Bemærk
Adgang til denne side kræver godkendelse. Du kan prøve at logge på eller ændre mapper.
Adgang til denne side kræver godkendelse. Du kan prøve at ændre mapper.
Returns the inner product (dot product) between two float vectors. The vectors must have the same dimension.
For the corresponding Databricks SQL function, see vector_inner_product function.
Syntax
from pyspark.sql import functions as dbf
dbf.vector_inner_product(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: Inner product 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_inner_product('a', 'b')).first()[0]
# 32.0