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https://issues.apache.org/jira/browse/SPARK-37348?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tim Schwab updated SPARK-37348:
-------------------------------
Description:
Because Spark is built on the JVM, in PySpark, F.lit(-1) % F.lit(2) returns -1.
However, the modulus is often desired instead of the remainder.
There is a [PMOD() function in Spark
SQL|https://spark.apache.org/docs/latest/api/sql/#pmod], but [not in
PySpark|https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql.html#functions].
So at the moment, the two options for getting the modulus is to use
F.expr("pmod(A, B)"), or create a helper function such as:
{code:java}
def pmod(dividend, divisor):
return F.when(dividend < 0, (dividend % divisor) +
divisor).otherwise(dividend % divisor){code}
Neither are optimal - pmod should be native to PySpark as it is in Spark SQL.
was:
Because Spark is built on the JVM, in PySpark, F.lit(-1) % F.lit(2) returns -1.
However, the modulus is often desired instead of the remainder.
There is a PMOD() function in Spark SQL, but not in PySpark. So at the moment,
the two options for getting the modulus is to use F.expr("pmod(A, B)"), or
create a helper function such as:
{code:java}
def pmod(dividend, divisor):
return F.when(dividend < 0, (dividend % divisor) +
divisor).otherwise(dividend % divisor){code}
Neither are optimal - pmod should be native to PySpark as it is in Spark SQL.
> PySpark pmod function
> ---------------------
>
> Key: SPARK-37348
> URL: https://issues.apache.org/jira/browse/SPARK-37348
> Project: Spark
> Issue Type: New Feature
> Components: PySpark
> Affects Versions: 3.2.0
> Reporter: Tim Schwab
> Priority: Minor
> Labels: newbie
>
> Because Spark is built on the JVM, in PySpark, F.lit(-1) % F.lit(2) returns
> -1. However, the modulus is often desired instead of the remainder.
>
> There is a [PMOD() function in Spark
> SQL|https://spark.apache.org/docs/latest/api/sql/#pmod], but [not in
> PySpark|https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql.html#functions].
> So at the moment, the two options for getting the modulus is to use
> F.expr("pmod(A, B)"), or create a helper function such as:
>
> {code:java}
> def pmod(dividend, divisor):
> return F.when(dividend < 0, (dividend % divisor) +
> divisor).otherwise(dividend % divisor){code}
>
>
> Neither are optimal - pmod should be native to PySpark as it is in Spark SQL.
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