70.119
Style Recommendations for SQL

Overview

This lesson summarizes common practices for building SQL statements and creating SQL scripts. The guideslines are recommended and not prescriptive and individual development teams generally have their own guidelines.

The recommendations in this lesson are based on SQL Style Guide¹.

Recommendations

You are encouraged to:

• use consistent and descriptive identifiers and names for columns, tables, and aliases using CamelCase rather than underscores.
• use white space and indentation to make code easier to read.
• use ISO 8601 compliant time and date information (YYYY-MM-DD HH:MM:SS.SSSSS) and not store time and dates as character string (varchar or text).
• construct SQL statements using standard SQL rather than vendor-specific functions to increase portability to other databases.
• keep code succinct; avoid unnecessary quotes, backticks, parenthesis or conditions.
• include explanations in SQL scripts where helpful to make the intent clear.
• names tables using the common plural form on nouns, e.g., Staff or Transaction rather than Employee or Sale.

When possible, avoid:

• descriptive prefixes or Hungarian notation such as sp_ or tbl.
• using dot (.) in identifiers and table names.
• quoted identifiers

Naming conventions

• Ensure that identifiers and table names are unique and are not the same as a reserved keyword; if a keyword is necessary use backticks to “escape the keyword” meaning, e.g., `table` would be a valid (although unusual) identifier for a table name.
• Keep identifiers and table names short, abbreviate as appropriate, and do not exceed 30 characters for compatibility with older databases.
• Identifiers must begin with a letter and may not end with an underscore.
• Use only letters, digits and underscores in names.
• Avoid consecutive underscores.
• Use either underscores where you would naturally include a space in the name (first name becomes first_name) or use CamelCase (FirstName) but, above all be consistent.
• Avoid abbreviations, but if you need them make sure they are commonly understood.
• Use names that are meaningful for tables and columns.
• Name tables in the plural and columns in the sigular.
• Make column names lower case.
• Do not add the table name to columns, e.g. use name instead of employeeName for a column in the table employee.

Aliasing or correlations Should relate in some way to the object or expression they are aliasing. As a rule of thumb the correlation name should be the first letter of each word in the object’s name. If there is already a correlation with the same name then append a number. Always include the AS keyword—makes it easier to read as it is explicit. For computed data (SUM() or AVG()) use the name you would give it were it a column defined in the schema. SELECT first_name AS fn FROM staff AS s1 JOIN students AS s2 ON s2.mentor_id = s1.staff_num; SELECT SUM(s.monitor_tally) AS monitor_total FROM staff AS s; Stored procedures The name must contain a verb. Do not prefix with sp_ or any other such descriptive prefix or Hungarian notation. Uniform suffixes The following suffixes have a universal meaning ensuring the columns can be read and understood easily from SQL code. Use the correct suffix where appropriate.

_id—a unique identifier such as a column that is a primary key. _status—flag value or some other status of any type such as publication_status. _total—the total or sum of a collection of values. _num—denotes the field contains any kind of number. _name—signifies a name such as first_name. _seq—contains a contiguous sequence of values. _date—denotes a column that contains the date of something. _tally—a count. _size—the size of something such as a file size or clothing. _addr—an address for the record could be physical or intangible such as ip_addr. Query syntax Reserved words Always use uppercase for the reserved keywords like SELECT and WHERE.

It is best to avoid the abbreviated keywords and use the full length ones where available (prefer ABSOLUTE to ABS).

Do not use database server specific keywords where an ANSI SQL keyword already exists performing the same function. This helps to make the code more portable.

SELECT model_num FROM phones AS p WHERE p.release_date > ‘2014-09-30’; White space To make the code easier to read it is important that the correct complement of spacing is used. Do not crowd code or remove natural language spaces.

Spaces Spaces should be used to line up the code so that the root keywords all end on the same character boundary. This forms a river down the middle making it easy for the readers eye to scan over the code and separate the keywords from the implementation detail. Rivers are bad in typography (Links to an external site.), but helpful here.

(SELECT f.species_name, AVG(f.height) AS average_height, AVG(f.diameter) AS average_diameter FROM flora AS f WHERE f.species_name = ‘Banksia’ OR f.species_name = ‘Sheoak’ OR f.species_name = ‘Wattle’ GROUP BY f.species_name, f.observation_date)

UNION ALL

(SELECT b.species_name, AVG(b.height) AS average_height, AVG(b.diameter) AS average_diameter FROM botanic_garden_flora AS b WHERE b.species_name = ‘Banksia’ OR b.species_name = ‘Sheoak’ OR b.species_name = ‘Wattle’ GROUP BY b.species_name, b.observation_date); Notice that SELECT, FROM, etc. are all right aligned while the actual column names and implementation-specific details are left aligned.

Although not exhaustive always include spaces:

before and after equals (=) after commas (,) surrounding apostrophes (‘) where not within parentheses or with a trailing comma or semicolon. SELECT a.title, a.release_date, a.recording_date FROM albums AS a WHERE a.title = ’Charcoal Lane’ OR a.title = ‘The New Danger’; Line spacing Always include newlines/vertical space:

before AND or OR after semicolons to separate queries for easier reading after each keyword definition after a comma when separating multiple columns into logical groups to separate code into related sections, which helps to ease the readability of large chunks of code. Keeping all the keywords aligned to the righthand side and the values left aligned creates a uniform gap down the middle of the query. It also makes it much easier to to quickly scan over the query definition.

INSERT INTO albums (title, release_date, recording_date) VALUES (‘Charcoal Lane’, ‘1990-01-01 01:01:01.00000’, ‘1990-01-01 01:01:01.00000’), (‘The New Danger’, ‘2008-01-01 01:01:01.00000’, ‘1990-01-01 01:01:01.00000’); UPDATE albums SET release_date = ‘1990-01-01 01:01:01.00000’ WHERE title = ‘The New Danger’; SELECT a.title, a.release_date, a.recording_date, a.production_date – grouped dates together FROM albums AS a WHERE a.title = ‘Charcoal Lane’ OR a.title = ‘The New Danger’; Indentation To ensure that SQL is readable it is important that standards of indentation are followed.

Joins Joins should be indented to the other side of the river and grouped with a new line where necessary.

SELECT r.last_name FROM riders AS r INNER JOIN bikes AS b ON r.bike_vin_num = b.vin_num AND b.engine_tally > 2

   INNER JOIN crew AS c
   ON r.crew_chief_last_name = c.last_name
      AND c.chief = 'Y';

Subqueries Subqueries should also be aligned to the right side of the river and then laid out using the same style as any other query. Sometimes it will make sense to have the closing parenthesis on a new line at the same character position as its opening partner—this is especially true where you have nested subqueries.

SELECT r.last_name, (SELECT MAX(YEAR(championship_date)) FROM champions AS c WHERE c.last_name = r.last_name AND c.confirmed = ‘Y’) AS last_championship_year FROM riders AS r WHERE r.last_name IN (SELECT c.last_name FROM champions AS c WHERE YEAR(championship_date) > ‘2008’ AND c.confirmed = ‘Y’); Preferred formalisms Make use of BETWEEN where possible instead of combining multiple statements with AND. Similarly use IN() instead of multiple OR clauses. Where a value needs to be interpreted before leaving the database use the CASE expression. CASE statements can be nested to form more complex logical structures. Avoid the use of UNION clauses and temporary tables where possible. If the schema can be optimised to remove the reliance on these features then it most likely should be. SELECT CASE postcode WHEN ‘BN1’ THEN ‘Brighton’ WHEN ‘EH1’ THEN ‘Edinburgh’ END AS city FROM office_locations WHERE country = ‘United Kingdom’ AND opening_time BETWEEN 8 AND 9 AND postcode IN (‘EH1’, ‘BN1’, ‘NN1’, ‘KW1’); Create syntax When declaring schema information it is also important to maintain human-readable code. To facilitate this ensure that the column definitions are ordered and grouped together where it makes sense to do so.

Indent column definitions by four (4) spaces within the CREATE definition.

Choosing data types Where possible do not use vendor-specific data types—these are not portable and may not be available in older versions of the same vendor’s software. Only use REAL or FLOAT types where it is strictly necessary for floating point mathematics otherwise prefer NUMERIC and DECIMAL at all times. Floating point rounding errors are a nuisance! Specifying default values The default value must be the same type as the column—if a column is declared a DECIMAL do not provide an INTEGER default value. Default values must follow the data type declaration and come before any NOT NULL statement. Constraints and keys Constraints and their subset, keys, are a very important component of any database definition. They can quickly become very difficult to read and reason about though so it is important that a standard set of guidelines are followed.

Choosing keys Deciding the column(s) that will form the keys in the definition should be a carefully considered activity as it will effect performance and data integrity.

The key should be unique to some degree. Consistency in terms of data type for the value across the schema and a lower likelihood of this changing in the future. Can the value be validated against a standard format (such as one published by ISO)? Encouraging conformity to point 2. Keeping the key as simple as possible whilst not being scared to use compound keys where necessary. It is a reasoned and considered balancing act to be performed at the definition of a database. Should requirements evolve in the future it is possible to make changes to the definitions to keep them up to date.

Defining constraints Once the keys are decided it is possible to define them in the system using constraints along with field value validation.

General Tables must have at least one key to be complete and useful. Constraints should be given a custom name excepting UNIQUE, PRIMARY KEY and FOREIGN KEY where the database vendor will generally supply sufficiently intelligible names automatically. Layout and order Specify the primary key first right after the CREATE TABLE statement. Constraints should be defined directly beneath the column they correspond to. Indent the constraint so that it aligns to the right of the column name. If it is a multi-column constraint then consider putting it as close to both column definitions as possible and where this is difficult as a last resort include them at the end of the CREATE TABLE definition. If it is a table-level constraint that applies to the entire table then it should also appear at the end. Use alphabetical order where ON DELETE comes before ON UPDATE. If it make senses to do so align each aspect of the query on the same character position. For example all NOT NULL definitions could start at the same character position. This is not hard and fast, but it certainly makes the code much easier to scan and read. Validation Use LIKE and SIMILAR TO constraints to ensure the integrity of strings where the format is known. Where the ultimate range of a numerical value is known it must be written as a range CHECK() to prevent incorrect values entering the database or the silent truncation of data too large to fit the column definition. In the least it should check that the value is greater than zero in most cases. CHECK() constraints should be kept in separate clauses to ease debugging. Example CREATE TABLE staff ( PRIMARY KEY (staff_num), staff_num INT(5) NOT NULL, first_name VARCHAR(100) NOT NULL, pens_in_drawer INT(2) NOT NULL, CONSTRAINT pens_in_drawer_range CHECK(pens_in_drawer BETWEEN 1 AND 99) ); Designs to avoid Object-oriented design principles do not effectively translate to relational database designs—avoid this pitfall. Placing the value in one column and the units in another column. The column should make the units self-evident to prevent the requirement to combine columns again later in the application. Use CHECK() to ensure valid data is inserted into the column. Entity–Attribute–Value (Links to an external site.) (EAV) tables—use a specialist product intended for handling such schema-less data instead. Splitting up data that should be in one table across many tables because of arbitrary concerns such as time-based archiving or location in a multinational organisation. Later queries must then work across multiple tables with UNION rather than just simply querying one table.

See Also

TBD

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Files & Resources

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References

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