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https://issues.apache.org/jira/browse/SPARK-13802?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16942906#comment-16942906
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Simeon H.K. Fitch commented on SPARK-13802:
-------------------------------------------
Is there a workaround to this problem? Ordering is important when encoders are
used to reify structs into Scala types, and not being able to specify the order
(without a lot of boilerplate schema work) results in Exceptions.
> Fields order in Row(**kwargs) is not consistent with Schema.toInternal method
> -----------------------------------------------------------------------------
>
> Key: SPARK-13802
> URL: https://issues.apache.org/jira/browse/SPARK-13802
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.0
> Reporter: Szymon Matejczyk
> Priority: Major
>
> When using Row constructor from kwargs, fields in the tuple underneath are
> sorted by name. When Schema is reading the row, it is not using the fields in
> this order.
> {code}
> from pyspark.sql import Row
> from pyspark.sql.types import *
> schema = StructType([
> StructField("id", StringType()),
> StructField("first_name", StringType())])
> row = Row(id="39", first_name="Szymon")
> schema.toInternal(row)
> Out[5]: ('Szymon', '39')
> {code}
> {code}
> df = sqlContext.createDataFrame([row], schema)
> df.show(1)
> +------+----------+
> | id|first_name|
> +------+----------+
> |Szymon| 39|
> +------+----------+
> {code}
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