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https://issues.apache.org/jira/browse/SPARK-32053?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17177073#comment-17177073
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Kayal commented on SPARK-32053:
-------------------------------
The code to reproduce the issue on windows jupyter notebook:
import pyspark
#from pyspark.sql import SQLContext
from pyspark import SparkContext
sc = SparkContext("local", "First App")
from pyspark.sql import SparkSession
sess = SparkSession(sc)
training = sess.createDataFrame([
("0L", "a b c d e WML", 1.0),
("1L", "b d", 0.0),
("2L", "WML f g h", 1.0),
("3L", "hadoop mapreduce", 0.0)], ["id", "text", "label"])
evaluation = sess.createDataFrame([
("4L", "a b c WML", 1.0),
("5L", "l m n o p", 0.0),
("6L", "WML g h i k", 1.0),
("7L", "apache hadoop zuzu", 0.0)], ["id", "text", "label"])
testing = sess.createDataFrame([
("4L", "a b c z WML"),
("5L", "l m n"),
("6L", "WML g h i j k"),
("7L", "apache hadoop")], ["id", "text"])
import traceback
from pyspark.ml.pipeline import Pipeline
from pyspark.ml.classification import LogisticRegression
from pyspark.ml.feature import HashingTF, Tokenizer
from pyspark.sql import SQLContext as sql_context
tokenizer = Tokenizer(inputCol="text", outputCol="words")
hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol="features")
lr = LogisticRegression(maxIter=10, regParam=0.01)
stages=[tokenizer, hashingTF, lr]
pipeline = Pipeline(stages=stages)
model = pipeline.fit(training)
test_result = model.transform(testing)
pipeline.write().overwrite().save("tempfile")
The write operation is failing with the error that I mentioned above. This is
blocking our product delivery. could consider this with high priority blocker
issue. Is there a work around for this ? sparkml is supported on windows
pyspark ?
I also noticed the same error with
pipline.save() method.
> pyspark save of serialized model is failing for windows.
> --------------------------------------------------------
>
> Key: SPARK-32053
> URL: https://issues.apache.org/jira/browse/SPARK-32053
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Kayal
> Priority: Major
> Attachments: image-2020-06-22-18-19-32-236.png
>
>
> {color:#172b4d}Hi, {color}
> {color:#172b4d}We are using spark functionality to save the serialized model
> to disk . On windows platform we are seeing save of the serialized model is
> failing with the error: o288.save() failed. {color}
>
>
>
> !image-2020-06-22-18-19-32-236.png!
>
>
>
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