本文介绍了使用正则表达式查找字符串中的特定字符的处理方法,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
我有这些样本值
prm_2020 P02 United Kingdom London 2 for 2
prm_2020 P2 United Kingdom London 2 for 2
prm_2020 P10 United Kingdom London 2 for 2
prm_2020 P11 United Kingdom London 2 for 2
需要找到这样的P2,P02,P11,p06,p05,并尝试在数据块中使用Regexp_extract函数.努力寻找正确的表达方式.一旦找到P10,字符串中的p6,我需要将数字放在名为ID的新列中
Need to find P2, P02, P11,p06,p05 like this, trying to use Regexp_extract function in databricks. struggling to find the correct expression. Once i find P10, p6 from string i need to put numbers in new column called ID
select distinct
promo_name
,regexp_extract(promo_name, '(?<=p\d+\s+)P\d+') as regexp_id
from stock
where promo_name is not null
select distinct
promo_name
,regexp_extract(promo_name, 'P[0-9]+') as regexp_id
from stock
where promo_name is not null
两者都会产生错误
推荐答案
函数 regexp_extract
将使用3个参数.
- 列值
- 正则表达式模式
- 组索引
def regexp_extract(e: org.apache.spark.sql.Column,exp: String,groupIdx: Int): org.apache.spark.sql.Column
您缺少 regexp_extract
函数中的最后一个参数.
You are missing last parameter in regexp_extract
function.
检查以下代码.
scala> df.show(truncate=False)
+------------------------------------------+
|data |
+------------------------------------------+
|prm_2020 P02 United Kingdom London 2 for 2|
|prm_2020 P2 United Kingdom London 2 for 2 |
|prm_2020 P10 United Kingdom London 2 for 2|
|prm_2020 P11 United Kingdom London 2 for 2|
+------------------------------------------+
df
.withColumn("parsed_data",regexp_extract(col("data"),"(P[0-9]*)",0))
.show(truncate=False)
+------------------------------------------+-----------+
|data |parsed_data|
+------------------------------------------+-----------+
|prm_2020 P02 United Kingdom London 2 for 2|P02 |
|prm_2020 P2 United Kingdom London 2 for 2 |P2 |
|prm_2020 P10 United Kingdom London 2 for 2|P10 |
|prm_2020 P11 United Kingdom London 2 for 2|P11 |
+------------------------------------------+-----------+
df.createTempView("tbl")
spark
.sql("select data,regexp_extract(data,'(P[0-9]*)',0) as parsed_data from tbl")
.show(truncate=False)
+------------------------------------------+-----------+
|data |parsed_data|
+------------------------------------------+-----------+
|prm_2020 P02 United Kingdom London 2 for 2|P02 |
|prm_2020 P2 United Kingdom London 2 for 2 |P2 |
|prm_2020 P10 United Kingdom London 2 for 2|P10 |
|prm_2020 P11 United Kingdom London 2 for 2|P11 |
+------------------------------------------+-----------+
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