summarize_z_score {sparklyr.flint} | R Documentation |
Z-score summarizer
Description
Compute z-score of value(s) in the column specified, with respect to the sample mean and standard deviation observed so far, with the option for out- of-sample calculation, and store result in a new column named '<column>_zScore'.
Usage
summarize_z_score(
ts_rdd,
column,
include_current_observation = FALSE,
key_columns = list(),
incremental = FALSE
)
Arguments
ts_rdd |
Timeseries RDD being summarized |
column |
Column to be summarized |
include_current_observation |
If true, then use unbiased sample standard deviation with current observation in z-score calculation, otherwise use unbiased sample standard deviation excluding current observation |
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. |
Value
A TimeSeriesRDD containing the summarized result
See Also
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_avg()
,
summarize_weighted_corr()
,
summarize_weighted_covar()
Examples
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 = rnorm(10)))
ts <- fromSDF(sdf, is_sorted = TRUE, time_unit = "SECONDS", time_column = "t")
ts_z_score <- summarize_z_score(ts, column = "v", include_current_observation = TRUE)
} else {
message("Unable to establish a Spark connection!")
}