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Aggregate function: returns the element-wise sum of float vectors in a group. All vectors must have the same dimension.
For the corresponding Databricks SQL function, see vector_sum aggregate function.
Syntax
from pyspark.sql import functions as dbf
dbf.vector_sum(col=<col>)
Parameters
| Parameter | Type | Description |
|---|---|---|
col |
pyspark.sql.Column or column name |
Input vector column. |
Returns
pyspark.sql.Column: The element-wise sum vector as an array of floats.
Examples
from pyspark.sql import functions as dbf
from pyspark.sql.types import ArrayType, FloatType, StructType, StructField
schema = StructType([StructField('v', ArrayType(FloatType()))])
df = spark.createDataFrame([([1.0, 2.0],), ([3.0, 4.0],)], schema)
df.select(dbf.vector_sum('v')).first()[0]
# [4.0, 6.0]