Type Members

1.  case class GroupByBins(bins: Seq[String]) extends GroupBy with Product with Serializable

   Each object of the response JSON contains the group_by information you specified in the query as well as a group object.

   Each object of the response JSON contains the group_by information you specified in the query as well as a group object. The group object contains the group number starting with a group number of 0. For example, for Seq("2", "4", "6", "8"), the first group (bin number 0) contains data points whose values are between 0 and 2. The second group (bin number 1) contains data points whose values are between 2 and 4, etc.

2.  case class GroupByTags(tags: Seq[String]) extends GroupBy with Product with Serializable

   You can group results by specifying one or more tag names.

   You can group results by specifying one or more tag names. For example, if you have a customer tag, grouping by customer would create a resulting object for each customer.

   Multiple tag names can be used to further group the data points.

3.  case class GroupByTime(rangeSize: TimeRange, groupCount: Int) extends GroupBy with Product with Serializable

   The time grouper groups results by time ranges.

   The time grouper groups results by time ranges. For example, you could group data by day of week.

   Note that the grouper calculates ranges based on the start time of the query. So if you wanted to group by day of week and wanted the first group to be Sunday, then you need to set the query’s start time to be on Sunday.

   rangeSize

   A value and a unit. For example, 1 day would group by day of the week (Sunday - Saturday).

   groupCount

   The number of groups. This would typically be 7 to group by day of week. But you could set this to 14 to group by fortnight.

4.  case class GroupByType(typeName: String) extends GroupBy with Product with Serializable
5.  case class GroupByValue(rangeSize: Int) extends GroupBy with Product with Serializable

   The value grouper groups by data point values.

   The value grouper groups by data point values. Values are placed into groups based on a range size. For example, if the range size is 10, then values between 0-9 are placed in the first group, values between 10-19 into the second group, and so forth.