Phases of SQL system development
In developing any system, you start at the beginning and go through to the end, and it’s no different with SQL. The following list shows you what to consider at each phase of the SQL development life cycle:
- Definition phase: Precisely define the problem to be solved, its magnitude, and who will work on it.
- Requirements phase: Develop a detailed description of exactly what the development effort will produce. Gather all relevant information and put it into a requirements document (Statement of Requirements). Get client signoff.
- Evaluation phase: Determine exactly how you will meet the requirements. What tools will you use? How will you deploy your development team? Determine whether the job is doable within time and budget constraints.
- Design phase: Create a database model and then design a database and database application that satisfy the terms of the requirements document.
- Implementation phase: Build the database and the database application. Include copious documentation within the code and in external documents.
- Final documentation and testing phase: Give the database and application a tough workout. Hit the system with every conceivable input condition and a few inconceivable ones. Try to overload it. See where it breaks. When it breaks, send it back to the implementers or even back to the designers. Document everything.
- Maintenance phase: Fix latent bugs as they arise. Provide updates and enhancements called for by the client.
SQL criteria for normal forms
In SQL, normal forms are defining characteristics of relational databases. SQL forms get classified according to the types of modification anomalies they’re subject to. First, second, and third normal forms (1NF, 2NF, 3NF) serve as remedies to the three main sources of modification anomalies.
The normal forms are nested in the sense that a table that’s in 2NF is automatically also in 1NF. Similarly, a table in 3NF is automatically in 2NF, and so on. For most practical applications, putting a database in 3NF is sufficient to ensure a high degree of integrity. To be absolutely sure of its integrity, you must put the database into DK/NF.
The following lists lay out the criteria for each form:
First Normal Form (1NF):
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Table must be two-dimensional, with rows and columns.
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Each row contains data that pertains to one thing or one portion of a thing.
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Each column contains data for a single attribute of the thing being described.
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Each cell (intersection of row and column) of the table must be single-valued.
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All entries in a column must be of the same kind.
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Each column must have a unique name.
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No two rows may be identical.
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The order of the columns and of the rows does not matter.
Second Normal Form (2NF):
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Table must be in first normal form (1NF).
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All non-key attributes (columns) must be dependent on the entire key.
Third Normal Form (3NF):
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Table must be in second normal form (2NF).
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Table has no transitive dependencies.
Domain-Key Normal Form (DK/NF):
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Every constraint on the table is a logical consequence of the definition of keys and domains.
SQL data types
Depending on their histories, different SQL implementations support a variety of data types. The SQL specification recognizes nine predefined general types, shown in the lists below
Exact numerics:
-
INTEGER
-
SMALLINT
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BIGINT
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NUMERIC
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DECIMAL
- DECFLOAT
Approximate numerics:
-
REAL
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DOUBLE PRECISION
-
FLOAT
Boolean:
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BOOLEAN
Character strings:
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CHARACTER (CHAR)
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CHARACTER VARYING (VARCHAR)
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NATIONAL CHARACTER (NCHAR)
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NATIONAL CHARACTER VARYING (NVARCHAR)
Datetimes:
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DATE
-
TIME
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TIMESTAMP
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TIME WITH TIMEZONE
-
TIMESTAMP WITH TIMEZONE
Intervals:
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INTERVAL DAY
-
INTERVAL YEAR
Large objects:
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BLOB
-
CLOB
Collection types:
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ARRAY
-
MULTISET
Other types:
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ROW
-
XML
- JSON
SQL value functions
These SQL value functions perform operations on data. There are all kinds of operations that could conceivably be performed on data items, but these are some that are needed most often.
String value functions
| Function | Effect |
|---|---|
| SUBSTRING | Extracts a substring from a source string |
| SUBSTRING SIMILAR | Extracts a substring from a source string, using POSIX-based regular expressions |
| SUBSTRING_REGEX | Extracts from a string the first occurrence of an XQuery regular expression pattern and returns one occurrence of the matching substring |
| TRANSLATE_REGEX | Extracts from a string the first or every occurrence of an XQuery regular expression pattern and replaces it or them with an XQuery replacement string |
| UPPER | Converts a character string to all uppercase |
| LOWER | Converts a character string to all lowercase |
| BTRIM | Trims multiple characters both before and after the text |
| LTRIM | Trims multiple characters to the left of the text |
| RTRIM | Trims multiple characters to the right of the text |
| TRIM | Trims off leading or trailing blanks |
| LPAD | Adds padding characters to the left of the text |
| RPAD | Adds padding characters to the right of the text |
| TRANSLATE | Transforms a source string from one character set to another |
| CONVERT | Transforms a source string from one character set to another |
Numeric value functions
| Function | Effect |
|---|---|
| POSITION | Returns the starting position of a target string within a source string |
| CHARACTER_LENGTH | Returns the number of characters in a string |
| OCTET_LENGTH | Returns the number of octets (bytes) in a character string |
| EXTRACT | Extracts a single field from a datetime or interval |
Datetime value functions
| Function | Effect |
|---|---|
| CURRENT_DATE | Returns the current date |
| CURRENT_TIME(p) | Returns the current time; (p) is precision of seconds |
| CURRENT_TIMESTAMP(p) | Returns the current date and the current time; (p) is precision of seconds |
SQL set functions
The SQL set functions give you a quick answer to questions you may have about the characteristics of your data as a whole. How many rows does a table have? What is the highest value in the table? What is the lowest? These are the kinds of questions that the SQL set functions can answer for you.
| Function | Effect |
|---|---|
COUNT |
Returns the number of rows in the specified table |
MAX |
Returns the maximum value that occurs in the specified able |
MIN |
Returns the minimum value that occurs in the specified table |
SUM |
Adds up the values in a specified column |
AVG |
Returns the average of all the values in the specified column |
ANY_VALUE |
Returns a random value from a specified set of data |
GREATEST |
Returns the largest value from a specified set of data |
LEAST |
Returns the smallest value from a specified set of data |
LISTAGG |
Transforms values from a group of rows into a delimited string |
Trigonometric and logarithmic functions
sin, cos, tan, asin, acos, atan, sinh, cosh, tanh, log(<base>, <value>), log10(<value>). ln( <value>)
JSON constructor functions
JSON_OBJECT
JSON_ARRAY
JSON_OBJECTAGG
JSON_ARRAYAGG
JSON query functions
JSON_EXISTS
JSON_VALUE
JSON_QUERY
JSON_TABLE
SQL WHERE clause predicates
Predicates boil down to either a TRUE or a FALSE result. You can filter out unwanted rows from the result of an SQL query by applying a WHERE clause whose predicate excludes the unwanted rows.
Comparison predicates
| = | Equal |
| <> | Not equal |
| < | Less than |
| <= | Less than or equal |
| > | Greater than |
| >= | Greater than or equal |
Other predicates
| ALL | BETWEEN |
| DISTINCT | EXISTS |
| IN | LIKE |
| MATCH | NOT IN |
| NOT LIKE | NULL |
| OVERLAPS | SOME, ANY |
| UNIQUE |