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https://issues.apache.org/jira/browse/SPARK-8670?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen updated SPARK-8670:
------------------------------
Issue Type: Sub-task (was: Bug)
Parent: SPARK-9564
> Nested columns can't be referenced (but they can be selected)
> -------------------------------------------------------------
>
> Key: SPARK-8670
> URL: https://issues.apache.org/jira/browse/SPARK-8670
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 1.4.0, 1.4.1, 1.5.0
> Reporter: Nicholas Chammas
>
> This is strange and looks like a regression from 1.3.
> {code}
> import json
> daterz = [
> {
> 'name': 'Nick',
> 'stats': {
> 'age': 28
> }
> },
> {
> 'name': 'George',
> 'stats': {
> 'age': 31
> }
> }
> ]
> df = sqlContext.jsonRDD(sc.parallelize(daterz).map(lambda x: json.dumps(x)))
> df.select('stats.age').show()
> df['stats.age'] # 1.4 fails on this line
> {code}
> On 1.3 this works and yields:
> {code}
> age
> 28
> 31
> Out[1]: Column<stats.age AS age#2958L>
> {code}
> On 1.4, however, this gives an error on the last line:
> {code}
> +---+
> |age|
> +---+
> | 28|
> | 31|
> +---+
> ---------------------------------------------------------------------------
> IndexError Traceback (most recent call last)
> <ipython-input-1-04bd990e94c6> in <module>()
> 19
> 20 df.select('stats.age').show()
> ---> 21 df['stats.age']
> /path/to/spark/python/pyspark/sql/dataframe.pyc in __getitem__(self, item)
> 678 if isinstance(item, basestring):
> 679 if item not in self.columns:
> --> 680 raise IndexError("no such column: %s" % item)
> 681 jc = self._jdf.apply(item)
> 682 return Column(jc)
> IndexError: no such column: stats.age
> {code}
> This means, among other things, that you can't join DataFrames on nested
> columns.
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