Finding frequent items for columns, possibly with false positives

Finding frequent items for columns, possibly with false positives. Using the frequent element count algorithm described in https://dl.acm.org/doi/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou.

Usage

# S4 method for class 'SparkDataFrame,character'
freqItems(x, cols, support = 0.01)

Arguments

x

A SparkDataFrame.

cols

A vector column names to search frequent items in.

support

(Optional) The minimum frequency for an item to be considered frequent. Should be greater than 1e-4. Default support = 0.01.

Value

a local R data.frame with the frequent items in each column

Note

freqItems since 1.6.0

See also

Other stat functions: approxQuantile(), corr(), cov(), crosstab(), sampleBy()

Examples

if (FALSE) { # \dontrun{
df <- read.json("/path/to/file.json")
fi = freqItems(df, c("title", "gender"))
} # }