druid.query.timeseries: Query time series data

In druid-io/RDruid: Druid connector for R

Description

Queries druid for timeseries data and returns it as a data frame

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
verbose	prints out the JSON query sent to druid
...	additional parameters to pass to druid.resulttodf

Value

Returns a data frame where each column represents a time series

See Also

druid.query.groupBy druid.query.topN granularity

Examples

## Not run: 

   # Get the time series associated with the twitter hashtag #druid, by hour
   druid.query.timeseries(url = druid.url(host = "<hostname>"),
                         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("<hostname>"),
                         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)

druid-io/RDruid documentation built on May 15, 2019, 2:54 p.m.