Notiz
Zougrëff op dës Säit erfuerdert Autorisatioun. Dir kënnt probéieren, Iech unzemellen oder Verzeechnesser ze änneren.
Zougrëff op dës Säit erfuerdert Autorisatioun. Dir kënnt probéieren, Verzeechnesser ze änneren.
Returns the Euclidean (L2) distance between two float vectors. The vectors must have the same dimension.
For the corresponding Databricks SQL function, see vector_l2_distance function.
Syntax
from pyspark.sql import functions as dbf
dbf.vector_l2_distance(left=<left>, right=<right>)
Parameters
| Parameter | Type | Description |
|---|---|---|
left |
pyspark.sql.Column or column name |
First vector column. |
right |
pyspark.sql.Column or column name |
Second vector column. |
Returns
pyspark.sql.Column: L2 distance as a float value.
Examples
from pyspark.sql import functions as dbf
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(dbf.vector_l2_distance('a', 'b')).first()[0]
# 5.196152...