问题
After exploding a nested structure I have a DataFrame with column names like this:
sales_data.metric1
sales_data.type.metric2
sales_data.type3.metric3
When performing a select I'm getting the error:
cannot resolve 'sales_data.metric1' given input columns: [sales_data.metric1, sales_data.type.metric2, sales_data.type3.metric3]
How should I select from the DataFrame so the column names are parsed correctly?
I've tried the following: the substrings after dots are extracted successfully. But since I also have columns without dots like date
- their names are getting removed completely.
var salesDf_new = salesDf
for(col <- salesDf .columns){
salesDf_new = salesDf_new.withColumnRenamed(col, StringUtils.substringAfterLast(col, "."))
}
I want to leave just metric1, metric2, metric3
回答1:
You can use backticks to select columns whose names include periods.
val df = (1 to 1000).toDF("column.a.b")
df.printSchema
// root
// |-- column.a.b: integer (nullable = false)
df.select("`column.a.b`")
Also, you can rename them easily like this. Basically starting with your current DataFrame, keep updating it with a new column name for each field and return the final result.
val df2 = df.columns.foldLeft(df)(
(myDF, col) => myDF.withColumnRenamed(col, col.replace(".", "_"))
)
EDIT: Get the last component
To rename with just the last name component, this regex will work:
val df2 = df.columns.foldLeft(df)(
(myDF, col) => myDF.withColumnRenamed(col, col.replaceAll(".+\\.([^.]+)$", "$1"))
)
EDIT 2: Get the last two components
This is a little more complicated, and there might be a cleaner way to write this, but here is a way that works:
val pattern = (
".*?" + // Lazy match leading chars so we ignore that bits we don't want
"([^.]+\\.)?" + // Optional 2nd to last group
"([^.]+)$" // Last group
)
val df2 = df.columns.foldLeft(df)(
(myDF, col) => myDF.withColumnRenamed(col, col.replaceAll(pattern, "$1$2"))
)
df2.printSchema
来源:https://stackoverflow.com/questions/51616666/scala-how-to-substring-column-names-after-the-last-dot