# Series Query: Regularize

# Description

The underlying series can be regularized by applying periodic aggregation using the FIRST or LAST function and turning on interpolation to fill the gaps created by periods without data. The technique is called "downsampling" in reference to a fewer number of returned data points.

• FIRST returns the first observed value in the given period.
• LAST returns the last observed value in the given period.

Both functions return detailed values, unlike AVERAGE and PERCENTILE functions, which calculate smoothed statistics.

# Request

# URI

POST /api/v1/series/query

# Payload

[
  {
    "startDate": "2016-06-27T14:10:00Z",
    "endDate":   "2016-06-27T14:15:00Z",
    "entity": "nurswgvml007",
    "metric": "cpu_busy",
    "aggregate": {
      "period": {"count": 1, "unit": "MINUTE"},
      "type": "FIRST",
      "interpolate": {"type": "LINEAR"}
    }
  }
]

# Response

# Payload

[
  {
    "entity": "nurswgvml007",
    "metric": "cpu_busy",
    "tags": {},
    "type": "HISTORY",
    "aggregate": {
      "type": "FIRST",
      "period": {
        "count": 1,
        "unit": "MINUTE"
      }
    },
    "data": [
      {
        "d": "2016-06-27T14:10:00.000Z",
        "v": 11.83
      },
      {
        "d": "2016-06-27T14:11:00.000Z",
        "v": 6.12
      },
      {
        "d": "2016-06-27T14:12:00.000Z",
        "v": 12
      },
      {
        "d": "2016-06-27T14:13:00.000Z",
        "v": 3
      },
      {
        "d": "2016-06-27T14:14:00.000Z",
        "v": 5.05
      }
    ]
  }
]