scala> spark.range(1).select(lit(3) > 2).explain(true)
...
TRACE SparkOptimizer:
=== Applying Rule org.apache.spark.sql.catalyst.optimizer.ConstantFolding ===
!Project [(3 > 2) AS (3 > 2)#3] Project [true AS (3 > 2)#3]
+- Range (0, 1, step=1, splits=Some(8)) +- Range (0, 1, step=1, splits=Some(8))
scala> spark.range(1).select('id + 'id > 0).explain(true)
...
TRACE SparkOptimizer:
=== Applying Rule org.apache.spark.sql.catalyst.optimizer.ConstantFolding ===
!Project [((id#7L + id#7L) > cast(0 as bigint)) AS ((id + id) > 0)#10] Project [((id#7L + id#7L) > 0) AS ((id + id) > 0)#10]
+- Range (0, 1, step=1, splits=Some(8)) +- Range (0, 1, step=1, splits=Some(8))ConstantFolding Logical Optimization
ConstantFolding is a base logical optimization that replaces expressions that can be statically evaluated with their equivalent literal values.
ConstantFolding is part of the Operator Optimization before Inferring Filters fixed-point batch in the standard batches of the Catalyst Optimizer.
ConstantFolding is simply a Catalyst rule for transforming logical plans, i.e. Rule[LogicalPlan].
Executing Rule — apply Method
apply(plan: LogicalPlan): LogicalPlan|
Note
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apply is part of the Rule Contract to execute (apply) a rule on a TreeNode (e.g. LogicalPlan).
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apply…FIXME