SnowConvert AI - Redshift - Built-in functions¶

Note

For more information about built-in functions and their Snowflake equivalents, also see Common built-in functions.

Fonctions d’agrégation¶

Aggregate functions compute a single result value from a set of input values. (Redshift SQL Language Reference Aggregate Functions).

Redshift	Snowflake
ANY_VALUE ( [ DISTINCT	ALL ] expression )
AVG ( [ DISTINCT \| ALL ] expression )	AVG ( [ DISTINCT ] expression) Notes: Redshift and Snowflake may show different precision/decimals due to data type rounding/formatting.
COUNT	COUNT
LISTAGG	LISTAGG Notes: Redshift’s DISTINCT ignores trailing spaces (“a “ = “a”); Snowflake’s does not. (See SSC-FDM-PG0013).
MAX	MAX
MEDIAN	MEDIAN Notes: Snowflake does not allow the use of date types, while Redshift does. (See SSC-FDM-PG0013).
MIN	MIN
PERCENTILE_CONT	PERCENTILE_CONT
STDDEV/STDDEV_SAMP ( [ DISTINCT	ALL ] expression) STDDEV_POP ( [ DISTINCT
SUM	SUM
VARIANCE/VAR_SAMP ( [ DISTINCT	ALL ] expression) VAR_POP ( [ DISTINCT

Array Functions¶

Creates an array of the SUPER data type. (Redshift SQL Language Reference Array Functions).

Redshift	Snowflake
ARRAY ( [ expr1 ] [ , expr2 [ , … ] ] )	ARRAY_CONSTRUCT ( [ <expr1> ] [ , <expr2> [ , … ] ] )
ARRAY_CONCAT ( super_expr1, super_expr2 )	ARRAY_CAT ( <array1> , <array2> )
ARRAY_FLATTEN ( super_expr1,super_expr2,.. )	ARRAY_FLATTEN ( <array> ) Notes: the results may vary between platforms (See SSC-FDM-PG0013).
GET_ARRAY_LENGTH ( super_expr )	ARRAY_SIZE ( <array> \| <variant>)
SPLIT_TO_ARRAY ( string,delimiter )	SPLIT (<string>, <separator>) Notes: Redshift allows missing delimiters; Snowflake requires them, defaulting to comma
SUBARRAY ( super_expr, start_position, length )	ARRAY_SLICE ( <array> , <from> , <to> ) Notes: Function names and the second argument differ; adjust arguments for equivalence.

Conditional expressions¶

Redshift	Snowflake
DECODE	DECODE Notes: the results may vary between platforms (See SSC-FDM-PG0013).
COALESCE ( expression, expression, … )	COALESCE ( expression, expression, … )
GREATEST ( value [, …] )	GREATEST_IGNORE_NULLS ( <expr1> [, <expr2> … ] )
LEAST ( value [, …] )	LEAST_IGNORE_NULLS ( <expr1> [, <expr2> … ])
NVL( expression, expression, … )	NVL ( expression, expression ) Notes: Redshift’s NVL accepts multiple arguments; Snowflake’s NVL accepts only two. To match Redshift behavior, NVL with more than two arguments is converted to COALESCE.
NVL2	NVL2
NULLIF	NULLIF Notes: Redshift’s NULLIF ignores trailing spaces in some string comparisons, unlike Snowflake. Therefore, the transformation adds RTRIM for equivalence.

Data type formatting functions¶

Data type formatting functions provide an easy way to convert values from one data type to another. For each of these functions, the first argument is always the value to be formatted and the second argument contains the template for the new format. (Redshift SQL Language Reference Data type formatting functions).

Redshift	Snowflake
TO_CHAR	TO_CHAR Notes: Snowflake’s support for this function is partial (see SSC-EWI-0006).
TO_DATE	TO_DATE Notes: Snowflake’s `TO_DATE` fails on invalid dates like “20010631” (June has 30 days), unlike Redshift’s lenient `TO_DATE`. Use `TRY_TO_DATE` in Snowflake to handle these cases by returning NULL. (see SSC-FDM-RS0004, SSC-EWI-0006, SSC-FDM-0032).

Redshift

Snowflake

TO_CHAR

Notes: Snowflake’s support for this function is partial (see SSC-EWI-0006).

TO_DATE

Notes: Snowflake’s TO_DATE fails on invalid dates like “20010631” (June has 30 days), unlike Redshift’s lenient TO_DATE. Use TRY_TO_DATE in Snowflake to handle these cases by returning NULL. (see SSC-FDM-RS0004, SSC-EWI-0006, SSC-FDM-0032).

Date and time functions¶

Redshift	Snowflake
ADD_MONTHS	ADD_MONTHS Notes: the results may vary between platforms (See SSC-FDM-PG0013).
AT TIME ZONE “timezone”	CONVERT_TIMEZONE ( <source_tz> , <target_tz> , <source_timestamp_ntz> ) CONVERT_TIMEZONE ( <target_tz> , <source_timestamp> ) Notes: Redshift defaults to UTC; the Snowflake function requires explicit UTC specification. Therefore, it will be added as the target timezone.
CONVERT_TIMEZONE	CONVERT_TIMEZONE
CURRENT_DATE	CURRENT_DATE()
DATE	DATE
DATEADD/DATE_ADD ( datepart, interval, {date \| time \| timetz \| timestamp} )	DATE_ADD ( <date_or_time_part>, <value>, <date_or_time_expr> ) Notes: Invalid date part formats are translated to Snowflake-compatible formats.
DATEDIFF/DATE_DIFF	DATEDIFF Notes: Invalid date part formats are translated to Snowflake-compatible formats.
DATE_PART/PGDATE_PART	DATE_PART Notes: this function is partially supported by Snowflake. (See SSC-EWI-OOO6).
DATE_PART_YEAR (date)	YEAR ( <date_or_timestamp_expr> ) Notes: the results may vary between platforms (See SSC-FDM-PG0013).
DATE_TRUNC	DATE_TRUNC Notes: Invalid date part formats are translated to Snowflake-compatible formats.
GETDATE()	GETDATE()
LAST_DAY	LAST_DAY Notes: the results may vary between platforms (See SSC-FDM-PG0013).
NEXT_DAY	NEXT_DAY Notes: the results may vary between platforms (See SSC-FDM-PG0013).
SYSDATE	SYSDATE()
TIMESTAMP	TO_TIMESTAMP
TRUNC	TRUNC
EXTRACT	EXTRACT Notes: Part-time or Date time supported: DAY, DOW, DOY, EPOCH, HOUR, MINUTE, MONTH, QUARTER, SECOND, WEEK, YEAR.

Note

Redshift timestamps default to microsecond precision (6 digits); Snowflake defaults to nanosecond precision (9 digits). Adjust precision as needed using ALTER SESSION (e.g., ALTER SESSION SET TIMESTAMP_OUTPUT_FORMAT = 'YYYY-MM-DD HH24:MI:SS.FF2';). Precision loss may occur depending on the data type used.

Since some formats are incompatible with Snowflake, adjusting the account parameters DATE_INPUT_FORMAT or TIME_INPUT_FORMAT might maintain functional equivalence between platforms.

Fonctions de hachage¶

A hash function is a mathematical function that converts a numerical input value into another value. (Redshift SQL Language Reference Hash functions).

Redshift	Snowflake
FNV_HASH (value [, seed])	HASH ( <expr> [ , <expr> … ]

Redshift

Snowflake

FNV_HASH (value [, seed])

HASH ( <expr> [ , <expr> … ]

Fonctions JSON¶

Redshift	Snowflake
JSON_EXTRACT_PATH_TEXT	JSON_EXTRACT_PATH_TEXT Notes: Redshift treats newline, tab, and carriage return characters literally; Snowflake interprets them. A JSON literal and dot-separated path are required to access nested objects in the Snowflake function. Paths with spaces in variables must be quoted.

Redshift

Snowflake

JSON_EXTRACT_PATH_TEXT

Notes:

Redshift treats newline, tab, and carriage return characters literally; Snowflake interprets them.
A JSON literal and dot-separated path are required to access nested objects in the Snowflake function.
Paths with spaces in variables must be quoted.

Math functions¶

Redshift	Snowflake
ACOS	ACOS
ASIN	ASIN
ATAN	ATAN
ATAN2	ATAN2
CBRT	CBRT
CEIL/CEILING	CEIL
COS	COS
COT	COT
DEGREES	DEGREES
DEXP	EXP
DLOG1/LN	LN
DLOG10 (number)	LOG (10, number)
EXP	EXP
FLOOR	FLOOR
LOG	LOG
MOD	MOD
PI	PI
POWER/POW	POWER/POW
RADIANS	RADIANS
RANDOM	RANDOM
ROUND	ROUND
SIN	SIN
SIGN	SIGN
SQRT	SQRT
TAN	TAN
TRUNC	TRUNC

Note

Redshift and Snowflake results may differ in scale.

String functions¶

String functions process and manipulate character strings or expressions that evaluate to character strings. (Redshift SQL Language Reference String functions).

Redshift	Snowflake
ASCII	ASCII
BTRIM	TRIM
CHAR_LENGTH	LENGTH
CHARACTER_LENGTH	LENGTH
CHARINDEX	CHARINDEX
CHR	CHR
CONCAT	CONCAT
INITCAP	INITCAP
LEFT/RIGHT	LEFT/RIGHT Notes: For negative lengths in `LEFT`/`RIGHT`, Snowflake returns an empty string; Redshift raises an error.
LEN	LEN
LOWER	LOWER
OCTET_LENGTH	OCTET_LENGTH Notes: the results may vary between platforms (See SSC-FDM-PG0013).
QUOTE_IDENT (string)	CONCAT (“ »”, string, “ »”)
REGEXP_REPLACE	REGEXP_REPLACE Notes: This function includes a `parameters` argument that enables the user to interpret the pattern using the Perl Compatible Regular Expression (PCRE) dialect, represented by the `p` value, this is removed to avoid any issues. (See SSC-EWI-0009, SC-FDM-0032, SSC-FDM- PG0011).
REPEAT	REPEAT
REPLACE	REPLACE
REPLICATE	REPEAT
REVERSE	REVERSE
SOUNDEX	SOUNDEX Notes: Certain special characters, the results may vary between platforms (See SSC-FDM-PG0013).
SPLIT_PART	SPLIT_PART Notes: Snowflake and Redshift handle SPLIT_PART differently with case-insensitive collations.
STRPOS (string, substring )	POSITION ( <expr1> IN <expr> )
SUBSTRING	SUBSTRING Notes: Snowflake partially supports this function. Redshift’s `SUBSTRING`, with a non-positive `start_position`, calculates `start_position + number_characters` (returning “” if the result is non-positive). Snowflake’s behavior differs. (See SSC-EWI-RS0006).
TEXTLEN	LENGTH
TRANSLATE	TRANSLATE
TRIM	TRIM Notes: Redshift uses keywords (BOTH, LEADING, TRAILING) for trim; Snowflake uses TRIM, LTRIM, RTRIM.
UPPER	UPPER

SUPER type information functions¶

Redshift	Snowflake
IS_ARRAY	IS_ARRAY Notes: the results may vary between platforms (See SSC-FDM-PG0013).
IS_BOOLEAN	IS_BOOLEAN Notes: the results may vary between platforms (See SSC-FDM-PG0013).

Redshift

Snowflake

IS_ARRAY

Notes: the results may vary between platforms (See SSC-FDM-PG0013).

IS_BOOLEAN

Notes: the results may vary between platforms (See SSC-FDM-PG0013).

Window functions¶

Redshift	Snowflake
AVG	AVG Notes: AVG rounding/formatting can vary by data type between Redshift and Snowflake.
COUNT	COUNT
DENSE_RANK	DENSE_RANK Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with `ORDER BY 1`.
FIRST_VALUE	FIRST_VALUE Notes: Snowflake needs ORDER BY; missing clauses get `ORDER BY <expr>.`
LAG	LAG
LAST_VALUE	LAST_VALUE Notes: Snowflake needs ORDER BY; missing clauses get `ORDER BY <expr>`.
LEAD	LEAD Notes: Redshift allows constant or expression offsets; Snowflake allows only constant offsets.
LISTAGG	LISTAGG Notes: Redshift’s DISTINCT ignores trailing spaces (“a “ = “a”); Snowflake’s does not. (See SSC-FDM-PG0013).
MEDIAN	MEDIAN Notes: Snowflake does not allow the use of date types, while Redshift does. (See SSC-FDM-PG0013).
NTH_VALUE	NTH_VALUE Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with `ORDER BY 1`.
NTILE	NTILE Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with `ORDER BY 1`. (See SSC-FDM-PG0013).
PERCENT_RANK	PERCENT_RANK Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with `ORDER BY 1`.
PERCENTILE_CONT	PERCENTILE_CONT Notes: Rounding varies between platforms.
PERCENTILE_DISC	PERCENTILE_DISC
RANK	RANK
RATIO_TO_REPORT	RATIO_TO_REPORT Notes: the results may vary between platforms (See SSC-FDM-PG0013).
ROW_NUMBER	ROW_NUMBER Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with `ORDER BY 1`.
STDDEV_SAMP	STDDEV
VAR_SAMP	VARIANCE

Problèmes connus ¶

For more information about quoted identifiers in functions, click here.

IDENTITY¶

Description ¶

La fonction IDENTITY est une fonction de système qui opère sur une colonne spécifiée d’une table pour déterminer la valeur initiale de l’identité. Si la valeur initiale n’est pas disponible, elle prend par défaut la valeur fournie dans la fonction. Ceci sera traduit en séquence dans Snowflake.

Grammar Syntax ¶

 "identity"(oid_id, oid_table_id, default)

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Note

Cette fonction n’est plus prise en charge dans Redshift. Elle utilise la valeur par défaut pour définir l’identité et se comporte comme une colonne d’identité standard.

Modèles d’échantillons de sources¶

Code d’entrée :¶

Redshift¶

 CREATE TABLE IF NOT EXISTS table_test
(
    id integer,
    inventory_combo BIGINT  DEFAULT "identity"(850178, 0, '5,3'::text)
);

INSERT INTO table_test (id) VALUES
    (1),
    (2),
    (3),
    (4);

SELECT * FROM table_test;

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Results¶

id	inventory_combo
1	5
2	8
3	11
3	14

Code de sortie :

Snowflake¶

 CREATE TABLE IF NOT EXISTS table_test
(
    id integer,
    inventory_combo BIGINT IDENTITY(5,3) ORDER
)
COMMENT = '{ "origin": "sf_sc", "name": "snowconvert", "version": {  "major": 0,  "minor": 0,  "patch": "0" }, "attributes": {  "component": "redshift",  "convertedOn": "11/13/2024",  "domain": "test" }}';

INSERT INTO table_test (id) VALUES
    (1),
    (2),
    (3),
    (4);

SELECT * FROM
    table_test;

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Results¶

id	inventory_combo
1	5
2	8
3	11
3	14

EWIs connexes¶

Il n’y a pas de problème connu.

TO_CHAR¶

Date function

Description¶

TO\CHAR convertit un horodatage ou une expression numérique en format de données de type chaîne de caractères. (Référence linguistique Redshift SQL fonction TO_CHAR fonction)

Avertissement

Cette fonction est partiellement prise en charge par Snowflake.

Pour plus d’informations sur les identificateurs cités dans les fonctions, cliquez ici.

Grammar Syntax¶

 TO_CHAR(timestamp_expression | numeric_expression , 'format')

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Modèles d’échantillons de sources¶

Code d’entrée :¶

Redshift¶

 SELECT TO_CHAR(timestamp '2009-12-31 23:15:59', 'YYYY'),
       TO_CHAR(timestamp '2009-12-31 23:15:59', 'YYY'),
       TO_CHAR(timestamp '2009-12-31 23:15:59', 'TH'),
       "to_char"(timestamp '2009-12-31 23:15:59', 'MON-DY-DD-YYYY HH12:MIPM'),
       TO_CHAR(125.8, '999.99'),
       "to_char"(125.8, '999.99');

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Results¶

TO_CHAR	TO_CHAR	TO_CHAR	TO_CHAR	TO_CHAR
2009	009	DEC-THU-31-2009 11:15PM	125,80	125,80

Code de sortie :¶

Snowflake¶

 SELECT
       TO_CHAR(timestamp '2009-12-31 23:15:59', 'YYYY'),
       PUBLIC.YEAR_PART_UDF(timestamp '2009-12-31 23:15:59', 3),
       TO_CHAR(timestamp '2009-12-31 23:15:59', 'TH') !!!RESOLVE EWI!!! /*** SSC-EWI-0006 - TH FORMAT MAY FAIL OR MAY HAVE A DIFFERENT BEHAVIOR IN SNOWFLAKE. ***/!!!,
       PUBLIC.MONTH_SHORT_UDF(timestamp '2009-12-31 23:15:59', 'uppercase') || '-' || PUBLIC.DAYNAME_SHORT_UDF(timestamp '2009-12-31 23:15:59', 'uppercase') || TO_CHAR(timestamp '2009-12-31 23:15:59', '-DD-YYYY HH12:MI') || PUBLIC.MERIDIAN_INDICATORS_UDF(timestamp '2009-12-31 23:15:59', 'uppercase'),
       TO_CHAR(125.8, '999.99'),
       TO_CHAR(125.8, '999.99');

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Results¶

TO_CHAR	TO_CHAR
2009	Déc-Jeu-31-2009 11 :15PM

Problèmes connus ¶

Aucun problème n’a été constaté.

EWIs connexes¶

SSC-EWI-0006: The current date/numeric format may have a different behavior in Snowflake.

Pour les valeurs temporelles¶

Translation specification for the TO_CHAR function when transforming date or timestamp values to string

Description¶

Les chaînes de format suivantes s’appliquent à des fonctions telles que TO_CHAR. Ces chaînes peuvent contenir des séparateurs de date (tels que “-”, “/” ou “:”) ainsi que les « dateparts » et « timeparts » suivants. (Page de référence des chaînes de format datetime de Redshift)

Grammar Syntax¶

TO_CHAR (timestamp_expression, 'format')

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La table suivante spécifie le mappage de chaque élément de format à Snowflake :

Redshift	Snowflake
`BC AD, bc, ad` (indicateurs d’époque en majuscules et minuscules)	`PUBLIC.ERA_INDICATORS_UDF`
`B.C,. A.D., b.c., a.d.` (majuscules et minuscules, indicateurs d’époque avec points)	`PUBLIC.ERA_INDICATORS_WITH_POINTS_UDF`
`CC`	`PUBLIC.CENTURY_UDF`
`YYYY` et `YY`	Pris en charge directement
`YYY` et `Y`	`PUBLIC.YEAR_PART_UDF`
`Y,YYY`	`PUBLIC.YEAR_WITH_COMMA_UDF`
`IYYY`	`YEAROFWEEKISO`
`I, IY, IYY`	`PUBLIC.ISO_YEAR_PART_UDF`
`Q`	`QUARTER`
`MONTH Mois, mois`	`PUBLIC.FULL_MONTH_NAME_UDF`
`MON, Moi, moi`	`PUBLIC.MONTH_SHORT_UDF`
`RM, rm`	`PUBLIC.ROMAN_NUMERALS_MONTH_UDF`
`W`	`PUBLIC.WEEK_OF_MONTH_UDF`
`WW`	`PUBLIC.WEEK_NUMBER_UDF`
`IW`	`WEEKISO`
`DAY, Jour, jour`	`PUBLIC.DAYNAME_LONG_UDF`
`DY, Jr, jr`	`PUBLIC.DAYNAME_SHORT_UDF`
`DDD`	`DAYOFYEAR`
`IDDD`	`PUBLIC.DAY_OF_YEAR_ISO_UDF`
`D`	`PUBLIC.DAY_OF_WEEK_UDF` Notes: For this UDF to work correctly the Snowflake session parameter `WEEK_START` should have its default value (`0`).
`ID`	`DAYOFWEEKISO`
`J`	`PUBLIC.JULIAN_DAY_UDF`
`HH24`	Pris en charge directement
`HH`	`HH12`
`HH12`	Pris en charge directement
`MI`	Pris en charge directement
`SS`	Pris en charge directement
`MS`	`FF3`
`US`	`FF6`
`AM PM, am, pm (indicateurs méridiens en majuscules et minuscules)`	`PUBLIC.MERIDIAN_INDICATORS_UDF`
`A.M., P.M., a.m., p.m.` (indicateurs méridiens majuscules et minuscules avec points)	`PUBLIC.MERIDIAN_INDICATORS_WITH_POINTS_UDF`
`TZ` et `tz`	`UTC` and `utc` Notes: According to the redshift documentation, all timestamp with time zone are stored in UTC, which causes this format element to return a fixed result.
`OF`	+00 Notes: According to the redshift documentation, all timestamp with time zone are stored in UTC, which causes this format element to return a fixed result.
`SSSS`	`PUBLIC.SECONDS_PAST_MIDNIGHT`
`SP`	Notes: This is a PostgreSQL template pattern modifier for « spell mode », however it does nothing on Redshift, so it is removed from the output.
`FX`	Notes: This is another template pattern modifier for « fixed format », however it has no use on the TO_CHAR function so it is removed.

Modèles d’échantillons de sources¶

Transformation directe des éléments de format (pas de fonctions/UDFs)¶

Le résultat est conservé sous la forme d’une fonction unique TO_CHAR

Redshift¶

Query¶

 SELECT TO_CHAR('2013-10-03 13:50:15.456871'::TIMESTAMP, 'DD/MM/YY HH:MI:SS.MS') AS col1;

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Result¶

+----------------------+
|col1                  |
+----------------------+
|03/10/13 01:50:15.456 |
+----------------------+

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Snowflake¶

Query¶

 SELECT TO_CHAR('2013-10-03 13:50:15.456871'::TIMESTAMP, 'DD/MM/YY HH12:MI:SS.FF3') AS col1;

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Result¶

+----------------------+
|col1                  |
+----------------------+
|03/10/13 01:50:15.456 |
+----------------------+

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Transformation de format à l’aide de fonctions/UDFs¶

Le résultat est une concaténation de plusieurs fonctions intégrées TOCHAR, UDFs et Snowflake qui génèrent la représentation équivalente sous forme de chaîne de la valeur de l’heure de la date

Redshift¶

Query¶

 SELECT TO_CHAR(DATE '2025-07-05', '"Today is " Month DAY DD, "it belongs to the week " IW') AS result;

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Result¶

+-------------------------------------------------------------+
|result                                                       |
+-------------------------------------------------------------+
|Today is  July      SATURDAY  05, it belongs to the week  27 |
+-------------------------------------------------------------+

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Snowflake¶

Query¶

 SELECT
    'Today is ' ||
    TO_CHAR(DATE '2025-07-05', ' ') ||
    PUBLIC.FULL_MONTH_NAME_UDF(DATE '2025-07-05', 'firstOnly') ||
    ' ' ||
    PUBLIC.DAYNAME_LONG_UDF(DATE '2025-07-05', 'uppercase') ||
    TO_CHAR(DATE '2025-07-05', ' DD, ') ||
    'it belongs to the week ' ||
    TO_CHAR(DATE '2025-07-05', ' ') ||
    WEEKISO(DATE '2025-07-05') AS result;

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Result¶

+-------------------------------------------------------------+
|result                                                       |
+-------------------------------------------------------------+
|Today is  July      SATURDAY  05, it belongs to the week  27 |
+-------------------------------------------------------------+

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Texte cité¶

Les éléments de format dans le texte entre guillemets doubles sont ajoutés à la sortie directement sans les interpréter, les guillemets doubles échappés sont transformés en leur équivalent échappé dans Snowflake.

Redshift¶

Query¶

 SELECT
    TO_CHAR(DATE '2025-01-16', 'MM "TESTING DD" DD') AS result1,
    TO_CHAR(DATE '2025-01-16', 'MM TESTING \\"DD\\" DD') AS result2,
    TO_CHAR(DATE '2025-01-16', 'MM "TESTING \\"DD\\"" DD') AS result3;

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Result¶

+-----------------+-------------------+-------------------+
|result1          |result2            |result3            |
+-----------------+-------------------+-------------------+
|01 TESTING DD 16 |01 TEST5NG "16" 16 |01 TESTING "DD" 16 |
+-----------------+-------------------+-------------------+

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Snowflake¶

Query¶

 SELECT
    TO_CHAR(DATE '2025-01-16', 'MM ') || 'TESTING DD' || TO_CHAR(DATE '2025-01-16', ' DD') AS result1,
    TO_CHAR(DATE '2025-01-16', 'MM TEST') || PUBLIC.ISO_YEAR_PART_UDF(DATE '2025-01-16', 1) || TO_CHAR(DATE '2025-01-16', 'NG ""DD"" DD') AS result2,
    TO_CHAR(DATE '2025-01-16', 'MM ') || 'TESTING "DD"' || TO_CHAR(DATE '2025-01-16', ' DD') AS result3;

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Result¶

+-----------------+-------------------+-------------------+
|result1          |result2            |result3            |
+-----------------+-------------------+-------------------+
|01 TESTING DD 16 |01 TEST5NG "16" 16 |01 TESTING "DD" 16 |
+-----------------+-------------------+-------------------+

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Problèmes connus¶

Les modificateurs de modèles ne sont pas pris en charge¶

Les modificateurs de modèles de format suivants :

FM (mode remplissage)
TH et th (suffixe du nombre ordinal en majuscules et minuscules)
TM (mode traduction)

Are not supported, including them in a format will generate SSC-EWI-0006

Code d’entrée :

 SELECT TO_CHAR(CURRENT_DATE, 'FMMonth'),
TO_CHAR(CURRENT_DATE, 'DDTH'),
TO_CHAR(CURRENT_DATE, 'DDth'),
TO_CHAR(CURRENT_DATE, 'TMMonth');

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Code de sortie :

 SELECT
TO_CHAR(CURRENT_DATE(), 'FM') || PUBLIC.FULL_MONTH_NAME_UDF(CURRENT_DATE(), 'firstOnly') !!!RESOLVE EWI!!! /*** SSC-EWI-0006 - FMMonth FORMAT MAY FAIL OR MAY HAVE A DIFFERENT BEHAVIOR IN SNOWFLAKE. ***/!!!,
TO_CHAR(CURRENT_DATE(), 'DDTH') !!!RESOLVE EWI!!! /*** SSC-EWI-0006 - DDTH FORMAT MAY FAIL OR MAY HAVE A DIFFERENT BEHAVIOR IN SNOWFLAKE. ***/!!!,
TO_CHAR(CURRENT_DATE(), 'DDth') !!!RESOLVE EWI!!! /*** SSC-EWI-0006 - DDth FORMAT MAY FAIL OR MAY HAVE A DIFFERENT BEHAVIOR IN SNOWFLAKE. ***/!!!,
TO_CHAR(CURRENT_DATE(), 'TM') || PUBLIC.FULL_MONTH_NAME_UDF(CURRENT_DATE(), 'firstOnly') !!!RESOLVE EWI!!! /*** SSC-EWI-0006 - TMMonth FORMAT MAY FAIL OR MAY HAVE A DIFFERENT BEHAVIOR IN SNOWFLAKE. ***/!!!;

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Paramètre du format transmis par la variable

Lorsque le paramètre du format est transmis comme une variable au lieu d’un littéral de chaîne, la transformation des éléments de format ne peut pas être appliquée, un avertissement FDM sera ajouté aux utilisations de la fonction à ce sujet.

Code d’entrée :

 SELECT TO_CHAR(d, 'YYYY/MM/DD'),
TO_CHAR(d, f)
FROM (SELECT TO_DATE('2001-01-01','YYYY-MM-DD') as d, 'DD/MM/YYYY' as f);

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Code de sortie :

 SELECT TO_CHAR(d, 'YYYY/MM/DD'),
--** SSC-FDM-0032 - PARAMETER 'format_string' IS NOT A LITERAL VALUE, TRANSFORMATION COULD NOT BE FULLY APPLIED **
TO_CHAR(d, f)
FROM (SELECT TO_DATE('2001-01-01','YYYY-MM-DD') as d, 'DD/MM/YYYY' as f);

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EWIs connexes¶

SSC-EWI-0006: The current date/numeric format may have a different behavior in Snowflake.
[SSC-FDM-0032](../../general/technical-documentation/issues-and-troubleshooting/functional-difference/generalFDM. md#ssc-fdm-0032) : le paramètre n’est pas une valeur littérale, la transformation n’a pas pu être entièrement appliquée