[GitHub] spark pull request #21710: [SPARK-24207][R]add R API for PrefixSpan

[felixcheung <gi...@git.apache.org>]

Github user felixcheung commented on a diff in the pull request:

    https://github.com/apache/spark/pull/21710#discussion_r223568243
  
    --- Diff: R/pkg/R/mllib_fpm.R ---
    @@ -154,3 +160,74 @@ setMethod("write.ml", signature(object = "FPGrowthModel", path = "character"),
               function(object, path, overwrite = FALSE) {
                 write_internal(object, path, overwrite)
               })
    +
    +#' PrefixSpan
    +#'
    +#' A parallel PrefixSpan algorithm to mine frequent sequential patterns.
    +#' \code{spark.prefixSpan} returns an instance of PrefixSpan.
    +#' \code{spark.findFrequentSequentialPatterns} returns a complete set of frequent sequential
    +#' patterns.
    +#' For more details, see
    +#' \href{https://spark.apache.org/docs/latest/mllib-frequent-pattern-mining.html#prefixspan}{
    +#' PrefixSpan}.
    +#'
    +#' @param minSupport Minimal support level.
    +#' @param maxPatternLength Maximal pattern length.
    +#' @param maxLocalProjDBSize Maximum number of items (including delimiters used in the internal
    +#'                           storage format) allowed in a projected database before local
    +#'                           processing.
    +#' @param sequenceCol name of the sequence column in dataset.
    +#' @param ... additional argument(s) passed to the method.
    +#' @return \code{spark.prefixSpan} returns an instance of PrefixSpan
    +#' @rdname spark.prefixSpan
    +#' @name spark.prefixSpan
    +#' @aliases spark.prefixSpan,ANY-method
    +#' @examples
    +#' \dontrun{
    +#' df <- createDataFrame(list(list(list(list(1L, 2L), list(3L))),
    +#'                       list(list(list(1L), list(3L, 2L), list(1L, 2L))),
    +#'                       list(list(list(1L, 2L), list(5L))),
    +#'                       list(list(list(6L)))), schema = c("sequence"))
    +#' prefix_Span <- spark.prefixSpan(minSupport = 0.5, maxPatternLength = 5L,
    +#'                                 maxLocalProjDBSize = 32000000L)
    +#' frequency <- spark.findFrequentSequentialPatterns(prefix_Span, df)
    +#' showDF(frequency)
    +#' }
    +#' @note spark.prefixSpan since 3.0.0
    +setMethod("spark.prefixSpan", signature(),
    +          function(minSupport=0.1, maxPatternLength=10L,
    +                   maxLocalProjDBSize=32000000L, sequenceCol="sequence") {
    +            if (!is.numeric(minSupport) || minSupport < 0) {
    +              stop("minSupport should be a number with value >= 0.")
    +            }
    +            if (!is.integer(maxPatternLength) || maxPatternLength <= 0) {
    +              stop("maxPatternLength should be a number with value > 0.")
    +            }
    +            if (!is.numeric(maxLocalProjDBSize) || maxLocalProjDBSize <= 0) {
    +              stop("maxLocalProjDBSize should be a number with value > 0.")
    +            }
    +
    +            jobj <- callJStatic("org.apache.spark.ml.r.PrefixSpanWrapper", "getPrefixSpan",
    +                                as.numeric(minSupport), as.integer(maxPatternLength),
    +                                as.numeric(maxLocalProjDBSize), as.character(sequenceCol))
    +            new("PrefixSpan", jobj = jobj)
    +          })
    +
    +# Find frequent sequential patterns.
    +
    +#' @param object a PrefixSpan object.
    +#' @param data A SparkDataFrame.
    +#' @return A complete set of frequent sequential patterns in the input sequences of itemsets.
    +#'         The returned \code{SparkDataFrame} contains columns of sequence and corresponding
    +#'         frequency. The schema of it will be:
    +#'         \code{sequence: ArrayType(ArrayType(T))} (T is the item type)
    +#'         \code{freq: Long}
    +#' @rdname spark.prefixSpan
    +#' @aliases findFrequentSequentialPatterns,PrefixSpan,SparkDataFrame-method
    +#' @note spark.findFrequentSequentialPatterns(PrefixSpan, SparkDataFrame) since 3.0.0
    +
    --- End diff --
    
    remove extra line - note this might break doc generation


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