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README.md

PostgreSQL Views and Functions

The functions and views published in this repository are some of those, which I regularly need in my daily job.

As these procedures are sort of essential, at least to me, I install them in the public schema. That way they are available for everyone without having to know a schema name.

All functions and views are covered by tests. The tests are done in simple SQL statements. Each test does raise division by zero if it fails.

The tests have been done with PostgreSQL 9.6 and 10. There have been some changes in the behaviour in PostgreSQL 10, Timestamp and Date functions and conversions have become more strict.

All examples have been done with PostgreSQL 10, differences in the behaviour of previous versions are noted.

Repositories

The main repository is now on GitLab. A mirror will stay on GitHub.

If you discover any issue, please file them on https://gitlab.com/sjstoelting/pgsql-tweaks/issues.

Building the extension

All functions and tests are located in single files.

The files for the extension are build by the shell script "create-sql.sh". To be able to run the script, you need to have a configuration with the connection information. Please copy "build.cfg.example" to "build.cfg" and change the configuration to fit your environment.
The script assumes, that you have a .pgpass file with login information matching the configuration.

Installation

You may either, install all functions as a package, or install single functions of your choice.

Install the package from source

Get the source by either, download the code as ZIP file, or by git clone.

cd pgsql_tweaks
make install

Afterwards you are able to create the extension in a database:

CREATE EXTENSION pgsql_tweaks;

Install the package with PGXN

pgsql_tweaks is now available over the PostgreSQL extension management, PGXN.

The installation is done with the PGXN installer.

pgxn install pgsql_tweaks

Afterwards you are able to create the extension in a database:

Table of content

1 List of functions

1.1 Functions to check data types
1.1.1 FUNCTION is_date
1.1.2 FUNCTION is_time
1.1.3 FUNCTION is_timestamp
1.1.4 FUNCTION is_real
1.1.5 FUNCTION is_double_precision
1.1.6 FUNCTION is_numeric
1.1.7 FUNCTION is_bigint
1.1.8 FUNCTION is_integer
1.1.9 FUNCTION is_smallint
1.1.10 FUNCTION is_boolean
1.1.11 FUNCTION is_json
1.1.12 FUNCTION is_jsonb
1.1.13 FUNCTION is_empty

1.2 Functions about encryption
1.2.1 FUNCTION sha256

1.3 Functions and views to get extended system information
1.3.1 FUNCTION pg_schema_size
1.3.2 VIEW pg_db_views
1.3.3 VIEW pg_foreign_keys
1.3.4 VIEW pg_functions
1.3.4 VIEW pg_active_locks
1.3.5 VIEW pg_table_matview_infos

1.4 Functions about encodings
1.4.1 FUNCTION is_encoding
1.4.2 FUNCTION is_latin1
1.4.3 FUNCTION return_not_part_of_latin1
1.4.4 FUNCTION replace_latin1
1.4.4.1 replace_latin1(s VARCHAR)
1.4.4.2 replace_latin1(s VARCHAR, replacement VARCHAR)
1.4.4.3 replace_latin1(s VARCHAR, s_search VARCHAR[], s_replace VARCHAR[])
1.4.5 FUNCTION return_not_part_of_encoding
1.4.6 FUNCTION replace_encoding
1.4.6.1 replace_encoding(s VARCHAR, e VARCHAR)
1.4.6.2 replace_encoding(s VARCHAR, e VARCHAR, replacement VARCHAR)
1.4.6.3 replace_encoding(s VARCHAR, s_search VARCHAR[], s_replace VARCHAR[])

1.5 User defined aggregates
1.5.1 AGGREGATE gap_fill
1.5.2 AGGREGATE array_min
1.5.3 AGGREGATE array_max
1.5.4 AGGREGATE array_avg
1.5.5 AGGREGATE array_sum

1.6 Format functions
1.6.1 FUNCTION date_de
1.6.2 FUNCTION datetime_de

1.7 Conversion functions
1.7.1 FUNCTION to_unix_timestamp

1.8 Other functions
1.8.1 FUNCTION array_trim

List of functions

Functions to check data types

FUNCTION is_date

The function checks strings for being a date.
You might pass a second parameter to use a format string. Without the format, the default format of PostgreSQL is used.

There has been a behaviour change in PostgreSQL 10. A conversion is now handled strict, as in previous versions the conversion tried to calculate dates.

Example PostgreSQL < 10

SELECT is_date('31.02.2018', 'DD.MM.YYYY') AS res;
-- Result is true because the conversion would return a valid result for
SELECT to_date('31.02.2018', 'DD.MM.YYYY');

Result PostgreSQL 9.6 and previous versions:

to_date
2018-03-03

Examples

/**
 * Parameter is in PostgreSQL default format
 */
SELECT is_date('2018-01-01') AS res;

Result:

res
t
SELECT is_date('2018-02-31') AS res;

Result:

res
f
/**
 * Parameter is in PostgreSQL German format
 */
SELECT is_date('01.01.2018', 'DD.MM.YYYY') AS res;

Result:

res
t
SELECT is_date('31.02.2018', 'DD.MM.YYYY') AS res;

Result:

res
f

FUNCTION is_time

The function checks strings for being a time.
You might pass a second parameter to use a format string. Without the format, the default format of PostgreSQL is used.

There has been a behaviour change in PostgreSQL 10. A conversion is now handled strict, as in previous versions the conversion tried to calculate time.

Example PostgreSQL < 10

SELECT is_time('25.33.55,456574', 'HH24.MI.SS,US') AS res;
-- Result is true because the conversion would return a valid result for
SELECT to_timestamp('25.33.55,456574', 'HH24.MI.SS,US')::TIME;

Result PostgreSQL 9.6 and previous versions:

to_timestamp
01:33:55.456574

Examples

/**
 * Parameter is in PostgreSQL default format
 */
SELECT is_time('14:33:55.456574') AS res;

Result:

res
t
SELECT is_time('25:33:55.456574') AS res;

Result:

res
f
/**
 * Parameter is some time format
 */
SELECT is_time('14.33.55,456574', 'HH24.MI.SS,US') AS res;

Result:

res
t
SELECT is_time('25.33.55,456574', 'HH24.MI.SS,US') AS res;

Result:

res
f

FUNCTION is_timestamp

The function checks strings for being a timestamp.
You might pass a second parameter to use a format string. Without the format, the default format of PostgreSQL is used.

There has been a behaviour change in PostgreSQL 10. A conversion is now handled strict, as in previous versions the conversion tried to calculate a date.

Example PostgreSQL < 10

SELECT is_timestamp('2018-01-01 25:00:00') AS res;
-- Result is true because the conversion would return a valid result for
SELECT to_timestamp('01.01.2018 25:00:00', 'DD.MM.YYYY HH24.MI.SS')::TIMESTAMP;

Result PostgreSQL 9.6 and previous versions:

to_timestamp
2018-01-02 01:00:00

Examples

/**
 * Parameter is in PostgreSQL default format
 */
SELECT is_timestamp('2018-01-01 00:00:00') AS res;

Result:

res
t
SELECT is_timestamp('2018-01-01 25:00:00') AS res;
-- Result is false in PostgreSQL >= 10

Result:

res
f
/**
 * Parameter is in PostgreSQL German format
 */
SELECT is_timestamp('01.01.2018 00:00:00', 'DD.MM.YYYY HH24.MI.SS') AS res;

Result:

res
t
SELECT is_timestamp('01.01.2018 25:00:00', 'DD.MM.YYYY HH24.MI.SS') AS res;

Result:

res
f

FUNCTION is_real

The function checks strings for being of data type REAL.

Examples

SELECT is_real('123.456') AS res;

Result:

res
t
SELECT is_real('123,456') AS res;
-- Result is false

Result:

res
f

FUNCTION is_double_precision

The function checks strings for being of data type DOUBLE PRECISION.

Examples

SELECT is_double_precision('123.456') AS res;

Result:

res
t
SELECT is_double_precision('123,456') AS res;
-- Result is false

Result:

res
f

FUNCTION is_numeric

The function checks strings for being of data type NUMERIC.

Examples

SELECT is_numeric('123') AS res;

Result:

res
t
SELECT is_numeric('1 2') AS res;
-- Result is false

Result:

res
f

FUNCTION is_bigint

The function checks strings for being of data type BIGINT.

Examples

SELECT is_bigint('3243546343') AS res;
-- Result is true

Result:

res
t
SELECT is_bigint('123.456') AS res;
-- Result is false

FUNCTION is_integer

The function checks strings for being of data type INTEGER.

Examples

SELECT is_integer('123') AS res;
-- Result is true

Result:

res
t
SELECT is_integer('123.456') AS res;
-- Result is false

FUNCTION is_smallint

The function checks strings for being of data type SMALLINT.

Examples

SELECT is_smallint('123') AS res;
-- Result is true

Result:

res
t
SELECT is_smallint('123.456') AS res;
-- Result is false

Result:

res
f

FUNCTION is_boolean

The function checks a string variable for containing valid BOOLEAN values.

boolean strings
t
f
T
F
y
n
Y
N
true
false
TRUE
FALSE
yes
no
YES
NO
0
1

Examples

SELECT is_boolean('t');
-- Result is true

Result:

res
t
SELECT is_boolean('F');
-- Result is true

Result:

res
t
SELECT is_boolean('True');
-- Result is true

Result:

res
t
SELECT is_boolean('False');
-- Result is true

Result:

res
t
SELECT is_boolean('0');
-- Result is true

Result:

res
t
SELECT is_boolean('1');
-- Result is true

Result:

res
t
SELECT is_boolean('-1');
-- Result is false

Result:

res
f

FUNCTION is_json

The function checks a string variable for containing a valid JSON.

Examples

SELECT is_json('{"review": {"date": "1970-12-30", "votes": 10, "rating": 5, "helpful_votes": 0}, "product": {"id": "1551803542", "group": "Book", "title": "Start and Run a Coffee Bar (Start & Run a)", "category": "Business & Investing", "sales_rank": 11611, "similar_ids": ["0471136174", "0910627312", "047112138X", "0786883561", "0201570483"], "subcategory": "General"}, "customer_id": "AE22YDHSBFYIP"}') AS res;

Result:

res
t
SELECT is_json('Not a JSON') AS

Result:

res
f

FUNCTION is_jsonb

The function checks a string variable for containing a valid JSONB.

Example

SELECT is_jsonb('{"review": {"date": "1970-12-30", "votes": 10, "rating": 5, "helpful_votes": 0}, "product": {"id": "1551803542", "group": "Book", "title": "Start and Run a Coffee Bar (Start & Run a)", "category": "Business & Investing", "sales_rank": 11611, "similar_ids": ["0471136174", "0910627312", "047112138X", "0786883561", "0201570483"], "subcategory": "General"}, "customer_id": "AE22YDHSBFYIP"}') AS res;

Result:

res
t
SELECT is_jsonb('Not a JSONB') AS

Result:

res
f

FUNCTION is_empty

The function checks a string variable for being either, NULL or ''.

Examples

SELECT is_empty('abc');
-- Result is false

Result:

res
f
SELECT is_empty('');
-- Result is true

Result:

res
t
SELECT is_empty(NULL);
-- Result is true

Result:

res
t

Functions about encryption

FUNCTION sha256

Creates a function which returns a SHA256 hash for the given string.
The parameter has to be converted into a binary string of bytea.
❗️The function needs the pgcrypto package❗️

❗️This function has an external dependency and is only installed, if the package pgcrypto is installed❗️

Example

SELECT sha256('test-string'::bytea) AS res;

Result:

res
ffe65f1d98fafedea3514adc956c8ada5980c6c5d2552fd61f48401aefd5c00e

Functions and views to get extended system information

FUNCTION pg_schema_size

The function returns the size for schema given as parameter in bytes.

Examples

-- Returns the size of the schema public in bytes
SELECT pg_schema_size('public');

Result:

pg_schema_size
348536832
-- Returns the size of the schema public formatted
SELECT pg_size_pretty(pg_schema_size('public'));

Result:

pg_schema_size
332 MB

VIEW pg_db_views

Creates a view to get all views of the current database but excluding system views and all views which do start with "pg" or "_pg".

SELECT * FROM pg_db_views;
view_catalog view_schema view_name view_definition
chinook public v_json_artist_data WITH tracks AS (
SELECT "Track"."AlbumId" AS album_id,
"Track"."TrackId" AS track_id,
"Track"."Name" AS track_name,
"Track"."MediaTypeId" AS media_type_id,
"Track"."Milliseconds" AS milliseconds,
"Track"."UnitPrice" AS unit_price
FROM "Track"
), json_tracks AS (
SELECT row_to_json(tracks.*) AS tracks
FROM tracks
), albums AS (
SELECT a."ArtistId" AS artist_id,
a."AlbumId" AS album_id,
a."Title" AS album_title,
array_agg(t.tracks) AS album_tracks
FROM ("Album" a
JOIN json_tracks t ON ((a."AlbumId" = ((t.tracks ->> 'album_id'::text))::integer)))
GROUP BY a."ArtistId", a."AlbumId", a."Title"
), json_albums AS (
SELECT albums.artist_id,
array_agg(row_to_json(albums.*)) AS album
FROM albums
GROUP BY albums.artist_id
), artists AS (
SELECT a."ArtistId" AS artist_id,
a."Name" AS artist,
jsa.album AS albums
FROM ("Artist" a
JOIN json_albums jsa ON ((a."ArtistId" = jsa.artist_id)))
)
SELECT (row_to_json(artists.*))::jsonb AS artist_data
FROM artists;

VIEW pg_foreign_keys

Creates a view to get all views of the current database but excluding system views and all views which do start with "pg" or "_pg".

SELECT * FROM pg_foreign_keys;
table_catalog table_schema table_name column_name foreign_table_name foreign_column_name
chinook public Album ArtistId Artist ArtistId
chinook public Customer SupportRepId Employee EmployeeId
chinook public Employee ReportsTo Employee EmployeeId
chinook public Invoice CustomerId Customer CustomerId
chinook public InvoiceLine InvoiceId Invoice InvoiceId
chinook public InvoiceLine TrackId Track TrackId
chinook public PlaylistTrack PlaylistId Playlist PlaylistId
chinook public PlaylistTrack TrackId Track TrackId
chinook public Track AlbumId Album AlbumId
chinook public Track GenreId Genre GenreId
chinook public Track MediaTypeId MediaType MediaTypeId

VIEW pg_functions

Creates a view to get all functions of the current database, excluding those in the schema pg_catalog and information_schema.

As there have been changes to the system tables used in this view, there are now two scripts dependend on the PostgreSQL version on which it has to be used, one for PostgreSQL 11 or newer and one for PostgreSQL 10 or older. This is handled in the script that creates the view.

SELECT * FROM pg_functions;
schema_name function_name returning_data_type parameters function_type function_comment
public date_de character varying d date function Creates a function which returns the given date in German format
public datetime_de character varying t timestamp without time zone function Creates a function which returns the given timestamp in German format

VIEW pg_active_locks

Creates a view to view all live locks with all necessary information about the connections and the query.
The view needs PostgreSQL 9.2 as minimum version. The column application_name was added in 9.2.

SELECT * FROM pg_active_locks;

Result:

pid state datname usename application_name client_addr query_start wait_event_type wait_event locktype mode query
8872 active chinook stefanie psql 127.0.0.1 2018-02-18 14:45:53.943047+01 relation AccessShareLock SELECT * FROM pg_active_locks;
8872 active chinook stefanie psql 127.0.0.1 2018-02-18 14:45:53.943047+01 virtualxid ExclusiveLock SELECT * FROM pg_active_locks;

VIEW pg_table_matview_infos

Creates a view with information about the size of the table/materialized view and sizes of indexes on that table/materialized view. It does also list all indexes on that table in an array.

SELECT * FROM pg_table_matview_infos;

Result:

type schemaname tablename tableowner tablespace indexes table_size indexes_size total_relation_size table_size_pretty indexes_size_pretty total_relation_size_pretty
table public MediaType stefanie [NULL] {PK_MediaType} 8192 16384 24576 8192 bytes 16 kB 24 kB
table public Playlist stefanie [NULL] {PK_Playlist} 8192 16384 24576 8192 bytes 16 kB 24 kB

Functions about encodings

FUNCTION is_encoding

The function checks if all characters are in included in a given encoding. That is especially useful, if you have to deal with exports into other encodings than the database encoding.

The function with two parameters uses UTF-8 as source encoding,
The one with three parameters uses the third parameter as source encoding.

Examples

SELECT is_encoding('Some characters', 'LATIN1') AS res;

Result:

res
f
SELECT is_encoding('Some characters, ğ is Turkish and not latin1', 'LATIN1') AS res;
-- Returns false: The Turkish character ğ is not part of latin1

Result:

res
f
SELECT is_encoding('Some characters', 'LATIN1', 'UTF8') AS res;

Result:

res
t
SELECT is_encoding('Some characters, ğ is Turkish and not latin1', 'UTF8', 'LATIN1') AS res;
-- Returns false: The Turkish character ğ is not part of latin1

Result:

res
f

FUNCTION is_latin1

The function is a shortcut for is_encoding('Some characters', 'LATIN1'), you don't have to give the target encoding.

Examples

SELECT is_latin1('Some characters') AS res;

Result:

res
t
SELECT is_latin1('Some characters, ğ is Turkish and not latin1') AS res;
-- Returns false: The Turkish character ğ is not part of latin1

Result:

res
f

FUNCTION return_not_part_of_latin1

The function returns a distinct array containing all characters, which are not defined in latin1.
The function depends on is_latin1 which is part of this repository.

Example

-- Returns an array containing the characters ğ and Ƶ each one time
SELECT return_not_part_of_latin1('ağbƵcğeƵ') AS res;

Result:

res
{ğ,Ƶ}

FUNCTION replace_latin1

The function has three implementations. All implementations depend on the function is_latin1, the function is included in this repository.

replace_latin1(s VARCHAR)

The function takes one parameter with characters to be checked and replaced with an empty string, if they are not part of latin1.

Example
SELECT replace_latin1('Some characters, ğ is Turkish and not latin1') AS res;

Result:

res
Some characters, is Turkish and not latin1

replace_latin1(s VARCHAR, replacement VARCHAR)

The function takes a second parameter which is used to replace all characters, which are not part of latin1.

Example
SELECT replace_latin1(
  'Some characters, ğ is Turkish and not latin1 and replaced with a g',
  'g'
) AS res;

Result:

res
Some characters, g is Turkish and not latin1 and replaced with a g

replace_latin1(s VARCHAR, s_search VARCHAR[], s_replace VARCHAR[])

The function takes as first parameter a string which may or may not have none latin1 characters. The second parameter is an arrays containing all characters, that should be replaced. The third parameter is an array, too. The characters defined in s_search are replaced with the characters in s_replace, it takes the position in the array to identify which character should be replaced by which one.

Example
-- First identify the characters which should be replaced, which are {ğ,Ƶ}
SELECT return_not_part_of_latin1('ağbƵcğeƵ') AS res;

-- The ğ will be replaced whit a g and the Ƶ with a Z}
SELECT 'ağbƵcğeƵ' AS original
  , replace_latin1(
      'ağbƵcğeƵ',
      string_to_array('ğ,Ƶ', ','),
      string_to_array('g,Z', ',')
    ) AS res;

Result:

original res
ağbƵcğeƵ agbZcgeZ

FUNCTION return_not_part_of_encoding

The function returns a distinct array containing all characters, which are not defined in the second parameter as encoding.
The function depends on is_encoding which is part of this repository.

Example

-- Returns an array containing the characters ğ and Ƶ each one time
SELECT return_not_part_of_encoding('ağbƵcğeƵ', 'latin1') AS res;

Result:

res
{ğ,Ƶ}

FUNCTION replace_encoding

The function has three implementations. All implementations depend on the function is_encoding, the function is included in this repository.

replace_encoding(s VARCHAR, e VARCHAR)

The function takes one parameter with characters to be checked and replaced with an empty string, if they are not part of the encoding given in the second parameter.

Example
SELECT replace_encoding(
  'Some characters, ğ is Turkish and not latin1',
  'latin1'
) AS res;

Result:

res
Some characters, is Turkish and not latin1

replace_encoding(s VARCHAR, e VARCHAR, replacement VARCHAR)

The function takes a third parameter which is used to replace all characters which are not part of the encoding given in parameter 2.

Example
SELECT replace_encoding(
  'Some characters, ğ is Turkish and not latin1 and replaced with a g',
  'latin1',
  'g'
) AS res;

Result:

res
Some characters, g is Turkish and not latin1 and replaced with a g

replace_encoding(s VARCHAR, s_search VARCHAR[], s_replace VARCHAR[])

The function takes as first parameter a string which may or may not have none latin1 characters. The second parameter is an arrays containing all characters, that should be replaced. The third parameter is an array, too. The characters defined in s_search are replaced with the characters in s_replace, it takes the position in the array to identify which character should be replaced by which one.

Example
-- First identify the characters which should be replaced, which are {ğ,Ƶ}
SELECT return_not_part_of_latin1('ağbƵcğeƵ') AS res;

-- The ğ will be replaced whit a g and the Ƶ with a Z}
SELECT 'ağbƵcğeƵ' AS original
  , replace_encoding(
      'ağbƵcğeƵ',
      string_to_array('ğ,Ƶ', ','),
      string_to_array('g,Z', ',')
  ) AS res;

Result:

original res
ağbƵcğeƵ agbZcgeZ

User defined aggregates

AGGREGATE gap_fill

The aggregate is used in Window Functions to show the last value in case the current value is null.

Example

BEGIN;

CREATE TABLE test_gap_fill(id INTEGER, some_value VARCHAR);

INSERT INTO test_gap_fill(id, some_value) VALUES
  (1, 'value 1'),
  (1, NULL),
  (2, 'value 2'),
  (2, NULL),
  (2, NULL),
  (3, 'value 3')
;

SELECT id
  , some_value
FROM test_gap_fill
;

ROLLBACK;

Result:

id some_value
1 value 1
1
2 value 2
2
2
3 value 3
BEGIN;

CREATE TABLE test_gap_fill(id INTEGER, some_value VARCHAR);

INSERT INTO test_gap_fill(id, some_value) VALUES
  (1, 'value 1'),
  (1, NULL),
  (2, 'value 2'),
  (2, NULL),
  (2, NULL),
  (3, 'value 3')
;

-- Fill the empty rows with values
SELECT id
  , gap_fill(some_value) OVER (ORDER BY id) AS some_value
FROM test_gap_fill
;

ROLLBACK;

Result:

id some_value
1 value 1
1 value 1
2 value 2
2 value 2
2 value 2
3 value 3

AGGREGATE array_min

Calculate minimum values from arrays.

Supported data types are SMALLINT, INTEGER, BIGINT, REAL, DOUBLE PRECISION, NUMERIC, and TEXT;

Examples

SELECT array_min(ARRAY[45, 60, 43, 99]::SMALLINT[]);

Result:

array_min
43
SELECT array_min(ARRAY[45, 60, 43, 99]::INTEGER[]);

Result:

array_min
43
SELECT array_min(ARRAY[45, 60, 43, 99]::BIGINT[]);

Result:

array_min
43
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::REAL[]);

Result:

array_min
43.7
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::DOUBLE PRECISION[]);

Result:

array_min
43.7
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::NUMERIC[]);

Result:

array_min
43.7
SELECT array_min(ARRAY['def', 'abc', 'ghi']::TEXT[]);

Result:

array_min
abc

AGGREGATE array_max

Calculate minimum values from arrays.

Supported data types are SMALLINT, INTEGER, BIGINT, REAL, DOUBLE PRECISION, NUMERIC, and TEXT;

Examples

SELECT array_max(ARRAY[45, 60, 43, 99]::SMALLINT[]);

Result:

array_max
99
SELECT array_max(ARRAY[45, 60, 43, 99]::INTEGER[]);

Result:

array_max
99
SELECT array_max(ARRAY[45, 60, 43, 99]::BIGINT[]);

Result:

array_max
99
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::REAL[]);

Result:

array_max
99.3
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::DOUBLE PRECISION[]);

Result:

array_max
99.3
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::NUMERIC[]);

Result:

array_max
99.3
SELECT array_max(ARRAY['def', 'abc', 'ghi']::TEXT[]);

Result:

array_max
ghi

AGGREGATE array_avg

Calculate average values from arrays.

Supported data types are SMALLINT, INTEGER, BIGINT, REAL, DOUBLE PRECISION, and NUMERIC;

Examples

SELECT array_avg(ARRAY[45, 60, 43, 99]::SMALLINT[]);

Result:

array_avg
62
SELECT array_avg(ARRAY[45, 60, 43, 99]::INTEGER[]);

Result:

array_avg
62
SELECT array_avg(ARRAY[45, 60, 43, 99]::BIGINT[]);

Result:

array_avg
62
SELECT array_avg(ARRAY[45.6, 60.8, 43, 99.3]::REAL[]);

Result:

array_avg
62.1750001907349
SELECT array_avg(ARRAY[45.6, 60.8, 43, 99.3]::DOUBLE PRECISION[]);

Result:

array_avg
62.175
SELECT array_avg(ARRAY[45.6, 60.8, 43, 99.3]::NUMERIC[]);

Result:

array_avg
62.1750000000000000

AGGREGATE array_sum

Calculate sum of values from arrays.

Supported data types are SMALLINT, INTEGER, BIGINT, REAL, DOUBLE PRECISION, and, NUMERIC;

Examples

SELECT array_sum(ARRAY[45, 60, 43, 99]::SMALLINT[]);

Result:

array_sum
247
SELECT array_sum(ARRAY[45, 60, 43, 99]::INTEGER[]);

Result:

array_sum
247
SELECT array_sum(ARRAY[45, 60, 43, 99]::BIGINT[]);

Result:

array_sum
247
SELECT array_sum(ARRAY[45.6, 60.8, 43.7, 99.3]::REAL[]);

Result:

array_sum
249.4
SELECT array_sum(ARRAY[45.6, 60.8, 43.7, 99.3]::DOUBLE PRECISION[]);

Result:

array_sum
249.4
SELECT array_sum(ARRAY[45.6, 60.8, 43.7, 99.3]::NUMERIC[]);

Result:

array_sum
249.4

Format functions

Several countries use different formats for numbers, dates, and timestamps. Therefore I needed some functions, which is easy to remember than the format codes which differ in different programming languages.

German formats

FUNCTION date_de

Creates a function which returns the given date in German format.

Example
SELECT date_de('2018-01-01') AS d_de;

Result:

d_de
01.01.2018

FUNCTION datetime_de

Creates a function which returns the given timestamp in German format.

Example
SELECT datetime_de('2018-01-01 13:30:30 GMT') AS ts_de;

Result:

ts_de
01.01.2018 14:30:30

Conversion functions

FUNCTION to_unix_timestamp

Creates two functions which returns unix timestamp for the a given timestamp or a given timestamp with time zone.

Examples

-- Timestamp without time zone, server uses German / Berlin time zone
SELECT to_unix_timestamp('2018-01-01 00:00:00') AS unix_timestamp;

Result:

unix_timestamp
1514761200
-- Timestamp with time zone
SELECT to_unix_timestamp('2018-01-01 00:00:00+01') AS unix_timestamp;

Result:

unix_timestamp
1514761200

Other functions

FUNCTION array_trim

Removes empty strings and null entries from a given array. In addition the function can remove duplicate entries. The function supports strings, numbers, dates, and timestamps with or without time zone.

Examples

-- Untrimmed timestamp array with time zone with duplicates
SELECT array_trim(ARRAY['2018-11-11 11:00:00 MEZ',NULL,'2018-11-11 11:00:00 MEZ']::TIMESTAMP WITH TIME ZONE[]) AS trimmed_array;

Result:

untrimmed_array
{'2018-11-11 11:00:00.000',,'2018-11-11 11:00:00.000'}
-- Timestamp array with time zone with duplicates
SELECT ARRAY['2018-11-11 11:00:00 MEZ',NULL,'2018-11-11 11:00:00 MEZ']::TIMESTAMP WITH TIME ZONE[] AS untrimmed_array;

Result:

trimmed_array
{'2018-11-11 11:00:00.000','2018-11-11 11:00:00.000'}
-- Timestamp array with time zone without duplicates
SELECT array_trim(ARRAY['2018-11-11 11:00:00 MEZ',NULL,'2018-11-11 11:00:00 MEZ']::TIMESTAMP WITH TIME ZONE[], TRUE) AS trimmed_array_distinct;

Result:

trimmed_array_distinct
{'2018-11-11 11:00:00.000'}
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