You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/12/15 01:42:58 UTC
[jira] [Closed] (SPARK-18783) ML StringIndexer does not work with
nested fields
[ https://issues.apache.org/jira/browse/SPARK-18783?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley closed SPARK-18783.
-------------------------------------
Resolution: Won't Fix
> ML StringIndexer does not work with nested fields
> -------------------------------------------------
>
> Key: SPARK-18783
> URL: https://issues.apache.org/jira/browse/SPARK-18783
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.0.0
> Reporter: manuel garrido
>
> Using StringIndexer.transform with a nested field (from parsing json data) results in the output dataframe not having the new column.
> {code}
> sample = [
> {'city': u'',
> 'device': {u'make': u'HTC',
> u'os': u'Android'}
> },
> {'city': u'Bangalore',
> 'device': {u'make': u'Xiaomi',
> u'os': u'Android'}
> },
> {'city': u'Overpelt',
> 'device': {u'make': u'Samsung',
> u'os': u'Android'}
> }
> ]
> sample_df = sc.parallelize(sample).toDF()
> # First we use a StringIndexer with a non nested field
> city_indexer = StringIndexer(inputCol="city", outputCol="cityIndex", handleInvalid="skip")
> city_indexed = city_indexer.fit(sample_df).transform(sample_df)
> print([i.asDict() for i in city_indexed.collect()])
> >>>[{'device': {u'make': u'HTC', u'os': u'Android'}, 'city': u'', 'cityIndex': 0.0}, {'device': {u'make': u'Xiaomi', u'os': u'Android'}, 'city': u'Bangalore', 'cityIndex': 2.0}, {'device': {u'make': u'Samsung', u'os': u'Android'}, 'city': u'Overpelt', 'cityIndex': 1.0}]
> # Now we try with a nested field
> os_indexer = StringIndexer(inputCol="device.os", outputCol="osIndex", handleInvalid="skip")
> os_indexed = os_indexer.fit(sample_df).transform(sample_df)
> print([i.asDict() for i in os_indexed.collect()])
> >>>[{'device': {u'make': u'HTC', u'os': u'Android'}, 'city': u''}, {'device': {u'make': u'Xiaomi', u'os': u'Android'}, 'city': u'Bangalore'}, {'device': {u'make': u'Samsung', u'os': u'Android'}, 'city': u'Overpelt'}] #===> we see the field osIndex is not showing up
> #If we rename the same field device.os as a flat field it works as expected
> os_indexer = StringIndexer(inputCol="device_os", outputCol="osIndex", handleInvalid="skip")
> os_indexed = os_indexer.fit(
> sample_df.withColumn('device_os', col('device.os'))
> ).transform(
> sample_df.withColumn('device_os', col('device.os'))
> )
> print([i.asDict() for i in os_indexed.collect()])
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org