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Converts a string into a map after splitting the text into key/value pairs using delimiters. Both pairDelim and keyValueDelim are treated as regular expressions.
Syntax
from pyspark.sql import functions as sf
sf.str_to_map(text, pairDelim=None, keyValueDelim=None)
Parameters
| Parameter | Type | Description |
|---|---|---|
text |
pyspark.sql.Column or str |
Input column or strings. |
pairDelim |
pyspark.sql.Column or str, optional |
Delimiter to use to split pairs. Default is comma (,). |
keyValueDelim |
pyspark.sql.Column or str, optional |
Delimiter to use to split key/value. Default is colon (:). |
Returns
pyspark.sql.Column: A new column of map type where each string in the original column is converted into a map.
Examples
Example 1: Using default delimiters
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a:1,b:2,c:3",)], ["e"])
df.select(sf.str_to_map(df.e)).show(truncate=False)
+------------------------+
|str_to_map(e, ,, :) |
+------------------------+
|{a -> 1, b -> 2, c -> 3}|
+------------------------+
Example 2: Using custom delimiters
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a=1;b=2;c=3",)], ["e"])
df.select(sf.str_to_map(df.e, sf.lit(";"), sf.lit("="))).show(truncate=False)
+------------------------+
|str_to_map(e, ;, =) |
+------------------------+
|{a -> 1, b -> 2, c -> 3}|
+------------------------+
Example 3: Using different delimiters for different rows
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a:1,b:2,c:3",), ("d=4;e=5;f=6",)], ["e"])
df.select(sf.str_to_map(df.e,
sf.when(df.e.contains(";"), sf.lit(";")).otherwise(sf.lit(",")),
sf.when(df.e.contains("="), sf.lit("=")).otherwise(sf.lit(":"))).alias("str_to_map")
).show(truncate=False)
+------------------------+
|str_to_map |
+------------------------+
|{a -> 1, b -> 2, c -> 3}|
|{d -> 4, e -> 5, f -> 6}|
+------------------------+
Example 4: Using a column of delimiters
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a:1,b:2,c:3", ","), ("d=4;e=5;f=6", ";")], ["e", "delim"])
df.select(sf.str_to_map(df.e, df.delim, sf.lit(":"))).show(truncate=False)
+---------------------------------------+
|str_to_map(e, delim, :) |
+---------------------------------------+
|{a -> 1, b -> 2, c -> 3} |
|{d=4 -> NULL, e=5 -> NULL, f=6 -> NULL}|
+---------------------------------------+
Example 5: Using a column of key/value delimiters
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a:1,b:2,c:3", ":"), ("d=4;e=5;f=6", "=")], ["e", "delim"])
df.select(sf.str_to_map(df.e, sf.lit(","), df.delim)).show(truncate=False)
+------------------------+
|str_to_map(e, ,, delim) |
+------------------------+
|{a -> 1, b -> 2, c -> 3}|
|{d -> 4;e=5;f=6} |
+------------------------+