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Aggregate Functions ​

SQL aggregate function expressions.

AggregateNode ​

The AggregateNode class represents a SQL AST node for an aggregate function call. Users should not need to instantiate AggregateNode instances directly, but instead should use aggregate function methods such as count(), sum(), etc.

distinct ​

AggregateNode.distinct()

Returns a new AggregateNode instance that applies the aggregation over distinct values only.

where ​

AggregateNode.where(filter)

Returns a new AggregateNode instance filtered according to a Boolean-valied filter expression.

window ​

AggregateNode.window()

Returns a windowed version of this aggregate function as a new WindowNode instance.

partitionby ​

AggregateNode.partitionby(...expressions)

Provide one or more expressions by which to partition a windowed version of this aggregate function and returns a new WindowNode instance.

orderby ​

AggregateNode.orderby(...expressions)

Provide one or more expressions by which to sort a windowed version of this aggregate function and returns a new WindowNodw instance.

rows ​

AggregateNode.rows(expression)

Provide a window "rows" frame specification as an array or array-valued expression and returns a windowed version of this aggregate function as a new WindowNode instance. A "rows" window frame is insensitive to peer rows (those that are tied according to the orderby criteria). The frame expression should evaluate to a two-element array indicating the number of preceding or following rows. A zero value (0) indicates the current row. A non-finite value (including null and undefined) indicates either unbounded preceding row (for the first array entry) or unbounded following rows (for the second array entry).

range ​

AggregateNode.range(expression)

Provide a window "range" frame specification as an array or array-valued expression and returns a windowed version of this aggregate function as a new WindowNode instance. A "range" window grows to include peer rows (those that are tied according to the orderby criteria). The frame expression should evaluate to a two-element array indicating the number of preceding or following rows. A zero value (0) indicates the current row. A non-finite value (including null and undefined) indicates either unbounded preceding row (for the first array entry) or unbounded following rows (for the second array entry).

count ​

count()

Create an aggregate function that counts the number of records.

avg ​

avg(expression)

Create an aggregate function that calculates the average of the input expression.

mad ​

mad(expression)

Create an aggregate function that calculates the median absolute deviation (MAD) of the input expression.

max ​

max(expression)

Create an aggregate function that calculates the maximum of the input expression.

min ​

min(expression)

Create an aggregate function that calculates the minimum of the input expression.

sum ​

sum(expression)

Create an aggregate function that calculates the sum of the input expression.

product ​

product(expression)

Create an aggregate function that calculates the product of the input expression.

median ​

median(expression)

Create an aggregate function that calculates the average of the input expression.

quantile ​

quantile(expression, p)

Create an aggregate function that calculates the p-th quantile of the input expression. For example, p = 0.5 computes the median, while 0.25 computes the lower inter-quartile range boundary.

mode ​

mode(expression)

Create an aggregate function that calculates the mode of the input expression.

variance ​

variance(expression)

Create an aggregate function that calculates the sample variance of the input expression.

stddev ​

stddev(expression)

Create an aggregate function that calculates the sample standard deviation of the input expression.

skewness ​

skewness(expression)

Create an aggregate function that calculates the skewness of the input expression.

kurtosis ​

kurtosis(expression)

Create an aggregate function that calculates the kurtosis of the input expression.

entropy ​

entropy(expression)

Create an aggregate function that calculates the entropy of the input expression.

varPop ​

varPop(expression)

Create an aggregate function that calculates the population variance of the input expression.

stddevPop ​

stddevPop(expression)

Create an aggregate function that calculates the population standard deviation of the input expression.

corr ​

corr(a, b)

Create an aggregate function that calculates the correlation between the input expressions a and b.

covarPop ​

covarPop(a, b)

Create an aggregate function that calculates the population covariance between the input expressions a and b.

regrIntercept ​

regrIntercept(y, x)

Create an aggregate function that returns the intercept of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrSlope ​

regrSlope(y, x)

Create an aggregate function that returns the slope of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrCount ​

regrCount(y, x)

Create an aggregate function that returns the count of non-null values used to fit the linear regression model that predicts the target expression y based on the predictor expression x.

regrR2 ​

regrR2(y, x)

Create an aggregate function that returns the R^2 value of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrSXX ​

regrSXX(y, x)

Create an aggregate function that returns the SXX value (regrCount(y, x) * varPop(x)) of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrSYY ​

regrSYY(y, x)

Create an aggregate function that returns the SYY value (regrCount(y, x) * varPop(y)) of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrSXY ​

regrSXY(y, x)

Create an aggregate function that returns the SXY (regrCount(y, x) * covarPop(y, x)) value of the fitted linear regression model that predicts the target expression y based on the predictor expression x.

regrAvgX ​

regrAvgX(y, x)

Create an aggregate function that returns the average x value of the data used to fit the linear regression model that predicts the target expression y based on the predictor expression x.

regrAvgY ​

regrAvgY(y, x)

Create an aggregate function that returns the average x value of the data used to fit the linear regression model that predicts the target expression y based on the predictor expression x.

first ​

first(expression)

Create an aggregate function that calculates the first observed value of the input expression.

last ​

last(expression)

Create an aggregate function that calculates the last observed value of the input expression.

argmax ​

argmax(arg, value)

Create an aggregate function that returns the expression arg corresponding to the maximum value of the expression value.

argmin ​

argmin(arg, value)

Create an aggregate function that returns the expression arg corresponding to the minimum value of the expression value.

stringAgg ​

stringAgg(expression)

Create an aggregate function that returns the string concatenation of the input expression values.

arrayAgg ​

arrayAgg(expression)

Create an aggregate function that returns a list of the input expression values.