Extensions
- pgsql_tweaks 0.10.2
- Contains PostgreSQL functions and views which I regularly needed and might help others, too.
Documentation
- help
- PostgreSQL Views and Functions
- PGXNREADME
- PostgreSQL Views and Functions
- LICENSE
- LICENSE
README
Contents
- PostgreSQL Views and Functions
- Repositories
- Building the extension
- Installation
- Table of content
- List of functions
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 11 up to 16 beta 1.
All examples have been tested with PostgreSQL 16 beta 1, differences in the behavior 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.
bash
cd pgsql_tweaks
make install
Afterwards you are able to create the extension in a database:
sql
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.
bash
pgxn install pgsql_tweaks
Afterwards you are able to create the extension in a database:
Table of content
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
1.1.14 FUNCTION is_hex
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
1.3.6 VIEW pg_object_ownership
1.3.7 VIEW pg_partitioned_tables_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 text)
1.4.4.2 replace_latin1(s text, replacement text)
1.4.4.3 replace_latin1(s text, s_search text[], s_replace text[])
1.4.5 FUNCTION return_not_part_of_encoding
1.4.6 FUNCTION replace_encoding
1.4.6.1 replace_encoding(s text, e text)
1.4.6.2 replace_encoding(s text, e text, replacement text)
1.4.6.3 replace_encoding(s text, s_search text[], s_replace text[])
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
1.7.2 FUNCTION hex2bigint
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
sql
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
sql
/**
* Parameter is in PostgreSQL default format
*/
SELECT is_date('2018-01-01') AS res;
Result:
| res | |:---:| | t |
sql
SELECT is_date('2018-02-31') AS res;
Result:
| res | |:---:| | f |
sql
/**
* Parameter is in PostgreSQL German format
*/
SELECT is_date('01.01.2018', 'DD.MM.YYYY') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
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
sql
/**
* Parameter is in PostgreSQL default format
*/
SELECT is_time('14:33:55.456574') AS res;
Result:
| res | |:---:| | t |
sql
SELECT is_time('25:33:55.456574') AS res;
Result:
| res | |:---:| | f |
sql
/**
* Parameter is some time format
*/
SELECT is_time('14.33.55,456574', 'HH24.MI.SS,US') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
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
sql
/**
* Parameter is in PostgreSQL default format
*/
SELECT is_timestamp('2018-01-01 00:00:00') AS res;
Result:
| res | |:---:| | t |
sql
SELECT is_timestamp('2018-01-01 25:00:00') AS res;
-- Result is false in PostgreSQL >= 10
Result:
| res | |:---:| | f |
sql
/**
* 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 |
sql
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
sql
SELECT is_real('123.456') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
SELECT is_double_precision('123.456') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
SELECT is_numeric('123') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
SELECT is_bigint('3243546343') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_bigint('123.456') AS res;
-- Result is false
FUNCTION is_integer
The function checks strings for being of data type INTEGER.
Examples
sql
SELECT is_integer('123') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_integer('123.456') AS res;
-- Result is false
FUNCTION is_smallint
The function checks strings for being of data type SMALLINT.
Examples
sql
SELECT is_smallint('123') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
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
sql
SELECT is_boolean('t') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('F') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('True') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('False');
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('0') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('1') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_boolean('-1') AS res;
-- Result is false
Result:
| res | |:---:| | f |
FUNCTION is_json
The function checks a string variable for containing a valid JSON.
Examples
sql
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 |
sql
SELECT is_json('Not a JSON') AS res;
Result:
| res | |:---:| | f |
FUNCTION is_jsonb
The function checks a string variable for containing a valid JSONB.
Example
sql
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 |
sql
SELECT is_jsonb('Not a JSONB') AS res;
Result:
| res | |:---:| | f |
FUNCTION is_empty
The function checks a string variable for being either, NULL or ''.
Examples
sql
SELECT is_empty('abc') AS res;
-- Result is false
Result:
| res | |:---:| | f |
sql
SELECT is_empty('') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_empty(NULL) AS res;
-- Result is true
Result:
| res | |:---:| | t |
FUNCTION is_hex
The function checks a string variable for being a hexadecimal number being a bigint.
:heavy_exclamation_mark:This function needs to have hex2bigint being installed!:heavy_exclamation_mark:
If you use the package, both functions are installed in the correct sort order.
Examples
sql
SELECT is_hex('a1b0') AS res;
-- Result is true
Result:
| res | |:---:| | t |
sql
SELECT is_hex('a1b0w') AS res;
-- Result is false
Result:
| res | |:---:| | f |
sql
SELECT is_hex('a1b0c3c3c3c4b5d3') AS res;
-- Result is false (does not fit into a bigint)
Result:
| res | |:---:| | f |
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.
:heavy_exclamation_mark:The function needs the pgcrypto package:heavy_exclamation_mark:
:heavy_exclamation_mark:This function has an external dependency and is only installed, if the package pgcrypto is installed:heavy_exclamation_mark:
Example
sql
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
sql
-- Returns the size of the schema public in bytes
SELECT pg_schema_size('public');
Result:
| pg_schema_size | | --------------:| | 348536832 |
sql
-- 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".
sql
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 a list of foreign keys in the database. That includes the check for an existing single index, see boolean result of column "is_indexed".
Below PostgreSQL 11 the column "enforced" is not available and therefore not part of the result.
sql
SELECT *
FROM pg_foreign_keys;
|constraint_name|is_deferrable|initially_deferred|enforced|table_schema|table_name|column_name|foreign_table_schema|foreign_table_name|foreign_column_name|is_indexed| |---------------|-------------|------------------|--------|------------|----------|-----------|--------------------|------------------|-------------------|----------| |FK_AlbumArtistId|NO|NO|YES|public|Album|ArtistId|public|Artist|ArtistId|true| |FK_CustomerSupportRepId|NO|NO|YES|public|Customer|SupportRepId|public|Employee|EmployeeId|true| |FK_EmployeeReportsTo|NO|NO|YES|public|Employee|ReportsTo|public|Employee|EmployeeId|true| |FK_InvoiceCustomerId|NO|NO|YES|public|Invoice|CustomerId|public|Customer|CustomerId|true| |FK_InvoiceLineInvoiceId|NO|NO|YES|public|InvoiceLine|InvoiceId|public|Invoice|InvoiceId|true| |FK_InvoiceLineTrackId|NO|NO|YES|public|InvoiceLine|TrackId|public|Track|TrackId|true| |FK_PlaylistTrackPlaylistId|NO|NO|YES|public|PlaylistTrack|PlaylistId|public|Playlist|PlaylistId|true| |FK_PlaylistTrackTrackId|NO|NO|YES|public|PlaylistTrack|TrackId|public|Track|TrackId|true| |FK_TrackAlbumId|NO|NO|YES|public|Track|AlbumId|public|Album|AlbumId|true| |FK_TrackGenreId|NO|NO|YES|public|Track|GenreId|public|Genre|GenreId|true| |FK_TrackMediaTypeId|NO|NO|YES|public|Track|MediaTypeId|public|MediaType|MediaTypeId|true|
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.
sql
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.
sql
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.
List of supported object types
| object type | <=10 | >=11 | | ----------- |:----:|:----:| | PARTITIONED INDEX | | X | | SEQUENCE | X | X | | COMPOSITE TYPE | X | X | | FOREIGN TABLE | X | X | | INDEX | X | X | | MATERIALIZED VIEW | X | X | | PARTITIONED TABLE | X | X | | TABLE | X | X | | VIEW | X | X | | DATABASE | X | X | | EXTENSION | X | X | | FOREIGN DATA WRAPPER | X | X | | FOREIGN SERVER | X | X | | LANGUAGE | X | X | | SCHEMA | X | X | | OPERATOR CLASS | | X | | PROCEDURE | | X | | AGGREGATE FUNCTION | | X | | WINDOW FUNCTION | | X | | COLLATION | X | X | | CONVERSION | X | X | | EVENT TRIGGER | X | X | | OPERATION FAMILY | X | X | | PUBLICATIONS | X | X |
sql
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 |
VIEW pg_object_ownership
Creates a view with information about the ownership of objects. Since PostgreSQL 11 supports procedures, therefore there is one version vor PostgreSQL 10. This view is supported in PostgreSQL 10 or newer. Older versions are not supported.
sql
SELECT *
FROM pg_object_ownership
WHERE owner = 'stefanie';
Result:
| oid | object_schema | object_name | owner | object_type | deptype | dependency_type | | ---:| -------------- | ----------- | ----- | ----------- |:-------:| --------------- | | 17078 | public | pg_object_ownership | stefanie | VIEW | n | DEPENDENCY_NORMAL | | 17079 | public | gapfillinternal | stefanie | FUNCTION | n | DEPENDENCY_NORMAL | | 18028 | public | gapfill | stefanie | AGGREGATE FUNCTION | n | DEPENDENCY_NORMAL | | 18039 | public | to_unix_timestamp | stefanie | FUNCTION | n | DEPENDENCY_NORMAL | | 18068 | public | to_unix_timestamp | stefanie | FUNCTION | n | DEPENDENCY_NORMAL |
VIEW pg_partitioned_tables_infos
Creates a view to get information about partitioned tables. Since PostgreSQL 10 supports partitions, but they became usable only in later versions. A system table to identify partitions has been added in PostgreSQL 11. Therefore this view is only available on systems with PostgreSQL 11 or newer.
sql
SELECT *
FROM pg_partitioned_tables_infos;
Result:
| parent_relid | parent_schemaname | parent_tablename | parent_owner | partition_strategy | count_o_partitions | overall_size | child_relid | child_schemaname | child_tablename | child_owner | child_size | | -----------: | ----------------- | ---------------- | ------------ | ------------------ | -----------------: | -----------: | ----------- | ---------------- | --------------- | ----------- | ---------- | | 16389 | test | parted | stefanie | LIST | 3 | 0 | 16396 | test | parted_part_1 | stefanie | 0 | | 16389 | test | parted | stefanie | LIST | 3 | 0 | 16406 | test | parted_part_2 | stefanie | 0 | | 16389 | test | parted | stefanie | LIST | 3 | 0 | 16416 | test | parted_part_3 | stefanie | 0 | | 16441 | test | parted_test2 | stefanie | HASH | 0 | 0 | | | | | |
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
sql
SELECT is_encoding('Some characters', 'LATIN1') AS res;
Result:
| res | |:---:| | f |
sql
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 |
sql
SELECT is_encoding('Some characters', 'LATIN1', 'UTF8') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
SELECT is_latin1('Some characters') AS res;
Result:
| res | |:---:| | t |
sql
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
sql
-- 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 text)
The function takes one parameter with characters to be checked and replaced with an empty string, if they are not part of latin1.
Example
sql
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 text, replacement text)
The function takes a second parameter which is used to replace all characters, which are not part of latin1.
Example
sql
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 text, s_search text[], s_replace text[])
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
```sql -- 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
sql
-- 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 text, e text)
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
sql
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 text, e text, replacement text)
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
sql
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 text, s_search text[], s_replace text[])
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
```sql -- 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
```sql BEGIN;
CREATE TABLE test_gap_fill(id INTEGER, some_value text);
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 |
```sql BEGIN;
CREATE TABLE test_gap_fill(id INTEGER, some_value text);
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
sql
SELECT array_min(ARRAY[45, 60, 43, 99]::SMALLINT[]);
Result:
| array_min | | ---------:| | 43 |
sql
SELECT array_min(ARRAY[45, 60, 43, 99]::INTEGER[]);
Result:
| array_min | | ---------:| | 43 |
sql
SELECT array_min(ARRAY[45, 60, 43, 99]::BIGINT[]);
Result:
| array_min | | ---------:| | 43 |
sql
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::REAL[]);
Result:
| array_min | | ---------:| | 43.7 |
sql
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::DOUBLE PRECISION[]);
Result:
| array_min | | ---------:| | 43.7 |
sql
SELECT array_min(ARRAY[45.6, 60.8, 43.7, 99.3]::NUMERIC[]);
Result:
| array_min | | ---------:| | 43.7 |
sql
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
sql
SELECT array_max(ARRAY[45, 60, 43, 99]::SMALLINT[]);
Result:
| array_max | | ---------:| | 99 |
sql
SELECT array_max(ARRAY[45, 60, 43, 99]::INTEGER[]);
Result:
| array_max | | ---------:| | 99 |
sql
SELECT array_max(ARRAY[45, 60, 43, 99]::BIGINT[]);
Result:
| array_max | | ---------:| | 99 |
sql
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::REAL[]);
Result:
| array_max | | ---------:| | 99.3 |
sql
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::DOUBLE PRECISION[]);
Result:
| array_max | | ---------:| | 99.3 |
sql
SELECT array_max(ARRAY[45.6, 60.8, 43, 99.3]::NUMERIC[]);
Result:
| array_max | | ---------:| | 99.3 |
sql
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
sql
SELECT array_avg(ARRAY[45, 60, 43, 99]::SMALLINT[]);
Result:
| array_avg | | ---------:| | 62 |
sql
SELECT array_avg(ARRAY[45, 60, 43, 99]::INTEGER[]);
Result:
| array_avg | | ---------:| | 62 |
sql
SELECT array_avg(ARRAY[45, 60, 43, 99]::BIGINT[]);
Result:
| array_avg | | ---------:| | 62 |
sql
SELECT array_avg(ARRAY[45.6, 60.8, 43, 99.3]::REAL[]);
Result:
| array_avg | | ----------------:| | 62.1750001907349 |
sql
SELECT array_avg(ARRAY[45.6, 60.8, 43, 99.3]::DOUBLE PRECISION[]);
Result:
| array_avg | | ---------:| | 62.175 |
sql
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
sql
SELECT array_sum(ARRAY[45, 60, 43, 99]::SMALLINT[]);
Result:
| array_sum | | ---------:| | 247 |
sql
SELECT array_sum(ARRAY[45, 60, 43, 99]::INTEGER[]);
Result:
| array_sum | | ---------:| | 247 |
sql
SELECT array_sum(ARRAY[45, 60, 43, 99]::BIGINT[]);
Result:
| array_sum | | ---------:| | 247 |
sql
SELECT array_sum(ARRAY[45.6, 60.8, 43.7, 99.3]::REAL[]);
Result:
| array_sum | | ---------:| | 249.4 |
sql
SELECT array_sum(ARRAY[45.6, 60.8, 43.7, 99.3]::DOUBLE PRECISION[]);
Result:
| array_sum | | ---------:| | 249.4 |
sql
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
sql
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
sql
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
sql
-- 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 |
sql
-- Timestamp with time zone
SELECT to_unix_timestamp('2018-01-01 00:00:00+01') AS unix_timestamp;
Result:
| unix_timestamp | | --------------:| | 1514761200 |
FUNCTION hex2bigint
Creates a functions which returns a hexadecimal number given as text as bigint.
Example
sql
SELECT hex2bigint('a1b0') AS hex_as_bigint;
Result:
| hex_as_bigint| | ------------:| | 41392 |
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
sql
-- 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'} |
sql
-- 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'} |
sql
-- 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'} |