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[SPARK-12327][SPARKR] fix code for lintr warning for commented code
shivaram Author: felixcheung <felixcheung_m@hotmail.com> Closes apache#10408 from felixcheung/rcodecomment.
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‎R/pkg/.lintr

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,2 +1,2 @@
1-
linters: with_defaults(line_length_linter(100), camel_case_linter = NULL, open_curly_linter(allow_single_line = TRUE), closed_curly_linter(allow_single_line = TRUE), commented_code_linter = NULL)
1+
linters: with_defaults(line_length_linter(100), camel_case_linter = NULL, open_curly_linter(allow_single_line = TRUE), closed_curly_linter(allow_single_line = TRUE))
22
exclusions: list("inst/profile/general.R" = 1, "inst/profile/shell.R")

‎R/pkg/R/RDD.R

Lines changed: 38 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -180,7 +180,7 @@ setMethod("getJRDD", signature(rdd = "PipelinedRDD"),
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}
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# Save the serialization flag after we create a RRDD
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rdd@env$serializedMode <- serializedMode
183-
rdd@env$jrdd_val <- callJMethod(rddRef, "asJavaRDD") # rddRef$asJavaRDD()
183+
rdd@env$jrdd_val <- callJMethod(rddRef, "asJavaRDD")
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rdd@env$jrdd_val
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})
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@@ -225,7 +225,7 @@ setMethod("cache",
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#'
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#' Persist this RDD with the specified storage level. For details of the
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#' supported storage levels, refer to
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#' http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence.
228+
#'\url{http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence}.
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#'
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#' @param x The RDD to persist
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#' @param newLevel The new storage level to be assigned
@@ -382,11 +382,13 @@ setMethod("collectPartition",
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#' \code{collectAsMap} returns a named list as a map that contains all of the elements
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#' in a key-value pair RDD.
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#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, list(list(1, 2), list(3, 4)), 2L)
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#' collectAsMap(rdd) # list(`1` = 2, `3` = 4)
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#'}
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# nolint end
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#' @rdname collect-methods
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#' @aliases collectAsMap,RDD-method
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#' @noRd
@@ -442,11 +444,13 @@ setMethod("length",
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#' @return list of (value, count) pairs, where count is number of each unique
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#' value in rdd.
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#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, c(1,2,3,2,1))
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#' countByValue(rdd) # (1,2L), (2,2L), (3,1L)
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#'}
453+
# nolint end
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#' @rdname countByValue
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#' @aliases countByValue,RDD-method
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#' @noRd
@@ -597,11 +601,13 @@ setMethod("mapPartitionsWithIndex",
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#' @param x The RDD to be filtered.
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#' @param f A unary predicate function.
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#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, 1:10)
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#' unlist(collect(filterRDD(rdd, function (x) { x < 3 }))) # c(1, 2)
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#'}
610+
# nolint end
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#' @rdname filterRDD
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#' @aliases filterRDD,RDD,function-method
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#' @noRd
@@ -756,11 +762,13 @@ setMethod("foreachPartition",
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#' @param x The RDD to take elements from
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#' @param num Number of elements to take
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#' @examples
765+
# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, 1:10)
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#' take(rdd, 2L) # list(1, 2)
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#'}
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# nolint end
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#' @rdname take
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#' @aliases take,RDD,numeric-method
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#' @noRd
@@ -824,11 +832,13 @@ setMethod("first",
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#' @param x The RDD to remove duplicates from.
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#' @param numPartitions Number of partitions to create.
826834
#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, c(1,2,2,3,3,3))
830839
#' sort(unlist(collect(distinct(rdd)))) # c(1, 2, 3)
831840
#'}
841+
# nolint end
832842
#' @rdname distinct
833843
#' @aliases distinct,RDD-method
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#' @noRd
@@ -974,11 +984,13 @@ setMethod("takeSample", signature(x = "RDD", withReplacement = "logical",
974984
#' @param x The RDD.
975985
#' @param func The function to be applied.
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#' @examples
987+
# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, list(1, 2, 3))
980991
#' collect(keyBy(rdd, function(x) { x*x })) # list(list(1, 1), list(4, 2), list(9, 3))
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#'}
993+
# nolint end
982994
#' @rdname keyBy
983995
#' @aliases keyBy,RDD
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#' @noRd
@@ -1113,11 +1125,13 @@ setMethod("saveAsTextFile",
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#' @param numPartitions Number of partitions to create.
11141126
#' @return An RDD where all elements are sorted.
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#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, list(3, 2, 1))
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#' collect(sortBy(rdd, function(x) { x })) # list (1, 2, 3)
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#'}
1134+
# nolint end
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#' @rdname sortBy
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#' @aliases sortBy,RDD,RDD-method
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#' @noRd
@@ -1188,11 +1202,13 @@ takeOrderedElem <- function(x, num, ascending = TRUE) {
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#' @param num Number of elements to return.
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#' @return The first N elements from the RDD in ascending order.
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#' @examples
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# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, list(10, 1, 2, 9, 3, 4, 5, 6, 7))
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#' takeOrdered(rdd, 6L) # list(1, 2, 3, 4, 5, 6)
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#'}
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# nolint end
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#' @rdname takeOrdered
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#' @aliases takeOrdered,RDD,RDD-method
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#' @noRd
@@ -1209,11 +1225,13 @@ setMethod("takeOrdered",
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#' @return The top N elements from the RDD.
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#' @rdname top
12111227
#' @examples
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# nolint start
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#'\dontrun{
12131230
#' sc <- sparkR.init()
12141231
#' rdd <- parallelize(sc, list(10, 1, 2, 9, 3, 4, 5, 6, 7))
12151232
#' top(rdd, 6L) # list(10, 9, 7, 6, 5, 4)
12161233
#'}
1234+
# nolint end
12171235
#' @aliases top,RDD,RDD-method
12181236
#' @noRd
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setMethod("top",
@@ -1261,6 +1279,7 @@ setMethod("fold",
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#' @rdname aggregateRDD
12621280
#' @seealso reduce
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#' @examples
1282+
# nolint start
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#'\dontrun{
12651284
#' sc <- sparkR.init()
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#' rdd <- parallelize(sc, list(1, 2, 3, 4))
@@ -1269,6 +1288,7 @@ setMethod("fold",
12691288
#' combOp <- function(x, y) { list(x[[1]] + y[[1]], x[[2]] + y[[2]]) }
12701289
#' aggregateRDD(rdd, zeroValue, seqOp, combOp) # list(10, 4)
12711290
#'}
1291+
# nolint end
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#' @aliases aggregateRDD,RDD,RDD-method
12731293
#' @noRd
12741294
setMethod("aggregateRDD",
@@ -1367,12 +1387,14 @@ setMethod("setName",
13671387
#' @return An RDD with zipped items.
13681388
#' @seealso zipWithIndex
13691389
#' @examples
1390+
# nolint start
13701391
#'\dontrun{
13711392
#' sc <- sparkR.init()
13721393
#' rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
13731394
#' collect(zipWithUniqueId(rdd))
13741395
#' # list(list("a", 0), list("b", 3), list("c", 1), list("d", 4), list("e", 2))
13751396
#'}
1397+
# nolint end
13761398
#' @rdname zipWithUniqueId
13771399
#' @aliases zipWithUniqueId,RDD
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#' @noRd
@@ -1408,12 +1430,14 @@ setMethod("zipWithUniqueId",
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#' @return An RDD with zipped items.
14091431
#' @seealso zipWithUniqueId
14101432
#' @examples
1433+
# nolint start
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#'\dontrun{
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#' sc <- sparkR.init()
14131436
#' rdd <- parallelize(sc, list("a", "b", "c", "d", "e"), 3L)
14141437
#' collect(zipWithIndex(rdd))
14151438
#' # list(list("a", 0), list("b", 1), list("c", 2), list("d", 3), list("e", 4))
14161439
#'}
1440+
# nolint end
14171441
#' @rdname zipWithIndex
14181442
#' @aliases zipWithIndex,RDD
14191443
#' @noRd
@@ -1454,12 +1478,14 @@ setMethod("zipWithIndex",
14541478
#' @return An RDD created by coalescing all elements within
14551479
#' each partition into a list.
14561480
#' @examples
1481+
# nolint start
14571482
#'\dontrun{
14581483
#' sc <- sparkR.init()
14591484
#' rdd <- parallelize(sc, as.list(1:4), 2L)
14601485
#' collect(glom(rdd))
14611486
#' # list(list(1, 2), list(3, 4))
14621487
#'}
1488+
# nolint end
14631489
#' @rdname glom
14641490
#' @aliases glom,RDD
14651491
#' @noRd
@@ -1519,13 +1545,15 @@ setMethod("unionRDD",
15191545
#' @param other Another RDD to be zipped.
15201546
#' @return An RDD zipped from the two RDDs.
15211547
#' @examples
1548+
# nolint start
15221549
#'\dontrun{
15231550
#' sc <- sparkR.init()
15241551
#' rdd1 <- parallelize(sc, 0:4)
15251552
#' rdd2 <- parallelize(sc, 1000:1004)
15261553
#' collect(zipRDD(rdd1, rdd2))
15271554
#' # list(list(0, 1000), list(1, 1001), list(2, 1002), list(3, 1003), list(4, 1004))
15281555
#'}
1556+
# nolint end
15291557
#' @rdname zipRDD
15301558
#' @aliases zipRDD,RDD
15311559
#' @noRd
@@ -1557,12 +1585,14 @@ setMethod("zipRDD",
15571585
#' @param other An RDD.
15581586
#' @return A new RDD which is the Cartesian product of these two RDDs.
15591587
#' @examples
1588+
# nolint start
15601589
#'\dontrun{
15611590
#' sc <- sparkR.init()
15621591
#' rdd <- parallelize(sc, 1:2)
15631592
#' sortByKey(cartesian(rdd, rdd))
15641593
#' # list(list(1, 1), list(1, 2), list(2, 1), list(2, 2))
15651594
#'}
1595+
# nolint end
15661596
#' @rdname cartesian
15671597
#' @aliases cartesian,RDD,RDD-method
15681598
#' @noRd
@@ -1587,13 +1617,15 @@ setMethod("cartesian",
15871617
#' @param numPartitions Number of the partitions in the result RDD.
15881618
#' @return An RDD with the elements from this that are not in other.
15891619
#' @examples
1620+
# nolint start
15901621
#'\dontrun{
15911622
#' sc <- sparkR.init()
15921623
#' rdd1 <- parallelize(sc, list(1, 1, 2, 2, 3, 4))
15931624
#' rdd2 <- parallelize(sc, list(2, 4))
15941625
#' collect(subtract(rdd1, rdd2))
15951626
#' # list(1, 1, 3)
15961627
#'}
1628+
# nolint end
15971629
#' @rdname subtract
15981630
#' @aliases subtract,RDD
15991631
#' @noRd
@@ -1619,13 +1651,15 @@ setMethod("subtract",
16191651
#' @param numPartitions The number of partitions in the result RDD.
16201652
#' @return An RDD which is the intersection of these two RDDs.
16211653
#' @examples
1654+
# nolint start
16221655
#'\dontrun{
16231656
#' sc <- sparkR.init()
16241657
#' rdd1 <- parallelize(sc, list(1, 10, 2, 3, 4, 5))
16251658
#' rdd2 <- parallelize(sc, list(1, 6, 2, 3, 7, 8))
16261659
#' collect(sortBy(intersection(rdd1, rdd2), function(x) { x }))
16271660
#' # list(1, 2, 3)
16281661
#'}
1662+
# nolint end
16291663
#' @rdname intersection
16301664
#' @aliases intersection,RDD
16311665
#' @noRd
@@ -1653,6 +1687,7 @@ setMethod("intersection",
16531687
#' Assumes that all the RDDs have the *same number of partitions*, but
16541688
#' does *not* require them to have the same number of elements in each partition.
16551689
#' @examples
1690+
# nolint start
16561691
#'\dontrun{
16571692
#' sc <- sparkR.init()
16581693
#' rdd1 <- parallelize(sc, 1:2, 2L) # 1, 2
@@ -1662,6 +1697,7 @@ setMethod("intersection",
16621697
#' func = function(x, y, z) { list(list(x, y, z))} ))
16631698
#' # list(list(1, c(1,2), c(1,2,3)), list(2, c(3,4), c(4,5,6)))
16641699
#'}
1700+
# nolint end
16651701
#' @rdname zipRDD
16661702
#' @aliases zipPartitions,RDD
16671703
#' @noRd

‎R/pkg/R/deserialize.R

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Original file line numberDiff line numberDiff line change
@@ -17,6 +17,7 @@
1717

1818
# Utility functions to deserialize objects from Java.
1919

20+
# nolint start
2021
# Type mapping from Java to R
2122
#
2223
# void -> NULL
@@ -32,6 +33,8 @@
3233
#
3334
# Array[T] -> list()
3435
# Object -> jobj
36+
#
37+
# nolint end
3538

3639
readObject <- function(con) {
3740
# Read type first

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