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From sun-rui <>
Subject [GitHub] spark pull request: [SPARK-10752][SPARKR] Implement corr() and cov...
Date Tue, 29 Sep 2015 06:51:26 GMT
Github user sun-rui commented on a diff in the pull request:
    --- Diff: R/pkg/R/DataFrameStatFunctions.R ---
    @@ -0,0 +1,102 @@
    +# Licensed to the Apache Software Foundation (ASF) under one or more
    +# contributor license agreements.  See the NOTICE file distributed with
    +# this work for additional information regarding copyright ownership.
    +# The ASF licenses this file to You under the Apache License, Version 2.0
    +# (the "License"); you may not use this file except in compliance with
    +# the License.  You may obtain a copy of the License at
    +# Unless required by applicable law or agreed to in writing, software
    +# distributed under the License is distributed on an "AS IS" BASIS,
    +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    +# See the License for the specific language governing permissions and
    +# limitations under the License.
    +# DataFrameStatFunctions.R - Statistic functions for DataFrames.
    +#' crosstab
    +#' Computes a pair-wise frequency table of the given columns. Also known as a contingency
    +#' table. The number of distinct values for each column should be less than 1e4. At most
    +#' non-zero pair frequencies will be returned.
    +#' @param col1 name of the first column. Distinct items will make the first item of each
    +#' @param col2 name of the second column. Distinct items will make the column names of
the output.
    +#' @return a local R data.frame representing the contingency table. The first column
of each row
    +#'         will be the distinct values of `col1` and the column names will be the distinct
    +#'         of `col2`. The name of the first column will be `$col1_$col2`. Pairs that
have no
    +#'         occurrences will have zero as their counts.
    +#' @rdname statfunctions
    +#' @name crosstab
    +#' @export
    +#' @examples
    +#' \dontrun{
    +#' df <- jsonFile(sqlCtx, "/path/to/file.json")
    +#' ct <- crosstab(df, "title", "gender")
    +#' }
    +          signature(x = "DataFrame", col1 = "character", col2 = "character"),
    +          function(x, col1, col2) {
    +            statFunctions <- callJMethod(x@sdf, "stat")
    +            sct <- callJMethod(statFunctions, "crosstab", col1, col2)
    +            collect(dataFrame(sct))
    +          })
    +#' cov
    +#' Calculate the sample covariance of two numerical columns of a DataFrame.
    +#' @param x A SparkSQL DataFrame
    +#' @param col1 the name of the first column
    +#' @param col2 the name of the second column
    +#' @return the covariance of the two columns.
    +#' @rdname statfunctions
    +#' @name cov
    +#' @export
    +#' @examples
    +#' df <- jsonFile(sqlCtx, "/path/to/file.json")
    +#' cov <- cov(df, "title", "gender")
    +#' }
    +          signature(x = "DataFrame", col1 = "character", col2 = "character"),
    --- End diff --
    @NarineK, thank you for your comments. You suggestion needs extensions to Scala DataFrame.
I prefer that you can submit a new JIRA in the community. @shivaram, what do you think?

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