PySpark Throwing error Method __getnewargs__([]) does not exist

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I have a set of files. The path to the files are saved in a file., say all_files.txt. Using apache spark, I need to do an operation on all the files and club the results.

The steps that I want to do are:

  • Create an RDD by reading all_files.txt
  • For each line in all_files.txt (Each line is a path to some file), read the contents of each of the files into a single RDD
  • Then do an operation all contents

This is the code I wrote for the same:

def return_contents_from_file (file_name):
    return spark.read.text(file_name).rdd.map(lambda  r: r[0])

def run_spark():
    file_name = 'path_to_file'

    spark = SparkSession \
        .builder \
        .appName("PythonWordCount") \
        .getOrCreate()

    counts = spark.read.text(file_name).rdd.map(lambda r: r[0]) \ # this line is supposed to return the paths to each file
        .flatMap(return_contents_from_file) \ # here i am expecting to club all the contents of all files
        .flatMap(do_operation_on_each_line_of_all_files) # here i am expecting do an operation on each line of all files

This is throwing the error:

line 323, in get_return_value py4j.protocol.Py4JError: An error occurred while calling o25.getnewargs. Trace: py4j.Py4JException: Method getnewargs([]) does not exist at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318) at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:326) at py4j.Gateway.invoke(Gateway.java:272) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:214) at java.lang.Thread.run(Thread.java:745)

Can someone please tell me what I am doing wrong and how I should proceed further. Thanks in advance.

Using spark inside flatMap or any transformation that occures on executors is not allowed (spark session is available on driver only). It is also not possible to create RDD of RDDs (see: Is it possible to create nested RDDs in Apache Spark?)

But you can achieve this transformation in another way - read all content of all_files.txt into dataframe, use local map to make them dataframes and local reduce to union all, see example:

>>> filenames = spark.read.text('all_files.txt').collect()
>>> dataframes = map(lambda r: spark.read.text(r[0]), filenames)
>>> all_lines_df = reduce(lambda df1, df2: df1.unionAll(df2), dataframes)

py4j.Py4JException: Method __getnewargs__([]) does not exist, Py4JExceptionMethod __getnewargs__([]) does not exist. This crash GatewayConnection.run() has thrown a Py4JException. Py4J. 1 Pyspark error - py4j. Python has built-in abs method. pyspark also provides abs method but that is for DataFrame column. If you do import pyspark method 'abs' in pyspark shell then you do override built-in abs method. It looks like you have override abs method something like below:

I meet this problem today, finally figure out that I refered to a spark.DataFrame object in pandas_udf , which result to this error .

The conclution:

You can't use sparkSession object , spark.DataFrame object or other Spark distributed objects in udf and pandas_udf, because they are unpickled.

If you meet this error and you are using udf, check it carefully , must be relative problem.

py4j.Py4JException: Method __getnewargs__([]) does not exist , Using spark inside flatMap or any transformation that occures on executors is not allowed ( spark session is available on driver only). It is also not possible to� Test build #85607 has finished for PR 20137 at commit 8216b6b.. This patch fails PySpark unit tests.; This patch merges cleanly. This patch adds no public classes.

I also got this error trying to log my model with MLFlow using mlflow.sklearn.log_model when the model itself was a pyspark.ml.classification model. Using mlflow.spark.log_model solved the issue.

PySpark Throwing error Method __getnewargs__([]) does not exist Using apache spark, I need to do an operation on all the files and club the results. Why do banks take deposits if they do not need them to make loans? Where and when did the `0x` convention for hexadecimal literals originate? How can one argue against income inequality while defending achievement and expertise inequality - beyond invoking Rawl's difference principle?

PySpark Throwing error Method __getnewargs__([]) does not exist. 发布于 2020- 05-01 17:28:38. I have a set of files. The path to the files are saved in a file., say� I have a very large dataset that is loaded in Hive. It consists of about 1.9 million rows and 1450 columns. I need to determine the 'coverage' of each of the columns, meaning, the fraction of rows that have non-NaN values for each column. Here is my code: from pyspark import SparkContext from pysp

File "/usr/local/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 312, in get_return_value Py4JError: An error occurred while calling o17.getnewargs. Py4JException: Method __getnewargs__([]) does not exist #69. Spark does not support nested RDDs or performing Spark actions inside of transformations; this usually leads to NullPointerExceptions (see SPARK-718 as one example). The confusing NPE is one of the most common sources of Spark questions on StackOverflow:

I am using Ionic and Firebase with cloud function. Whenever data is updated I am sending notification. I have two type of users: members and non-member.

Comments
  • Thank you for your reply. But how do I parallelize the whole process? wouldn't map(lambda r: spark.read.text(r[0]), filenames) serialize the whole process?
  • The process of reading files run in parallel, the only serialized part is building execution plan. Try it out!
  • What's your solution then?
  • @Rock Only make sure no Spark distributed objects in udf and pandas_udf
  • Similarly, this error popped up for me when I accidentally returned a spark dataframe from a pandas_udf.