sparkR 读取 csv 错误 return status==0 not TRUE

sparkR reading csv ERROR return status==0 not TRUE

我使用

启动了我的 spark shell
>>./bin/sparkR --packages com.databricks:spark-csv_2.10:1.2.0

现在我正在尝试在 sparkR 中读取 csv shell

d <- read.df(sqlContext,
    "data/mllib/sample_tree_data.csv","com.databricks.spark.csv", header="true")

但每次我都收到错误

Error: returnStatus == 0 is not TRUE

启动sparkR时的日志shell如下:

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Launching java with spark-submit command /opt/spark/bin/spark-submit   "--packages" "com.databricks:spark-csv_2.10:1.2.0" "sparkr-shell" /tmp/RtmpXZM96Y/backend_porte2670057297 
Ivy Default Cache set to: /home/ravimanik/.ivy2/cache
The jars for the packages stored in: /home/ravimanik/.ivy2/jars
:: loading settings :: url = jar:file:/opt/alti-spark-1.4.1.hadoop24.hive13/assembly/target/scala-2.10/spark-assembly-1.4.1-hadoop2.4.1.jar!/org/apache/ivy/core/settings/ivysettings.xml
com.databricks#spark-csv_2.10 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent;1.0
    confs: [default]
    found com.databricks#spark-csv_2.10;1.2.0 in central
    found org.apache.commons#commons-csv;1.1 in central
    found com.univocity#univocity-parsers;1.5.1 in central
:: resolution report :: resolve 297ms :: artifacts dl 30ms
    :: modules in use:
    com.databricks#spark-csv_2.10;1.2.0 from central in [default]
    com.univocity#univocity-parsers;1.5.1 from central in [default]
    org.apache.commons#commons-csv;1.1 from central in [default]
    ---------------------------------------------------------------------
    |                  |            modules            ||   artifacts   |
    |       conf       | number| search|dwnlded|evicted|| number|dwnlded|
    ---------------------------------------------------------------------
    |      default     |   3   |   0   |   0   |   0   ||   3   |   0   |
    ---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent
    confs: [default]
    0 artifacts copied, 3 already retrieved (0kB/21ms)

 Welcome to SparkR!
 Spark context is available as sc, SQL context is available as sqlContext

我遇到了完全相同的问题。它在我重新启动 R-session 后起作用。