Type predicates in Snowflake are used to determine if a value in a VARIANT column is a particular data type. Learn how type predicates work with semi-structured data.
Table of Contents
Question
What are type predicates used for?
A. Extracting data from a VARIANT column
B. Casting a value in a VARIANT column to a particular data type
C. Determining if a value in a VARIANT column is a particular data type
D. Manipulating objects and arrays in a VARIANT column
Answer
C. Determining if a value in a VARIANT column is a particular data type
Explanation
Type predicates in Snowflake are used for determining if a value stored in a VARIANT column is of a particular data type.
VARIANT is a semi-structured data type in Snowflake that can hold values of different data types within the same column, such as objects, arrays, numbers, strings, booleans, and nulls. This flexibility is useful for storing JSON, Avro, XML, and other semi-structured data.
Since a VARIANT column can contain mixed data types, type predicates allow you to test the data type of a value. The type predicate functions have names like IS_ARRAY, IS_BOOLEAN, IS_NUMBER, IS_OBJECT, IS_STRING, etc. They return true if the VARIANT value matches the specified data type.
For example, if you had a VARIANT column called “data”, you could use IS_NUMBER(data) to check if each value is a number. This would return true for numeric values and false for strings, objects, nulls, etc.
Type predicates are helpful for querying and filtering VARIANT data based on type. But to actually retrieve a value cast as a particular data type, you would use a type conversion function like TO_NUMBER() or TO_STRING() instead.
So in summary, type predicates test the data type, while conversion functions extract a value as a specific type. Both are key for working with semi-structured VARIANT data in Snowflake.
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