从 reduceByKey() 调用函数时单元测试期间的导入错误

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【中文标题】从 reduceByKey() 调用函数时单元测试期间的导入错误【英文标题】：Import error during unit test while calling a function from reduceByKey() 【发布时间】：2016-01-11 14:44:17 【问题描述】：

我的测试脚本的当前目录结构如下：

project/
    script/
        __init__.py 
        map.py
    test/
        __init.py__
        test_map.py

我的map.py定义如下：

def add(x,y):
    return x+y

def map_add(df):
    result = df.map(lambda x: (x.key, x.value)).reduceByKey(add)
    return result

test_map.py 如下所示：

def add_pyspark_path():
    """
    Add PySpark to the PYTHONPATH
    """
    import sys
    import os
    try:
        sys.path.append(os.path.join(os.environ['SPARK_HOME'], "python"))
        # Spark 1.6
        sys.path.append(os.path.join(os.environ['SPARK_HOME'],
                                     "python", "lib", "py4j-0.9-src.zip"))
    except KeyError:
        print("SPARK_HOME not set")
        sys.exit(1)

# To import pyspark
add_pyspark_path()

import unittest

from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext
from script.map import map_add


class PySparkTestCase(unittest.TestCase):
    def setUp(self):
        # Setup a new spark context for each test
        conf = SparkConf()
        conf.set("spark.executor.memory", "1g")
        conf.set("spark.cores.max", "1")
        conf.set("spark.app.name", "nosetest")
        self.sc = SparkContext(conf=conf)

    def tearDown(self):
        self.sc.stop()


# This would go in tests/project_test.py
class MapTests(PySparkTestCase):

    def MockDataFrame(self):
        # Get a mock dataframe to test the script
        sqlContext = SQLContext(self.sc)
        rdd = self.sc.parallelize([(1,0), (1,1), (2,0), (2,2)])
        schema = [
            "key",
            "value"
        ]
        dataset = sqlContext.createDataFrame(rdd, schema)
        return dataset

    def test_add(self):
        df = self.MockDataFrame()
        result = map_add(df)
        print(result.collect())
        self.assertEqual(result.count(), 2)

当我在测试目录中运行nosetest 时，测试失败。我没有找到名为“脚本”的模块。 但是，当我修改 map_add 函数以替换在 map.py 中的 reduceByKey 中添加的调用时，如下所示：

def map_add(df):
    result = df.map(lambda x: (x.key, x.value)).reduceByKey(lambda x,y: x+y)
    return result

测试通过。

另外，当我从项目目录运行原始 test_map.py 时，测试通过了。

我无法弄清楚为什么当脚本模块位于测试目录中时测试没有检测到它。

这是错误的日志 sn-p：

test_add (test.test_map.MapTests) ... 16/01/11 15:38:10 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 5)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 98, in main
    command = pickleSer._read_with_length(infile)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
    return self.loads(obj)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 419, in loads
    return pickle.loads(obj, encoding=encoding)
ImportError: No module named 'script'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
    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)
16/01/11 15:38:10 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job
ERROR

======================================================================
ERROR: test_add (test.test_map.MapTests)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/datitran/Desktop/pyspark_test/test/test_map.py", line 56, in test_add
    print(result.collect())
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/pyspark/rdd.py", line 771, in collect
    port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/pyspark/sql/utils.py", line 45, in deco
    return f(*a, **kw)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
    format(target_id, ".", name), value)
nose.proxy.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 5, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 98, in main
    command = pickleSer._read_with_length(infile)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
    return self.loads(obj)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 419, in loads
    return pickle.loads(obj, encoding=encoding)
ImportError: No module named 'script'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
    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$$failJobAndIndependentStages(DAGScheduler.scala:1431)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/worker.py", line 98, in main
    command = pickleSer._read_with_length(infile)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
    return self.loads(obj)
  File "/usr/local/Cellar/apache-spark/1.6.0/libexec/python/lib/pyspark.zip/pyspark/serializers.py", line 419, in loads
    return pickle.loads(obj, encoding=encoding)
ImportError: No module named 'script'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    ... 1 more

我们将不胜感激。

【问题讨论】：

【参考方案1】：

找到了此问题的答案，并认为将其分享给社区是个好主意。如果代码库被分成不同的文件夹，这可能很有用。 因此，不知何故，相对重要性不适用于 pyspark，因为导入不会发生在工作人员身上，但我找到了解决这个问题的方法。

首先，在主目录中创建另一个 _ init _.py 文件，在本例中称为“项目”，因此结构如下所示：

project/
    __init__.py
    script/
        __init__.py 
        map.py
    test/
        __init.py__
        test_map.py

其次，将 PYTHONPATH 显式添加到 spark 环境中，以便每个工作人员都知道在哪里搜索导入：

class PySparkTestCase(unittest.TestCase):
    def setUp(self):
        conf = SparkConf()
        conf.set("spark.executor.memory", "1g")
        conf.set("spark.cores.max", "1")
        conf.set("spark.app.name", "nosetest")
        conf.setExecutorEnv("PYTHONPATH", "$PYTHONPATH:" +
                            os.path.abspath(os.path.join(os.path.join(os.path.dirname(os.path.abspath(__file__)), os.pardir), os.pardir)))
        self.sc = SparkContext(conf=conf)

最后，我们需要在 python 脚本之上导入模块：

from project.script.map import map_add

那么现在执行 spark 作业就可以了！

【讨论】：

我试过这个，但不能让它工作（在 Spark 1.6.3 中）。我恢复到另一个解决方案，我将其添加为替代答案。 也许我认为可以通过在“本地”或“客户端模式”中执行您的 Spark 作业来解决。请将以下命令放入测试脚本中。 os.environ["PYSPARK_PYTHON"]= '你的集群的 PYTHON 路径(/usr/XXX)'

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