Miscellaneous functions

Documents additional functions and those contributed by other projects.

array_get

Returns the object value at a given array index.

array_get(array, index)

array is the object type, index must be an integer, and the return type is an object.

1-based indexing is used. The actual array value should be a java.sql.Array or java array type. A null is returned if either argument is null, or if the index is out of bounds.

array_length

Returns the length for a given array.

array_length(array)

array is the object type, and the return type is integer.

The actual array value should be a java.sql.Array or java array type. An exception is thrown if the array value is the wrong type.

uuid

Returns a universally unique identifier.

uuid()

The return type is string.

Generates a type 4 (pseudo randomly generated) UUID using a cryptographically strong random number generator. The format is XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX where each X is a hex digit.

Data quality functions

Data Quality functions are contributed by the ODDQ Project. The functions are prefixed with osdq., but can be called without the prefix.

osdq.random

Returns the randomized string. For example, jboss teiid may randomize to jtids soibe.

random(sourceValue)

The sourceValue is the string to be randomized.

osdq.digit

Returns digit characters of the string. For example, a1 b2 c3 d4 becomes 1234.

digit(sourceValue)

The sourceValue is the string from which you want to extract digit characters.

osdq.whitespaceIndex

Returns the index of the first whitespace. For example, jboss teiid will return 5.

whitespaceIndex(sourceValue)

The sourceValue is the string from which you want to find the whitespace index.

osdq.validCreditCard

Check whether a credit card number is valid. Returns true if it matches credit card logic and checksum.

validCreditCard(cc)

cc is the credit card number string to check.

osdq.validSSN

Check whether a social security number (SSN) is valid. Returns true if it matches SSN logic.

validSSN(ssn)

ssn is the social security number string to check.

osdq.validPhone

Check whether a phone number is valid. Returns true if the number matches phone logic. Numbers must contain more than 8, but less than 12 characters, and cannot start with 000.

validPhone(phone)

`phone is the phone number string need to check.

osdq.validEmail

Check whether an email address is valid. Returns true if valid.

validEmail(email)

email is the email address string to check.

osdq.cosineDistance

Returns the float distance between two strings based on the Cosine Similarity algorithm.

cosineDistance(a, b)

a and b are strings for which you want to calculate the distance.

osdq.jaccardDistance

Returns the float distance between two strings, based on the Jaccard similarity algorithm.

jaccardDistance(a, b)

The a and b are strings for which you want to calculate the distance.

osdq.jaroWinklerDistance

Returns the float distance between two strings based on the Jaro-Winkler algorithm.

jaroWinklerDistance(a, b)

The a and b are strings for which you want to calculate the distance.

osdq.levenshteinDistance

Returns the float distance between two strings based on the Levenshtein algorithm.

levenshteinDistance(a, b)

The a and b are strings for which you want to calculate the distance.

osdq.intersectionFuzzy

Returns the set of unique elements from the first set with cosine distance less than the specified value to every member of the second set.

intersectionFuzzy(a, b)

a and b are string arrays. c is a float representing the distance, such that 0.0 or less will match any and > 1.0 will match exact.

osdq.minusFuzzy

Returns the set of unique elements from the first set with cosine distance less than the specified value to every member of the second set.

minusFuzzy(a, b, c)

a and b are string arrays. c is a float representing the distance, such that 0.0 or less will match any and > 1.0 will match exact.

osdq.unionFuzzy

Returns the set of unique elements that contains members from the first set and members of the second set that have a cosine distance less than the specified value to every member of the first set.

unionFuzzy(a, b, c)

a and b are string arrays. c is a float representing the distance, such that 0.0 or less will match any and > 1.0 will match exact.

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