Functions

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correlation(x:y:)

Calculates the correlation coefficient between two numeric columns.

correlation(x: DOUBLE, y: DOUBLE) -> DOUBLE

population_covariance(x:y:)

Calculates the population covariance between two numeric columns.

population_covariance(x: DOUBLE, y: DOUBLE) -> DOUBLE

sample_covariance(x:y:)

Calculates the sample covariance between two numeric columns.

sample_covariance(x: DOUBLE, y: DOUBLE) -> DOUBLE

kurtosis(x:)

The excess kurtosis (Fisher’s definition) with bias correction according to the sample size.

kurtosis(x: DOUBLE) -> DOUBLE

population_standard_deviation(arg:)

Calculates the population standard deviation of the input values.

population_standard_deviation(arg: DOUBLE) -> DOUBLE

sample_standard_deviation(arg:)

Calculates the sample standard deviation of the input values.

sample_standard_deviation(arg: DOUBLE) -> DOUBLE

population_variance(arg:)

Calculates the population variance of the input values.

population_variance(arg: DOUBLE) -> DOUBLE

sample_variance(arg:)

Calculates the sample variance of the input values.

sample_variance(arg: DOUBLE) -> DOUBLE

average(arg:)

Calculates the average of all non-null values in arg.

average(arg: DOUBLE) -> DOUBLE

geometric_mean(arg:)

Calculates the geometric mean of all non-null values in arg.

geometric_mean(arg: DOUBLE) -> DOUBLE

max(arg:)

Returns the maximum value present in arg.

max(arg: DOUBLE) -> DOUBLE

min(arg:)

Returns the minimum value present in arg.

min(arg: DOUBLE) -> DOUBLE

sum(arg:)

Calculates the sum of all non-null values in arg.

sum(arg: DOUBLE) -> DOUBLE

product(arg:)

Calculates the product of all non-null values in arg.

product(arg: DOUBLE) -> DOUBLE

count(arg:)

Returns the number of non-null values in arg.

count(arg: DOUBLE) -> BIGINT

approx_quantile(arg:quantile:)

Returns the approximate quantile value for the given quantile (0.0 to 1.0) from arg.

approx_quantile(arg: DOUBLE, quantile: DOUBLE) -> DOUBLE