# Series Query: Interpolate with Delta

# Description

When interpolation is specified in the aggregate object, the database performs operations in the following order:

1. Calculate period values by applying a given statistical functions to detailed samples recorded within the given period.
2. Add missing (empty) periods by applying an interpolation function.

Since both aggregate and group objects support interpolation functions, changing their default order can be used as a technique to apply DELTA function to interpolated period values.

# Data

• Detailed data, collected every 15 seconds, is missing between 2016-01-02T12:44:08Z and 2016-01-04T08:14:12Z.
• The metric is a counter, always incrementing.

# Detailed Data

[{
  "startDate": "2016-01-02T12:00:00Z",
  "endDate":   "2016-01-04T09:00:00Z",
  "entity": "e-1",
  "metric": "m-1"
}]

| datetime                 | value |
|--------------------------|-------|
| 2016-01-02T12:14:08.000Z | 13.40 |
| 2016-01-02T12:29:08.000Z | 13.43 |
| 2016-01-02T12:44:08.000Z | 13.44 |
-- no data --
| 2016-01-04T08:14:12.000Z | 15.93 |
| 2016-01-04T08:29:40.000Z | 16.01 |
| 2016-01-04T08:44:18.000Z | 16.26 |
| 2016-01-04T08:59:04.000Z | 16.47 |

# Aggregated Data

[{
  "startDate": "2016-01-02T12:00:00Z",
  "endDate":   "2016-01-04T09:00:00Z",
  "entity": "e-1",
  "metric": "m-1",
  "aggregate" : {
    "type": "MAX",
    "period": {"count": 30, "unit": "MINUTE"}
  },
}]

| datetime                 | max(value) |
|--------------------------|------------|
| 2016-01-02T12:00:00.000Z | 13.43      |
| 2016-01-02T12:30:00.000Z | 13.44      |
| 2016-01-04T08:00:00.000Z | 16.01      |
| 2016-01-04T08:30:00.000Z | 16.47      |

# Interpolation with Period in Group

[{
  "startDate": "2016-01-02T12:00:00Z",
  "endDate":   "2016-01-04T09:00:00Z",
  "entity": "e-1",
  "metric": "m-1",
  "group": {
    "type": "MAX",
    "interpolate": {"type": "LINEAR"},
    "period": {"count": 30, "unit": "MINUTE"}
  }
}]

| datetime                 | value |
|--------------------------|-------|
| 2016-01-02T12:00:00.000Z | 13.43 |
| 2016-01-02T12:30:00.000Z | 13.44 |
| 2016-01-02T13:00:00.000Z | 13.47 |
| 2016-01-02T13:30:00.000Z | 13.50 |
| 2016-01-02T14:00:00.000Z | 13.53 |
| 2016-01-02T14:30:00.000Z | 13.56 |
... interpolate MAX in group
| 2016-01-04T07:00:00.000Z | 15.95 |
| 2016-01-04T07:30:00.000Z | 15.98 |
| 2016-01-04T08:00:00.000Z | 16.01 |
| 2016-01-04T08:30:00.000Z | 16.47 |

# Request

[{
  "startDate": "2016-01-02T12:00:00Z",
  "endDate":   "2016-01-04T09:00:00Z",
  "entity": "e-1",
  "metric": "m-1",
  "aggregate" : {
    "type": "DELTA",
    "period": {"count": 30, "unit": "MINUTE"}
  },
  "group": {
    "type": "MAX",
    "interpolate": {"type": "LINEAR"},
    "period": {"count": 30, "unit": "MINUTE"},
    "order": -1
  }
}]

# Response

[{"entity":"e-1","metric":"m-1","tags":{},"type":"HISTORY",
"aggregate":{"type":"DELTA","period":{"count":30,"unit":"MINUTE","align":"CALENDAR"},"counter":false},
"group":{"type":"MAX","period":{"count":30,"unit":"MINUTE","align":"CALENDAR"},
"interpolate":{"type":"LINEAR","value":0.0,"extend":false},"order":-1},
"data":[
{"d":"2016-01-02T12:30:00.000Z","v":0.009000000000014552},
{"d":"2016-01-02T13:00:00.000Z","v":0.02860919540228224},
{"d":"2016-01-02T13:30:00.000Z","v":0.02860919540228224},
...
{"d":"2016-01-04T07:00:00.000Z","v":0.02860919540228224},
{"d":"2016-01-04T07:30:00.000Z","v":0.02860919540228224},
{"d":"2016-01-04T08:00:00.000Z","v":0.10960919540229952},
{"d":"2016-01-04T08:30:00.000Z","v":0.4539999999999509}]}]