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Posted to issues@spark.apache.org by "Bago Amirbekian (JIRA)" <ji...@apache.org> on 2017/10/10 02:51:03 UTC
[jira] [Updated] (SPARK-22232) Row objects in pyspark using the
`Row(**kwars)` syntax do not get serialized/deserialized properly
[ https://issues.apache.org/jira/browse/SPARK-22232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Bago Amirbekian updated SPARK-22232:
------------------------------------
Description:
The fields in a Row object created from a dict (ie `Row(**kwargs)`) should be accessed by field name, not by position because `Row.__new__` sorts the fields alphabetically by name. It seems like this promise is not being honored when these Row objects are shuffled. I've included an example to help reproduce the issue.
```
from pyspark.sql.types import *
from pyspark.sql import *
def toRow(i):
return Row(a="a", c=3.0, b=2)
schema = StructType([
StructField("a", StringType(), False),
StructField("c", FloatType(), False),
StructField("b", IntegerType(), False),
])
rdd = sc.parallelize(range(10)).repartition(2).map(lambda i: toRow(i))
# As long as we don't shuffle things work fine.
print rdd.toDF(schema).take(2)
# If we introduce a shuffle we have issues
print rdd.repartition(3).toDF(schema).take(2)
```
was:
The fields in a Row object created from a dict (ie `Row(**kwargs)`) should be accessed by field name, not by position because `Row.__new__` sorts the fields alphabetically by name. It seems like this promise is not being honored when these Row objects are shuffled. I've included an example to help reproduce the issue.
```
from pyspark.sql.types import *
from pyspark.sql import *
def toRow(i):
return Row(a="a", c=3.0, b=2)
schema = StructType([
StructField("a", StringType(), False),
StructField("c", FloatType(), False),
StructField("b", IntegerType(), False),
])
rdd = sc.parallelize(range(10)).repartition(2).map(lambda i: toRow(i))
# As long as we don't shuffle things work fine.
print rdd.toDF(schema).take(2)
# If we introduce a shuffle we have issues
print rdd.repartition(3).toDF(schema).take(2)
```
> Row objects in pyspark using the `Row(**kwars)` syntax do not get serialized/deserialized properly
> --------------------------------------------------------------------------------------------------
>
> Key: SPARK-22232
> URL: https://issues.apache.org/jira/browse/SPARK-22232
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.2.0
> Reporter: Bago Amirbekian
>
> The fields in a Row object created from a dict (ie `Row(**kwargs)`) should be accessed by field name, not by position because `Row.__new__` sorts the fields alphabetically by name. It seems like this promise is not being honored when these Row objects are shuffled. I've included an example to help reproduce the issue.
> ```
> from pyspark.sql.types import *
> from pyspark.sql import *
> def toRow(i):
> return Row(a="a", c=3.0, b=2)
> schema = StructType([
> StructField("a", StringType(), False),
> StructField("c", FloatType(), False),
> StructField("b", IntegerType(), False),
> ])
> rdd = sc.parallelize(range(10)).repartition(2).map(lambda i: toRow(i))
> # As long as we don't shuffle things work fine.
> print rdd.toDF(schema).take(2)
> # If we introduce a shuffle we have issues
> print rdd.repartition(3).toDF(schema).take(2)
> ```
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