Query time series data

Usage

druid.query.timeseries(url = druid.url(), dataSource, intervals, aggregations, filter = NULL, 
  granularity = "all", postAggregations = NULL, context = NULL, rawData = FALSE, 
      verbose = F, ...)

Arguments

url

URL to connect to druid, defaults to druid.url()

dataSource

name of the data source to query

intervals

time period to retrieve data for as an interval object or list of interval objects

aggregations

list of metric aggregations to compute for this datasource

filter

filter specifying the subset of the data to extract.

granularity

time granularity at which to aggregate

postAggregations

post-aggregations to perform on the aggregations

context

query context

rawData

if set, returns the result object as is, without converting to a data frame

...

additional parameters to pass to druid.resulttodf

verbose

prints out the JSON query sent to druid

Examples

## Not run: # #    # Get the time series associated with the twitter hashtag #druid, by hour#    druid.query.timeseries(url = druid.url(host = ""),#                          dataSource   = "twitter",#                          intervals    = interval(ymd("2012-07-01"), ymd("2012-07-15")),#                          aggregations = sum(metric("count")),#                          filter       = dimension("hashtag") == "druid",#                          granularity  = granularity("hour"))# #    # Average tweet length for a combination of hashtags in a given time zone#    druid.query.timeseries(url = druid.url(""),#                          dataSource   = "twitter",#                          intervals    = interval(ymd("2012-07-01"), ymd("2012-08-30")),#                          aggregations = list(#                                            sum(metric("count")),#                                            sum(metric("length")#                                         ),#                          postAggregations = list(#                                            avg_length = field("length") / field("count")#                                         )#                          filter       =   dimension("hashtag") == "london2012"#                                         | dimension("hashtag") == "olympics",#                          granularity  = granularity("PT6H", timeZone="Europe/London"))#   ## End(Not run)

See also