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If there is only one argument, then this takes the natural logarithm of the argument. Supports Spark Connect.
For the corresponding Databricks SQL function, see log function.
Syntax
from pyspark.databricks.sql import functions as dbf
dbf.log(arg1=<arg1>, arg2=<arg2>)
Parameters
| Parameter | Type | Description |
|---|---|---|
arg1 |
pyspark.sql.Column, str or float |
base number or actual number (in this case base is e) |
arg2 |
pyspark.sql.Column, str or float, optional |
number to calculate logariphm for. |
Returns
pyspark.sql.Column: logariphm of given value.
Examples
from pyspark.databricks.sql import functions as dbf
df = spark.sql("SELECT * FROM VALUES (1), (2), (4) AS t(value)")
df.select("*", dbf.log(2.0, df.value)).show()
+-----+---------------+
|value|LOG(2.0, value)|
+-----+---------------+
| 1| 0.0|
| 2| 1.0|
| 4| 2.0|
+-----+---------------+
from pyspark.databricks.sql import functions as dbf
df = spark.sql("SELECT * FROM VALUES (1), (2), (0), (-1), (NULL) AS t(value)")
df.select("*", dbf.log(3.0, df.value)).show()
+-----+------------------+
|value| LOG(3.0, value)|
+-----+------------------+
| 1| 0.0|
| 2|0.6309297535714...|
| 0| NULL|
| -1| NULL|
| NULL| NULL|
+-----+------------------+