Returns the number of non-null number pairs in a group. Returns the average of the dependent variable for non-null pairs in a group, where x is the independent variable and y is the dependent variable. Returns the average of the independent variable for non-null pairs in a group, where x is the independent variable and y is the dependent variable. If pos is a LIST of FLOATs, then the result is a LIST of the corresponding exact quantiles. Returns the exact quantile number between 0 and 1. If pos is a LIST of FLOATs, then the result is a LIST of the corresponding intepolated quantiles. Returns the intepolated quantile number between 0 and 1. Returns the most frequent value for the values within x. For even value counts, quantitiative values are averaged and ordinal values return the lower value. Temporal types return a positive INTERVAL. Returns the median absolute deviation for the values within x. Returns the excess kurtosis (Fisher’s definition) of all input values, with a bias correction according to the sample size. Returns the log-2 entropy of count input-values. Returns the population covariance of input values. Returns the correlation coefficient for non-null pairs in a group.ĬOVAR_POP(y, x) / (STDDEV_POP(x) * STDDEV_POP(y)) The table below shows the available statistical aggregate functions.
Gives the approximate quantile using reservoir sampling, the sample size is optional and uses 8192 as a default size. Reservoir_quantile(x,quantile,sample_size=8192) Gives the approximate quantile using T-Digest. Gives the approximate count of distintinct elements using HyperLogLog. The table below shows the available approximate aggregate functions. Returns the minumum value present in arg.Ĭalculates the product of all tuples in argĬoncatenates the column string values with a separatorĬalculates the sum value for all tuples in arg. Returns the maximum value present in arg. Returns a LIST containing all the values of a column. Returns a LIST of STRUCTs with the fields bucket and count. Returns TRUE if any input value is TRUE, otherwise FALSE.Ĭalculates the number of tuples tuples in arg.Ĭalculates the average using a more accurate floating point summation (Kahan Sum).Ĭalculates the sum using a more accurate floating point summation (Kahan Sum). Returns TRUE if every input value is TRUE, otherwise FALSE. Returns a bitstring with bits set for each distinct value. Returns the bitwise XOR of all bits in a given expression. Returns the bitwise OR of all bits in a given expression. Returns the bitwise AND of all bits in a given expression. Calculates the arg expression at that row.Ĭalculates the average value for all tuples in arg.
Calculates the arg expression at that row.įinds the row with the minimum val. Returns the first non-null value from arg.įinds the row with the maximum val. The table below shows the available general aggregate functions. These can be made deterministic by ordering the arguments.įor order-insensitive aggregates, this clause is parsed and applied, which is inefficient, but still produces the same result. (e.g., first, last, list and string_agg). Usually this is not important, but there are some order-sensitive aggregates that can have indeterminate results When the ORDER BY clause is provided, the values being aggregated are sorted before applying the function. This is typically used in combination with the COUNT aggregate to get the number of distinct elements but it can be used together with any aggregate function in the system. When the DISTINCT clause is provided, only distinct values are considered in the computation of the aggregate. As such, aggregates can only be used in the SELECT and HAVING clauses of a SQL query. Aggregates are different from scalar functions and window functions because they change the cardinality of the result. Aggregates are functions that combine multiple rows into a single value.
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