MapFromEntries¶

Overview¶

The MapFromEntries expression converts an array of struct entries into a map. Each struct in the input array must contain exactly two fields, where the first field becomes the key and the second field becomes the value in the resulting map.

Syntax¶

map_from_entries(array_of_structs)

Arguments¶

Argument	Type	Description
child	Expression	An array of struct expressions where each struct has exactly two fields

Return Type¶

Returns a MapType where the key type corresponds to the first field type of the input struct and the value type corresponds to the second field type.

Supported Data Types¶

Input: Array of struct types with exactly two fields
The struct fields can be of any supported Spark SQL data type
Key types must be orderable/hashable types (cannot be complex types like arrays, maps, or structs)
Value types can be any Spark SQL data type

Algorithm¶

Takes an array of struct entries as input
Iterates through each struct element in the array
Extracts the first field of each struct as the map key
Extracts the second field of each struct as the map value
Constructs a new map from the key-value pairs
Returns the resulting map structure

Partitioning Behavior¶

How this expression affects partitioning:

Preserves partitioning as it operates on individual rows
Does not require shuffle operations
Can be evaluated locally on each partition

Edge Cases¶

Null handling: If the input array is null, returns null
Empty array: Returns an empty map
Null struct elements: Null entries in the array are skipped
Duplicate keys: Later entries with the same key will overwrite earlier entries
Struct validation: Runtime error if structs don't have exactly two fields

Code Generation¶

This expression supports Tungsten code generation for improved performance when processing large datasets with map transformations.

Examples¶

-- Convert array of structs to map
SELECT map_from_entries(array(struct(1, 'a'), struct(2, 'b')));
-- Result: {1:"a", 2:"b"}

-- Using with named struct fields
SELECT map_from_entries(array(struct(1 as id, 'Alice' as name), struct(2 as id, 'Bob' as name)));
-- Result: {1:"Alice", 2:"Bob"}

-- Empty array case
SELECT map_from_entries(array());
-- Result: {}

// DataFrame API usage
import org.apache.spark.sql.functions._

df.select(map_from_entries(
  array(
    struct(lit(1), lit("a")),
    struct(lit(2), lit("b"))
  )
))

// Using existing array column
df.select(map_from_entries(col("struct_array")))