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https://issues.apache.org/jira/browse/SPARK-14083?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15222634#comment-15222634
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Kazuaki Ishizaki commented on SPARK-14083:
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Good point. On the other hand, should we follow JVM behavior exactly? We need 
to follow the semantics of Dataset. In my opinion, since Dataset is still 
experimental, we could update the semantics of Dataset. Dataset may be written 
in other languages such as Python, too.

According to my experiments to implement Java just-in-time compiler, too strict 
semantics may loose opportunities for optimizations while to throw an exception 
is useful for efficient debugging. 

> Analyze JVM bytecode and turn closures into Catalyst expressions
> ----------------------------------------------------------------
>
>                 Key: SPARK-14083
>                 URL: https://issues.apache.org/jira/browse/SPARK-14083
>             Project: Spark
>          Issue Type: New Feature
>          Components: SQL
>            Reporter: Reynold Xin
>
> One big advantage of the Dataset API is the type safety, at the cost of 
> performance due to heavy reliance on user-defined closures/lambdas. These 
> closures are typically slower than expressions because we have more 
> flexibility to optimize expressions (known data types, no virtual function 
> calls, etc). In many cases, it's actually not going to be very difficult to 
> look into the byte code of these closures and figure out what they are trying 
> to do. If we can understand them, then we can turn them directly into 
> Catalyst expressions for more optimized executions.
> Some examples are:
> {code}
> df.map(_.name)  // equivalent to expression col("name")
> ds.groupBy(_.gender)  // equivalent to expression col("gender")
> df.filter(_.age > 18)  // equivalent to expression GreaterThan(col("age"), 
> lit(18)
> df.map(_.id + 1)  // equivalent to Add(col("age"), lit(1))
> {code}
> The goal of this ticket is to design a small framework for byte code analysis 
> and use that to convert closures/lambdas into Catalyst expressions in order 
> to speed up Dataset execution. It is a little bit futuristic, but I believe 
> it is very doable. The framework should be easy to reason about (e.g. similar 
> to Catalyst).
> Note that a big emphasis on "small" and "easy to reason about". A patch 
> should be rejected if it is too complicated or difficult to reason about.



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