use first line as the title convention

R/pkg/R/DataFrame.R

@@ -23,9 +23,11 @@ NULL
 setOldClass("jobj")
 setOldClass("structType")
 
-#' @title S4 class that represents a SparkDataFrame
-#' @description DataFrames can be created using functions like \link{createDataFrame},
-#'              \link{read.json}, \link{table} etc.
+#' S4 class that represents a SparkDataFrame
+#'
+#' DataFrames can be created using functions like \link{createDataFrame},
+#' \link{read.json}, \link{table} etc.
+#'
 #' @family SparkDataFrame functions
 #' @rdname SparkDataFrame
 #' @docType class
@@ -1940,8 +1942,9 @@ setMethod("join",
             dataFrame(sdf)
           })
 
+#' Merges two data frames
+#'
 #' @name merge
-#' @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
@@ -2111,8 +2114,9 @@ setMethod("unionAll",
             dataFrame(unioned)
           })
 
-#' @title Union two or more SparkDataFrames
-#' @description Returns a new SparkDataFrame containing rows of all parameters.
+#' Union two or more SparkDataFrames
+#'
+#' Returns a new SparkDataFrame containing rows of all parameters.
 #'
 #' @rdname rbind
 #' @name rbind
@@ -2474,11 +2478,12 @@ setMethod("fillna",
             dataFrame(sdf)
           })
 
+#' Download data from a SparkDataFrame into a data.frame
+#'
 #' This function downloads the contents of a SparkDataFrame into an R's data.frame.
 #' Since data.frames are held in memory, ensure that you have enough memory
 #' in your system to accommodate the contents.
 #'
-#' @title Download data from a SparkDataFrame into a data.frame
 #' @param x a SparkDataFrame
 #' @return a data.frame
 #' @family SparkDataFrame functions
@@ -2494,13 +2499,14 @@ setMethod("as.data.frame",
             as.data.frame(collect(x), row.names, optional, ...)
           })
 
+#' Attach SparkDataFrame to R search path
+#'
 #' The specified SparkDataFrame is attached to the R search path. This means that
 #' the SparkDataFrame is searched by R when evaluating a variable, so columns in
 #' the SparkDataFrame can be accessed by simply giving their names.
 #'
 #' @family SparkDataFrame functions
 #' @rdname attach
-#' @title Attach SparkDataFrame to R search path
 #' @param what (SparkDataFrame) The SparkDataFrame to attach
 #' @param pos (integer) Specify position in search() where to attach.
 #' @param name (character) Name to use for the attached SparkDataFrame. Names
@@ -2520,7 +2526,7 @@ setMethod("attach",
             attach(newEnv, pos = pos, name = name, warn.conflicts = warn.conflicts)
           })
 
-#' Evaluate an expression in an environment constructed from SparkDataFrame
+#' Evaluate a R expression in an environment constructed from a SparkDataFrame
 #'
 #' Evaluate a R expression in an environment constructed from a SparkDataFrame
 #' with() allows access to columns of a SparkDataFrame by simply referring to
@@ -2530,7 +2536,6 @@ setMethod("attach",
 #'
 #' @rdname with
 #' @family SparkDataFrame functions
-#' @title Evaluate a R expression in an environment constructed from a SparkDataFrame
 #' @param data (SparkDataFrame) SparkDataFrame to use for constructing an environment.
 #' @param expr (expression) Expression to evaluate.
 #' @param ... arguments to be passed to future methods.
@@ -2546,10 +2551,12 @@ setMethod("with",
             eval(substitute(expr), envir = newEnv, enclos = newEnv)
           })
 
+#' Compactly display the structure of a dataset
+#'
 #' Display the structure of a SparkDataFrame, including column names, column types, as well as a
 #' a small sample of rows.
+#'
 #' @name str
-#' @title Compactly display the structure of a dataset
 #' @rdname str
 #' @family SparkDataFrame functions
 #' @param object a SparkDataFrame
@@ -2662,10 +2669,11 @@ setMethod("drop",
             base::drop(x)
           })
 
+#' Histogram
+#'
 #' This function computes a histogram for a given SparkR Column.
 #'
 #' @name histogram
-#' @title Histogram
 #' @param nbins the number of bins (optional). Default value is 10.
 #' @param df the SparkDataFrame containing the Column to build the histogram from.
 #' @param colname the name of the column to build the histogram from.

R/pkg/R/RDD.R

@@ -19,9 +19,11 @@
 
 setOldClass("jobj")
 
-#' @title S4 class that represents an RDD
-#' @description RDD can be created using functions like
+#' S4 class that represents an RDD
+#'
+#' RDD can be created using functions like
 #'              \code{parallelize}, \code{textFile} etc.
+#'
 #' @rdname RDD
 #' @seealso parallelize, textFile
 #' @slot env An R environment that stores bookkeeping states of the RDD

R/pkg/R/WindowSpec.R

@@ -20,9 +20,10 @@
 #' @include generics.R jobj.R column.R
 NULL
 
-#' @title S4 class that represents a WindowSpec
-#' @description WindowSpec can be created by using window.partitionBy()
-#'              or window.orderBy()
+#' S4 class that represents a WindowSpec
+#'
+#' WindowSpec can be created by using window.partitionBy() or window.orderBy()
+#'
 #' @rdname WindowSpec
 #' @seealso \link{window.partitionBy}, \link{window.orderBy}
 #'

R/pkg/R/broadcast.R

@@ -23,9 +23,11 @@
 .broadcastValues <- new.env()
 .broadcastIdToName <- new.env()
 
-# @title S4 class that represents a Broadcast variable
-# @description Broadcast variables can be created using the broadcast
-#              function from a \code{SparkContext}.
+# S4 class that represents a Broadcast variable
+#
+# Broadcast variables can be created using the broadcast
+# function from a \code{SparkContext}.
+#
 # @rdname broadcast-class
 # @seealso broadcast
 #

R/pkg/R/column.R

@@ -22,8 +22,10 @@ NULL
 
 setOldClass("jobj")
 
-#' @title S4 class that represents a SparkDataFrame column
-#' @description The column class supports unary, binary operations on SparkDataFrame columns
+#' S4 class that represents a SparkDataFrame column
+#'
+#' The column class supports unary, binary operations on SparkDataFrame columns
+#'
 #' @rdname column
 #'
 #' @slot jc reference to JVM SparkDataFrame column

R/pkg/R/context.R

@@ -173,9 +173,8 @@ includePackage <- function(sc, pkg) {
   .sparkREnv$.packages <- packages
 }
 
-#' @title Broadcast a variable to all workers
+#' Broadcast a variable to all workers
 #'
-#' @description
 #' Broadcast a read-only variable to the cluster, returning a \code{Broadcast}
 #' object for reading it in distributed functions.
 #'
@@ -207,7 +206,7 @@ broadcast <- function(sc, object) {
   Broadcast(id, object, jBroadcast, objName)
 }
 
-#' @title Set the checkpoint directory
+#' Set the checkpoint directory
 #'
 #' Set the directory under which RDDs are going to be checkpointed. The
 #' directory must be a HDFS path if running on a cluster.
@@ -226,9 +225,8 @@ setCheckpointDir <- function(sc, dirName) {
   invisible(callJMethod(sc, "setCheckpointDir", suppressWarnings(normalizePath(dirName))))
 }
 
-#' @title Run a function over a list of elements, distributing the computations with Spark.
+#' Run a function over a list of elements, distributing the computations with Spark.
 #'
-#' @description
 #' Applies a function in a manner that is similar to doParallel or lapply to elements of a list.
 #' The computations are distributed using Spark. It is conceptually the same as the following code:
 #'   lapply(list, func)

R/pkg/R/group.R

@@ -22,8 +22,10 @@ NULL
 
 setOldClass("jobj")
 
-#' @title S4 class that represents a GroupedData
-#' @description GroupedDatas can be created using groupBy() on a SparkDataFrame
+#' S4 class that represents a GroupedData
+#'
+#' GroupedDatas can be created using groupBy() on a SparkDataFrame
+#'
 #' @rdname GroupedData
 #' @seealso groupBy
 #'

R/pkg/R/mllib.R

@@ -25,22 +25,26 @@
 # - a set of methods that reflect the arguments of the other languages supported by Spark. These
 #   methods are prefixed with the `spark.` prefix: spark.glm, spark.kmeans, etc.
 
-#' @title S4 class that represents a generalized linear model
+#' S4 class that represents a generalized linear model
+#'
 #' @param jobj a Java object reference to the backing Scala GeneralizedLinearRegressionWrapper
 #' @export
 setClass("GeneralizedLinearRegressionModel", representation(jobj = "jobj"))
 
-#' @title S4 class that represents a NaiveBayesModel
+#' S4 class that represents a NaiveBayesModel
+#'
 #' @param jobj a Java object reference to the backing Scala NaiveBayesWrapper
 #' @export
 setClass("NaiveBayesModel", representation(jobj = "jobj"))
 
-#' @title S4 class that represents a AFTSurvivalRegressionModel
+#' S4 class that represents a AFTSurvivalRegressionModel
+#'
 #' @param jobj a Java object reference to the backing Scala AFTSurvivalRegressionWrapper
 #' @export
 setClass("AFTSurvivalRegressionModel", representation(jobj = "jobj"))
 
-#' @title S4 class that represents a KMeansModel
+#' S4 class that represents a KMeansModel
+#'
 #' @param jobj a Java object reference to the backing Scala KMeansModel
 #' @export
 setClass("KMeansModel", representation(jobj = "jobj"))
@@ -197,10 +201,11 @@ print.summary.GeneralizedLinearRegressionModel <- function(x, ...) {
   invisible(x)
   }
 
+#' predict
+#'
 #' Makes predictions from a generalized linear model produced by glm() or spark.glm(),
 #' similarly to R's predict().
 #'
-#' @title predict
 #' @param object A fitted generalized linear model
 #' @param newData SparkDataFrame for testing
 #' @return SparkDataFrame containing predicted labels in a column named "prediction"
@@ -217,10 +222,11 @@ setMethod("predict", signature(object = "GeneralizedLinearRegressionModel"),
             return(dataFrame(callJMethod(object@jobj, "transform", newData@sdf)))
           })
 
+#' predict
+#'
 #' Makes predictions from a naive Bayes model or a model produced by spark.naiveBayes(),
 #' similarly to R package e1071's predict.
 #'
-#' @title predict
 #' @param object A fitted naive Bayes model
 #' @param newData SparkDataFrame for testing
 #' @return SparkDataFrame containing predicted labels in a column named "prediction"
@@ -355,9 +361,10 @@ setMethod("summary", signature(object = "KMeansModel"),
                    cluster = cluster, is.loaded = is.loaded))
           })
 
+#' predict
+#'
 #' Makes predictions from a k-means model or a model produced by spark.kmeans().
 #'
-#' @title predict
 #' @param object A fitted k-means model
 #' @param newData SparkDataFrame for testing
 #' @return SparkDataFrame containing predicted labels in a column named "prediction"
@@ -579,10 +586,11 @@ setMethod("summary", signature(object = "AFTSurvivalRegressionModel"),
             return(list(coefficients = coefficients))
           })
 
+#' predict
+#'
 #' Makes predictions from an AFT survival regression model or a model produced by spark.survreg(),
 #' similarly to R package survival's predict.
 #'
-#' @title predict
 #' @param object A fitted AFT survival regression model
 #' @param newData SparkDataFrame for testing
 #' @return SparkDataFrame containing predicted labels in a column named "prediction"