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It It contains valuable then moves on to describe one of the most important con- information regarding cepts you need to know about the language—logical query the skills you need to processing. However, the information in this chapter is critical in order to correctly understand the rest of the book.

Without strong foundations, their lifespan can be very short, and if they do survive, often the changes are very rapid due to changes in trends. T-SQL is different, mainly because it has strong foundations—mathematics. Without those foundations, you can still write T-SQL code—even code that runs successfully—but it will be like eating soup with a fork!

Understanding some of the key principals from those foundations can help you better understand the language you are dealing with. Figure illustrates the evolution of T-SQL from its core mathematical foundations.

The two standards for SQL are basically the same. The SQL standard keeps evolving with time. Therefore, the core language elements look the same. However, each vendor decides which features to imple- ment and which not to. Also, the standard sometimes leaves some aspects as an implementa- tion choice. Writing in a standard way is considered a best practice.

When you do so, your code is more portable. Your knowledge is more portable, too, because it is easy for you to start working with new platforms. You should consider a nonstandard option only when it has some important benefit to you that is not covered by the standard alternative.

The former is standard and the latter is not. This case should be a no- brainer: go for the standard one! As an example of when the choice of standard or nonstandard depends on the circum- stances, consider the following: T-SQL supports multiple functions that convert a source value to a target type.

Because CAST is standard, you should consider it your default choice for conversions. According to standard SQL, you should terminate your statements with a semicolon. You should still follow the standard and terminate all of your state- ments even where it is currently not required.

Standard SQL is based on the relational model, which is a mathematical model for data Key management and manipulation. The relational model was initially created and proposed by Terms Edgar F. Codd in Since then, it has been explained and developed by Chris Date, Hugh Darwen, and others. A relation in the relational model is what SQL calls a table. The two are not synonymous. Some might say that it is not a very successful attempt. Even though SQL is based on the relational model, it deviates from it in a number of ways.

The heading is a set of attributes what SQL attempts to represent with columns , each of a given type. An attribute is identified by name and type name. The body is a set of tuples what SQL attempts to represent with rows.

Remember that the heading of a relation is a set of attributes, and the body a set of tuples. So what is a set? Dauben Princeton University Press, There are a number of very important principles in this definition that, if understood, should have direct implications on your T-SQL coding practices.

For one, notice the term whole. A set should be considered as a whole. This means that you do not interact with the individual elements of the set, rather with the set as a whole. In contrast, a sequence which is an ordered set , for example, does have an order to its ele- ments. The other branch of mathematics that the relational model is based on is called predicate logic. A predicate is an expression that when attributed to some object, makes a proposition Key either true or false. You can evalu- Terms ate this predicate for a specific employee, in which case you have a proposition.

When you evaluate the proposi- tion for that employee, you get a true proposition. In other words, a predicate is a parameter- ized proposition. The relational model uses predicates as one of its core elements. You can enforce data integrity by using predicates. You can filter data by using predicates. You can even use predi- cates to define the data model itself. You first identify propositions that need to be stored in the database. You then create predicates from the propositions by removing the data and keeping the heading.

Remember, the heading is a set of attributes, each identified by name and type name. Quick Check 1. What are the mathematical branches that the relational model is based on? Quick Check Answer 1. Set theory and predicate logic. But the language gives you enough tools so that if you understand the relational model, you can use the language in a relational manner, and thus write more-correct code. Remember that a relation has a heading and a body. The heading is a set of attributes and the body is a set of tuples.

Remember from the definition of a set that a set is supposed to be considered as a whole. You should try to avoid using iterative constructs like cursors and loops that iterate through the rows one at a time. You should also try to avoid thinking in iterative terms because this kind of thinking is what leads to iterative solutions. For people with a procedural programming background, the natural way to interact with data in a file, record set, or data reader is with iterations.

So using cursors and other iterative constructs in T-SQL is, in a way, an extension to what they already know. This, in T-SQL, translates to writing queries.

Remember also that a set has no duplicates. For ex- ample, you can create a table without a key. In such a case, you are allowed to have duplicate rows in the table.

To follow relational theory, you need to enforce uniqueness in your tables— for example, by using a primary key or a unique constraint. You'll find further discussion about duplicates in subsequent chap- ters, but here is an example for illustration purposes. Consider the following query. It returns the country attribute of the employees stored in the HR.

Employees table. According to the relational model, a relational operation against a relation is supposed to return a relation. In this case, this should translate to returning the set of countries where there are employees, with an emphasis on set, as in no duplicates.

A multiset also known Key as a bag or a superset in many respects is similar to a set, but can have duplicates. As men- Terms tioned, the T-SQL language does give you enough tools so that if you want to follow rela- tional theory, you can do so.

For this reason, rows in a table have no particular order, conceptually. As an example, consider the following query. For example, SQL Server could decide to parallelize the query or scan the data in file order as opposed to index order. If you do need to guarantee a specific presentation order to the rows in the result, you need to add an ORDER BY clause to the query, as follows. The order of the Key rows in the output is guaranteed based on the empid attribute.

Terms empid lastname 1 Davis 2 Funk 3 Lew 4 Peled 5 Buck 6 Suurs 7 King 8 Cameron 9 Dolgopyatova The heading of a relation is a set of attributes that are supposed to be identified by name and type name.

Conversely, T-SQL does keep track of ordinal positions of columns based on their order of appearance in the table definition. Therefore, the recommendation is to always indicate the names of the attributes that you need to order by. T-SQL has another deviation from the relational model in that it allows defining result columns based on an expression without assigning a name to the target column. For example, the following query is valid in T-SQL.

Employees; This query generates the following output. In order for the query to be relational, you need to assign an alias to the target attribute. You can do so by using the AS clause, as follows. For example, consider a join between two tables, T1 and T2, both with a column called keycol. For the result to be relational, all attributes must have unique names, so you would need to use different aliases for the result attributes, as in the following. As for predicates, following the law of excluded middle in mathematical logic, a predicate Key can evaluate to true or false.

In other words, predicates are supposed to use two-valued logic. Terms However, Codd wanted to reflect the possibility for values to be missing in his model. He referred to two kinds of missing values: missing but applicable and missing but inapplicable.

Take a mobilephone attribute of an employee as an example. A missing but applicable value would be if an employee has a mobile phone but did not want to provide this information, for example, for privacy reasons. This leads to three-valued predicate logic. But if one of them is NULL, the result evaluates to a third logical value— unknown. Note that some believe that a valid relational model should follow two-valued logic, and strongly object to the concept of NULLs in SQL.

But as mentioned, the creator of the rela- tional model believed in the idea of supporting missing values, and predicates that extend beyond two-valued logic. If the answer is yes, you want to make sure that you understand the treatment of NULLs in your query, and ensure that your tests address treatment of NULLs specifically. Name two aspects in which T-SQL deviates from the relational model.

Explain how you can address the two items in question 1 and use T-SQL in a relational way. A relation has a body with a distinct set of tuples. Define a key in every table.

Using Correct Terminology Your use of terminology reflects on your knowledge. Therefore, you should make an effort to understand and use correct terminology. When discussing T-SQL—related topics, people often use incorrect terms.

Fields and records are physical. Fields are what you have in user interfaces in client applications, and records are what you have in files and cursors. Tables are logical, and they have logical rows and columns. Remember from the previous section that T-SQL attempts to represent a relation with a table, a tuple with a row, and an attribute with a column; but the T-SQL concepts and their relational counterparts differ in a number of ways.

As long as you are conscious of those differences, you can, and should, strive to use T-SQL in a relational way. If you encounter a problem completing an exercise, you can install the completed projects from the companion content for this chapter and lesson. Your task is to identify the nonrelational elements in the query. Type the following query in the query window and execute it. Review the code and its output. The query is supposed to return for each customer and order year the customer ID custid and order year YEAR orderdate.

Can you identify what the nonrelational aspects of the query are? The query can return duplicates. After you identify the nonrelational elements in the query, you need to apply the appropriate revi- sions to make it relational. Ap- ply revisions to the query to make it relational. A number of revisions are required to make the query relational. Your code should look like the following. It is based on standard SQL, which in turn is based on the relational model, which in turn is based on set theory and predicate logic.

Lesson Review Answer the following questions to test your knowledge of the information in this lesson. Choose all that apply. It is not important to code using standard SQL. Standard SQL code is more portable between platforms. Standard SQL code is more efficient. Knowing what standard SQL code is makes your knowledge more portable. Which of the following is not a violation of the relational model? Using ordinal positions for columns B. Returning duplicate rows C.

Not defining a key in a table D. Ensuring that all attributes in the result of a query have names 3. The logical side is the conceptual interpreta- tion of the query that explains what the correct result of the query is.

The physical side is the processing of the query by the database engine. Physical processing must produce the result defined by logical query processing. To achieve this goal, the database engine can apply op- timization. Optimization can rearrange steps from logical query processing or remove steps altogether—but only as long as the result remains the one defined by logical query process- ing.

The focus of this lesson is logical query processing—the conceptual interpretation of the Key query that defines the correct result. In this language, declarative means you define what you want, as opposed to imperative languages that define also how to achieve what you want.

For this reason, it is important not to draw any performance-related conclusions from what you learn about logical query processing. When addressing performance aspects of the query, you need to understand how optimization works. Consider the following request in T-SQL. Now try to think of the order in which the request needs to be logically interpreted. For example, how would you define the instructions to a robot instead of a human? Therefore, contrary to the keyed-in order of the previous query, the logical query processing has to be as follows.

FROM Sales. Of course, things can get more com- plex. If you understand the concept of logical query processing well, you will be able to ex- plain many things about the way the language behaves—things that are very hard to explain otherwise. Logical Query Processing Phases This section covers logical query processing and the phases involved.

Subsequent chapters in this Training Kit provide more detail, and after you go over those, this topic should make more sense. To make sure you really understand these concepts, make a first pass over the topic now and then revisit it later after going over Chapters 2 through 5. FROM 3. WHERE 4. It starts with the FROM clause. Here is the logical query processing order of the six main query clauses: 1. FROM 2. The output table of one phase is considered the input to the next phase.

This is in accord with operations on relations that yield a relation. It filters only employees that were hired in or after the year It groups the remaining employees by country and the hire year. It keeps only groups with more than one employee. For each qualifying group, the query returns the hire year and count of employees, sorted by country and hire year, in de- scending order.

The following sections provide a brief description of what happens in each phase accord- ing to logical query processing. If you need to query just one table, you indicate the table name as the input table in this clause. Then, the output of this phase is a table result with all rows from the input table. Employees table nine rows , and the output is a table result with all nine rows only a subset of the attributes are shown. Only rows for which the predicate evaluates to true are returned.

Six rows are returned from this phase and are provided as input to the next one. Msg , Level 16, State 1, Line 3 Invalid column name 'yearhired'. It then associates each input row to its respective group. Within the six rows in the input table, this step identifies four groups. Here are the groups and the detail rows that are associated with them redundant information removed for purposes of illustration. The final result of this query has one row representing each group unless filtered out.

Therefore, expressions in all phases that take place after the current grouping phase are somewhat limited. All expressions processed in subsequent phases must guarantee a single value per group.

If you refer to an element from the GROUP BY list for example, country , you already have such a guarantee, so such a reference is allowed. Filter Rows Based on the HAVING Clause This phase is also responsible for filtering data based on a predicate, but it is evaluated after the data has been grouped; hence, it is evaluated per group and filters groups as a whole.

As is usual in T-SQL, the filtering predicate can evaluate to true, false, or unknown. Only groups for which the predicate evaluates to true are returned from this phase.

If you look at the number of rows that were associated with each group in the previous step, you will notice that only the groups UK, and UK, qualify. Hence, the result of this phase has the following remaining groups, shown here with their associated detail rows.

This phase includes two main steps. This includes assigning attributes with names if they are derived from expressions. Remember that if a query is a grouped query, each group is represented by a single row in the result. Therefore, this step generates two rows. Employees; This query generates the following error. Msg , Level 16, State 1, Line 1 Invalid column name 'yearhired'. Note the use of the word conceptually.

This behavior is different than many other programming languages where expressions usually get evaluated in a left-to- right order, making a result produced in one expression visible to the one that appears to its right. But T-SQL is different. Because all expressions that appear in the same logical query processing phase are evaluated conceptually at the same point in time. This phase is responsible for returning the result in a specific presentation order according to the expressions that appear in the ORDER BY list.

The query indicates that the result rows should be ordered first by country in ascending order by default , and then by yearhired, descending, yielding the following output. The result of this phase is what standard SQL calls a cursor. Note that the use of the term cursor here is conceptual. T-SQL also supports an object called a cursor that is defined based on a result of a query, and that allows fetching rows one at a time in a specified order.

You might care about returning the result of a query in a specific order for presentation purposes or if the caller needs to consume the result in that manner through some cursor mechanism that fetches the rows one at a time. If you need to process the query result in a relational manner—for example, define a table expression like a view based on the query details later in Chapter 4 —the result will need to be relational.

Also, sorting data can add cost to the query processing. If it does, the same ORDER BY clause that is normally used to define presentation ordering also defines which rows to filter for these options. You are provided with instructions on how to fix the query. Try to figure out why the query failed and what needs to be revised so that it would return the desired result. There are multiple possible orderid values per customer.

To fix the query, you need to apply an aggregate function to the orderid attribute. The task is to return the maximum orderid value per customer. Therefore, the aggregate function should be MAX. Your query should look like the following. As in the first exercise, you are provided with instructions on how to fix the query. Clear the query window, type the following query, and execute it. Try to identify the problem in the query.

The query filters individual orders with a freight value greater than 20,, and there are none. To correct the query, you need to apply the filter per each shipper group—not per each order. You need to filter the total of all freight values per shipper. You try to fix the problem by using the following query. Try to identify why it fails and what needs to be revised to achieve the desired result. Which of the following correctly represents the logical query processing order of the various query clauses?

Which of the following is invalid? It is relational as long as other relational requirements are met. It cannot have duplicates. The order of the rows in the output is guaranteed to be the same as the insertion order. The order of the rows in the output is guaranteed to be the same as that of the clustered index. Case Scenario 1: Importance of Theory You and a colleague on your team get into a discussion about the importance of understand- ing the theoretical foundations of T-SQL.

Answer the following questions posed to you by your colleague: 1. Can you give an example for an element from set theory that can improve your under- standing of T-SQL? Can you explain why understanding the relational model is important for people who write T-SQL code? Case Scenario 2: Interviewing for a Code Reviewer Position You are interviewed for a position as a code reviewer to help improve code quality. The queries have numerous problems, including logical bugs. Your interviewer poses a number of questions and asks for a concise answer of a few sentences to each question.

Answer the following questions ad- dressed to you by your interviewer: 1. Is it important to use standard code when possible, and why? Is that a bad practice, and if so why? Review code samples in the T-SQL threads.

Try to identify cases where nonrelational elements are used; if you find such cases, identify what needs to be revised to make them relational. Provide a brief paragraph summarizing what happens in each step. Lesson 1 1. Correct Answers: B and D A. Incorrect: It is important to use standard code. Correct: Use of standard code makes it easier to port code between platforms because fewer revisions are required.

Correct: When using standard code, you can adapt to a new environment more easily because standard code elements look similar in the different platforms. Correct Answer: D A. Incorrect: A relation has a header with a set of attributes, and tuples of the rela- tion have the same heading.

A set has no order, so ordinal positions do not have meaning and constitute a violation of the relational model. You should refer to attributes by their name. Incorrect: A query is supposed to return a relation. A relation has a body with a set of tuples. A set has no duplicates. Returning duplicate rows is a violation of the relational model. Correct: Because attributes are supposed to be identified by name, ensuring that all attributes have names is relational, and hence not a violation of the relational model.

Correct Answer: B A. Correct Answer: C and D A. Incorrect: T-SQL allows grouping by an expression. Correct Answer: A A. Even though T-SQL is based on the relational model, it deviates from it in a number of ways. But it gives you enough tools that if you understand the relational model, you can write in a relational way. Following the relational model helps you write code more correctly. Case Scenario 2 1. It is important to use standard SQL code.

From a relational per- spective, you are supposed to refer to attributes by name, and not by ordinal position. The order should be considered arbitrary. You also notice that the interviewer used the incorrect term record instead of row. You might want to mention something about this, because the interviewer may have done so on purpose to test you.

From a pure relational perspective, this actually could be valid, and perhaps even recommended. But from a practical perspective, there is the chance that SQL Server will try to remove duplicates even when there are none, and this will incur extra cost.

I t is hard to imagine searching for something on the web without modern search engines like Bing or Google. However, most contemporary applications still limit users to exact searches only.

In addition, many documents are stored in modern databases; end users would probably like to have powerful search capabilities inside document con- tents as well. Microsoft SQL Server enhances the full-text search support that was substantially available in previous editions. This chapter explains how to use full-text search and even semantic search inside a SQL Server database.

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