Rahul Batra - SQL Primer: An Accelerated Introduction to SQL Basics
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Build a core level of competency in SQL so you can recognize the parts of queries and write simple SQL statements. SQL knowledge is essential for anyone involved in programming, data science, and data management. This book covers features of SQL that are standardized and common across most database vendors. You will gain a base of knowledge that will prepare you to go deeper into the specifics of any database product you might encounter.
Examples in the book are worked in PostgreSQL and SQLite, but the bulk of the examples are platform agnostic and will work on any database platform supporting SQL. Early in the book you learn about table design, the importance of keys as row identifiers, and essential query operations. You then move into more advanced topics such as grouping and summarizing, creating calculated fields, joining data from multiple tables when it makes business sense to do so, and more. Throughout the book, you are exposed to a set-based approach to the language and are provided a good grounding in subtle but important topics such as the effects of null value on query results. With the explosion of data science, SQL has regained its prominence as a top skill to have for technologists and decision makers worldwide. SQL Primer will guide you from the very basics of SQL through to the mainstream features you need to have a solid, working knowledge of this important, data-oriented language.
What Youll Learn
Anyone new to SQL who is looking for step-by-step guidance toward understanding and writing SQL queries. The book is aimed at those who encounter SQL statements often in their work, and provides a sound baseline useful across all SQL database systems. Programmers, database managers, data scientists, and business analysts all can benefit from the baseline of SQL knowledge provided in this book.
Examples in the book are worked in PostgreSQL and SQLite, but the bulk of the examples are platform agnostic and will work on any database platform supporting SQL. Early in the book you learn about table design, the importance of keys as row identifiers, and essential query operations. You then move into more advanced topics such as grouping and summarizing, creating calculated fields, joining data from multiple tables when it makes business sense to do so, and more. Throughout the book, you are exposed to a set-based approach to the language and are provided a good grounding in subtle but important topics such as the effects of null value on query results. With the explosion of data science, SQL has regained its prominence as a top skill to have for technologists and decision makers worldwide. SQL Primer will guide you from the very basics of SQL through to the mainstream features you need to have a solid, working knowledge of this important, data-oriented language.
What Youll Learn
- Create and populate your own database tables
- Read SQL queries and understand what they are doing
- Execute queries that get correct results
- Bring together related rows from multiple tables
- Group and sort data in support of reporting applications
- Get a grip on nulls, normalization, and other key concepts
- Employ subqueries, unions, and other advanced features
Anyone new to SQL who is looking for step-by-step guidance toward understanding and writing SQL queries. The book is aimed at those who encounter SQL statements often in their work, and provides a sound baseline useful across all SQL database systems. Programmers, database managers, data scientists, and business analysts all can benefit from the baseline of SQL knowledge provided in this book.
Rahul Batra: author's other books
Who wrote SQL Primer: An Accelerated Introduction to SQL Basics? Find out the surname, the name of the author of the book and a list of all author's works by series.
Alex Bolenok
Shaik Baji
Itzik Ben-Gan
Kevin Languedoc
Ibrar Ahmed
Alan Beaulieu
Ben Forta
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Rahul Batra 2018
Rahul Batra SQL Primer1. An Introduction to SQL
Rahul Batra 1
(1)
Gurgaon, Haryana, India
Modern society is driven by data. Whether it is at a personal level, like a notebook containing scribbled notes; or at a countrywide level like Census data, it has permeated all our workflows. There is always a growing need to efficiently store and organize it so that meaningful information can be extracted out of raw data.
A database is nothing but a collection of organized data. It doesnt have to be in a digital format to be called a database. A telephone directory is a good example, which stores data about people and organizations with a contact number. A to-do list is also a rudimentary form of a database. With ever-larger amounts of data being collected about even the most mundane of processes, digital databases have become increasingly important since their inception in the 1960s.
Software that is used to manage a digital database is called a Database Management System (DBMS) . When you hear someone talking about PostgreSQL or MySQL , they are referring to a DBMS. A database is what is created when you use the DBMS software to store data about topics that make sense to you or your organization. For example, your company may use PostgreSQL to store inventory information about cellular phones the product that you sell. In this case, you have created an inventory database using PostgreSQL as your DBMS.
The Relational Model and SQL
Data comes in myriad shapes and sizes, and every context generates data in a different way. The data generated by a bank keeping a record of account balances is different from keeping track of members of a family tree. But for a DBMS to provide uniform data management and reporting capabilities, we must adhere to a data organization structure or data model .
The most prevalent database organizational model is the Relational Model , developed by Dr. E. F. Codd in his groundbreaking research paper A Relational Model of Data for Large Shared Data Banks in 1970. In this model, the data to be stored is organized in a tabular format with rows and columns. Each row inside a table represents a distinct record with the column headings specifying the corresponding type of data stored. This is not unlike a spreadsheet where the first row can be thought of as column headings and the subsequent rows storing the actual data.
A database would typically consist of more than one table, each with different column headings. There may be certain columns that are common between tables, but this is a topic we will approach later in the book.
Question
What does the word relational in relational database mean?
It is a common misconception that the word relational implies a relationship between the tables. A relation is a mathematical term that is roughly equivalent to a table itself. When used in conjunction with the word database, we mean to say that this particular system arranges data in a tabular fashion.
A possible origin of this misconception might have been the set relation command in dBase , a DBMS from the 1980s. That command indeed was used to create linkages between tables, but it has nothing to do with relational theory.
SQL stands for Structured Query Language , and it is the de facto standard for interacting with relational databases. Almost all database management systems youll come across will have an SQL implementation. SQL was standardized by the American National Standards Institute (ANSI) in 1986 and has undergone many revisions, most notably in 1992 and 1999. However, all DBMSs do not strictly adhere to the standard defined but rather remove some features and add others to provide a unique feature set. Nonetheless, the standardization process has been helpful in giving a uniform direction to the vendors in terms of their database interaction language.
While SQL is a computer language, it is not like the other programming languages that you may have heard of like Python or C. Such programming languages are generic in nature, suitable for a wide variety of tasks from programming basic calculating systems to advanced simulation models. SQL is a special purpose query language meant for interacting with relational databases. It has no use other than this context.
This does not mean that it is the only database query language to exist. In the 1980s, another language called QUEL from Ingres was fairly popular, but the standardization effort around SQL cemented its position. In recent years, we have seen a large number of non-relational databases being developed under the umbrella term of NoSQL . Most of their query languages, however, bear some resemblance to SQL even though their data model varies significantly from the relational model.
Advantages of Using SQL
- It is standardized no matter which relational database you choose, it will have an SQL query interpreter built in. The sheer popularity of SQL makes it worth everyones time who interacts with a data system.
- It has a reasonable English-like syntax. None of the painstaking detail of programming languages like C or Java have to be specified when using SQL. It is concise, easy to understand, and easy to write database queries with. It is declarative in nature, meaning you only have to declare what you want to achieve rather than going over the steps to achieve the results.
- It allows a uniform way to query and administer a relational database. Many of the database administration commands are standard SQL commands making the transfer of skills much easier.
- It is mature SQL has been around for over 35 years. While many new features have been added to it, the core of SQL has largely been unchanged. You can derive a lot of utility knowing a few basic SQL concepts and commands, and they will serve you well into the future.
SQL Commands Classification
SQL is a language for interacting with databases. It consists of a number of commands with further options to allow you to carry out your operations with a database. While DBMSs differ in the command subset they provide, usually you would find the classifications below.
- Data Definition Language (DDL) : CREATE TABLE, ALTER TABLE, DROP TABLE , etc. These commands allow you to create or modify your database structure.
- Data Manipulation Language (DML) : INSERT, UPDATE, DELETE . These commands are used to manipulate data stored inside your database.
- Data Query Language (DQL) : SELECT . Used for querying or selecting a subset of data from a database.
- Data Control Language (DCL) : GRANT, REVOKE , etc. Used for controlling access to data within a database, commonly used for granting user privileges.
- Transaction Control Commands : COMMIT, ROLLBACK , etc. Used for managing groups of statements as a unit of work.
Besides these, your database management system may give you other sets of commands to work more efficiently or to provide extra features. But it is safe to say that the ones above would be present in almost all DBMSs you encounter.
Explaining Tables
A table in a relational database is nothing but a two-dimensional matrix of data where the columns describe the type of data, and the row contains the actual data to be stored. Have a look at Table to get a sense of the visualization of a table in a database.
Table 1-1
A Table Describing Programming Languages
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