Chapter 1 : Inside Microsoft's Cosmos DB ZDNet Inside Relational Databases is an excellent introduction to the topic and a very good resource. I read the book cover to cover and found the authors' insights helpful. Sales 31 The employee "Williams" and the department "Marketing" do not appear in the query execution results. Neither of these has any matching rows in the other respective table: Depending on the desired results, this behavior may be a subtle bug, which can be avoided by replacing the inner join with an outer join. Programmers should take special care when joining tables on columns that can contain NULL values, since NULL will never match any other value not even NULL itself, unless the join condition explicitly uses a combination predicate that first checks that the joins columns are NOT NULL before applying the remaining predicate condition s. The Inner join can only be safely used in a database that enforces referential integrity or where the join columns are guaranteed not to be NULL. Many transaction processing relational databases rely on Atomicity, Consistency, Isolation, Durability ACID data update standards to ensure data integrity, making inner joins an appropriate choice. However transaction databases usually also have desirable join columns that are allowed to be NULL. Many reporting relational database and data warehouses use high volume Extract, Transform, Load ETL batch updates which make referential integrity difficult or impossible to enforce, resulting in potentially NULL join columns that an SQL query author cannot modify and which cause inner joins to omit data with no indication of an error. The choice to use an inner join depends on the database design and data characteristics. A left outer join can usually be substituted for an inner join when the join columns in one table may contain NULL values. Any data column that may be NULL empty should never be used as a link in an inner join, unless the intended result is to eliminate the rows with the NULL value. If NULL join columns are to be deliberately removed from the result set, an inner join can be faster than an outer join because the table join and filtering is done in a single step. Conversely, an inner join can result in disastrously slow performance or even a server crash when used in a large volume query in combination with database functions in an SQL Where clause. The database may read and inner join the selected columns from both tables before reducing the number of rows using the filter that depends on a calculated value, resulting in a relatively enormous amount of inefficient processing. When a result set is produced by joining several tables, including master tables used to look up full text descriptions of numeric identifier codes a Lookup table, a NULL value in any one of the foreign keys can result in the entire row being eliminated from the result set, with no indication of error. A complex SQL query that includes one or more inner joins and several outer joins has the same risk for NULL values in the inner join link columns. One can further classify inner joins as equi-joins, as natural joins, or as cross-joins. Equi-join[ edit ] An equi-join is a specific type of comparator-based join, that uses only equality comparisons in the join-predicate. The query shown above has already provided an example of an equi-join: Specifically, any columns mentioned in the USING list will appear only once, with an unqualified name, rather than once for each table in the join. In the case above, there will be a single DepartmentID column and no employee. Natural join[ edit ] The natural join is a special case of equi-join. For an example consider the tables Employee and Dept and their natural join: Page 1
Chapter 2 : Inside Relational Databases by Mark Whitehorn To ask other readers questions about Inside Relational Databases with Examples in Access, please sign up. Be the first to ask a question about Inside Relational Databases with Examples in Access Read this for a university course in databases. For what it is, its a good book. And I understand how. Relational databases use tables to store information. HowStuffWorks Databases have been a staple of business computing from the very beginning of the digital era. In fact, the relational database was born in when E. Codd, a researcher at IBM, wrote a paper outlining the process. Since then, relational databases have grown in popularity to become the standard. Originally, databases were flat. This means that the information was stored in one long text file, called a tab delimited file. Each entry in the tab delimited file is separated by a special character, such as a vertical bar. Each entry contains multiple pieces of information fields about a particular object or person grouped together as a record. The text file makes it difficult to search for specific information or to create reports that include only certain fields from each record. A relational database allows you to easily find specific information. It also allows you to sort based on any field and generate reports that contain only certain fields from each record. The standard fields and records are represented as columns fields and rows records in a table. With a relational database, you can quickly compare information because of the arrangement of data in columns. The relational database model takes advantage of this uniformity to build completely new tables out of required information from existing tables. In other words, it uses the relationship of similar data to increase the speed and versatility of the database. The "relational" part of the name comes into play because of mathmatical relations. A typical relational database has anywhere from 10 to more than 1, tables. Each table contains a column or columns that other tables can key on to gather information from that table. By storing this information in another table, the database can create a single small table with the locations that can then be used for a variety of purposes by other tables in the database. A typical large database, like the one a big Web site, such as Amazon would have, will contain hundreds or thousands of tables like this all used together to quickly find the exact information needed at any given time. Relational databases are created using a special computer language, structured query language SQL, that is the standard for database interoperability. SQL is the foundation for all of the popular database applications available today, from Access to Oracle. Here are some interesting links: Page 2
Chapter 3 : Inside Relational Databases with Examples in Access by Mark Whitehorn Inside Relational Databases will teach the newcomer to Access or relational databases in general, the theory needed to design and develop applications in the most efficient and professional manner. While certainly not mystical in the traditional sense, an Oracle database is still filled with nuances that make the system a bit hard to understand at times. Despite its perceived complexity, this groundbreaking software has become the backbone to many organizations. An Oracle database provides a flexible an efficient way to organize and retrieve information. In a way, the database works a lot like the human mind: These pieces of information all tie together to give you a comprehensive view of the person in question. Businesses use Oracle relational databases for the same purpose, applying the process to areas such as customer and product information. Just like the human brain, Oracle is able to organize and effectively place pieces of information for safe keeping. Every piece of information must have a permanent space. Oracle databases provide this space, thereby centralizing company information in a safe location. Retrieving Storing and organizing information is one thingâ recalling this information quickly is another. While our memories may sometimes fail us, an Oracle database, as a fully operational software, assures that your information can be retrieved almost instantly. This essential ability allows for more streamlined and effective business processes, saving you and your company precious time. Coding The coding element of relational databases can be one of the hardest concepts to understand. In short, the coding behind successful databases such as Oracle systems ensures that information is properly categorized and connected in a way that is beneficial to users. Oracle systems are built to perform two basic tasks: For example, when we are asked a question our brains search our previous knowledge to generate an answer. Likewise, when speaking with someone, our brains are built in a way that provides us with relevant information regarding that person that can help guide the conversation. Oracle systems operate similarly. If a user types a search query, an Oracle relational database is able to search its system to find the piece of information needed. Further, an Oracle system can recognize an entity such as a web site or intranet page and automatically generate information relevant to the intended purpose of the page, providing the user with additional information they need to perform a given task. Just like our brain is responsible for communicating with other parts of our body, coding is used to assist databases in communicating effectively with its users. Are you interested in learning more about Oracle systems, how they work, and how you can leverage these systems to advance your business goals? Check out our Oracle Database Associate Certificate! Page 3
Chapter 4 : Relational database - Wikipedia Inside Relational Databases was first published in and, rather to our surprise, rapidly reached the status of a classic work in the database field. Translated into three other languages and sold all over the world, it has helped thousands of people to understand the relational model that. Relation database and Table database A relation is defined as a set of tuples that have the same attributes. A tuple usually represents an object and information about that object. Objects are typically physical objects or concepts. A relation is usually described as a table, which is organized into rows and columns. All the data referenced by an attribute are in the same domain and conform to the same constraints. The relational model specifies that the tuples of a relation have no specific order and that the tuples, in turn, impose no order on the attributes. Applications access data by specifying queries, which use operations such as select to identify tuples, project to identify attributes, and join to combine relations. Relations can be modified using the insert, delete, and update operators. New tuples can supply explicit values or be derived from a query. Similarly, queries identify tuples for updating or deleting. Tuples by definition are unique. If the tuple contains a candidate or primary key then obviously it is unique; however, a primary key need not be defined for a row or record to be a tuple. The definition of a tuple requires that it be unique, but does not require a primary key to be defined. Because a tuple is unique, its attributes by definition constitute a superkey. Base and derived relations[ edit ] Main articles: Relvar and View database In a relational database, all data are stored and accessed via relations. Relations that store data are called "base relations", and in implementations are called "tables". Other relations do not store data, but are computed by applying relational operations to other relations. These relations are sometimes called "derived relations". In implementations these are called " views " or "queries". Derived relations are convenient in that they act as a single relation, even though they may grab information from several relations. Also, derived relations can be used as an abstraction layer. Mathematically, attaching a domain to an attribute means that any value for the attribute must be an element of the specified set. The character string "ABC", for instance, is not in the integer domain, but the integer value is. Another example of domain describes the possible values for the field "CoinFace" as "Heads","Tails". So, the field "CoinFace" will not accept input values like 0,1 or H,T. Constraints[ edit ] Constraints make it possible to further restrict the domain of an attribute. For instance, a constraint can restrict a given integer attribute to values between 1 and Constraints provide one method of implementing business rules in the database and support subsequent data use within the application layer. SQL implements constraint functionality in the form of check constraints. Constraints restrict the data that can be stored in relations. These are usually defined using expressions that result in a boolean value, indicating whether or not the data satisfies the constraint. Constraints can apply to single attributes, to a tuple restricting combinations of attributes or to an entire relation. Since every attribute has an associated domain, there are constraints domain constraints. The two principal rules for the relational model are known as entity integrity and referential integrity. Unique key A primary key uniquely specifies a tuple within a table. In order for an attribute to be a good primary key it must not repeat. While natural attributes attributes used to describe the data being entered are sometimes good primary keys, surrogate keys are often used instead. A surrogate key is an artificial attribute assigned to an object which uniquely identifies it for instance, in a table of information about students at a school they might all be assigned a student ID in order to differentiate them. The surrogate key has no intrinsic inherent meaning, but rather is useful through its ability to uniquely identify a tuple. Another common occurrence, especially in regard to N: M cardinality is the composite key. A composite key is a key made up of two or more attributes within a table that together uniquely identify a record. For example, in a database relating students, teachers, and classes. Classes could be uniquely identified by a composite key of their room number and time slot, since no other class could have exactly the same combination of attributes. In fact, use of a composite key such as this can be a form of data verification, albeit a weak one. Foreign key A foreign key is a field in a relational table that matches the primary key column of another table. The foreign key can be used to cross-reference tables. Foreign keys do not need to have unique values in the referencing relation. Foreign keys effectively use Page 4
the values of attributes in the referenced relation to restrict the domain of one or more attributes in the referencing relation. A foreign key could be described formally as: Stored procedure A stored procedure is executable code that is associated with, and generally stored in, the database. Stored procedures usually collect and customize common operations, like inserting a tuple into a relation, gathering statistical information about usage patterns, or encapsulating complex business logic and calculations. Frequently they are used as an application programming interface API for security or simplicity. Stored procedures are not part of the relational database model, but all commercial implementations include them. Index database An index is one way of providing quicker access to data. Indexes can be created on any combination of attributes on a relation. Queries that filter using those attributes can find matching tuples randomly using the index, without having to check each tuple in turn. This is analogous to using the index of a book to go directly to the page on which the information you are looking for is found, so that you do not have to read the entire book to find what you are looking for. Relational databases typically supply multiple indexing techniques, each of which is optimal for some combination of data distribution, relation size, and typical access pattern. Indices are usually not considered part of the database, as they are considered an implementation detail, though indices are usually maintained by the same group that maintains the other parts of the database. The use of efficient indexes on both primary and foreign keys can dramatically improve query performance. This is because B-tree indexes result in query times proportional to log n where n is the number of rows in a table and hash indexes result in constant time queries no size dependency as long as the relevant part of the index fits into memory. Relational algebra Queries made against the relational database, and the derived relvars in the database are expressed in a relational calculus or a relational algebra. In his original relational algebra, Codd introduced eight relational operators in two groups of four operators each. The first four operators were based on the traditional mathematical set operations: The union operator combines the tuples of two relations and removes all duplicate tuples from the result. The intersection operator produces the set of tuples that two relations share in common. The difference operator acts on two relations and produces the set of tuples from the first relation that do not exist in the second relation. The cartesian product of two relations is a join that is not restricted by any criteria, resulting in every tuple of the first relation being matched with every tuple of the second relation. The cartesian product is implemented in SQL as the Cross join operator. The remaining operators proposed by Codd involve special operations specific to relational databases: The selection, or restriction, operation retrieves tuples from a relation, limiting the results to only those that meet a specific criterion, i. The projection operation extracts only the specified attributes from a tuple or set of tuples. The join operation defined for relational databases is often referred to as a natural join. In this type of join, two relations are connected by their common attributes. The relational division operation is a slightly more complex operation and essentially involves using the tuples of one relation the dividend to partition a second relation the divisor. The relational division operator is effectively the opposite of the cartesian product operator hence the name. Database normalization Normalization was first proposed by Codd as an integral part of the relational model. It encompasses a set of procedures designed to eliminate non-simple domains non-atomic values and the redundancy duplication of data, which in turn prevents data manipulation anomalies and loss of data integrity. The most common forms of normalization applied to databases are called the normal forms. Chapter 5 : Join (SQL) - Wikipedia Databases are designed to model the real world 74 Chapter 12 # Getting the data into the correct tables 75 Not normalization (and not ER modeling either) Chapter 6 : Library Resource Finder: Staff View for: Inside relational databases with example The second edition of this best-seller is revised and updated. It delivers a reader-friendly explanation of the relational model and its importance to database designers and builders. Clear explanations make use of examples rather than equations, and show how an understanding of the relational model. Page 5
Chapter 7 : What are relational databases? HowStuffWorks Inside Relational Databases with Examples in Access / Edition 1 The first two editions of Inside Relational Databases have both been best sellers. These new editions will also cover the relational database model but will use different engines to illustrate the model. Chapter 8 : Inside Relational Databases : Bill Marklyn : Synopsis. The second edition of the best-selling Inside Relational Databasesis revised and updated to bring you the most reader-friendly explanation of the relational model and its importance to database designers and builders. Chapter 9 : Inside the Mind of an Oracle Relational Database Databases have been a staple of business computing from the very beginning of the digital era. In fact, the relational database was born in when E.F. Codd, a researcher at IBM, wrote a paper outlining the process. Since then, relational databases have grown in popularity to become the standard. Page 6