Calculates the requested statistics of the given column(s) in a given table.The available statistics are: count (number of total objects), mean, stdv
(standard deviation), variance, skew, kurtosis, sum, min, max,
weighted_average, cardinality (unique count), estimated_cardinality,
percentile, and percentile_rank.Estimated cardinality is calculated by using the hyperloglog approximation
technique.Percentiles and percentile ranks are approximate and are calculated using the
t-digest algorithm. They must include the desired
percentile/percentile_rank. To compute multiple percentiles each value must
be specified separately (i.e.
‘percentile(75.0),percentile(99.0),percentile_rank(1234.56),percentile_rank(-5)’).A second, comma-separated value can be added to the percentile statistic to
calculate percentile resolution, e.g., a 50th percentile with 200 resolution
would be ‘percentile(50,200)’.The weighted average statistic requires a weight column to be specified in
weight_column_name. The weighted average is then defined as the sum of the
products of input parameter column_name times the weight_column_name values
divided by the sum of the weight_column_name values.Additional columns can be used in the calculation of statistics via
additional_column_names. Values in these columns will be included in the
overall aggregate calculation—individual aggregates will not be calculated per
additional column. For instance, requesting the count and mean of input
parameter column_name x and additional_column_names y and z, where x holds
the numbers 1-10, y holds 11-20, and z holds 21-30, would return the total
number of x, y, and z values (30), and the single average value across all x,
y, and z values (15.5).The response includes a list of key/value pairs of each statistic requested and
its corresponding value.
Comma separated list of the statistics to calculate, e.g. “sum,mean”.
count: Number of objects (independent of the given column(s)).
mean: Arithmetic mean (average), equivalent to sum/count.
stdv: Sample standard deviation (denominator is count-1).
variance: Unbiased sample variance (denominator is count-1).
skew: Skewness (third standardized moment).
kurtosis: Kurtosis (fourth standardized moment).
sum: Sum of all values in the column(s).
min: Minimum value of the column(s).
max: Maximum value of the column(s).
weighted_average: Weighted arithmetic mean (using the option weight_column_name as the weighting column).
cardinality: Number of unique values in the column(s).
estimated_cardinality: Estimate (via hyperloglog technique) of the number of unique values in the column(s).
percentile: Estimate (via t-digest) of the given percentile of the column(s) (percentile(50.0) will be an approximation of the median). Add a second, comma-separated value to calculate percentile resolution, e.g., ‘percentile(75,150)’.
percentile_rank: Estimate (via t-digest) of the percentile rank of the given value in the column(s) (if the given value is the median of the column(s), percentile_rank(<median>) will return approximately 50.0).
A list of comma separated column names over which statistics can be accumulated along with the primary column. All columns listed and input parameter column_name must be of the same type. Must not include the column specified in input parameter column_name and no column can be listed twice.
The Kinetica server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query. Here is a description of the various fields of the wrapper:
