org.apache.flink.table.planner.plan.rules.physical.batch.BatchPhysicalBoundedStreamScanRule.scala Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.flink.table.planner.plan.rules.physical.batch
import org.apache.flink.table.planner.plan.nodes.FlinkConventions
import org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalDataStreamTableScan
import org.apache.flink.table.planner.plan.nodes.physical.batch.BatchPhysicalBoundedStreamScan
import org.apache.flink.table.planner.plan.schema.DataStreamTable
import org.apache.calcite.plan.{RelOptRule, RelOptRuleCall}
import org.apache.calcite.rel.RelNode
import org.apache.calcite.rel.convert.ConverterRule
/**
* Rule that converts [[FlinkLogicalDataStreamTableScan]] to [[BatchPhysicalBoundedStreamScan]].
*/
class BatchPhysicalBoundedStreamScanRule
extends ConverterRule(
classOf[FlinkLogicalDataStreamTableScan],
FlinkConventions.LOGICAL,
FlinkConventions.BATCH_PHYSICAL,
"BatchPhysicalBoundedStreamScanRule") {
/**
* If the input is not a DataStreamTable, we want the TableScanRule to match instead
*/
override def matches(call: RelOptRuleCall): Boolean = {
val scan: FlinkLogicalDataStreamTableScan = call.rel(0)
val dataStreamTable = scan.getTable.unwrap(classOf[DataStreamTable[Any]])
dataStreamTable != null
}
def convert(rel: RelNode): RelNode = {
val scan = rel.asInstanceOf[FlinkLogicalDataStreamTableScan]
val newTrait = rel.getTraitSet.replace(FlinkConventions.BATCH_PHYSICAL)
new BatchPhysicalBoundedStreamScan(
rel.getCluster,
newTrait,
scan.getHints,
scan.getTable,
rel.getRowType)
}
}
object BatchPhysicalBoundedStreamScanRule {
val INSTANCE: RelOptRule = new BatchPhysicalBoundedStreamScanRule
}