Uday Yadav

Posted on Sep 2, 2021 • Updated on Sep 7, 2021

SQL : DataTypes

#sql #database #programming

This guide is for PostgreSQL : https://www.postgresql.org/

Getting Started with PostgreSQL :
https://dev117uday.gitbook.io/databases/sql/getting-started

Loading Sample Data Guide :
https://dev117uday.gitbook.io/databases/sql/getting-started/load-data

Boolean Data

TRUE
FALSE
NULL

TRUE	FALSE
TRUE	FALSE
'true'	'false'
't'	'f'
'yes'	'no'
'y'	'n'
'1'	'0'

CREATE TABLE booltable (
    id SERIAL PRIMARY KEY ,
    is_enable BOOLEAN NOT NULL
);

INSERT INTO booltable (is_enable) VALUES (TRUE), ('true'), 
    ('y') , ('yes'), ('t'), ('1');
INSERT INTO booltable (is_enable) VALUES (FALSE), ('false'), 
    ('n') , ('no'), ('f'), ('0');

SELECT * FROM booltable;

SELECT * FROM booltable WHERE is_enable = 'y';

SELECT * FROM booltable WHERE NOT is_enable;

Character Data

Character Type	Notes
CHARACTER (N), CHAR (N)	fixed-length, blank padded
CHARACTER VARYING (N), VARCHAR(N)	variable length with length limit
TEXT, VARCHAR	variable unlimited length, max 1GB

n is default to 1

-- INPUT
SELECT CAST('Uday' as character(10)) as "name";
-- OUTPUT
"Uday      "

-- INPUT
SELECT 'Uday'::character(10) as "name";
-- OUTPUT
"Uday      "

-- INPUT
SELECT 'uday'::varchar(10);
-- OUTPUT
"uday"

-- INPUT
SELECT 'lorem ipsum'::text;
-- OUTPUT
"lorem ipsum"

Numeric Data

Types	Notes
Integers	whole number, +ve and -ve
Fixed-point, floating point	for fractions of whole nu

type	size (bytes)	min	max
smallint	2	-32678	32767
integer	4	-2,147,483,648	2,147,483,647
bigint	8	-9223372036854775808	9223372036854775807

type	size	range
smallserial	2	1 to 32767
serial	4	1 to 2147483647
bigserial	8	1 to 9223372036854775807

Fixed Point Data

numeric ( precision , scale ) | decimal ( precision , scale )

precision : max number of digits to the left and right of the decimal point
scale : number of digits allowable on the right of the decimal point

Floating Point Data

Type	Notes
Real	allows precision to six decimal digits
Double precision	allows precision to 15 digits points of precision

type	size	storage type	Range
numeric, decimal	variable	fixed point	131072 digits before decimal point and 16383 digits after the decimal point
real	4	floating point	6 decimal digits precision
double precision	8	floating point	15 decimal digits precision

CREATE TABLE table_numbers (
    col_numeric numeric(20,5),
    col_real real,
    col_double double precision
);

INSERT INTO table_numbers (col_numeric,col_real,col_double)
VALUES (.9,.9,.9),
       (3.34675,3.34675,3.34675),
       (4.2345678910,4.2345678910,4.2345678910);

SELECT * FROM table_numbers;

-- OUTPUT
learning=# select * from table_numbers ;
 col_numeric | col_real | col_double  
-------------+----------+-------------
     0.90000 |      0.9 |         0.9
     3.34675 |  3.34675 |     3.34675
     4.23457 | 4.234568 | 4.234567891
(3 rows)

Hierarchical order to SELECT best type : numeric > decimal > float

Date Time Data

type	stores	low	high
Date	date only	4713 BC	294276 AD
Time	time only	4713 BC	5874897 AD
Timestamp	date and time	4713 BC	294276 AD
`Timestampz`	date, time and timezone	4713 BC	294276 AD
Interval	difference btw time

Date type

CREATE TABLE table_dates (
    id serial primary key,
    employee_name varchar(100) not null,
    hire_date DATE NOT NULL,
    add_date DATE DEFAULT CURRENT_DATE
);

INSERT INTO table_dates (employee_name, hire_date)
    VALUES ('uday','2020-02-02'),('another uday','2020-02-01');

SELECT *
FROM table_dates;

SELECT NOW();

Time type

CREATE TABLE table_time (
    id serial primary key ,
    class_name varchar(10) not null ,
    start_time time not null ,
    end_time time not null
);

INSERT INTO table_time (class_name, start_time, end_time) 
    VALUES ('maths','08:00:00','08:55:00'),
           ('chemistry','08:55:00','09:00:00');

SELECT * FROM table_time;

-- OUTPUT

 id | class_name | start_time | end_time 
----+------------+------------+----------
  1 | maths      | 08:00:00   | 08:55:00
  2 | chemistry  | 08:55:00   | 09:00:00
(2 rows)


SELECT CURRENT_TIME;

    current_time    
--------------------
 07:21:00.163354+00
(1 row)


SELECT CURRENT_TIME(2);

  current_time  
----------------
 07:21:14.96+00
(1 row)


SELECT LOCALTIME;

    localtime    
-----------------
 07:21:36.717509
(1 row)


SELECT time '12:10' - time '04:30' as RESULT;
  result  
----------
 07:40:00
(1 row)


-- format : interval 'n type'
-- n = number
-- type : second, minute, hours, day, month, year ....

SELECT CURRENT_TIME ,
    CURRENT_TIME + INTERVAL '2 hours' as RESULT;

    current_time    |       result       
--------------------+--------------------
 07:22:06.241919+00 | 09:22:06.241919+00
(1 row)


SELECT CURRENT_TIME ,
    CURRENT_TIME + INTERVAL '-2 hours' as RESULT;

    current_time    |       result       
--------------------+--------------------
 07:22:16.644727+00 | 05:22:16.644727+00
(1 row)

Timestamp and Timezone

timestamp : stores time without time zone
timestamptz : timestamp with time zone , stored using UTC format
adding timestamp to timestamptz without mentioning the zone will result in server automatically assumes timezone to system's timezone
Internally, PostgreSQL will store the timezoneaccurately but then OUTPUTting the data, will it be converted according to your timezone

SELECT name FROM pg_timezone_names 
    where name = 'posix/Asia/Calcutta';

SET TIMEZONE='Asia/Calcutta';

SELECT NOW()::TIMESTAMP;

            now             
----------------------------
 2021-08-12 12:53:03.971433
(1 row)


CREATE TABLE table_time_tz (
    ts timestamp,
    tstz timestamptz
);

INSERT INTO table_time_tz (ts, tstz) 
    VALUES ('2020-12-22 10:10:10',
            '2020-12-22 10:10:10.009+05:30');

SELECT * FROM table_time_tz;

         ts          |             tstz              
---------------------+-------------------------------
 2020-12-22 10:10:10 | 2020-12-22 10:10:10.009+05:30
(1 row)


SELECT CURRENT_TIMESTAMP;

        current_timestamp        
---------------------------------
 2021-08-12 12:53:29.54762+05:30
(1 row)


SELECT timezone('Asia/Singapore','2020-01-01 00:00:00')

      timezone       
---------------------
 2020-01-01 02:30:00
(1 row)

UUID

UUID : Universal Unique Identifier
PostgreSQL doesn't provide internal function to generate UUID's, use uuid-ossp

CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

SELECT uuid_generate_v1();

           uuid_generate_v1           
--------------------------------------
 4d459e0c-fb3e-11eb-a638-0242ac110002


-- pure randomness
SELECT uuid_generate_v4();

           uuid_generate_v4           
--------------------------------------
 418f39e5-8a46-4da2-8cea-884904f45d6f


CREATE TABLE products_uuid (
    id uuid default uuid_generate_v1(),
    product_name varchar(100) not null
);

INSERT INTO products_uuid (product_name) 
    VALUES ('ice cream'),('cake'),('candies');

SELECT * FROM products_uuid;

                  id                  | product_name 
--------------------------------------+--------------
 5cf1dbe0-fb3e-11eb-a638-0242ac110002 | ice cream
 5cf1df28-fb3e-11eb-a638-0242ac110002 | cake
 5cf1df46-fb3e-11eb-a638-0242ac110002 | candies

CREATE TABLE products_uuid_v4 (
    id uuid default uuid_generate_v4(),
    product_name varchar(100) not null
);

INSERT INTO products_uuid_v4 (product_name) 
    VALUES ('ice cream'),('cake'),('candies');

SELECT * FROM products_uuid_v4;

learning=# SELECT * FROM products_uuid_v4;
                  id                  | product_name 
--------------------------------------+--------------
 83b74bed-2cf8-4e26-80b0-c7c7b2e5f3e7 | ice cream
 ac563251-7a95-408d-966b-ed5ecc1f228d | cake
 1079f6d3-b0c3-40ef-bd2e-da4467b63432 | candies

HSTORE

stores data in key-value pairs
key and VALUES are text string only

CREATE EXTENSION IF NOT EXISTS hstore;

CREATE TABLE table_hstore (
    id SERIAL PRIMARY KEY ,
    title varchar(100) not null,
    book_info hstore
);

INSERT INTO table_hstore (title, book_info) VALUES
(
    'Title 1', ' "publisher" => "ABC publisher" , 
    "paper_cost" => "100" , "e_cost" => "5.85" '
);

SELECT * FROM table_hstore;

 id |  title  |   book_info                              

  1 | Title 1 | "e_cost"=>"5.85", "publisher"=>"ABC publisher", "paper_cost"=>"100"


SELECT book_info -> 'publisher' as publisher 
FROM table_hstore;

   publisher   
---------------
 ABC publisher

Json

PostgreSQL supports both
- JSON
- BSON or JSONB ( Binary JSON )
JSONB has full support for indexing

CREATE TABLE table_json (
    id SERIAL PRIMARY KEY ,
    docs json
);

INSERT INTO table_json (docs) 
    VALUES ('[1,2,3,4,5,6]'),('{"key":"value"}');

INSERT INTO table_json (docs)
VALUES ('[{"key":"value"},{"key2":"value2"}]');

SELECT * FROM table_json;

 id |                docs                 
----+-------------------------------------
  1 | [1,2,3,4,5,6]
  2 | {"key":"value"}
  3 | [{"key":"value"},{"key2":"value2"}]


ALTER TABLE table_json alter column docs type jsonb;

SELECT * FROM table_json where docs @> '2';

 id |        docs        
----+--------------------
  1 | [1, 2, 3, 4, 5, 6]


CREATE index on table_json USING GIN (docs jsonb_path_ops);

Network Address Data Types

Name	Storage Size	Notes
cidr	7 or 19 bytes	IPv4 and IPv6 networks
inet	7 or 19 bytes	IPv4 and IPv6 hosts and networks
macaddr	6 bytes	MAC addresses
macaddr8	8 bytes	MAC addresses ( EUI 64-bit )

It is better to use these types instead of plain text types of store network address, because these types offer input error checking and specialised operators and functions
Supports indexing and advance operations

CREATE TABLE table_netaddr (
    id SERIAL PRIMARY KEY ,
    ip inet
);

INSERT INTO table_netaddr (ip)
VALUES ('148.77.50.74'),
        ('110.158.172.66'),
        ('176.103.251.175'),
        ('84.84.14.58'),
        ('141.122.225.161'),
        ('78.44.113.33'),
        ('81.236.254.9'),
        ('82.116.85.21'),
        ('54.64.79.223'),
        ('162.240.78.253');

SELECT * FROM table_netaddr LIMIT 5;

 id |       ip        
----+-----------------
  1 | 148.77.50.74
  2 | 110.158.172.66
  3 | 176.103.251.175
  4 | 84.84.14.58
  5 | 141.122.225.161


SELECT 
       ip, 
       set_masklen(ip,24) as inet_24, 
       set_masklen(ip::cidr,24) as cidr_24 ,
       set_masklen(ip::cidr,27) as cidr_27,
       set_masklen(ip::cidr,28) as cidr_28 
FROM 
     table_netaddr LIMIT 2;

 ip | inet_24 | cidr_24 | cidr_27 | cidr_28 

 148.77.50.74   | 148.77.50.74/24   | 148.77.50.0/24   | 148.77.50.64/27   | 148.77.50.64/28
 110.158.172.66 | 110.158.172.66/24 | 110.158.172.0/24 | 110.158.172.64/27 | 110.158.172.64/28

DEV Community