summarizers: Wrapper functions for commonly used summarizer functions
In sparklyr.flint: Sparklyr Extension for 'Flint'

R wrapper functions for commonly used Flint summarizer functionalities such as sum and count.

`ts_rdd`	Timeseries RDD being summarized
`window`	Either an R expression specifying time windows to be summarized (e.g., 'in_past("1h")' to summarize data from looking behind 1 hour at each time point, 'in_future("5s")' to summarize data from looking forward 5 seconds at each time point), or 'NULL' to compute aggregate statistics on records grouped by timestamps
`column`	Column to be summarized
`key_columns`	Optional list of columns that will form an equivalence relation associating each record with the time series it belongs to (i.e., any 2 records having equal values in those columns will be associated with the same time series, and any 2 records having differing values in those columns are considered to be from 2 separate time series and will therefore be summarized separately) By default, 'key_colums' is empty and all records are considered to be part of a single time series.
`incremental`	If FALSE and 'key_columns' is empty, then apply the summarizer to all records of 'ts_rdd'. If FALSE and 'key_columns' is non-empty, then apply the summarizer to all records within each group determined by 'key_columns'. If TRUE and 'key_columns' is empty, then for each record in 'ts_rdd', the summarizer is applied to that record and all records preceding it, and the summarized result is associated with the timestamp of that record. If TRUE and 'key_columns' is non-empty, then for each record within a group of records determined by 1 or more key columns, the summarizer is applied to that record and all records preceding it within its group, and the summarized result is associated with the timestamp of that record.