Related to "aggregates"
aggregateWindow() function
aggregateWindow() downsamples data by grouping data into fixed windows of time and applying an aggregate or selector function to each window.
count() function
count() returns the number of records in each input table.
cov() function
cov() computes the covariance between two streams of tables.
covariance() function
covariance() computes the covariance between two columns.
experimental.count() function
experimental.count() returns the number of records in each input table.
experimental.histogramQuantile() function
experimental.histogramQuantile() approximates a quantile given a histogram with the cumulative distribution of the dataset.
experimental.integral() function
experimental.integral() computes the area under the curve per unit of time of subsequent non-null records.
experimental.mean() function
experimental.mean() computes the mean or average of non-null values in the _value column of each input table.
experimental.mode() function
experimental.mode() computes the mode or value that occurs most often in the _value column in each input table.
experimental.quantile() function
experimental.quantile() returns non-null records with values in the _value column that fall within the specified quantile or represent the specified quantile.
experimental.skew() function
experimental.skew() returns the skew of non-null values in the _value column for each input table as a float.
experimental.spread() function
experimental.spread() returns the difference between the minimum and maximum values in the _value column for each input table.
experimental.stddev() function
experimental.stddev() returns the standard deviation of non-null values in the _value column for each input table.
experimental.sum() function
experimental.sum() returns the sum of non-null values in the _value column for each input table.
integral() function
integral() computes the area under the curve per unit of time of subsequent non-null records.
mean() function
mean() returns the average of non-null values in a specified column from each input table.
median() function
median() returns the median _value of an input table or all non-null records in the input table with values that fall within the 0.5 quantile (50th percentile).
mode() function
mode() returns the non-null value or values that occur most often in a specified column in each input table.
pearsonr() function
pearsonr() returns the covariance of two streams of tables normalized to the Pearson R coefficient.
quantile() function
quantile() returns rows from each input table with values that fall within a specified quantile or returns the row with the value that represents the specified quantile.
reduce() function
reduce() aggregates rows in each input table using a reducer function (fn).
skew() function
skew() returns the skew of non-null records in each input table as a float.
spread() function
spread() returns the difference between the minimum and maximum values in a specified column.
stddev() function
stddev() returns the standard deviation of non-null values in a specified column.
sum() function
sum() returns the sum of non-null values in a specified column.
timeWeightedAvg() function
timeWeightedAvg() returns the time-weighted average of non-null values in _value column as a float for each input table.
aggregate.rate() function
aggregate.rate() calculates the average rate of increase per window of time for each input table.
geo.ST_LineString() function
geo.ST_LineString() converts a series of geographic points into linestring.
geo.totalDistance() function
geo.totalDistance() calculates the total distance covered by subsequent points in each input table.
prometheus.histogramQuantile() function
prometheus.histogramQuantile() calculates a quantile on a set of Prometheus histogram values.