map_from_entries
Transforms an array of key-value pair entries (structs with two fields) into a map. The first field of each entry is used as the key and the second field as the value in the resulting map column.
Syntax
Python
from pyspark.sql import functions as sf
sf.map_from_entries(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| Name of column or expression |
Returns
pyspark.sql.Column: A map created from the given array of entries.
Examples
Example 1: Basic usage of map_from_entries
Python
from pyspark.sql import functions as sf
df = spark.sql("SELECT array(struct(1, 'a'), struct(2, 'b')) as data")
df.select(sf.map_from_entries(df.data)).show()
Output
+----------------------+
|map_from_entries(data)|
+----------------------+
| {1 -> a, 2 -> b}|
+----------------------+
Example 2: map_from_entries with null values
Python
from pyspark.sql import functions as sf
df = spark.sql("SELECT array(struct(1, null), struct(2, 'b')) as data")
df.select(sf.map_from_entries(df.data)).show()
Output
+----------------------+
|map_from_entries(data)|
+----------------------+
| {1 -> NULL, 2 -> b}|
+----------------------+
Example 3: map_from_entries with a DataFrame
Python
from pyspark.sql import Row, functions as sf
df = spark.createDataFrame([([Row(1, "a"), Row(2, "b")],), ([Row(3, "c")],)], ['data'])
df.select(sf.map_from_entries(df.data)).show()
Output
+----------------------+
|map_from_entries(data)|
+----------------------+
| {1 -> a, 2 -> b}|
| {3 -> c}|
+----------------------+
Example 4: map_from_entries with empty array
Python
from pyspark.sql import functions as sf
from pyspark.sql.types import ArrayType, StringType, IntegerType, StructType, StructField
schema = StructType([
StructField("data", ArrayType(
StructType([
StructField("key", IntegerType()),
StructField("value", StringType())
])
), True)
])
df = spark.createDataFrame([([],)], schema=schema)
df.select(sf.map_from_entries(df.data)).show()
Output
+----------------------+
|map_from_entries(data)|
+----------------------+
| {}|
+----------------------+