Merge pull request apache#237 from sun-rui/SPARKR-154_3

[SPARKR-154] Phase 2: implement cartesian().

Author: Davies Liu

R/pkg/NAMESPACE

@@ -5,6 +5,7 @@ exportMethods(
               "aggregateByKey",
               "aggregateRDD",
               "cache",
+              "cartesian",
               "checkpoint",
               "coalesce",
               "cogroup",

R/pkg/R/RDD.R

@@ -1496,69 +1496,43 @@ setMethod("zipRDD",
               stop("Can only zip RDDs which have the same number of partitions.")
             }
 
-            if (getSerializedMode(x) != getSerializedMode(other) ||
-                getSerializedMode(x) == "byte") {
-              # Append the number of elements in each partition to that partition so that we can later
-              # check if corresponding partitions of both RDDs have the same number of elements.
-              #
-              # Note that this appending also serves the purpose of reserialization, because even if
-              # any RDD is serialized, we need to reserialize it to make sure its partitions are encoded
-              # as a single byte array. For example, partitions of an RDD generated from partitionBy()
-              # may be encoded as multiple byte arrays.
-              appendLength <- function(part) {
-                part[[length(part) + 1]] <- length(part) + 1
-                part
-              }
-              x <- lapplyPartition(x, appendLength)
-              other <- lapplyPartition(other, appendLength)
-            }
-
-            zippedJRDD <- callJMethod(getJRDD(x), "zip", getJRDD(other))
-            # The zippedRDD's elements are of scala Tuple2 type. The serialized
-            # flag Here is used for the elements inside the tuples.
-            serializerMode <- getSerializedMode(x)
-            zippedRDD <- RDD(zippedJRDD, serializerMode)
-
-            partitionFunc <- function(split, part) {
-              len <- length(part)
-              if (len > 0) {
-                if (serializerMode == "byte") {
-                  lengthOfValues <- part[[len]]
-                  lengthOfKeys <- part[[len - lengthOfValues]]
-                  stopifnot(len == lengthOfKeys + lengthOfValues)
-
-                  # check if corresponding partitions of both RDDs have the same number of elements.
-                  if (lengthOfKeys != lengthOfValues) {
-                    stop("Can only zip RDDs with same number of elements in each pair of corresponding partitions.")
-                  }
-
-                  if (lengthOfKeys > 1) {
-                    keys <- part[1 : (lengthOfKeys - 1)]
-                    values <- part[(lengthOfKeys + 1) : (len - 1)]
-                  } else {
-                    keys <- list()
-                    values <- list()
-                  }
-                } else {
-                  # Keys, values must have same length here, because this has
-                  # been validated inside the JavaRDD.zip() function.
-                  keys <- part[c(TRUE, FALSE)]
-                  values <- part[c(FALSE, TRUE)]
-                }
-                mapply(
-                    function(k, v) {
-                      list(k, v)
-                    },
-                    keys,
-                    values,
-                    SIMPLIFY = FALSE,
-                    USE.NAMES = FALSE)
-              } else {
-                part
-              }
-            }
+            rdds <- appendPartitionLengths(x, other)
+            jrdd <- callJMethod(getJRDD(rdds[[1]]), "zip", getJRDD(rdds[[2]]))
+            # The jrdd's elements are of scala Tuple2 type. The serialized
+            # flag here is used for the elements inside the tuples.
+            rdd <- RDD(jrdd, getSerializedMode(rdds[[1]]))
+            
+            mergePartitions(rdd, TRUE)
+          })
 
-            PipelinedRDD(zippedRDD, partitionFunc)
+#' Cartesian product of this RDD and another one.
+#'
+#' Return the Cartesian product of this RDD and another one, 
+#' that is, the RDD of all pairs of elements (a, b) where a 
+#' is in this and b is in other.
+#' 
+#' @param x An RDD.
+#' @param other An RDD.
+#' @return A new RDD which is the Cartesian product of these two RDDs.
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' rdd <- parallelize(sc, 1:2)
+#' sortByKey(cartesian(rdd, rdd)) 
+#' # list(list(1, 1), list(1, 2), list(2, 1), list(2, 2))
+#'}
+#' @rdname cartesian
+#' @aliases cartesian,RDD,RDD-method
+setMethod("cartesian",
+          signature(x = "RDD", other = "RDD"),
+          function(x, other) {
+            rdds <- appendPartitionLengths(x, other)
+            jrdd <- callJMethod(getJRDD(rdds[[1]]), "cartesian", getJRDD(rdds[[2]]))
+            # The jrdd's elements are of scala Tuple2 type. The serialized
+            # flag here is used for the elements inside the tuples.
+            rdd <- RDD(jrdd, getSerializedMode(rdds[[1]]))
+            
+            mergePartitions(rdd, FALSE)
           })
 
 #' Subtract an RDD with another RDD.

R/pkg/R/generics.R

@@ -237,6 +237,10 @@ setGeneric("countByKey", function(x) { standardGeneric("countByKey") })
 #' @export
 setGeneric("flatMapValues", function(X, FUN) { standardGeneric("flatMapValues") })
 
+#' @rdname cartesian
+#' @export
+setGeneric("cartesian", function(x, other) { standardGeneric("cartesian") })
+
 #' @rdname intersection
 #' @export
 setGeneric("intersection", function(x, other, numPartitions = 1L) {

R/pkg/R/utils.R

@@ -465,3 +465,83 @@ cleanClosure <- function(func, checkedFuncs = new.env()) {
   }
   func
 }
+
+# Append partition lengths to each partition in two input RDDs if needed.
+# param
+#   x An RDD.
+#   Other An RDD.
+# return value
+#   A list of two result RDDs.
+appendPartitionLengths <- function(x, other) {
+  if (getSerializedMode(x) != getSerializedMode(other) || 
+      getSerializedMode(x) == "byte") {
+    # Append the number of elements in each partition to that partition so that we can later
+    # know the boundary of elements from x and other.
+    #
+    # Note that this appending also serves the purpose of reserialization, because even if 
+    # any RDD is serialized, we need to reserialize it to make sure its partitions are encoded
+    # as a single byte array. For example, partitions of an RDD generated from partitionBy()
+    # may be encoded as multiple byte arrays.          
+    appendLength <- function(part) {
+      len <- length(part)
+      part[[len + 1]] <- len + 1
+      part
+    }
+    x <- lapplyPartition(x, appendLength)
+    other <- lapplyPartition(other, appendLength)
+  }
+  list (x, other)
+}
+
+# Perform zip or cartesian between elements from two RDDs in each partition
+# param
+#   rdd An RDD.
+#   zip A boolean flag indicating this call is for zip operation or not.
+# return value
+#   A result RDD.
+mergePartitions <- function(rdd, zip) {
+  serializerMode <- getSerializedMode(rdd)
+  partitionFunc <- function(split, part) {
+    len <- length(part)
+    if (len > 0) {
+      if (serializerMode == "byte") {
+        lengthOfValues <- part[[len]]
+        lengthOfKeys <- part[[len - lengthOfValues]]
+        stopifnot(len == lengthOfKeys + lengthOfValues)
+        
+        # For zip operation, check if corresponding partitions of both RDDs have the same number of elements.
+        if (zip && lengthOfKeys != lengthOfValues) {
+          stop("Can only zip RDDs with same number of elements in each pair of corresponding partitions.")
+        }
+        
+        if (lengthOfKeys > 1) {
+          keys <- part[1 : (lengthOfKeys - 1)]
+        } else {
+          keys <- list()
+        }
+        if (lengthOfValues > 1) {
+          values <- part[(lengthOfKeys + 1) : (len - 1)]                    
+        } else {
+          values <- list()
+        }
+        
+        if (!zip) {
+          return(mergeCompactLists(keys, values))
+        }
+      } else {
+        keys <- part[c(TRUE, FALSE)]
+        values <- part[c(FALSE, TRUE)]
+      }
+      mapply(
+        function(k, v) { list(k, v) },
+        keys,
+        values,
+        SIMPLIFY = FALSE,
+        USE.NAMES = FALSE)
+    } else {
+      part
+    }
+  }
+  
+  PipelinedRDD(rdd, partitionFunc)
+}

R/pkg/inst/tests/test_rdd.R

@@ -468,6 +468,49 @@ test_that("zipRDD() on RDDs", {
   unlink(fileName)
 })
 
+test_that("cartesian() on RDDs", {
+  rdd <- parallelize(sc, 1:3)
+  actual <- collect(cartesian(rdd, rdd))
+  expect_equal(sortKeyValueList(actual),
+               list(
+                 list(1, 1), list(1, 2), list(1, 3),
+                 list(2, 1), list(2, 2), list(2, 3),
+                 list(3, 1), list(3, 2), list(3, 3)))
+  
+  # test case where one RDD is empty
+  emptyRdd <- parallelize(sc, list())
+  actual <- collect(cartesian(rdd, emptyRdd))
+  expect_equal(actual, list())
+
+  mockFile = c("Spark is pretty.", "Spark is awesome.")
+  fileName <- tempfile(pattern="spark-test", fileext=".tmp")
+  writeLines(mockFile, fileName)
+  
+  rdd <- textFile(sc, fileName)
+  actual <- collect(cartesian(rdd, rdd))
+  expected <- list(
+    list("Spark is awesome.", "Spark is pretty."),
+    list("Spark is awesome.", "Spark is awesome."),
+    list("Spark is pretty.", "Spark is pretty."),
+    list("Spark is pretty.", "Spark is awesome."))
+  expect_equal(sortKeyValueList(actual), expected)
+  
+  rdd1 <- parallelize(sc, 0:1)
+  actual <- collect(cartesian(rdd1, rdd))
+  expect_equal(sortKeyValueList(actual),
+               list(
+                 list(0, "Spark is pretty."),
+                 list(0, "Spark is awesome."),
+                 list(1, "Spark is pretty."),
+                 list(1, "Spark is awesome.")))
+  
+  rdd1 <- map(rdd, function(x) { x })
+  actual <- collect(cartesian(rdd, rdd1))
+  expect_equal(sortKeyValueList(actual), expected)
+  
+  unlink(fileName)
+})
+
 test_that("subtract() on RDDs", {
   l <- list(1, 1, 2, 2, 3, 4)
   rdd1 <- parallelize(sc, l)

pkg/man/cartesian.Rd

@@ -0,0 +1,33 @@
+% Generated by roxygen2 (4.0.2): do not edit by hand
+\docType{methods}
+\name{cartesian,RDD,RDD-method}
+\alias{cartesian}
+\alias{cartesian,RDD,RDD-method}
+\title{Cartesian product of this RDD and another one.}
+\usage{
+\S4method{cartesian}{RDD,RDD}(x, other)
+
+cartesian(x, other)
+}
+\arguments{
+\item{x}{An RDD.}
+
+\item{other}{An RDD.}
+}
+\value{
+A new RDD which is the Cartesian product of these two RDDs.
+}
+\description{
+Return the Cartesian product of this RDD and another one,
+that is, the RDD of all pairs of elements (a, b) where a
+is in this and b is in other.
+}
+\examples{
+\dontrun{
+sc <- sparkR.init()
+rdd <- parallelize(sc, 1:2)
+sortByKey(cartesian(rdd, rdd))
+# list(list(1, 1), list(1, 2), list(2, 1), list(2, 2))
+}
+}
+