spark-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Reynold Xin <r...@databricks.com>
Subject Re: [SQL] Purpose of RuntimeReplaceable unevaluable unary expressions?
Date Wed, 30 May 2018 18:10:11 GMT
SQL expressions?

On Wed, May 30, 2018 at 11:09 AM Jacek Laskowski <jacek@japila.pl> wrote:

> Hi,
>
> I've been exploring RuntimeReplaceable expressions [1] and have been
> wondering what their purpose is.
>
> Quoting the scaladoc [2]:
>
> > An expression that gets replaced at runtime (currently by the optimizer)
> into a different expression for evaluation. This is mainly used to provide
> compatibility with other databases.
>
> For example, ParseToTimestamp expression is a RuntimeReplaceable
> expression and it is replaced by Cast(left, TimestampType)
> or Cast(UnixTimestamp(left, format), TimestampType) per to_timestamp
> function (there are two variants).
>
> My question is why is this RuntimeReplaceable better than simply using the
> Casts as the implementation of to_timestamp functions?
>
> def to_timestamp(s: Column, fmt: String): Column = withExpr {
>   // pseudocode
>   Cast(UnixTimestamp(left, format), TimestampType)
> }
>
> What's wrong with the above implementation compared to the current one?
>
> [1]
> https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala#L275
>
> [2]
> https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala#L266-L267
>
> Pozdrawiam,
> Jacek Laskowski
> ----
> https://about.me/JacekLaskowski
> Mastering Spark SQL https://bit.ly/mastering-spark-sql
> Spark Structured Streaming https://bit.ly/spark-structured-streaming
> Mastering Kafka Streams https://bit.ly/mastering-kafka-streams
> Follow me at https://twitter.com/jaceklaskowski
>

Mime
View raw message