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author | Felix Cheung <felixcheung_m@hotmail.com> | 2016-08-22 15:53:10 -0700 |
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committer | Felix Cheung <felixcheung@apache.org> | 2016-08-22 15:53:10 -0700 |
commit | 71afeeea4ec8e67edc95b5d504c557c88a2598b9 (patch) | |
tree | 20d6ea5bf24625983414503731210a794b826fd5 /R/pkg/R/DataFrame.R | |
parent | 84770b59f773f132073cd2af4204957fc2d7bf35 (diff) | |
download | spark-71afeeea4ec8e67edc95b5d504c557c88a2598b9.tar.gz spark-71afeeea4ec8e67edc95b5d504c557c88a2598b9.tar.bz2 spark-71afeeea4ec8e67edc95b5d504c557c88a2598b9.zip |
[SPARK-16508][SPARKR] doc updates and more CRAN check fixes
## What changes were proposed in this pull request?
replace ``` ` ``` in code doc with `\code{thing}`
remove added `...` for drop(DataFrame)
fix remaining CRAN check warnings
## How was this patch tested?
create doc with knitr
junyangq
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes #14734 from felixcheung/rdoccleanup.
Diffstat (limited to 'R/pkg/R/DataFrame.R')
-rw-r--r-- | R/pkg/R/DataFrame.R | 71 |
1 files changed, 35 insertions, 36 deletions
diff --git a/R/pkg/R/DataFrame.R b/R/pkg/R/DataFrame.R index 540dc3122d..52a6628ad7 100644 --- a/R/pkg/R/DataFrame.R +++ b/R/pkg/R/DataFrame.R @@ -150,7 +150,7 @@ setMethod("explain", #' isLocal #' -#' Returns True if the `collect` and `take` methods can be run locally +#' Returns True if the \code{collect} and \code{take} methods can be run locally #' (without any Spark executors). #' #' @param x A SparkDataFrame @@ -182,7 +182,7 @@ setMethod("isLocal", #' @param numRows the number of rows to print. Defaults to 20. #' @param truncate whether truncate long strings. If \code{TRUE}, strings more than #' 20 characters will be truncated. However, if set greater than zero, -#' truncates strings longer than `truncate` characters and all cells +#' truncates strings longer than \code{truncate} characters and all cells #' will be aligned right. #' @param ... further arguments to be passed to or from other methods. #' @family SparkDataFrame functions @@ -642,10 +642,10 @@ setMethod("unpersist", #' The following options for repartition are possible: #' \itemize{ #' \item{1.} {Return a new SparkDataFrame partitioned by -#' the given columns into `numPartitions`.} -#' \item{2.} {Return a new SparkDataFrame that has exactly `numPartitions`.} +#' the given columns into \code{numPartitions}.} +#' \item{2.} {Return a new SparkDataFrame that has exactly \code{numPartitions}.} #' \item{3.} {Return a new SparkDataFrame partitioned by the given column(s), -#' using `spark.sql.shuffle.partitions` as number of partitions.} +#' using \code{spark.sql.shuffle.partitions} as number of partitions.} #'} #' @param x a SparkDataFrame. #' @param numPartitions the number of partitions to use. @@ -1132,9 +1132,8 @@ setMethod("take", #' Head #' -#' Return the first NUM rows of a SparkDataFrame as a R data.frame. If NUM is NULL, -#' then head() returns the first 6 rows in keeping with the current data.frame -#' convention in R. +#' Return the first \code{num} rows of a SparkDataFrame as a R data.frame. If \code{num} is not +#' specified, then head() returns the first 6 rows as with R data.frame. #' #' @param x a SparkDataFrame. #' @param num the number of rows to return. Default is 6. @@ -1406,11 +1405,11 @@ setMethod("dapplyCollect", #' #' @param cols grouping columns. #' @param func a function to be applied to each group partition specified by grouping -#' column of the SparkDataFrame. The function `func` takes as argument +#' column of the SparkDataFrame. The function \code{func} takes as argument #' a key - grouping columns and a data frame - a local R data.frame. -#' The output of `func` is a local R data.frame. +#' The output of \code{func} is a local R data.frame. #' @param schema the schema of the resulting SparkDataFrame after the function is applied. -#' The schema must match to output of `func`. It has to be defined for each +#' The schema must match to output of \code{func}. It has to be defined for each #' output column with preferred output column name and corresponding data type. #' @return A SparkDataFrame. #' @family SparkDataFrame functions @@ -1497,9 +1496,9 @@ setMethod("gapply", #' #' @param cols grouping columns. #' @param func a function to be applied to each group partition specified by grouping -#' column of the SparkDataFrame. The function `func` takes as argument +#' column of the SparkDataFrame. The function \code{func} takes as argument #' a key - grouping columns and a data frame - a local R data.frame. -#' The output of `func` is a local R data.frame. +#' The output of \code{func} is a local R data.frame. #' @return A data.frame. #' @family SparkDataFrame functions #' @aliases gapplyCollect,SparkDataFrame-method @@ -1657,7 +1656,7 @@ setMethod("$", signature(x = "SparkDataFrame"), getColumn(x, name) }) -#' @param value a Column or NULL. If NULL, the specified Column is dropped. +#' @param value a Column or \code{NULL}. If \code{NULL}, the specified Column is dropped. #' @rdname select #' @name $<- #' @aliases $<-,SparkDataFrame-method @@ -1747,7 +1746,7 @@ setMethod("[", signature(x = "SparkDataFrame"), #' @family subsetting functions #' @examples #' \dontrun{ -#' # Columns can be selected using `[[` and `[` +#' # Columns can be selected using [[ and [ #' df[[2]] == df[["age"]] #' df[,2] == df[,"age"] #' df[,c("name", "age")] @@ -1792,7 +1791,7 @@ setMethod("subset", signature(x = "SparkDataFrame"), #' select(df, df$name, df$age + 1) #' select(df, c("col1", "col2")) #' select(df, list(df$name, df$age + 1)) -#' # Similar to R data frames columns can also be selected using `$` +#' # Similar to R data frames columns can also be selected using $ #' df[,df$age] #' } #' @note select(SparkDataFrame, character) since 1.4.0 @@ -2443,7 +2442,7 @@ generateAliasesForIntersectedCols <- function (x, intersectedColNames, suffix) { #' Return a new SparkDataFrame containing the union of rows #' #' Return a new SparkDataFrame containing the union of rows in this SparkDataFrame -#' and another SparkDataFrame. This is equivalent to `UNION ALL` in SQL. +#' and another SparkDataFrame. This is equivalent to \code{UNION ALL} in SQL. #' Note that this does not remove duplicate rows across the two SparkDataFrames. #' #' @param x A SparkDataFrame @@ -2486,7 +2485,7 @@ setMethod("unionAll", #' Union two or more SparkDataFrames #' -#' Union two or more SparkDataFrames. This is equivalent to `UNION ALL` in SQL. +#' Union two or more SparkDataFrames. This is equivalent to \code{UNION ALL} in SQL. #' Note that this does not remove duplicate rows across the two SparkDataFrames. #' #' @param x a SparkDataFrame. @@ -2519,7 +2518,7 @@ setMethod("rbind", #' Intersect #' #' Return a new SparkDataFrame containing rows only in both this SparkDataFrame -#' and another SparkDataFrame. This is equivalent to `INTERSECT` in SQL. +#' and another SparkDataFrame. This is equivalent to \code{INTERSECT} in SQL. #' #' @param x A SparkDataFrame #' @param y A SparkDataFrame @@ -2547,7 +2546,7 @@ setMethod("intersect", #' except #' #' Return a new SparkDataFrame containing rows in this SparkDataFrame -#' but not in another SparkDataFrame. This is equivalent to `EXCEPT` in SQL. +#' but not in another SparkDataFrame. This is equivalent to \code{EXCEPT} in SQL. #' #' @param x a SparkDataFrame. #' @param y a SparkDataFrame. @@ -2576,8 +2575,8 @@ setMethod("except", #' Save the contents of SparkDataFrame to a data source. #' -#' The data source is specified by the `source` and a set of options (...). -#' If `source` is not specified, the default data source configured by +#' The data source is specified by the \code{source} and a set of options (...). +#' If \code{source} is not specified, the default data source configured by #' spark.sql.sources.default will be used. #' #' Additionally, mode is used to specify the behavior of the save operation when data already @@ -2613,7 +2612,7 @@ setMethod("except", #' @note write.df since 1.4.0 setMethod("write.df", signature(df = "SparkDataFrame", path = "character"), - function(df, path, source = NULL, mode = "error", ...){ + function(df, path, source = NULL, mode = "error", ...) { if (is.null(source)) { source <- getDefaultSqlSource() } @@ -2635,14 +2634,14 @@ setMethod("write.df", #' @note saveDF since 1.4.0 setMethod("saveDF", signature(df = "SparkDataFrame", path = "character"), - function(df, path, source = NULL, mode = "error", ...){ + function(df, path, source = NULL, mode = "error", ...) { write.df(df, path, source, mode, ...) }) #' Save the contents of the SparkDataFrame to a data source as a table #' -#' The data source is specified by the `source` and a set of options (...). -#' If `source` is not specified, the default data source configured by +#' The data source is specified by the \code{source} and a set of options (...). +#' If \code{source} is not specified, the default data source configured by #' spark.sql.sources.default will be used. #' #' Additionally, mode is used to specify the behavior of the save operation when @@ -2675,7 +2674,7 @@ setMethod("saveDF", #' @note saveAsTable since 1.4.0 setMethod("saveAsTable", signature(df = "SparkDataFrame", tableName = "character"), - function(df, tableName, source = NULL, mode="error", ...){ + function(df, tableName, source = NULL, mode="error", ...) { if (is.null(source)) { source <- getDefaultSqlSource() } @@ -2752,11 +2751,11 @@ setMethod("summary", #' @param how "any" or "all". #' if "any", drop a row if it contains any nulls. #' if "all", drop a row only if all its values are null. -#' if minNonNulls is specified, how is ignored. +#' if \code{minNonNulls} is specified, how is ignored. #' @param minNonNulls if specified, drop rows that have less than -#' minNonNulls non-null values. +#' \code{minNonNulls} non-null values. #' This overwrites the how parameter. -#' @param cols optional list of column names to consider. In `fillna`, +#' @param cols optional list of column names to consider. In \code{fillna}, #' columns specified in cols that do not have matching data #' type are ignored. For example, if value is a character, and #' subset contains a non-character column, then the non-character @@ -2879,8 +2878,8 @@ setMethod("fillna", #' in your system to accommodate the contents. #' #' @param x a SparkDataFrame. -#' @param row.names NULL or a character vector giving the row names for the data frame. -#' @param optional If `TRUE`, converting column names is optional. +#' @param row.names \code{NULL} or a character vector giving the row names for the data frame. +#' @param optional If \code{TRUE}, converting column names is optional. #' @param ... additional arguments to pass to base::as.data.frame. #' @return A data.frame. #' @family SparkDataFrame functions @@ -3058,7 +3057,7 @@ setMethod("str", #' @note drop since 2.0.0 setMethod("drop", signature(x = "SparkDataFrame"), - function(x, col, ...) { + function(x, col) { stopifnot(class(col) == "character" || class(col) == "Column") if (class(col) == "Column") { @@ -3218,8 +3217,8 @@ setMethod("histogram", #' and to not change the existing data. #' } #' -#' @param x s SparkDataFrame. -#' @param url JDBC database url of the form `jdbc:subprotocol:subname`. +#' @param x a SparkDataFrame. +#' @param url JDBC database url of the form \code{jdbc:subprotocol:subname}. #' @param tableName yhe name of the table in the external database. #' @param mode one of 'append', 'overwrite', 'error', 'ignore' save mode (it is 'error' by default). #' @param ... additional JDBC database connection properties. @@ -3237,7 +3236,7 @@ setMethod("histogram", #' @note write.jdbc since 2.0.0 setMethod("write.jdbc", signature(x = "SparkDataFrame", url = "character", tableName = "character"), - function(x, url, tableName, mode = "error", ...){ + function(x, url, tableName, mode = "error", ...) { jmode <- convertToJSaveMode(mode) jprops <- varargsToJProperties(...) write <- callJMethod(x@sdf, "write") |