Merge remote-tracking branch 'origin/master' into json-encoding-line-sep

Author: MaxGekk

R/pkg/NAMESPACE

@@ -201,6 +201,9 @@ exportMethods("%<=>%",
               "approxCountDistinct",
               "approxQuantile",
               "array_contains",
+              "array_max",
+              "array_min",
+              "array_position",
               "asc",
               "ascii",
               "asin",
@@ -245,6 +248,7 @@ exportMethods("%<=>%",
               "decode",
               "dense_rank",
               "desc",
+              "element_at",
               "encode",
               "endsWith",
               "exp",

R/pkg/R/functions.R

@@ -189,6 +189,11 @@ NULL
 #'              the map or array of maps.
 #'          \item \code{from_json}: it is the column containing the JSON string.
 #'          }
+#' @param value A value to compute on.
+#'          \itemize{
+#'          \item \code{array_contains}: a value to be checked if contained in the column.
+#'          \item \code{array_position}: a value to locate in the given array.
+#'          }
 #' @param ... additional argument(s). In \code{to_json} and \code{from_json}, this contains
 #'            additional named properties to control how it is converted, accepts the same
 #'            options as the JSON data source.
@@ -201,14 +206,17 @@ NULL
 #' df <- createDataFrame(cbind(model = rownames(mtcars), mtcars))
 #' tmp <- mutate(df, v1 = create_array(df$mpg, df$cyl, df$hp))
 #' head(select(tmp, array_contains(tmp$v1, 21), size(tmp$v1)))
+#' head(select(tmp, array_max(tmp$v1), array_min(tmp$v1)))
+#' head(select(tmp, array_position(tmp$v1, 21)))
 #' tmp2 <- mutate(tmp, v2 = explode(tmp$v1))
 #' head(tmp2)
 #' head(select(tmp, posexplode(tmp$v1)))
 #' head(select(tmp, sort_array(tmp$v1)))
 #' head(select(tmp, sort_array(tmp$v1, asc = FALSE)))
 #' tmp3 <- mutate(df, v3 = create_map(df$model, df$cyl))
 #' head(select(tmp3, map_keys(tmp3$v3)))
-#' head(select(tmp3, map_values(tmp3$v3)))}
+#' head(select(tmp3, map_values(tmp3$v3)))
+#' head(select(tmp3, element_at(tmp3$v3, "Valiant")))}
 NULL
 
 #' Window functions for Column operations
@@ -2975,7 +2983,6 @@ setMethod("row_number",
 #' \code{array_contains}: Returns null if the array is null, true if the array contains
 #' the value, and false otherwise.
 #'
-#' @param value a value to be checked if contained in the column
 #' @rdname column_collection_functions
 #' @aliases array_contains array_contains,Column-method
 #' @note array_contains since 1.6.0
@@ -2986,6 +2993,48 @@ setMethod("array_contains",
             column(jc)
           })
 
+#' @details
+#' \code{array_max}: Returns the maximum value of the array.
+#'
+#' @rdname column_collection_functions
+#' @aliases array_max array_max,Column-method
+#' @note array_max since 2.4.0
+setMethod("array_max",
+          signature(x = "Column"),
+          function(x) {
+            jc <- callJStatic("org.apache.spark.sql.functions", "array_max", x@jc)
+            column(jc)
+          })
+
+#' @details
+#' \code{array_min}: Returns the minimum value of the array.
+#'
+#' @rdname column_collection_functions
+#' @aliases array_min array_min,Column-method
+#' @note array_min since 2.4.0
+setMethod("array_min",
+          signature(x = "Column"),
+          function(x) {
+            jc <- callJStatic("org.apache.spark.sql.functions", "array_min", x@jc)
+            column(jc)
+          })
+
+#' @details
+#' \code{array_position}: Locates the position of the first occurrence of the given value
+#' in the given array. Returns NA if either of the arguments are NA.
+#' Note: The position is not zero based, but 1 based index. Returns 0 if the given
+#' value could not be found in the array.
+#'
+#' @rdname column_collection_functions
+#' @aliases array_position array_position,Column-method
+#' @note array_position since 2.4.0
+setMethod("array_position",
+          signature(x = "Column", value = "ANY"),
+          function(x, value) {
+            jc <- callJStatic("org.apache.spark.sql.functions", "array_position", x@jc, value)
+            column(jc)
+          })
+
 #' @details
 #' \code{map_keys}: Returns an unordered array containing the keys of the map.
 #'
@@ -3012,6 +3061,22 @@ setMethod("map_values",
             column(jc)
           })
 
+#' @details
+#' \code{element_at}: Returns element of array at given index in \code{extraction} if
+#' \code{x} is array. Returns value for the given key in \code{extraction} if \code{x} is map.
+#' Note: The position is not zero based, but 1 based index.
+#'
+#' @param extraction index to check for in array or key to check for in map
+#' @rdname column_collection_functions
+#' @aliases element_at element_at,Column-method
+#' @note element_at since 2.4.0
+setMethod("element_at",
+          signature(x = "Column", extraction = "ANY"),
+          function(x, extraction) {
+            jc <- callJStatic("org.apache.spark.sql.functions", "element_at", x@jc, extraction)
+            column(jc)
+          })
+
 #' @details
 #' \code{explode}: Creates a new row for each element in the given array or map column.
 #'

R/pkg/R/generics.R

@@ -757,6 +757,18 @@ setGeneric("approxCountDistinct", function(x, ...) { standardGeneric("approxCoun
 #' @name NULL
 setGeneric("array_contains", function(x, value) { standardGeneric("array_contains") })
 
+#' @rdname column_collection_functions
+#' @name NULL
+setGeneric("array_max", function(x) { standardGeneric("array_max") })
+
+#' @rdname column_collection_functions
+#' @name NULL
+setGeneric("array_min", function(x) { standardGeneric("array_min") })
+
+#' @rdname column_collection_functions
+#' @name NULL
+setGeneric("array_position", function(x, value) { standardGeneric("array_position") })
+
 #' @rdname column_string_functions
 #' @name NULL
 setGeneric("ascii", function(x) { standardGeneric("ascii") })
@@ -886,6 +898,10 @@ setGeneric("decode", function(x, charset) { standardGeneric("decode") })
 #' @name NULL
 setGeneric("dense_rank", function(x = "missing") { standardGeneric("dense_rank") })
 
+#' @rdname column_collection_functions
+#' @name NULL
+setGeneric("element_at", function(x, extraction) { standardGeneric("element_at") })
+
 #' @rdname column_string_functions
 #' @name NULL
 setGeneric("encode", function(x, charset) { standardGeneric("encode") })

R/pkg/tests/fulltests/test_sparkSQL.R

@@ -1479,24 +1479,40 @@ test_that("column functions", {
   df5 <- createDataFrame(list(list(a = "010101")))
   expect_equal(collect(select(df5, conv(df5$a, 2, 16)))[1, 1], "15")
 
-  # Test array_contains() and sort_array()
+  # Test array_contains(), array_max(), array_min(), array_position(), element_at()
+  # and sort_array()
   df <- createDataFrame(list(list(list(1L, 2L, 3L)), list(list(6L, 5L, 4L))))
   result <- collect(select(df, array_contains(df[[1]], 1L)))[[1]]
   expect_equal(result, c(TRUE, FALSE))
 
+  result <- collect(select(df, array_max(df[[1]])))[[1]]
+  expect_equal(result, c(3, 6))
+
+  result <- collect(select(df, array_min(df[[1]])))[[1]]
+  expect_equal(result, c(1, 4))
+
+  result <- collect(select(df, array_position(df[[1]], 1L)))[[1]]
+  expect_equal(result, c(1, 0))
+
+  result <- collect(select(df, element_at(df[[1]], 1L)))[[1]]
+  expect_equal(result, c(1, 6))
+
   result <- collect(select(df, sort_array(df[[1]], FALSE)))[[1]]
   expect_equal(result, list(list(3L, 2L, 1L), list(6L, 5L, 4L)))
   result <- collect(select(df, sort_array(df[[1]])))[[1]]
   expect_equal(result, list(list(1L, 2L, 3L), list(4L, 5L, 6L)))
 
-  # Test map_keys() and map_values()
+  # Test map_keys(), map_values() and element_at()
   df <- createDataFrame(list(list(map = as.environment(list(x = 1, y = 2)))))
   result <- collect(select(df, map_keys(df$map)))[[1]]
   expect_equal(result, list(list("x", "y")))
 
   result <- collect(select(df, map_values(df$map)))[[1]]
   expect_equal(result, list(list(1, 2)))
 
+  result <- collect(select(df, element_at(df$map, "y")))[[1]]
+  expect_equal(result, 2)
+
   # Test that stats::lag is working
   expect_equal(length(lag(ldeaths, 12)), 72)
 

assembly/pom.xml

@@ -254,6 +254,14 @@
           <artifactId>spark-hadoop-cloud_${scala.binary.version}</artifactId>
           <version>${project.version}</version>
         </dependency>
+        <!--
+        Redeclare this dependency to force it into the distribution.
+        -->
+        <dependency>
+          <groupId>org.eclipse.jetty</groupId>
+          <artifactId>jetty-util</artifactId>
+          <scope>${hadoop.deps.scope}</scope>
+        </dependency>
       </dependencies>
     </profile>
   </profiles>

common/network-common/src/main/java/org/apache/spark/network/server/TransportServer.java

@@ -32,6 +32,7 @@
 import io.netty.channel.ChannelOption;
 import io.netty.channel.EventLoopGroup;
 import io.netty.channel.socket.SocketChannel;
+import org.apache.commons.lang3.SystemUtils;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
@@ -98,6 +99,7 @@ private void init(String hostToBind, int portToBind) {
       .group(bossGroup, workerGroup)
       .channel(NettyUtils.getServerChannelClass(ioMode))
       .option(ChannelOption.ALLOCATOR, allocator)
+      .option(ChannelOption.SO_REUSEADDR, !SystemUtils.IS_OS_WINDOWS)
       .childOption(ChannelOption.ALLOCATOR, allocator);
 
     this.metrics = new NettyMemoryMetrics(

common/unsafe/src/main/java/org/apache/spark/unsafe/array/ByteArrayMethods.java

@@ -33,7 +33,11 @@ public static long nextPowerOf2(long num) {
   }
 
   public static int roundNumberOfBytesToNearestWord(int numBytes) {
-    int remainder = numBytes & 0x07;  // This is equivalent to `numBytes % 8`
+    return (int)roundNumberOfBytesToNearestWord((long)numBytes);
+  }
+
+  public static long roundNumberOfBytesToNearestWord(long numBytes) {
+    long remainder = numBytes & 0x07;  // This is equivalent to `numBytes % 8`
     if (remainder == 0) {
       return numBytes;
     } else {

common/unsafe/src/test/java/org/apache/spark/unsafe/memory/MemoryBlockSuite.java

@@ -120,6 +120,8 @@ private void check(MemoryBlock memory, Object obj, long offset, int length) {
     } catch (Exception expected) {
       Assert.assertThat(expected.getMessage(), containsString("should not be larger than"));
     }
+
+    memory.setPageNumber(MemoryBlock.NO_PAGE_NUMBER);
   }
 
   @Test
@@ -165,11 +167,13 @@ public void testOffHeapArrayMemoryBlock() {
     int length = 56;
 
     check(memory, obj, offset, length);
+    memoryAllocator.free(memory);
 
     long address = Platform.allocateMemory(112);
     memory = new OffHeapMemoryBlock(address, length);
     obj = memory.getBaseObject();
     offset = memory.getBaseOffset();
     check(memory, obj, offset, length);
+    Platform.freeMemory(address);
   }
 }

core/pom.xml

@@ -95,6 +95,12 @@
       <groupId>org.apache.curator</groupId>
       <artifactId>curator-recipes</artifactId>
     </dependency>
+    <!-- With curator 2.12  SBT/Ivy doesn't get ZK on the build classpath.
+         Explicitly declaring it as a dependency fixes this. -->
+    <dependency>
+      <groupId>org.apache.zookeeper</groupId>
+      <artifactId>zookeeper</artifactId>
+    </dependency>
 
     <!-- Jetty dependencies promoted to compile here so they are shaded
          and inlined into spark-core jar -->

core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala

@@ -26,7 +26,7 @@ import scala.util.control.{ControlThrowable, NonFatal}
 import com.codahale.metrics.{Gauge, MetricRegistry}
 
 import org.apache.spark.internal.Logging
-import org.apache.spark.internal.config.{DYN_ALLOCATION_MAX_EXECUTORS, DYN_ALLOCATION_MIN_EXECUTORS}
+import org.apache.spark.internal.config._
 import org.apache.spark.metrics.source.Source
 import org.apache.spark.scheduler._
 import org.apache.spark.storage.BlockManagerMaster
@@ -69,6 +69,10 @@ import org.apache.spark.util.{Clock, SystemClock, ThreadUtils, Utils}
  *   spark.dynamicAllocation.maxExecutors - Upper bound on the number of executors
  *   spark.dynamicAllocation.initialExecutors - Number of executors to start with
  *
+ *   spark.dynamicAllocation.executorAllocationRatio -
+ *     This is used to reduce the parallelism of the dynamic allocation that can waste
+ *     resources when tasks are small
+ *
  *   spark.dynamicAllocation.schedulerBacklogTimeout (M) -
  *     If there are backlogged tasks for this duration, add new executors
  *
@@ -116,9 +120,12 @@ private[spark] class ExecutorAllocationManager(
   // TODO: The default value of 1 for spark.executor.cores works right now because dynamic
   // allocation is only supported for YARN and the default number of cores per executor in YARN is
   // 1, but it might need to be attained differently for different cluster managers
-  private val tasksPerExecutor =
+  private val tasksPerExecutorForFullParallelism =
     conf.getInt("spark.executor.cores", 1) / conf.getInt("spark.task.cpus", 1)
 
+  private val executorAllocationRatio =
+    conf.get(DYN_ALLOCATION_EXECUTOR_ALLOCATION_RATIO)
+
   validateSettings()
 
   // Number of executors to add in the next round
@@ -209,8 +216,13 @@ private[spark] class ExecutorAllocationManager(
       throw new SparkException("Dynamic allocation of executors requires the external " +
         "shuffle service. You may enable this through spark.shuffle.service.enabled.")
     }
-    if (tasksPerExecutor == 0) {
-      throw new SparkException("spark.executor.cores must not be less than spark.task.cpus.")
+    if (tasksPerExecutorForFullParallelism == 0) {
+      throw new SparkException("spark.executor.cores must not be < spark.task.cpus.")
+    }
+
+    if (executorAllocationRatio > 1.0 || executorAllocationRatio <= 0.0) {
+      throw new SparkException(
+        "spark.dynamicAllocation.executorAllocationRatio must be > 0 and <= 1.0")
     }
   }
 
@@ -273,7 +285,9 @@ private[spark] class ExecutorAllocationManager(
    */
   private def maxNumExecutorsNeeded(): Int = {
     val numRunningOrPendingTasks = listener.totalPendingTasks + listener.totalRunningTasks
-    (numRunningOrPendingTasks + tasksPerExecutor - 1) / tasksPerExecutor
+    math.ceil(numRunningOrPendingTasks * executorAllocationRatio /
+              tasksPerExecutorForFullParallelism)
+      .toInt
   }
 
   private def totalRunningTasks(): Int = synchronized {