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https://issues.apache.org/jira/browse/SPARK-14083?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15220001#comment-15220001
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Josh Rosen commented on SPARK-14083:
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I'm aware of Soot but chose not to use it for a few reasons:

1. Its LGPL license likely prevents us from using it in Spark.
2. It doesn't publish releases to Maven Central.
3. While Soot provides higher-level analysis capabilities, I think that many of 
its features aren't necessary for the relatively simple types of analysis that 
we need to do, so I'd be slightly concerned that Soot might introduce an 
undesirable performance / complexity penalty.

> 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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