Aggregations are specifications of processing over metrics available in Druid. Available aggregations are:
count
computes the row count that match the filters
{ "type" : "count", "name" : <output_name> }
longSum
aggregatorcomputes the sum of values as a 64-bit, signed integer
{ "type" : "longSum", "name" : <output_name>, "fieldName" : <metric_name> }
name
– output name for the summed value fieldName
– name of the metric column to sum over
doubleSum
aggregatorComputes the sum of values as 64-bit floating point value. Similar to longSum
{ "type" : "doubleSum", "name" : <output_name>, "fieldName" : <metric_name> }
min
aggregatormin
computes the minimum metric value
{ "type" : "min", "name" : <output_name>, "fieldName" : <metric_name> }
max
aggregatormax
computes the maximum metric value
{ "type" : "max", "name" : <output_name>, "fieldName" : <metric_name> }
Computes an arbitrary JavaScript function over a set of columns (both metrics and dimensions).
All JavaScript functions must return numerical values.
{ "type": "javascript", "name": "<output_name>", "fieldNames" : [ <column1>, <column2>, ... ], "fnAggregate" : "function(current, column1, column2, ...) { <updates partial aggregate (current) based on the current row values> return <updated partial aggregate> }", "fnCombine" : "function(partialA, partialB) { return <combined partial results>; }", "fnReset" : "function() { return <initial value>; }" }
Example
{ "type": "javascript", "name": "sum(log(x)/y) + 10", "fieldNames": ["x", "y"], "fnAggregate" : "function(current, a, b) { return current + (Math.log(a) * b); }", "fnCombine" : "function(partialA, partialB) { return partialA + partialB; }", "fnReset" : "function() { return 10; }" }