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ASF GitHub Bot commented on FLINK-3225: --------------------------------------- Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/1559#discussion_r51245496 --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/plan/nodes/dataset/DataSetRel.scala --- @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.api.table.plan.nodes.dataset + +import org.apache.calcite.rel.RelNode +import org.apache.flink.api.java.DataSet +import org.apache.flink.api.table.Row + +trait DataSetRel extends RelNode { + + /** + * Translate the FlinkRelNode into Flink operator. + */ + def translateToPlan: DataSet[Row] --- End diff -- Right, I'll change that to `Any`. > Optimize logical Table API plans in Calcite > ------------------------------------------- > > Key: FLINK-3225 > URL: https://issues.apache.org/jira/browse/FLINK-3225 > Project: Flink > Issue Type: Sub-task > Components: Table API > Reporter: Fabian Hueske > Assignee: Fabian Hueske > > This task implements the optimization of logical Table API plans with Apache > Calcite. The input of the optimization process is a logical query plan > consisting of Calcite RelNodes. FLINK-3223 translates Table API queries into > this representation. > The result of this issue is an optimized logical plan. > Calcite's rule-based optimizer applies query rewriting and optimization > rules. For Batch SQL, we can use (a subset of) Calcite’s default optimization > rules. > For this issue we have to > - add the Calcite optimizer to the translation process > - select an appropriate set of batch optimization rules from Calcite’s > default rules. We can reuse the rules selected by Timo’s first SQL > implementation. -- This message was sent by Atlassian JIRA (v6.3.4#6332)