如何将数据帧列转换为序列 [英] How to convert a dataframe column to sequence
问题描述
我有一个数据框如下:
+-----+--------------------+
|LABEL| TERM|
+-----+--------------------+
| 4| inhibitori_effect|
| 4| novel_therapeut|
| 4| antiinflammator...|
| 4| promis_approach|
| 4| cell_function|
| 4| cell_line|
| 4| cancer_cell|
我想通过将所有术语作为序列创建一个新的数据框,以便我可以使用它们与Word2vec 。那就是:
I want to create a new dataframe by taking all terms as sequence so that I can use them with Word2vec. That is:
+-----+--------------------+
|LABEL| TERM|
+-----+--------------------+
| 4| inhibitori_effect, novel_therapeut,..., cell_line |
因此,我想应用这里给出的示例代码: https://spark.apache.org/docs/latest/ml-features.html#word2vec
As a result I want to apply this sample code as given here: https://spark.apache.org/docs/latest/ml-features.html#word2vec
到目前为止,我已经尝试将df转换为RDD并将其映射。然后我无法将其重新转换为df。
So far I have tried to convert df to RDD and map it. And then I could not manage to re-convert it to a df.
提前感谢。
编辑:
import org.apache.spark.{SparkContext, SparkConf}
import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.sql.SQLContext
val sc = new SparkContext(conf)
val sqlContext: SQLContext = new HiveContext(sc)
val df = sqlContext.load("jdbc",Map(
"url" -> "jdbc:oracle:thin:...",
"dbtable" -> "table"))
df.show(20)
df.groupBy($"label").agg(collect_list($"term").alias("term"))
推荐答案
您可以使用 collect_list
或 collect_set
函数:
import org.apache.spark.sql.functions.{collect_list, collect_set}
df.groupBy($"label").agg(collect_list($"term").alias("term"))
在Spark< 2.0它需要 HiveContext
,而在Spark 2.0+中,您必须在 SessionBuilder
中启用配置单元支持。请参阅在Spark SQL中使用collect_list和collect_set
In Spark < 2.0 it requires HiveContext
and in Spark 2.0+ you have to enable hive support in SessionBuilder
. See Use collect_list and collect_set in Spark SQL
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