如何将数据框列转换为序列

本文介绍了如何将数据框列转换为序列的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

限时送ChatGPT账号..

我有一个如下的数据框:

I have a dataframe as below:

+-----+--------------------+
|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来创建一个新的数据框，以便我可以将它们与 Word2vec 一起使用.即:

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，我想应用此处给出的示例代码:https://spark.apache/docs/latest/ml-features.html#word2vec

As a result I want to apply this sample code as given here: https://spark.apache/docs/latest/ml-features.html#word2vec

到目前为止，我已经尝试将 df 转换为 RDD 并进行映射.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.

提前致谢.

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:

You can use collect_list or collect_set functions:

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 并且在 Spark 2.0+ 中你必须在 SessionBuilder 中启用 hive 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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