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Created May 15, 2016 08:53
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SparkR unit test
Raw
error-message
Loading required package: methods
Attaching package: ‘SparkR’
The following object is masked from ‘package:testthat’:
describe
The following objects are masked from ‘package:stats’:
cov, filter, lag, na.omit, predict, sd, var, window
The following objects are masked from ‘package:base’:
as.data.frame, colnames, colnames<-, drop, intersect, rank, rbind,
sample, subset, summary, transform
functions on binary files: ....
binary functions: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
...........
broadcast variables: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
..
functions in client.R: .....
test functions in sparkR.R: .....Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
........Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
..........Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
.
include an external JAR in SparkContext: ..
include R packages: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
MLlib functions: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
.........................SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
.May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Writer version is: PARQUET_1_0
May 15, 2016 8:47:57 AM INFO: org.apache.parquet.hadoop.InternalParquetRecordWriter: Flushing mem columnStore to file. allocated memory: 65,622
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 70B for [label] BINARY: 1 values, 21B raw, 23B comp, 1 pages, encodings: [PLAIN, BIT_PACKED, RLE]
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 87B for [terms, list, element, list, element] BINARY: 2 values, 42B raw, 43B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 30B for [hasIntercept] BOOLEAN: 1 values, 1B raw, 3B comp, 1 pages, encodings: [PLAIN, BIT_PACKED]
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetFileReader: Initiating action with parallelism: 5
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Writer version is: PARQUET_1_0
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.InternalParquetRecordWriter: Flushing mem columnStore to file. allocated memory: 49
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 90B for [labels, list, element] BINARY: 3 values, 50B raw, 50B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:58 AM INFO: org.apache.parquet.hadoop.ParquetFileReader: Initiating action with parallelism: 5
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Writer version is: PARQUET_1_0
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.InternalParquetRecordWriter: Flushing mem columnStore to file. allocated memory: 92
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 61B for [vectorCol] BINARY: 1 values, 18B raw, 20B comp, 1 pages, encodings: [PLAIN, BIT_PACKED, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 126B for [prefixesToRewrite, key_value, key] BINARY: 2 values, 61B raw, 61B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 58B for [prefixesToRewrite, key_value, value] BINARY: 2 values, 15B raw, 17B comp, 1 pages, encodings: [PLAIN_DICTIONARY, RLE], dic { 1 entries, 12B raw, 1B comp}
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetFileReader: Initiating action with parallelism: 5
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Writer version is: PARQUET_1_0
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.InternalParquetRecordWriter: Flushing mem columnStore to file. allocated memory: 54
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 122B for [columnsToPrune, list, element] BINARY: 2 values, 59B raw, 59B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetFileReader: Initiating action with parallelism: 5
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Writer version is: PARQUET_1_0
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.InternalParquetRecordWriter: Flushing mem columnStore to file. allocated memory: 56
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 51B for [intercept] DOUBLE: 1 values, 8B raw, 10B comp, 1 pages, encodings: [PLAIN, BIT_PACKED]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 45B for [coefficients, type] INT32: 1 values, 10B raw, 12B comp, 1 pages, encodings: [PLAIN, BIT_PACKED, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 30B for [coefficients, size] INT32: 1 values, 7B raw, 9B comp, 1 pages, encodings: [PLAIN, BIT_PACKED, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 36B for [coefficients, indices, list, element] INT32: 1 values, 13B raw, 15B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 79B for [coefficients, values, list, element] DOUBLE: 3 values, 37B raw, 38B comp, 1 pages, encodings: [PLAIN, RLE]
May 15, 2016 8:47:59 AM INFO: org.apache.parquet.hadoop.ParquetFileReader: Initiating action with parallelism: 5
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.codec.CodecConfig: Compression: SNAPPY
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet block size to 134217728
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet page size to 1048576
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Parquet dictionary page size to 1048576
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Dictionary is on
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.hadoop.ParquetOutputFormat: Validation is off
May 15, 2016 8:48:00 AM INFO: org.apache.parquet.had.........................................................................
parallelize() and collect(): Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
.............................
basic RDD functions: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
............................................................................................................................................................................................................................................................................................................................................................................1.............................................................
SerDe functionality: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
...................
partitionBy, groupByKey, reduceByKey etc.: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
....................
SparkSQL functions: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
tests RDD function take(): Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
................
the textFile() function: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
.............
functions in utils.R: Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context
.................................
Failed -------------------------------------------------------------------------
1. Error: pipeRDD() on RDDs (@test_rdd.R#427) ----------------------------------
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 811.0 failed 1 times, most recent failure: Lost task 0.0 in stage 811.0 (TID 1913, localhost): org.apache.spark.SparkException: R computation failed with
[1] 2
[1] 3
[1] 1
[1] 1
[1] 3
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
ignoring SIGPIPE signal
Calls: source ... <Anonymous> -> lapply -> lapply -> FUN -> writeRaw -> writeBin
Execution halted
ignoring SIGPIPE signal
Calls: source ... <Anonymous> -> lapply -> lapply -> FUN -> writeRaw -> writeBin
Execution halted
cannot open the connection
Calls: source ... computeFunc -> FUN -> system2 -> writeLines -> file
In addition: Warning message:
In file(con, "w") :
cannot open file '/tmp/Rtmpjftqho/file422bf18e60c': No such file or directory
Execution halted
cannot open the connection
Calls: source ... computeFunc -> FUN -> system2 -> writeLines -> file
In addition: Warning message:
In file(con, "w") :
cannot open file '/tmp/Rtmpjftqho/file422af18e60c': No such file or directory
Execution halted
at org.apache.spark.api.r.RRunner.compute(RRunner.scala:107)
at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1863)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1876)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1889)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1903)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:883)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:357)
at org.apache.spark.rdd.RDD.collect(RDD.scala:882)
at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:349)
at org.apache.spark.api.java.AbstractJavaRDDLike.collect(JavaRDDLike.scala:45)
at sun.reflect.GeneratedMethodAccessor35.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:141)
at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:86)
at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:38)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:244)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:137)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: R computation failed with
[1] 2
[1] 3
[1] 1
[1] 1
[1] 3
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
[1] 2
ignoring SIGPIPE signal
Calls: source ... <Anonymous> -> lapply -> lapply -> FUN -> writeRaw -> writeBin
Execution halted
ignoring SIGPIPE signal
Calls: source ... <Anonymous> -> lapply -> lapply -> FUN -> writeRaw -> writeBin
Execution halted
cannot open the connection
Calls: source ... computeFunc -> FUN -> system2 -> writeLines -> file
In addition: Warning message:
In file(con, "w") :
cannot open file '/tmp/Rtmpjftqho/file422bf18e60c': No such file or directory
Execution halted
cannot open the connection
Calls: source ... computeFunc -> FUN -> system2 -> writeLines -> file
In addition: Warning message:
In file(con, "w") :
cannot open file '/tmp/Rtmpjftqho/file422af18e60c': No such file or directory
Execution halted
at org.apache.spark.api.r.RRunner.compute(RRunner.scala:107)
at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
1: collect(pipeRDD(rdd, "more")) at /root/spark/R/lib/SparkR/tests/testthat/test_rdd.R:427
2: collect(pipeRDD(rdd, "more"))
3: .local(x, ...)
4: callJMethod(getJRDD(x), "collect")
5: invokeJava(isStatic = FALSE, objId$id, methodName, ...)
6: stop(readString(conn))
DONE ===========================================================================
Error: Test failures
Execution halted
@wangmiao1981
Copy link

I got different error messages:

Warnings -----------------------------------------------------------------------

  1. multiple packages don't produce a warning (@test_client.R#35) - not() is deprecated.
  2. sparkJars sparkPackages as comma-separated strings (@test_context.R#136) - not() is deprecated.
  3. date functions on a DataFrame (@test_sparkSQL.R#1186) - Deprecated: please use expect_gt() instead
  4. date functions on a DataFrame (@test_sparkSQL.R#1187) - Deprecated: please use expect_gt() instead
  5. date functions on a DataFrame (@test_sparkSQL.R#1188) - Deprecated: please use expect_gt() instead

Failed -------------------------------------------------------------------------

  1. Failure: Check masked functions (@test_context.R#30) ------------------------
    length(maskedBySparkR) not equal to length(namesOfMasked).
    1/1 mismatches
    [1] 20 - 18 == 2
  2. Failure: Check masked functions (@test_context.R#31) ------------------------
    sort(maskedBySparkR) not equal to sort(namesOfMasked).
    Lengths differ: 20 vs 18
  3. Failure: Check masked functions (@test_context.R#40) ------------------------
    length(maskedCompletely) not equal to length(namesOfMaskedCompletely).
    1/1 mismatches
    [1] 5 - 3 == 2
  4. Failure: Check masked functions (@test_context.R#41) ------------------------
    sort(maskedCompletely) not equal to sort(namesOfMaskedCompletely).
    Lengths differ: 5 vs 3
  5. Failure: showDF() (@test_sparkSQL.R#1464) -----------------------------------
    s produced no output

DONE ===========================================================================
Error: Test failures
Execution halted
Had test failures; see logs.

@wangmiao1981
Copy link

Rebuild and Reproduced the issue:

In addition: Warning message:
In file(con, "w") :
cannot open file '/var/folders/s_/83b0sgvj2kl2kwq4stvft_pm0000gn/T//RtmpJXzTT8/file172edf4eb6f': No such file or directory
Execution halted
cannot open the connection
Calls: source ... computeFunc -> FUN -> system2 -> writeLines -> file
In addition: Warning message:
In file(con, "w") :
cannot open file '/var/folders/s_/83b0sgvj2kl2kwq4stvft_pm0000gn/T//RtmpJXzTT8/file172fdf4eb6f': No such file or directory
Execution halted
at org.apache.spark.api.r.RRunner.compute(RRunner.scala:107)
at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.conc
1: collect(pipeRDD(rdd, "more")) at /Users/mwang/spark_ws_0904/R/lib/SparkR/tests/testthat/test_rdd.R:427
2: collect(pipeRDD(rdd, "more"))
3: .local(x, ...)
4: callJMethod(getJRDD(x), "collect")
5: invokeJava(isStatic = FALSE, objId$id, methodName, ...)
6: stop(readString(conn))

  1. Error: subsetting (@test_sparkSQL.R#922) ------------------------------------
    argument "subset" is missing, with no default
    1: subset(df, select = "name", drop = F) at /Users/mwang/spark_ws_0904/R/lib/SparkR/tests/testthat/test_sparkSQL.R:922
    2: subset(df, select = "name", drop = F)
    3: .local(x, ...)
    4: x[subset, select, drop = drop]

DONE ===========================================================================
Error: Test failures
Execution halted
Had test failures; see logs.

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