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Uday Yadav
Uday Yadav

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SQL : DataTypes

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;
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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"
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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)
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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();
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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)
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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)
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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
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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
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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);
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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
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