View Source Panoramix.Query (Panoramix v0.21.0)

Provides functions for building Druid query requests.

Summary

Types

t()

Functions

datasource(datasource)

from(source, kw)

Use from macro to build Druid queries. See Druid documentation to learn about available fields and general query object structure.

post_aggregation_field_accessor(type_name, accessor_name, accessor, options \\ [])

to_json(query)

Convert a Panoramix.Query struct into its JSON representation.

to_map(query)

Convert a Panoramix.Query struct into a map ready to be converted to JSON.

Types

t()

@type t() :: %Panoramix.Query{
  aggregations: term(),
  analysis_types: term(),
  bound: term(),
  context: term(),
  data_source: term(),
  dimension: term(),
  dimensions: term(),
  filter: term(),
  granularity: term(),
  intervals: term(),
  limit: term(),
  limit_spec: term(),
  merge: term(),
  metric: term(),
  post_aggregations: term(),
  query: term(),
  query_type: term(),
  search_dimensions: term(),
  sort: term(),
  subtotals_spec: term(),
  threshold: term(),
  to_include: term(),
  virtual_columns: term()
}

Functions

datasource(datasource)

from(source, kw)

(since 1.0.0) (macro)

Use from macro to build Druid queries. See Druid documentation to learn about available fields and general query object structure.

Example

    iex(1)> use Panoramix
    Panoramix.Query
    iex(2)> q = from "my_datasource",
    ...(2)>       query_type: "timeseries",
    ...(2)>       intervals: ["2019-03-01T00:00:00+00:00/2019-03-04T00:00:00+00:00"],
    ...(2)>       granularity: :day,
    ...(2)>       filter: dimensions.foo == "bar",
    ...(2)>        aggregations: [event_count: count(),
    ...(2)>                       unique_id_count: hyperUnique(:user_unique)]
    %Panoramix.Query{
      aggregations: [
        %{name: :event_count, type: "count"},
        %{fieldName: :user_unique, name: :unique_id_count, type: :hyperUnique}
      ],
      analysis_types: nil,
      bound: nil,
      context: %{priority: 0, timeout: 120000},
      data_source: "my_datasource",
      dimension: nil,
      dimensions: nil,
      filter: %{dimension: "foo", type: "selector", value: "bar"},
      granularity: :day,
      intervals: ["2019-03-01T00:00:00+00:00/2019-03-04T00:00:00+00:00"],
      limit: nil,
      limit_spec: nil,
      merge: nil,
      metric: nil,
      post_aggregations: nil,
      query: nil,
      query_type: "timeseries",
      search_dimensions: nil,
      sort: nil,
      threshold: nil,
      to_include: nil,
      virtual_columns: nil,
      subtotals_spec: nil
    }

Some HLL aggregation names are capitalized and therefore won't play well with the macro. For such cases use their aliases as a workaround: hllSketchBuild, hllSketchMerge, hllSketchEstimate, hllSketchUnion, hllSketchToString.

The aggregation aliases will be replaced with original names when building a query.

Example

    iex(1)> use Panoramix
    Panoramix.Query
    iex(2)> query = from "my_datasource",
    ...(2)>       query_type: "timeseries",
    ...(2)>       intervals: ["2018-05-29T00:00:00+00:00/2018-06-05T00:00:00+00:00"],
    ...(2)>       granularity: :day,
    ...(2)>       aggregations: [event_count: count(),
    ...(2)>                     unique_ids: hllSketchMerge(:user_unique, round: true)]
    %Panoramix.Query{
      aggregations: [
        %{name: :event_count, type: "count"},
        %{
          fieldName: :user_unique,
          name: :unique_ids,
          round: true,
          type: "HLLSketchMerge"
        }
      ],
      ...
    }

post_aggregation_field_accessor(type_name, accessor_name, accessor, options \\ [])

to_json(query)

Convert a Panoramix.Query struct into its JSON representation.

to_map(query)

Convert a Panoramix.Query struct into a map ready to be converted to JSON.