基于Apache Spark中数组中的单词过滤DataFrame [英] Filter DataFrame based on words in array in Apache Spark

问题描述

我试图通过仅获取包含数组中的单词的行来过滤数据集.我正在使用 contains 方法，它适用于字符串但不适用于数组.下面是代码

I am trying to Filter a Dataset by getting only those rows that contains words in array. I am using contains method,it works for string but not working for array. Below is code

val dataSet = spark.read.option("header","true").option("inferschema","true").json(path).na.drop.cache()

val threats_path = spark.read.textFile("src/main/resources/cyber_threats").collect()

val newData = dataSet.select("*").filter(col("_source.raw_text").contains(threats_path)).show()

它不起作用，因为威胁路径是字符串数组并包含字符串的工作.任何帮助将不胜感激.

It is not working becuase threats_path is array of strings and contains work for string. Any help would be appreciated.

推荐答案

您可以在列上使用 isin udf

You can use isin udf on columns

它会像，

val threats_path = spark.read.textFile("src/main/resources/cyber_threats").collect()

val dataSet = ???

dataSet.where(col("_source.raw_text").isin(thread_path: _*))

注意，如果thread_paths的大小很大，这将对性能产生影响，因为collect和使用isin的过滤器.

Note if the size of thread_paths is big, this will have performance impact both because of collect and because of filter using isin.

我建议您使用 join 过滤器 dataSet 和 threats_path.它会像这样，

I'll suggest you to use filter dataSet with threats_path using join. It will go something like,

val dataSet = spark.read.option("header","true").option("inferschema","true").json(path).na.drop

val threats_path = spark.read.textFile("src/main/resources/cyber_threats")

val newData = threats_path.join(dataSet, col("_source.raw_text") === col("<col in threats_path >"), "leftouter").show()

希望能帮到你

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