What type of function can be used to estimate the approximate number of distinct values from a table that has trillions of rows?
What type of function can be used to estimate the approximate number of distinct values from a table that has trillions of rows?
To estimate the approximate number of distinct values from a table with trillions of rows, the HyperLogLog (HLL) algorithm is appropriate. HLL is a state-of-the-art cardinality estimation technique used for providing efficient and precise estimates of distinct values in large datasets. It offers a trade-off between the accuracy of the estimates and storage requirements, making it feasible to handle such large data volumes with acceptable error rates.
Snowflake uses HyperLogLog to estimate the approximate number of distinct values in a data set. HyperLogLog is a state-of-the-art cardinality estimation algorithm, capable of estimating distinct cardinalities of trillions of rows with an average relative error of a few percent. HyperLogLog can be used in place of COUNT(DISTINCT …) in situations where estimating cardinality is acceptable.
Correct
D. HyperLogLog (HLL)