summarize_dot_product: Dot product summarizer
In sparklyr.flint: Sparklyr Extension for 'Flint'

Description Usage Arguments Value See Also Examples

Compute dot product of values from 'xcolumn' and 'ycolumn' within a moving time window or within each group of records with identical timestamps and store results in a new column named '<xcolumn>_<ycolumn>_dotProduct'

summarize_dot_product(
  ts_rdd,
  xcolumn,
  ycolumn,
  window = NULL,
  key_columns = list()
)

`ts_rdd`	Timeseries RDD being summarized
`xcolumn`	Name of the first column
`ycolumn`	Name of the second column
`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
`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.

A TimeSeriesRDD containing the summarized result

Other summarizers: ols_regression(), summarize_avg(), summarize_corr2(), summarize_corr(), summarize_count(), summarize_covar(), summarize_ema_half_life(), summarize_ewma(), summarize_geometric_mean(), summarize_kurtosis(), summarize_max(), summarize_min(), summarize_nth_central_moment(), summarize_nth_moment(), summarize_product(), summarize_quantile(), summarize_skewness(), summarize_stddev(), summarize_sum(), summarize_var(), summarize_weighted_avg(), summarize_weighted_corr(), summarize_weighted_covar(), summarize_z_score()

library(sparklyr)
library(sparklyr.flint)

sc <- try_spark_connect(master = "local")

if (!is.null(sc)) {
  sdf <- copy_to(sc, tibble::tibble(t = seq(10), u = seq(10, 1, -1), v = seq(10)))
  ts <- fromSDF(sdf, is_sorted = TRUE, time_unit = "SECONDS", time_column = "t")
  ts_dot_product <- summarize_dot_product(ts, xcolumn = "u", ycolumn = "v", window = in_past("3s"))
} else {
  message("Unable to establish a Spark connection!")
}