aggregate_statistics
- aggregate_statistics(
table_name: string,
column_name: string,
stats: string,
options?: Record<string, string>,
callback?: GPUdbCallback,
): Promise<AggregateStatisticsResponse>Parameters
- table_name: string
Name of the table on which the statistics operation will be performed, in [schema_name.]table_name format, using standard name resolution rules.
- column_name: string
Name of the primary column for which the statistics are to be calculated.
- stats: string
Comma separated list of the statistics to calculate, e.g. “sum,mean”.
Optionaloptions: Record<string, string>Optional parameters.
Optionalcallback: GPUdbCallbackOptional callback function
Returns Promise<AggregateStatisticsResponse>
Promise<Types.AggregateStatisticsResponse> - Promise resolving to the response
- Defined in src/GPUdb.ts:3403
- table_name: string
aggregate_statistics_request
- aggregate_statistics_request(
request: AggregateStatisticsRequest,
callback?: GPUdbCallback,
): Promise<AggregateStatisticsResponse>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
column_nametimes 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
column_namex 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.
Parameters
- request: AggregateStatisticsRequest
Request object containing the parameters for the operation
Optionalcallback: GPUdbCallbackOptional callback function
Returns Promise<AggregateStatisticsResponse>
Promise<Types.AggregateStatisticsResponse> - Promise resolving to the response
- Defined in src/GPUdb.ts:3340
- request: AggregateStatisticsRequest
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
column_nametimes 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
column_namex 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.