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author | Sun Rui <rui.sun@intel.com> | 2015-04-24 11:00:19 -0700 |
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committer | Shivaram Venkataraman <shivaram@cs.berkeley.edu> | 2015-04-24 11:00:19 -0700 |
commit | ebb77b2aff085e71906b5de9d266ded89051af82 (patch) | |
tree | f36e4927c100bb07955b1bf31cd18aa0e7619d63 /R | |
parent | 6e57d57b32ba2aa0514692074897b5edd34e0dd6 (diff) | |
download | spark-ebb77b2aff085e71906b5de9d266ded89051af82.tar.gz spark-ebb77b2aff085e71906b5de9d266ded89051af82.tar.bz2 spark-ebb77b2aff085e71906b5de9d266ded89051af82.zip |
[SPARK-7033] [SPARKR] Clean usage of split. Use partition instead where applicable.
Author: Sun Rui <rui.sun@intel.com>
Closes #5628 from sun-rui/SPARK-7033 and squashes the following commits:
046bc9e [Sun Rui] Clean split usage in tests.
d531c86 [Sun Rui] [SPARK-7033][SPARKR] Clean usage of split. Use partition instead where applicable.
Diffstat (limited to 'R')
-rw-r--r-- | R/pkg/R/RDD.R | 36 | ||||
-rw-r--r-- | R/pkg/R/context.R | 20 | ||||
-rw-r--r-- | R/pkg/R/pairRDD.R | 8 | ||||
-rw-r--r-- | R/pkg/R/utils.R | 2 | ||||
-rw-r--r-- | R/pkg/inst/tests/test_rdd.R | 12 |
5 files changed, 39 insertions, 39 deletions
diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R index 128431334c..cc09efb1e5 100644 --- a/R/pkg/R/RDD.R +++ b/R/pkg/R/RDD.R @@ -91,8 +91,8 @@ setMethod("initialize", "PipelinedRDD", function(.Object, prev, func, jrdd_val) # NOTE: We use prev_serializedMode to track the serialization mode of prev_JRDD # prev_serializedMode is used during the delayed computation of JRDD in getJRDD } else { - pipelinedFunc <- function(split, iterator) { - func(split, prev@func(split, iterator)) + pipelinedFunc <- function(partIndex, part) { + func(partIndex, prev@func(partIndex, part)) } .Object@func <- cleanClosure(pipelinedFunc) .Object@prev_jrdd <- prev@prev_jrdd # maintain the pipeline @@ -306,7 +306,7 @@ setMethod("numPartitions", signature(x = "RDD"), function(x) { jrdd <- getJRDD(x) - partitions <- callJMethod(jrdd, "splits") + partitions <- callJMethod(jrdd, "partitions") callJMethod(partitions, "size") }) @@ -452,8 +452,8 @@ setMethod("countByValue", setMethod("lapply", signature(X = "RDD", FUN = "function"), function(X, FUN) { - func <- function(split, iterator) { - lapply(iterator, FUN) + func <- function(partIndex, part) { + lapply(part, FUN) } lapplyPartitionsWithIndex(X, func) }) @@ -538,8 +538,8 @@ setMethod("mapPartitions", #'\dontrun{ #' sc <- sparkR.init() #' rdd <- parallelize(sc, 1:10, 5L) -#' prod <- lapplyPartitionsWithIndex(rdd, function(split, part) { -#' split * Reduce("+", part) }) +#' prod <- lapplyPartitionsWithIndex(rdd, function(partIndex, part) { +#' partIndex * Reduce("+", part) }) #' collect(prod, flatten = FALSE) # 0, 7, 22, 45, 76 #'} #' @rdname lapplyPartitionsWithIndex @@ -813,7 +813,7 @@ setMethod("distinct", #' @examples #'\dontrun{ #' sc <- sparkR.init() -#' rdd <- parallelize(sc, 1:10) # ensure each num is in its own split +#' rdd <- parallelize(sc, 1:10) #' collect(sampleRDD(rdd, FALSE, 0.5, 1618L)) # ~5 distinct elements #' collect(sampleRDD(rdd, TRUE, 0.5, 9L)) # ~5 elements possibly with duplicates #'} @@ -825,14 +825,14 @@ setMethod("sampleRDD", function(x, withReplacement, fraction, seed) { # The sampler: takes a partition and returns its sampled version. - samplingFunc <- function(split, part) { + samplingFunc <- function(partIndex, part) { set.seed(seed) res <- vector("list", length(part)) len <- 0 # Discards some random values to ensure each partition has a # different random seed. - runif(split) + runif(partIndex) for (elem in part) { if (withReplacement) { @@ -989,8 +989,8 @@ setMethod("coalesce", function(x, numPartitions, shuffle = FALSE) { numPartitions <- numToInt(numPartitions) if (shuffle || numPartitions > SparkR::numPartitions(x)) { - func <- function(s, part) { - set.seed(s) # split as seed + func <- function(partIndex, part) { + set.seed(partIndex) # partIndex as seed start <- as.integer(sample(numPartitions, 1) - 1) lapply(seq_along(part), function(i) { @@ -1035,7 +1035,7 @@ setMethod("saveAsObjectFile", #' Save this RDD as a text file, using string representations of elements. #' #' @param x The RDD to save -#' @param path The directory where the splits of the text file are saved +#' @param path The directory where the partitions of the text file are saved #' @examples #'\dontrun{ #' sc <- sparkR.init() @@ -1335,10 +1335,10 @@ setMethod("zipWithUniqueId", function(x) { n <- numPartitions(x) - partitionFunc <- function(split, part) { + partitionFunc <- function(partIndex, part) { mapply( function(item, index) { - list(item, (index - 1) * n + split) + list(item, (index - 1) * n + partIndex) }, part, seq_along(part), @@ -1382,11 +1382,11 @@ setMethod("zipWithIndex", startIndices <- Reduce("+", nums, accumulate = TRUE) } - partitionFunc <- function(split, part) { - if (split == 0) { + partitionFunc <- function(partIndex, part) { + if (partIndex == 0) { startIndex <- 0 } else { - startIndex <- startIndices[[split]] + startIndex <- startIndices[[partIndex]] } mapply( diff --git a/R/pkg/R/context.R b/R/pkg/R/context.R index ebbb8fba10..b4845b6948 100644 --- a/R/pkg/R/context.R +++ b/R/pkg/R/context.R @@ -17,12 +17,12 @@ # context.R: SparkContext driven functions -getMinSplits <- function(sc, minSplits) { - if (is.null(minSplits)) { +getMinPartitions <- function(sc, minPartitions) { + if (is.null(minPartitions)) { defaultParallelism <- callJMethod(sc, "defaultParallelism") - minSplits <- min(defaultParallelism, 2) + minPartitions <- min(defaultParallelism, 2) } - as.integer(minSplits) + as.integer(minPartitions) } #' Create an RDD from a text file. @@ -33,7 +33,7 @@ getMinSplits <- function(sc, minSplits) { #' #' @param sc SparkContext to use #' @param path Path of file to read. A vector of multiple paths is allowed. -#' @param minSplits Minimum number of splits to be created. If NULL, the default +#' @param minPartitions Minimum number of partitions to be created. If NULL, the default #' value is chosen based on available parallelism. #' @return RDD where each item is of type \code{character} #' @export @@ -42,13 +42,13 @@ getMinSplits <- function(sc, minSplits) { #' sc <- sparkR.init() #' lines <- textFile(sc, "myfile.txt") #'} -textFile <- function(sc, path, minSplits = NULL) { +textFile <- function(sc, path, minPartitions = NULL) { # Allow the user to have a more flexible definiton of the text file path path <- suppressWarnings(normalizePath(path)) #' Convert a string vector of paths to a string containing comma separated paths path <- paste(path, collapse = ",") - jrdd <- callJMethod(sc, "textFile", path, getMinSplits(sc, minSplits)) + jrdd <- callJMethod(sc, "textFile", path, getMinPartitions(sc, minPartitions)) # jrdd is of type JavaRDD[String] RDD(jrdd, "string") } @@ -60,7 +60,7 @@ textFile <- function(sc, path, minSplits = NULL) { #' #' @param sc SparkContext to use #' @param path Path of file to read. A vector of multiple paths is allowed. -#' @param minSplits Minimum number of splits to be created. If NULL, the default +#' @param minPartitions Minimum number of partitions to be created. If NULL, the default #' value is chosen based on available parallelism. #' @return RDD containing serialized R objects. #' @seealso saveAsObjectFile @@ -70,13 +70,13 @@ textFile <- function(sc, path, minSplits = NULL) { #' sc <- sparkR.init() #' rdd <- objectFile(sc, "myfile") #'} -objectFile <- function(sc, path, minSplits = NULL) { +objectFile <- function(sc, path, minPartitions = NULL) { # Allow the user to have a more flexible definiton of the text file path path <- suppressWarnings(normalizePath(path)) #' Convert a string vector of paths to a string containing comma separated paths path <- paste(path, collapse = ",") - jrdd <- callJMethod(sc, "objectFile", path, getMinSplits(sc, minSplits)) + jrdd <- callJMethod(sc, "objectFile", path, getMinPartitions(sc, minPartitions)) # Assume the RDD contains serialized R objects. RDD(jrdd, "byte") } diff --git a/R/pkg/R/pairRDD.R b/R/pkg/R/pairRDD.R index 13efebc11c..f99b474ff8 100644 --- a/R/pkg/R/pairRDD.R +++ b/R/pkg/R/pairRDD.R @@ -206,8 +206,8 @@ setMethod("partitionBy", get(name, .broadcastNames) }) jrdd <- getJRDD(x) - # We create a PairwiseRRDD that extends RDD[(Array[Byte], - # Array[Byte])], where the key is the hashed split, the value is + # We create a PairwiseRRDD that extends RDD[(Int, Array[Byte])], + # where the key is the target partition number, the value is # the content (key-val pairs). pairwiseRRDD <- newJObject("org.apache.spark.api.r.PairwiseRRDD", callJMethod(jrdd, "rdd"), @@ -866,8 +866,8 @@ setMethod("sampleByKey", } # The sampler: takes a partition and returns its sampled version. - samplingFunc <- function(split, part) { - set.seed(bitwXor(seed, split)) + samplingFunc <- function(partIndex, part) { + set.seed(bitwXor(seed, partIndex)) res <- vector("list", length(part)) len <- 0 diff --git a/R/pkg/R/utils.R b/R/pkg/R/utils.R index 23305d3c67..0e7b7bd5a5 100644 --- a/R/pkg/R/utils.R +++ b/R/pkg/R/utils.R @@ -501,7 +501,7 @@ appendPartitionLengths <- function(x, other) { # A result RDD. mergePartitions <- function(rdd, zip) { serializerMode <- getSerializedMode(rdd) - partitionFunc <- function(split, part) { + partitionFunc <- function(partIndex, part) { len <- length(part) if (len > 0) { if (serializerMode == "byte") { diff --git a/R/pkg/inst/tests/test_rdd.R b/R/pkg/inst/tests/test_rdd.R index 3ba7d17163..d55af93e3e 100644 --- a/R/pkg/inst/tests/test_rdd.R +++ b/R/pkg/inst/tests/test_rdd.R @@ -105,8 +105,8 @@ test_that("several transformations on RDD (a benchmark on PipelinedRDD)", { rdd2 <- rdd for (i in 1:12) rdd2 <- lapplyPartitionsWithIndex( - rdd2, function(split, part) { - part <- as.list(unlist(part) * split + i) + rdd2, function(partIndex, part) { + part <- as.list(unlist(part) * partIndex + i) }) rdd2 <- lapply(rdd2, function(x) x + x) actual <- collect(rdd2) @@ -121,8 +121,8 @@ test_that("PipelinedRDD support actions: cache(), persist(), unpersist(), checkp # PipelinedRDD rdd2 <- lapplyPartitionsWithIndex( rdd2, - function(split, part) { - part <- as.list(unlist(part) * split) + function(partIndex, part) { + part <- as.list(unlist(part) * partIndex) }) cache(rdd2) @@ -174,13 +174,13 @@ test_that("lapply with dependency", { }) test_that("lapplyPartitionsWithIndex on RDDs", { - func <- function(splitIndex, part) { list(splitIndex, Reduce("+", part)) } + func <- function(partIndex, part) { list(partIndex, Reduce("+", part)) } actual <- collect(lapplyPartitionsWithIndex(rdd, func), flatten = FALSE) expect_equal(actual, list(list(0, 15), list(1, 40))) pairsRDD <- parallelize(sc, list(list(1, 2), list(3, 4), list(4, 8)), 1L) partitionByParity <- function(key) { if (key %% 2 == 1) 0 else 1 } - mkTup <- function(splitIndex, part) { list(splitIndex, part) } + mkTup <- function(partIndex, part) { list(partIndex, part) } actual <- collect(lapplyPartitionsWithIndex( partitionBy(pairsRDD, 2L, partitionByParity), mkTup), |