PySpark：使用标记生成器

  • Z时代
  • 2024-01-10
  • 分类：问答

映射词

我开始我的旅程PySpark和我都停留在一个点，例： 我有这样的代码：（我把它从https://spark.apache.org/docs/2.1.0/ml-features.html）PySpark：使用标记生成器

from pyspark.ml.feature import Tokenizer, RegexTokenizer 
from pyspark.sql.functions import col, udf 
from pyspark.sql.types import IntegerType 
sentenceDataFrame = spark.createDataFrame([ 
    (0, "Hi I heard about Spark"), 
    (1, "I wish Java could use case classes"), 
    (2, "Logistic,regression,models,are,neat") 
], ["id", "sentence"]) 
tokenizer = Tokenizer(inputCol="sentence", outputCol="words") 
regexTokenizer = RegexTokenizer(inputCol="sentence", outputCol="words", pattern="\\W") 
# alternatively, pattern="\\w+", gaps(False) 
countTokens = udf(lambda words: len(words), IntegerType()) 
tokenized = tokenizer.transform(sentenceDataFrame) 
tokenized.select("sentence", "words")\ 
    .withColumn("tokens", countTokens(col("words"))).show(truncate=False) 
regexTokenized = regexTokenizer.transform(sentenceDataFrame) 
regexTokenized.select("sentence", "words") \ 
    .withColumn("tokens", countTokens(col("words"))).show(truncate=False)

而且我加入了这样的事情：

test = sqlContext.createDataFrame([ 
    (0, "spark"), 
    (1, "java"), 
    (2, "i") 
], ["id", "word"])

输出是：

id |sentence       |words          |tokens| 
+---+-----------------------------------+------------------------------------------+------+ 
|0 |Hi I heard about Spark    |[hi, i, heard, about, spark]    |5  | 
|1 |I wish Java could use case classes |[i, wish, java, could, use, case, classes]|7  | 
|2 |Logistic,regression,models,are,neat|[logistic, regression, models, are, neat] |5  |

上午I p ossible实现这样的事情： [ID从“测试”，编号从“regexTokenized”]

2, 0 
2, 1 
1, 1 
0, 1

从从那里符号化“字”可以映射“测试”我可以“regexTokenized”虎视眈眈的ID列表在这两个数据集？ 或者应该采取另一种解决方案？

在预先感谢您的任何帮助:)

回答：

explode和join：

from pyspark.sql.functions import explode 
(testTokenized.alias("train") 
    .select("id", explode("words").alias("word")) 
    .join(
     trainTokenized.select("id", explde("words").alias("word")).alias("test"), 
     "word"))

以上是 PySpark：使用标记生成器 的全部内容， 来源链接： utcz.com/qa/265360.html

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