dawidwys commented on a change in pull request #13413: URL: https://github.com/apache/flink/pull/13413#discussion_r490915183
########## File path: flink-examples/flink-examples-table/src/main/java/org/apache/flink/table/examples/java/basics/UpdatingTopCityExample.java ########## @@ -0,0 +1,193 @@ +/* + * 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.table.examples.java.basics; + +import org.apache.flink.table.api.EnvironmentSettings; +import org.apache.flink.table.api.Table; +import org.apache.flink.table.api.TableEnvironment; +import org.apache.flink.table.api.TableResult; +import org.apache.flink.types.Row; +import org.apache.flink.types.RowKind; +import org.apache.flink.util.CloseableIterator; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.ArrayList; +import java.util.List; + +/** + * Example for aggregating and ranking data using Flink SQL on updating (but bounded) streams. Review comment: nit: Is the `(but bounded)` note necessary or important for the example? Just wondering if it helps users understand the use case/example or introduces unnecessary distraction/additional concept to understand. ########## File path: flink-examples/flink-examples-table/src/main/java/org/apache/flink/table/examples/java/basics/UpdatingTopCityExample.java ########## @@ -0,0 +1,193 @@ +/* + * 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.table.examples.java.basics; + +import org.apache.flink.table.api.EnvironmentSettings; +import org.apache.flink.table.api.Table; +import org.apache.flink.table.api.TableEnvironment; +import org.apache.flink.table.api.TableResult; +import org.apache.flink.types.Row; +import org.apache.flink.types.RowKind; +import org.apache.flink.util.CloseableIterator; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.ArrayList; +import java.util.List; + +/** + * Example for aggregating and ranking data using Flink SQL on updating (but bounded) streams. + * + * <p>The example shows how to declare a table using SQL DDL for reading insert-only data and handling + * updating data. It should give a first impression about Flink SQL as a changelog processor. The example + * uses some streaming operations that produce a stream of updates. See the other examples for pure CDC + * processing and more complex operations. + * + * <p>In particular, the example shows how to + * <ul> + * <li>setup a {@link TableEnvironment}, + * <li>use the environment for creating a CSV file with example data, + * <li>aggregate the incoming INSERT changes, + * <li>compute a top-N result, + * <li>collect and materialize the updating stream locally. + * </ul> + * + * <p>The example executes two Flink jobs. The results are written to stdout. + * + * <p>Note: Make sure to include the SQL CSV format when submitting this example to Flink (e.g. via + * command line). This step is not necessary when executing the example in an IDE. + */ +public final class UpdatingTopCityExample { + + public static void main(String[] args) throws Exception { + // prepare the session + final EnvironmentSettings settings = EnvironmentSettings.newInstance() + .inStreamingMode() + .build(); + final TableEnvironment env = TableEnvironment.create(settings); + + // create an empty temporary CSV directory for this example + final String populationDirPath = createTemporaryDirectory(); + + // register a table in the catalog that points to the CSV file + env.executeSql( + "CREATE TABLE PopulationUpdates (" + + " city STRING," + + " state STRING," + + " update_year INT," + + " population_diff INT" + + ") WITH (" + + " 'connector' = 'filesystem'," + + " 'path' = '" + populationDirPath + "'," + + " 'format' = 'csv'" + + ")" + ); + + // insert some example data into the table + final TableResult insertionResult = env.executeSql( + "INSERT INTO PopulationUpdates VALUES" + + " ('Los Angeles', 'CA', 2013, 13106100), " + + " ('Los Angeles', 'CA', 2014, 72600), " + + " ('Los Angeles', 'CA', 2015, 72300), " + + " ('Chicago', 'IL', 2013, 9553270), " + + " ('Chicago', 'IL', 2014, 11340), " + + " ('Chicago', 'IL', 2015, -6730), " + + " ('Houston', 'TX', 2013, 6330660), " + + " ('Houston', 'TX', 2014, 172960), " + + " ('Houston', 'TX', 2015, 172940), " + + " ('Phoenix', 'AZ', 2013, 4404680), " + + " ('Phoenix', 'AZ', 2014, 86740), " + + " ('Phoenix', 'AZ', 2015, 89700), " + + " ('San Antonio', 'TX', 2013, 2280580), " + + " ('San Antonio', 'TX', 2014, 49180), " + + " ('San Antonio', 'TX', 2015, 50870), " + + " ('San Francisco', 'CA', 2013, 4521310), " + + " ('San Francisco', 'CA', 2014, 65940), " + + " ('San Francisco', 'CA', 2015, 62290), " + + " ('Dallas', 'TX', 2013, 6817520), " + + " ('Dallas', 'TX', 2014, 137740), " + + " ('Dallas', 'TX', 2015, 154020)" + ); + + // since all cluster operations of the Table API are executed asynchronously, + // we need wait until the insertion has been completed, Review comment: ```suggestion // we need to wait until the insertion has been completed, ``` ########## File path: flink-table/flink-table-planner-blink/src/main/scala/org/apache/flink/table/planner/plan/rules/logical/CorrelateSortToRankRule.scala ########## @@ -0,0 +1,186 @@ +/* + * 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.table.planner.plan.rules.logical + +import org.apache.flink.table.planner.calcite.FlinkRelBuilder +import org.apache.flink.table.runtime.operators.rank.{ConstantRankRange, RankType} + +import org.apache.calcite.plan.RelOptRule.{any, operand} +import org.apache.calcite.plan.{RelOptRule, RelOptRuleCall} +import org.apache.calcite.rel.RelCollations +import org.apache.calcite.rel.`type`.RelDataType +import org.apache.calcite.rel.core.{Aggregate, Correlate, Filter, JoinRelType, Project, Sort} +import org.apache.calcite.rex.{RexCall, RexCorrelVariable, RexFieldAccess, RexInputRef, RexLiteral, RexNode} +import org.apache.calcite.sql.SqlKind +import org.apache.calcite.util.ImmutableBitSet + +import java.util + +import scala.collection.JavaConversions._ + +/** + * Planner rule that rewrites sort correlation to a Rank. + * Typically, the following plan + * + * {{{ + * LogicalProject(state=[$0], name=[$1]) + * +- LogicalCorrelate(correlation=[$cor0], joinType=[inner], requiredColumns=[{0}]) + * :- LogicalAggregate(group=[{0}]) + * : +- LogicalProject(state=[$1]) + * : +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * +- LogicalSort(sort0=[$1], dir0=[DESC-nulls-last], fetch=[3]) + * +- LogicalProject(name=[$0], pop=[$2]) + * +- LogicalFilter(condition=[=($1, $cor0.state)]) + * +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * }}} + * + * <p>would be transformed to + * + * {{{ + * LogicalProject(state=[$0], name=[$1]) + * +- LogicalProject(state=[$1], name=[$0], pop=[$2]) + * +- LogicalRank(rankType=[ROW_NUMBER], rankRange=[rankStart=1, rankEnd=3], + * partitionBy=[$1], orderBy=[$2 DESC], select=[name=$0, state=$1, pop=$2]) + * +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * }}} + * + * <p>To match the Correlate, the LHS needs to be a global Aggregate on a scan, the RHS should + * be a Sort with an equal Filter predicate whose keys are same with the LHS grouping keys. + * + * <p>This rule can only be used in HepPlanner. + */ +class CorrelateSortToRankRule extends RelOptRule( + operand(classOf[Correlate], + operand(classOf[Aggregate], + operand(classOf[Project], any())), + operand(classOf[Sort], + operand(classOf[Project], + operand(classOf[Filter], any())))), + "CorrelateSortToRankRule") { + + override def matches(call: RelOptRuleCall): Boolean = { + val correlate: Correlate = call.rel(0) + if (correlate.getJoinType != JoinRelType.INNER) { + return false + } + val agg: Aggregate = call.rel(1) + if (agg.getAggCallList.size() > 0 + || agg.getGroupSets.size() > 1 + || agg.getGroupSet.cardinality() != 1) { + // only one group field is supported now + return false Review comment: Maybe I am missing something (probably I am), but why do we need that limit? From the first glance it looks very tailor made for the single example. ########## File path: flink-table/flink-table-planner-blink/src/test/scala/org/apache/flink/table/planner/runtime/stream/sql/RankITCase.scala ########## @@ -1305,4 +1308,50 @@ class RankITCase(mode: StateBackendMode) extends StreamingWithStateTestBase(mode assertEquals(expected2.sorted, sink2.getRetractResults.sorted) } + @Test + def testCorrelateSortToRank(): Unit = { + val citiesDataId = TestValuesTableFactory.registerData(TestData.citiesData) + tEnv.executeSql( + s""" + |CREATE TABLE cities ( + | name STRING NOT NULL, + | state STRING NOT NULL, + | pop INT NOT NULL + |) WITH ( + | 'connector' = 'values', + | 'data-id' = '$citiesDataId', + | 'changelog-mode' = 'I' + |) + |""".stripMargin) + + val query = + s""" + |SELECT state, name + |FROM + | (SELECT DISTINCT state FROM cities) states, + | LATERAL ( + | SELECT name, pop + | FROM cities + | WHERE state = states.state + | ORDER BY pop + | DESC LIMIT 3 + | ) + """.stripMargin + + val sink = new TestingRetractSink + tEnv.sqlQuery(query).toRetractStream[Row].addSink(sink).setParallelism(1) Review comment: nit: Can't we use Table#collect and assert lists of rows? ########## File path: flink-table/flink-table-planner-blink/src/main/scala/org/apache/flink/table/planner/plan/rules/logical/CorrelateSortToRankRule.scala ########## @@ -0,0 +1,186 @@ +/* + * 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.table.planner.plan.rules.logical + +import org.apache.flink.table.planner.calcite.FlinkRelBuilder +import org.apache.flink.table.runtime.operators.rank.{ConstantRankRange, RankType} + +import org.apache.calcite.plan.RelOptRule.{any, operand} +import org.apache.calcite.plan.{RelOptRule, RelOptRuleCall} +import org.apache.calcite.rel.RelCollations +import org.apache.calcite.rel.`type`.RelDataType +import org.apache.calcite.rel.core.{Aggregate, Correlate, Filter, JoinRelType, Project, Sort} +import org.apache.calcite.rex.{RexCall, RexCorrelVariable, RexFieldAccess, RexInputRef, RexLiteral, RexNode} +import org.apache.calcite.sql.SqlKind +import org.apache.calcite.util.ImmutableBitSet + +import java.util + +import scala.collection.JavaConversions._ + +/** + * Planner rule that rewrites sort correlation to a Rank. + * Typically, the following plan + * + * {{{ + * LogicalProject(state=[$0], name=[$1]) + * +- LogicalCorrelate(correlation=[$cor0], joinType=[inner], requiredColumns=[{0}]) + * :- LogicalAggregate(group=[{0}]) + * : +- LogicalProject(state=[$1]) + * : +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * +- LogicalSort(sort0=[$1], dir0=[DESC-nulls-last], fetch=[3]) + * +- LogicalProject(name=[$0], pop=[$2]) + * +- LogicalFilter(condition=[=($1, $cor0.state)]) + * +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * }}} + * + * <p>would be transformed to + * + * {{{ + * LogicalProject(state=[$0], name=[$1]) + * +- LogicalProject(state=[$1], name=[$0], pop=[$2]) + * +- LogicalRank(rankType=[ROW_NUMBER], rankRange=[rankStart=1, rankEnd=3], + * partitionBy=[$1], orderBy=[$2 DESC], select=[name=$0, state=$1, pop=$2]) + * +- LogicalTableScan(table=[[default_catalog, default_database, cities]]) + * }}} + * + * <p>To match the Correlate, the LHS needs to be a global Aggregate on a scan, the RHS should + * be a Sort with an equal Filter predicate whose keys are same with the LHS grouping keys. + * + * <p>This rule can only be used in HepPlanner. + */ +class CorrelateSortToRankRule extends RelOptRule( Review comment: nit: What about your own comment from https://github.com/apache/flink/pull/13291/files#r480880262 ;) ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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