by Markus Winand.

SQLite Example Scripts for “The Where Clause”


The Equals Operator

Surrogate Keys

Creating the EMPLOYEES table with 1000 rows.

CREATE TABLE employees (
   employee_id   NUMERIC      NOT NULL,
   first_name    VARCHAR(255) NOT NULL,
   last_name     VARCHAR(255) NOT NULL,
   date_of_birth DATE                 ,
   phone_number  VARCHAR(255) NOT NULL,
   junk          CHAR(255)            ,
   CONSTRAINT employees_pk PRIMARY KEY (employee_id)
);
CREATE VIEW generator_16
AS SELECT 0 n UNION ALL SELECT 1  UNION ALL SELECT 2  UNION ALL
   SELECT 3   UNION ALL SELECT 4  UNION ALL SELECT 5  UNION ALL
   SELECT 6   UNION ALL SELECT 7  UNION ALL SELECT 8  UNION ALL
   SELECT 9   UNION ALL SELECT 10 UNION ALL SELECT 11 UNION ALL
   SELECT 12  UNION ALL SELECT 13 UNION ALL SELECT 14 UNION ALL
   SELECT 15;
CREATE VIEW generator_256
AS SELECT ( ( hi.n << 4 ) | lo.n ) AS n
     FROM generator_16 lo, generator_16 hi;
CREATE VIEW generator_4k
AS SELECT ( ( hi.n << 8 ) | lo.n ) AS n
     FROM generator_256 lo, generator_16 hi;
CREATE VIEW generator_64k
AS SELECT ( ( hi.n << 8 ) | lo.n ) AS n
     FROM generator_256 lo, generator_256 hi;
INSERT INTO employees (employee_id,  first_name,
                       last_name,    date_of_birth, 
                       phone_number, junk)
SELECT gen.n +1,
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       DATE('now', '-' || (abs(random()) % 3650 + 40*365) || ' day'),
       ABS(RANDOM())%9000+1000,
       printf('%.1000c','x')
  FROM generator_4k gen
 WHERE gen.n < 1000;
UPDATE employees 
   SET first_name='MARKUS', 
       last_name='WINAND'
 WHERE employee_id=123;
ANALYZE employees;

Note:

  • The GENERATOR_X views are row generators as described in the MySQL Row Generator article. In the meanwhile, SQLite supports the recursive WITH clause (since 3.8.3) but this approach works with even older versions of SQLite.

  • The JUNK column is used to have a realistic row length. Without this column the table would become unrealistically small and some demonstrations would not work.

  • Random data is filled into the table, with exception to my entry, that is updated after the insert.

  • Table and index statistics are gathered so that the optimizer knows a little bit about the table’s content.

Concatenated Keys

DROP TABLE employees;
CREATE TABLE employees (
   employee_id   NUMERIC      NOT NULL,
   first_name    VARCHAR(255) NOT NULL,
   last_name     VARCHAR(255) NOT NULL,
   date_of_birth DATE                 ,
   phone_number  VARCHAR(255) NOT NULL,
   junk          CHAR(255)            ,
   subsidiary_id NUMERIC      NOT NULL,
   CONSTRAINT employees_pk PRIMARY KEY (employee_id, subsidiary_id)
);
INSERT INTO employees (employee_id,  first_name,
                       last_name,    date_of_birth, 
                       phone_number, junk, subsidiary_id)
SELECT gen.n +1,
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       DATE('now', '-' || (abs(random()) % 3650 + 40*365) || ' day'),
       ABS(RANDOM())%9000+1000,
       printf('%.1000c','x'),
       30
  FROM generator_4k gen
 WHERE gen.n < 1000;
UPDATE employees 
   SET first_name='MARKUS', 
       last_name='WINAND'
 WHERE employee_id=123
   AND subsidiary_id=30;
-- generate more records (Very Big Company)
INSERT INTO employees (employee_id,  first_name, 
                       last_name,    date_of_birth, 
                       phone_number, subsidiary_id, junk)
SELECT gen.n + 1,
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       DATE('now', '-' || (abs(random()) % 3650 + 40*365) || ' day'),
       ABS(RANDOM())%9000+1000,
       CAST(ABS(RANDOM())%(gen.n/9000.0 * 29 + 1) + 1 AS INTEGER),
       printf('%.10c','x')
  FROM generator_64k gen
 WHERE gen.n < 9000;
ANALYZE employees;

Notes:

  • As SQLite cannot change primary keys using ALTER TABLE, the entire table is dropped and recreated.

  • The new primary key includes by the SUBSIDIARY_ID; that is, the EMPLOYEE_ID remains in the first position.

  • The new records are randomly assigned to the subsidiaries 1 through 29.

  • The table and index are analyzed again to make the optimizer aware of the grown data volume.

The next script introduces the index on SUBSIDIARY_ID to support the query for all employees of one particular subsidiary:

CREATE INDEX emp_sub_id ON employees(subsidiary_id)

Although that gives decent performance, it’s better to use the index that supports the primary key:

DROP TABLE employees;
CREATE TABLE employees (
   employee_id   NUMERIC      NOT NULL,
   first_name    VARCHAR(255) NOT NULL,
   last_name     VARCHAR(255) NOT NULL,
   date_of_birth DATE                 ,
   phone_number  VARCHAR(255) NOT NULL,
   junk          CHAR(255)            ,
   subsidiary_id NUMERIC      NOT NULL,
   CONSTRAINT employees_pk PRIMARY KEY (subsidiary_id, employee_id)
);
INSERT INTO employees (employee_id,  first_name,
                       last_name,    date_of_birth, 
                       phone_number, junk, subsidiary_id)
SELECT gen.n +1,
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       DATE('now', '-' || (abs(random()) % 3650 + 40*365) || ' day'),
       ABS(RANDOM())%9000+1000,
       printf('%.1000c','x'),
       30
  FROM generator_4k gen
 WHERE gen.n < 1000;
UPDATE employees 
   SET first_name='MARKUS', 
       last_name='WINAND'
 WHERE employee_id=123
   AND subsidiary_id=30;
-- generate more records (Very Big Company)
INSERT INTO employees (employee_id,  first_name, 
                       last_name,    date_of_birth, 
                       phone_number, subsidiary_id, junk)
SELECT gen.n + 1,
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       CHAR( ABS(random()) % 26 + 65
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           , ABS(random()) % 26 + 97
           ),
       DATE('now', '-' || (abs(random()) % 3650 + 40*365) || ' day'),
       ABS(RANDOM())%9000+1000,
       CAST(ABS(RANDOM())%(gen.n/9000.0 * 29 + 1) + 1 AS INTEGER),
       printf('%.10c','x')
  FROM generator_64k gen
 WHERE gen.n < 9000;
ANALYZE employees;

Notes:

  • Everything is recreated again, as SQLite doesn’t support modifying the primary key.

Functions

SQLite doesn’t support create function syntax, thus we need to use the expression to calculate the current age directly into the query.

SELECT first_name, last_name
     , CAST(STRFTIME('%Y.%m%d', 'now') - STRFTIME('%Y.%m%d', date_of_birth) AS INT)
  FROM employees
 WHERE CAST(STRFTIME('%Y.%m%d', 'now') - STRFTIME('%Y.%m%d', date_of_birth) AS INT) = 42

Note that the age is calculated by formatting the dates as fractional years.

Expressions can be indexed if they are deterministic.

CREATE INDEX emp_age ON employees
     ( CAST(STRFTIME('%Y.%m%d', 'now') - STRFTIME('%Y.%m%d', date_of_birth) AS INT) )
Error: non-deterministic use of strftime() in an index

About the Author

Photo of Markus Winand

Markus Winand is the SQL Renaissance Ambassador. He is on a mission to introduce developers to the evolution of SQL in the 21st century. Markus can be hired as trainer, speaker and consultant via winand.at.

Buy his Book on Amazon

Cover of “SQL Performance Explained”: Squirrel running on grass

The essence of SQL tuning in 200 pages

Buy on Amazon
(paperback only)

Paperback and PDF also available at Markus’ store.

Hire Markus

Markus offers SQL training and consulting for developers working at companies of any size.
Learn more »

Do not use offset for pagination

Learn why

Visit my sibling!A lot changed since SQL-92!

The Use The Index, Luke! mug

Stickers, coasters, books and coffee mugs. All you need for learning.

Shop now

Connect with Markus Winand

Markus Winand on LinkedInMarkus Winand on XINGMarkus Winand on Twitter
“Use The Index, Luke!” by Markus Winand is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License.
Legal | Contact | NO WARRANTY | Trademarks | Privacy and GDPR | CC-BY-NC-ND 3.0 license