pyspark.sql.functions.vector_l2_distance#

pyspark.sql.functions.vector_l2_distance(left, right)[source]#

Returns the Euclidean (L2) distance between two float vectors. The vectors must have the same dimension.

Added in version 4.3.0.

Parameters:

leftColumn or column name: first vector column.
rightColumn or column name: second vector column.

Returns:

Column: L2 distance as a float value.

Examples

>>> from pyspark.sql import functions as sf
>>> from pyspark.sql.types import ArrayType, FloatType, StructType, StructField
>>> schema = StructType([StructField('a', ArrayType(FloatType())), StructField('b', ArrayType(FloatType()))])
>>> df = spark.createDataFrame([([1.0, 2.0, 3.0], [4.0, 5.0, 6.0])], schema)
>>> df.select(sf.vector_l2_distance('a', 'b')).first()[0]
5.196152...