Timestamp Min/Max aggregators

To use this Apache Druid extension, include druid-time-min-max in the extensions load list.

These aggregators enable more precise calculation of min and max time of given events than __time column whose granularity is sparse, the same as query granularity. To use this feature, a “timeMin” or “timeMax” aggregator must be included at indexing time. They can apply to any columns that can be converted to timestamp, which include Long, DateTime, Timestamp, and String types.

For example, when a data set consists of timestamp, dimension, and metric value like followings.

  1. 2015-07-28T01:00:00.000Z  A  1
  2. 2015-07-28T02:00:00.000Z  A  1
  3. 2015-07-28T03:00:00.000Z  A  1
  4. 2015-07-28T04:00:00.000Z  B  1
  5. 2015-07-28T05:00:00.000Z  A  1
  6. 2015-07-28T06:00:00.000Z  B  1
  7. 2015-07-29T01:00:00.000Z  C  1
  8. 2015-07-29T02:00:00.000Z  C  1
  9. 2015-07-29T03:00:00.000Z  A  1
  10. 2015-07-29T04:00:00.000Z  A  1

At ingestion time, timeMin and timeMax aggregator can be included as other aggregators.

  1. {
  2.     "type": "timeMin",
  3.     "name": "tmin",
  4.     "fieldName": "<field_name, typically column specified in timestamp spec>"
  5. }
  1. {
  2.     "type": "timeMax",
  3.     "name": "tmax",
  4.     "fieldName": "<field_name, typically column specified in timestamp spec>"
  5. }

name is output name of aggregator and can be any string. fieldName is typically column specified in timestamp spec but can be any column that can be converted to timestamp.

To query for results, the same aggregators “timeMin” and “timeMax” is used.

  1. {
  2.   "queryType": "groupBy",
  3.   "dataSource": "timeMinMax",
  4.   "granularity": "DAY",
  5.   "dimensions": ["product"],
  6.   "aggregations": [
  7.     {
  8.       "type": "count",
  9.       "name": "count"
  10.     },
  11.     {
  12.       "type": "timeMin",
  13.       "name": "<output_name of timeMin>",
  14.       "fieldName": "tmin"
  15.     },
  16.     {
  17.       "type": "timeMax",
  18.       "name": "<output_name of timeMax>",
  19.       "fieldName": "tmax"
  20.     }
  21.   ],
  22.   "intervals": [
  23.     "2010-01-01T00:00:00.000Z/2020-01-01T00:00:00.000Z"
  24.   ]
  25. }

Then, result has min and max of timestamp, which is finer than query granularity.

  1. 2015-07-28T00:00:00.000Z A 4 2015-07-28T01:00:00.000Z 2015-07-28T05:00:00.000Z
  2. 2015-07-28T00:00:00.000Z B 2 2015-07-28T04:00:00.000Z 2015-07-28T06:00:00.000Z
  3. 2015-07-29T00:00:00.000Z A 2 2015-07-29T03:00:00.000Z 2015-07-29T04:00:00.000Z
  4. 2015-07-29T00:00:00.000Z C 2 2015-07-29T01:00:00.000Z 2015-07-29T02:00:00.000Z