QUALIFY row_number() over (partition by d. 4 years in healthcare and 1.5years in mortgage/financial domain. Select '%' || $1 || '%' as mmm, seq8() as seq from values ('aa'),('ab'),('ba'),('ba') 10 years of exp in different databases/data warehouses like Snowflake, Oracle, DynamoDB, Splunk. However, in ANSI SQL the IN operator also allows you to filter on the result set of a SELECT statement. Where this one uses a sequence to also pick the "lowest" match: WITH match AS ( 1 Just as the IN operator allows you to specify multiple values in a WHERE clause, LIKE ANY / LIKE ALL can do the same for Wildcard queries in SnowSQL. QUALIFY row_number() over (partition by d.ddd ORDER BY true) = 1 That’s billions of trillions of them, now mostly melted away as spring approaches. Select '%' || $1 || '%' as mmm from values ('aa'),('ab'),('ba'),('ba') Sextillions of snowflakes fell from the sky this winter. If the input string matches any of the patterns, this returns the input string. Select $1 as ddd from values ('caa'),('cba'),('cbc')īut if you have multiple match rows that match the data, you will get multiple output rows, this can be removed via QUALIFY, but the one below is unstable: WITH match AS ( Allows case-sensitive matching of strings based on comparison with one or more patterns. Which can be written as a JOIN like so: WITH match AS ( WHERE d.ddd LIKE ANY (SELECT mmm FROM match) SELECT $1 as ddd FROM VALUES ('caa'),('cba'),('cbc') So this is Felipe's code with works, with both data and match strings push into CTE's WITH match AS ( Now this can be in of itself not optimal when table_b is huge, but then you might know how to push some filters down into that sub-select, but this is the nature of how to structure the work. ![]() JOIN (SELECT DISTINCT coulmn_y FROM table_b) AS b ON a.column_x = b.coulmn_y ![]() JOIN (SELECT DISTINCT coulmn_y FROM table_b) ON lumn_x = coulmn_yīut now you might have some there are multiple column_z things errors. WHERE column_x IN (SELECT column_y FROM table_b) LIKE ANY Snowflake Documentation Categories: String & Binary Functions (Matching/Comparison) LIKE ANY Allows case-sensitive matching of strings based on comparison with one or more patterns. But you can flip any sub-query into a JOIN. If small row based databases, doing lookups per row is simple/optimal, but on a big database like snowflake the optimal way is not so obvious. As Felipe noted 'it works' BUT it can sometime give you the error "unsupported correlated subquery" but it is a corolated sub-query. RLIKE function in Snowflake - SQL Syntax and Examples RLIKE Description Returns true if the subject matches the specified pattern.
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