调用map后调用POSpark EOFError

时间:2016-04-13 08:26:39

标签: python apache-spark pyspark

我是新来的火花& pyspark。

我正在将一个小的csv文件(~40k)读入数据帧。

from pyspark.sql import functions as F
df = sqlContext.read.format('com.databricks.spark.csv').options(header='true', inferschema='true').load('/tmp/sm.csv')
df = df.withColumn('verified', F.when(df['verified'] == 'Y', 1).otherwise(0))
df2 = df.map(lambda x: Row(label=float(x[0]), features=Vectors.dense(x[1:]))).toDF()

我得到一些奇怪的错误,每次都不会发生,但确实经常发生

>>> df2.show(1)
+--------------------+---------+
|            features|    label|
+--------------------+---------+
|[0.0,0.0,0.0,0.0,...|4700734.0|
+--------------------+---------+
only showing top 1 row

>>> df2.count()
41999                                                                           
>>> df2.show(1)
+--------------------+---------+
|            features|    label|
+--------------------+---------+
|[0.0,0.0,0.0,0.0,...|4700734.0|
+--------------------+---------+
only showing top 1 row

>>> df2.count()
41999                                                                           
>>> df2.show(1)
Traceback (most recent call last):
  File "spark-1.6.1/python/lib/pyspark.zip/pyspark/daemon.py", line 157, in manager
  File "spark-1.6.1/python/lib/pyspark.zip/pyspark/daemon.py", line 61, in worker    
  File "spark-1.6.1/python/lib/pyspark.zip/pyspark/worker.py", line 136, in main
    if read_int(infile) == SpecialLengths.END_OF_STREAM:
  File "spark-1.6.1/python/lib/pyspark.zip/pyspark/serializers.py", line 545, in read_int
    raise EOFError
EOFError
+--------------------+---------+
|            features|    label|
+--------------------+---------+
|[0.0,0.0,0.0,0.0,...|4700734.0|
+--------------------+---------+
only showing top 1 row

一旦提出了EOFError,我就不会再看到它了,直到我做了一些需要与spark服务器交互的东西

当我调用df2.count()时,它会显示[Stage xxx]提示符,这是我去火花服务器的意思。当我使用df2执行某些操作时,任何触发该操作的内容最终都会最终再次出现EOFError。

df(与df2相似)似乎没有发生,所以看起来它必须是df.map()行发生的事情。

2 个答案:

答案 0 :(得分:0)

将数据帧转换为rdd后,请尝试做地图吗?您正在数据框上应用map函数,然后再次从该数据框创建数据框。语法就像

df.rdd.map().toDF()

如果有效,请告诉我。谢谢。

答案 1 :(得分:0)

我相信你正在运行Spark 2.x及更高版本。下面的代码应该从csv:

创建数据框
public function get_billing_email() {
        $billing_email = $this->order->billing_email;
        return apply_filters( 'xc_woo_cloud_print_billing_email', $billing_email, $this );
    }
public function billing_email() {
    echo $this->get_billing_email();
}

然后你可以拥有以下代码:

df = spark.read.format("csv").option("header", "true").load("csvfile.csv")

然后你可以创建没有Row的df2和toDF()

让我知道这是否有效或者您使用的是Spark 1.6 ...谢谢。