Github user felixcheung commented on a diff in the pull request: https://github.com/apache/spark/pull/9012#discussion_r42200040 --- Diff: R/pkg/R/DataFrame.R --- @@ -1452,15 +1452,147 @@ setMethod("join", dataFrame(sdf) }) -#' @rdname merge +#' #' @name merge #' @aliases join +#' @title Merges two data frames +#' @param x the first data frame to be joined +#' @param y the second data frame to be joined +#' @param by a character vector specifying the join columns. If by is not +#' specified, the common column names in \code{x} and \code{y} will be used. +#' @param by.x a character vector specifying the joining columns for x. +#' @param by.y a character vector specifying the joining columns for y. +#' @param all.x a boolean value indicating whether all the rows in x should +#' be including in the join +#' @param all.y a boolean value indicating whether all the rows in y should +#' be including in the join +#' @param sort a logical argument indicating whether the resulting columns should be sorted +#' @details If all.x and all.y are set to FALSE, a natural join will be returned. If +#' all.x is set to TRUE and all.y is set to FALSE, a left outer join will +#' be returned. If all.x is set to FALSE and all.y is set to TRUE, a right +#' outer join will be returned. If all.x and all.y are set to TRUE, a full +#' outer join will be returned. +#' @rdname merge +#' @export +#' @examples +#'\dontrun{ +#' sc <- sparkR.init() +#' sqlContext <- sparkRSQL.init(sc) +#' df1 <- jsonFile(sqlContext, path) +#' df2 <- jsonFile(sqlContext, path2) +#' merge(df1, df2) # Performs a Cartesian +#' merge(df1, df2, by = "col1") # Performs an inner join based on expression +#' merge(df1, df2, by.x = "col1", by.y = "col2", all.y = TRUE) +#' merge(df1, df2, by.x = "col1", by.y = "col2", all.x = TRUE) +#' merge(df1, df2, by.x = "col1", by.y = "col2", all.x = TRUE, all.y = TRUE) +#' } setMethod("merge", signature(x = "DataFrame", y = "DataFrame"), - function(x, y, joinExpr = NULL, joinType = NULL, ...) { - join(x, y, joinExpr, joinType) - }) + function(x, y, by = intersect(names(x), names(y)), by.x = NULL, by.y = NULL, + all = FALSE, all.x = FALSE, all.y = FALSE, + sort = TRUE, suffixes = c("_x","_y"), ... ) { + + if (missing(x) | missing(y)) { + stop("x and y has to be specified") + } + + if (length(suffixes) != 2) { + stop("suffixes must have length 2") + } + + # join type is identified based on the values of all, all.x and all.y + # default join type is inner, according to R it should be natural but since it + # is not supported in spark inner join is used + joinType <- "inner" + if (all | (all.x & all.y)) { + joinType <- "outer" + } else if (all.x) { + joinType <- "left_outer" + } else if (all.y) { + joinType <- "right_outer" + } + + # join expression is based on by.x, by.y if both by.x and by.y are not missing + # and by if by.x or by.y are missing or have different lengths + if (length(by.x) > 0 & length(by.x) == length(by.y)) { + joinX <- by.x + joinY <- by.y + } else if (length(by) > 0) { + joinX <- by + joinY <- by + } else { + stop("The intersection of dataframes is empty") + } + + # sets alias for making colnames unique in dataframes 'x' and 'y' + colsX <- generateAliasesForIntersectedCols(x, names(x), by, suffixes[1]) + colsY <- generateAliasesForIntersectedCols(y, names(y), by, suffixes[2]) + + # selects columns with their aliases from dataframes + # in case same column names are present in both data frames + xsel <- select(x, colsX) + ysel <- select(y, colsY) + + joinColumns <- lapply(seq_len(length(joinX)), function(i) { + colX <- joinX[[i]] + colY <- joinY[[i]] + if (colX %in% by) { + colX <- paste(colX, suffixes[1], sep = "") + } + if (colY %in% by) { + colY <- paste(colY, suffixes[2], sep = "") + } + + colX <- getColumn(xsel, colX) + colY <- getColumn(ysel, colY) + + colX == colY + }) + + # concatanates join columns together with '&' + for (i in 1:length(joinColumns)) { + if (i == 1) { + joinExpr <- joinColumns[[i]] + } else { + joinExpr <- joinExpr & joinColumns[[i]] + } + } + + joinRes <- join(xsel, ysel, joinExpr, joinType) + + # sorts the result by 'by' columns if sort = TRUE + if (sort & length(by) > 0) { + colNameWithSuffix <- paste(by, suffixes[2], sep = "") + joinRes <- do.call("arrange", c(joinRes, colNameWithSuffix, decreasing = FALSE)) + } + + joinRes + }) + +#' +#' Creates a list of columns by replacing the intersected ones with aliases. +#' The name of the alias column is formed by concatanating the original column name and a suffix. +#' +#' @param x a DataFrame on which the +#' @param allColNames a list of column names +#' @param intersectedColNames a list of intersected column names +#' @param suffix a suffix for the column name +#' @return list of columns +#' +generateAliasesForIntersectedCols <- function (x, allColNames, intersectedColNames, suffix) { + # sets alias for making colnames unique in dataframe 'x' + cols <- lapply(seq_len(length(allColNames)), function(i) { + colName <- allColNames[[i]] + col <- getColumn(x, colName) + if (allColNames[i] %in% intersectedColNames) { + newJoin <- paste(colName, suffix, sep = "") + col <- alias(col, newJoin) --- End diff -- what if colName is "test", suffix is "_x" but there is already a column with the name "test_x"?
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