduces network traffic (only the EXECUTE or CALL is issued over the network between the client and SQL Server), but it speeds up the Transact-SQL because the code in the stored procedure residing on the server is already pre-compiled. Here are a couple of things to keep in mind when writing stored procedures for optimal performance.
When a stored procedure is first executed (and it does not have the WITH RECOMPILE option specified), it is optimized and a query plan is compiled and cached in SQL Server's memory. If the same stored procedure is called again, it will use the cached query plan instead of creating a new one, saving time and boosting performance. This may or may not be what you want. If the query in the stored procedure is the same each time, then this is a good thing. But if the query is dynamic (the WHERE clauses changes substantially from one execution of the stored procedure to the next), then this is a bad thing, as the query will not be optimized when it is run, and the performance of the query can suffer.
If you know that your query will vary each time it is run from the stored procedure, you will want to add the WITH RECOMPILE option when you create the stored procedure. This will force the stored procedure to be re-compiled each time it is run, ensuring the query is optimized each time it is run.
Always include in your stored procedures the statement, "SET NOCOUNT ON". If you don't turn this feature on, then every time a SQL statement is executed, SQL Server will send a response to the client indicating the number of rows affected by the statement. It is rare that the client will ever need this information. Using this statement helps reduce the traffic between the server and the client.
Deadlocking can occur within a stored procedure when two user processes have locks on separate objects and each process is trying to acquire a lock on the object that the other process has. When this happens, SQL Server ends the deadlock by automatically choosing one and aborting the process, allowing the other process to continue. The aborted transaction is rolled back and an error message is sent to the user of the aborted process.
To help avoid deadlocking in your SQL Server application, try to design your application using these suggestions: 1) have the application access server objects in the same order each time; 2) during transactions, don't allow any user input. Collect it before the transaction begins; 3) keep transactions short and within a single batch, and 4) if appropriate, use as low of an isolation level as possible for the user connection running the transaction.
How to Select Indexes for Optimal Database Performance:

Index selection is a mystery for many SQL Server DBAs and developers. Sure, we know what they do and how they boost performance. The problem often is how to select the ideal type of index (clustered vs. non-clustered), the number of columns to index (do I need multi-column indexes?), and which columns should be indexed.
In this section we will take a brief look at how to answer the above questions. Unfortunately, there is no absolute answer for every occasion. Like much of SQL Server performance tuning and optimization, you may have to do some experimenting to find the ideal indexes. So let's begin by looking as some general index creation guidelines, then we will take a more detailed look at selecting clustered and non-clustered indexes.
Is There Such a Thing as Too Many Indexes?Yes. Some people think that all you have to do is index everything, and then all of your performance issues will go away. It doesn't work that way. Just as an index can speed data access, it can also degrade access if it is inappropriately selected. The problem with extra indexes is that SQL Server must maintain them every time that a record is INSERTED, UPDATED, or DELETED from a table. While maintaining one or two indexes on a table is not too much overhead for SQL Server to deal with, if you have four, five, or more indexes, they can be a large performance burden on tables. Ideally, you want to have as few as indexes as you can. It is often a balancing act to select the ideal number of indexes for a table in order to find optimal performance.
As a general rule of thumb, don't automatically add indexes to a table because it seems like the right thing to do. Only add indexes if you know that they will be used by the queries run against the table. If you don't know what queries will be run against your table, then don't add any indexes until you know for sure. It is too easy to make a guess on what queries will be run, create indexes, and then later find out your guesses were wrong. You must know the type of queries that will be run against your data, and then these need to be analyzed to determine the most appropriate indexes, and then the indexes must be created and tested to see if they really help or not.
The problem of selecting optimal indexes is often difficult for OLTP applications because they tend to experience high levels of INSERT, UPDATE, and DELETE activity. While you need good indexes to quickly locate records that need to be SELECTED, UPDATED, or DELETED, you don't want every INSERT, UPDATE, or DELETE to result in too much overhead because you have too many indexes. On the other hand, if you have an OLAP application that is virtually read-only, then adding as many indexes as you need is not a problem because you don't have to worry about INSERT, UPDATE, or DELETE activity. As you can see, how your application is used makes a large difference in your indexing strategy.
Another thing to think about when selecting indexes is that the SQL Server Query Optimizer may not use the indexes you select. If the Query Optimizer chooses not to use your indexes, then they are a burden on SQL Server and should be deleted. So how come the SQL Server Query Optimizer won't always use an index if one is available?
This is too large a question to answer in detail here, but suffice to say, sometimes it is faster for SQL Server to perform a table scan on a table than it is to use an available index to access data in the table. Two reasons that this may happen is because the table is small (not many rows), or if the column that was indexed isn't at least 95% unique. How do you know if SQL Server won't use the indexes you create? We will answer this question a little later when we take a look at how to use the SQL Server Query Analyzer later in this article.
Tips for Selecting a Clustered Index:

Since you can only create one clustered index per table, take extra time to carefully consider how it will be used. Consider the type of queries that will be used against the table, and make an educated guess as to which query is the most critical, and if this query will benefit from having a clustered index.In general, use these rules of thumb when selecting a column for a possible clustered index.
The primary key you select for your table should not always be a clustered index. If you create the primary key and don't specify otherwise, then SQL Server automatically makes the primary key a clustered index. Only make the primary key a clustered index if it meets one of the following recommendations.
Clustered indexes are ideal for queries that select by a range of values or where you need sorted results. This is because the data is already presorted in the index for you. Examples of this include when you are using BETWEEN, <, >, GROUP BY, ORDER BY, and aggregates such as MAX, MIN, and COUNT in your queries.
Clustered indexes are good for queries that look up a record with a unique value (such as an employee number) and when you need to retrieve most or all of the data in the record. This is because the query is covered by the index.
Clustered indexes are good for queries that access columns with a limited number of distinct values, such as a columns that holds country or state data. But if column data has little distinctiveness, such as columns with a yes or no, or male or female, then these columns should not be indexed at all.
Clustered indexes are good for queries that use the JOIN or GROUP BY clauses.
Clustered indexes are good for queries where you want to return a lot of rows, just not a few. This is because the data is in the index and does not have to be looked up elsewhere.
Avoid putting a clustered index on columns that increment, such as an identity, date, or similarly incrementing columns, if your table is subject to a high level of INSERTS. Since clustered indexes force the data to be physically ordered, a clustered index on an incrementing column forces new data to be inserted at the same page in the table, creating a table hot spot, which can create disk I/O bottlenecks. Ideally, find another column or columns to become your clustered index.
What can be frustrating about the above advice is that there might be more than one column that should be clustered. But as we know, we can only have one clustered index per table. What you have to do is evaluate all the possibilities (assuming more than one column is a good candidate for a clustered index) and then select the one that provides the best overall benefit.
Tips for Selecting Non-Clustered Indexes:

Selecting non-clustered indexes is somewhat easier than clustered indexes because you can created as many as is appropriate for your table. Here are some tips for selecting which columns in your tables might be helped by adding non-clustered indexes.
Non-clustered indexes are best for queries that return few rows (including just one row) and where the index has good selectivity (above 95%).
If a column in a table is not at least 95% unique, then most likely the SQL Server Query Optimizer will not use a non-clustered index based on that column. Because of this, don't add non-clustered indexes to columns that aren't at least 95% unique. For example, a column with "yes" or "no" as the data won't be at least 95% unique.
Keep the "width" of your indexes as narrow as possible, especially when creating composite (multi-column) indexes. This reduces the size of the index and reduces the number of reads required to read the index, boosting performance.
If possible, try to create indexes on columns that have integer values instead of characters. Integer values have less overhead than character values.
If you know that your application will be performing the same query over and over on the same table, consider creating a covering index on the table. A covering index includes all of the columns referenced in the query. Because of this, the index contains the data you are looking for and SQL Server doesn't have to look up the actual data in the table, reducing logical and/or physical I/O. On the other hand, if the index gets too big (too many columns), this can increase I/O and degrade performance.
An index is only useful to a query if the WHERE clause of the query matches the column(s) that are leftmost in the index. So if you create a composite index, such as "City, State", then a query such as "WHERE City = 'Houston'" will use the index, but the query "WHERE STATE = 'TX'" will not use the index.
Generally, if a table needs only one index, make it a clustered index. If a table needs more than one index, then you have no choice but to use non-clustered indexes. By following the above recommendations, you will be well on your way to selecting the optimum indexes for your tables.