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package org.apache.spark.sql.catalyst.optimizer
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.catalyst.expressions.{Expression, Literal, SubqueryExpression}
import org.apache.spark.sql.catalyst.plans.logical.{DeleteFromTable, Filter, LocalRelation, LogicalPlan}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.catalyst.utils.PlanUtils.isIcebergRelation
import org.apache.spark.sql.execution.datasources.v2.DataSourceV2ScanRelation
// we have to optimize expressions used in delete/update before we can rewrite row-level operations
// otherwise, we will have to deal with redundant casts and will not detect noop deletes
// it is a temp solution since we cannot inject rewrite of row-level ops after operator optimizations
object OptimizeConditionsInRowLevelOperations extends Rule[LogicalPlan] {
override def apply(plan: LogicalPlan): LogicalPlan = plan transform {
case d @ DeleteFromTable(table, cond)
if !SubqueryExpression.hasSubquery(cond.getOrElse(Literal.TrueLiteral)) && isIcebergRelation(table) =>
val optimizedCond = optimizeCondition(cond.getOrElse(Literal.TrueLiteral), table)
d.copy(condition = Some(optimizedCond))
}
private def optimizeCondition(cond: Expression, table: LogicalPlan): Expression = {
val optimizer = SparkSession.active.sessionState.optimizer
optimizer.execute(Filter(cond, table)) match {
case Filter(optimizedCondition, _) => optimizedCondition
case _: LocalRelation => Literal.FalseLiteral
case _: DataSourceV2ScanRelation => Literal.TrueLiteral
case _ => cond
}
}
}