Description Usage Arguments Value See Also Examples
Compute product of values from the given column within a moving time window new column named '<column>_product'
1 | summarize_product(ts_rdd, column, window = NULL, key_columns = list())
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ts_rdd |
Timeseries RDD being summarized |
column |
Column to be 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 |
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_quantile(),
summarize_skewness(),
summarize_stddev(),
summarize_sum(),
summarize_var(),
summarize_weighted_avg(),
summarize_weighted_corr(),
summarize_weighted_covar(),
summarize_z_score()
1 2 3 4 5 6 7 8 9 10 11 12 | 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)))
ts <- fromSDF(sdf, is_sorted = TRUE, time_unit = "SECONDS", time_column = "t")
ts_product <- summarize_product(ts, column = "v", window = in_past("3s"))
} else {
message("Unable to establish a Spark connection!")
}
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