Description Usage Arguments Value See Also Examples
Compute moving weighted average, weighted standard deviation, weighted t- stat, and observation count with the column and weight column specified and store results in new columns named '<column>_<weighted_column>_mean', '<column>_<weighted_column>_weightedStandardDeviation', '<column>_<weighted_column>_weightedTStat', and '<column>_<weighted_column>_observationCount',
| 1 2 3 4 5 6 7 | summarize_weighted_avg(
  ts_rdd,
  column,
  weight_column,
  window = NULL,
  key_columns = list()
)
 | 
| ts_rdd | Timeseries RDD being summarized | 
| column | Column to be summarized | 
| weight_column | Column specifying relative weight of each data point | 
| 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_dot_product(),
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_corr(),
summarize_weighted_covar(),
summarize_z_score()
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | library(sparklyr)
library(sparklyr.flint)
sc <- try_spark_connect(master = "local")
if (!is.null(sc)) {
  sdf <- copy_to(sc, tibble::tibble(t = seq(10), v = seq(10), w = seq(1, 0.1, -0.1)))
  ts <- fromSDF(sdf, is_sorted = TRUE, time_unit = "SECONDS", time_column = "t")
  ts_weighted_avg <- summarize_weighted_avg(
    ts,
    column = "v", weight_column = "w", window = in_past("3s")
  )
} else {
  message("Unable to establish a Spark connection!")
}
 | 
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