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1）总结
1.创建 CSVProjectRule 继承 RelRule<CSVProjectRule.Config>
a）在 CSVProjectRule.Config 接口中实现匹配规则
Config DEFAULT = EMPTY.withOperandSupplier(b0 ->b0.operand(LogicalProject.class).anyInputs()).as(Config.class);
b）在 CSVProjectRule 实现类中，如果匹配上了规则，则进行转换
@Overridepublic void onMatch(RelOptRuleCall call) {final LogicalProject project = call.rel(0);final RelNode converted = convert(project);if (converted != null) {call.transformTo(converted);}}------------------------------------------------public RelNode convert(RelNode rel) {final LogicalProject project = (LogicalProject) rel;final RelTraitSet traitSet = project.getTraitSet();return new CSVProject(project.getCluster(), traitSet,project.getInput(), project.getProjects(),project.getRowType());}
2.创建转换后的RelNode 即 CSVProject
2）代码示例
CSVProjectRule
package cn.com.ptpress.cdm.optimization.RelBuilder.optimizer;import cn.com.ptpress.cdm.optimization.RelBuilder.csvRelNode.CSVProject;
import org.apache.calcite.plan.RelOptRuleCall;
import org.apache.calcite.plan.RelRule;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.logical.LogicalProject;public class CSVProjectRule extends RelRule<CSVProjectRule.Config> {@Overridepublic void onMatch(RelOptRuleCall call) {final LogicalProject project = call.rel(0);final RelNode converted = convert(project);if (converted != null) {call.transformTo(converted);}}/** Rule configuration. */public interface Config extends RelRule.Config {Config DEFAULT = EMPTY.withOperandSupplier(b0 ->b0.operand(LogicalProject.class).anyInputs()).as(Config.class);@Override default CSVProjectRule toRule() {return new CSVProjectRule(this);}}private CSVProjectRule(Config config) {super(config);}public RelNode convert(RelNode rel) {final LogicalProject project = (LogicalProject) rel;final RelTraitSet traitSet = project.getTraitSet();return new CSVProject(project.getCluster(), traitSet,project.getInput(), project.getProjects(),project.getRowType());}
}
CSVProjectRuleWithCost
package cn.com.ptpress.cdm.optimization.RelBuilder.optimizer;import cn.com.ptpress.cdm.optimization.RelBuilder.csvRelNode.CSVProject;
import cn.com.ptpress.cdm.optimization.RelBuilder.csvRelNode.CSVProjectWithCost;
import org.apache.calcite.plan.RelOptRuleCall;
import org.apache.calcite.plan.RelRule;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.logical.LogicalProject;public class CSVProjectRuleWithCost extends RelRule<CSVProjectRuleWithCost.Config> {@Overridepublic void onMatch(RelOptRuleCall call) {final LogicalProject project = call.rel(0);final RelNode converted = convert(project);if (converted != null) {call.transformTo(converted);}}/** Rule configuration. */public interface Config extends RelRule.Config {Config DEFAULT = EMPTY.withOperandSupplier(b0 ->b0.operand(LogicalProject.class).anyInputs()).as(Config.class);@Override default CSVProjectRuleWithCost toRule() {return new CSVProjectRuleWithCost(this);}}private CSVProjectRuleWithCost(Config config) {super(config);}public RelNode convert(RelNode rel) {final LogicalProject project = (LogicalProject) rel;final RelTraitSet traitSet = project.getTraitSet();return new CSVProjectWithCost(project.getCluster(), traitSet,project.getInput(), project.getProjects(),project.getRowType());}
}
CSVProject
package cn.com.ptpress.cdm.optimization.RelBuilder.csvRelNode;import com.google.common.collect.ImmutableList;
import org.apache.calcite.plan.RelOptCluster;
import org.apache.calcite.plan.RelOptCost;
import org.apache.calcite.plan.RelOptPlanner;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.core.Project;
import org.apache.calcite.rel.metadata.RelMetadataQuery;
import org.apache.calcite.rel.type.RelDataType;
import org.apache.calcite.rex.RexNode;import java.util.List;public class CSVProject extends Project {public CSVProject(RelOptCluster cluster, RelTraitSet traits, RelNode input, List<? extends RexNode> projects, RelDataType rowType) {super(cluster,traits, ImmutableList.of(),input,projects,rowType);}@Overridepublic Project copy(RelTraitSet traitSet, RelNode input, List<RexNode> projects, RelDataType rowType) {return new CSVProject(getCluster(),traitSet,input,projects,rowType);}@Overridepublic RelOptCost computeSelfCost(RelOptPlanner planner, RelMetadataQuery mq) {return planner.getCostFactory().makeZeroCost();}
}
CSVProjectWithCost
package cn.com.ptpress.cdm.optimization.RelBuilder.csvRelNode;import com.google.common.collect.ImmutableList;
import org.apache.calcite.plan.RelOptCluster;
import org.apache.calcite.plan.RelOptCost;
import org.apache.calcite.plan.RelOptPlanner;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.core.Project;
import org.apache.calcite.rel.metadata.RelMetadataQuery;
import org.apache.calcite.rel.type.RelDataType;
import org.apache.calcite.rex.RexNode;import java.util.List;public class CSVProjectWithCost extends Project{public CSVProjectWithCost(RelOptCluster cluster, RelTraitSet traits, RelNode input, List<? extends RexNode> projects, RelDataType rowType) {super(cluster,traits, ImmutableList.of(),input,projects,rowType);}@Overridepublic Project copy(RelTraitSet traitSet, RelNode input, List<RexNode> projects, RelDataType rowType) {return new CSVProjectWithCost(getCluster(),traitSet,input,projects,rowType);}@Overridepublic RelOptCost computeSelfCost(RelOptPlanner planner, RelMetadataQuery mq) {return planner.getCostFactory().makeInfiniteCost();}
}
SqlToRelNode
package cn.com.ptpress.cdm.optimization.RelBuilder.Utils;import cn.com.ptpress.cdm.ds.csv.CsvSchema;
import org.apache.calcite.config.CalciteConnectionConfigImpl;
import org.apache.calcite.config.CalciteConnectionProperty;
import org.apache.calcite.jdbc.CalciteSchema;
import org.apache.calcite.jdbc.JavaTypeFactoryImpl;
import org.apache.calcite.prepare.CalciteCatalogReader;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.calcite.sql.parser.SqlParser;
import org.apache.calcite.tools.Frameworks;import java.util.Properties;public class CatalogReaderUtil {public static CalciteCatalogReader createCatalogReader(SqlParser.Config parserConfig) {SchemaPlus rootSchema = Frameworks.createRootSchema(true);rootSchema.add("csv", new CsvSchema("data.csv"));return createCatalogReader(parserConfig, rootSchema);}public static CalciteCatalogReader createCatalogReader(SqlParser.Config parserConfig, SchemaPlus rootSchema) {Properties prop = new Properties();prop.setProperty(CalciteConnectionProperty.CASE_SENSITIVE.camelName(),String.valueOf(parserConfig.caseSensitive()));CalciteConnectionConfigImpl calciteConnectionConfig = new CalciteConnectionConfigImpl(prop);return new CalciteCatalogReader(CalciteSchema.from(rootSchema),CalciteSchema.from(rootSchema).path("csv"),new JavaTypeFactoryImpl(),calciteConnectionConfig);}
}
CatalogReaderUtil
package cn.com.ptpress.cdm.optimization.RelBuilder.Utils;import cn.com.ptpress.cdm.ds.csv.CsvSchema;
import org.apache.calcite.config.CalciteConnectionConfigImpl;
import org.apache.calcite.config.CalciteConnectionProperty;
import org.apache.calcite.jdbc.CalciteSchema;
import org.apache.calcite.jdbc.JavaTypeFactoryImpl;
import org.apache.calcite.prepare.CalciteCatalogReader;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.calcite.sql.parser.SqlParser;
import org.apache.calcite.tools.Frameworks;import java.util.Properties;public class CatalogReaderUtil {public static CalciteCatalogReader createCatalogReader(SqlParser.Config parserConfig) {SchemaPlus rootSchema = Frameworks.createRootSchema(true);rootSchema.add("csv", new CsvSchema("data.csv"));return createCatalogReader(parserConfig, rootSchema);}public static CalciteCatalogReader createCatalogReader(SqlParser.Config parserConfig, SchemaPlus rootSchema) {Properties prop = new Properties();prop.setProperty(CalciteConnectionProperty.CASE_SENSITIVE.camelName(),String.valueOf(parserConfig.caseSensitive()));CalciteConnectionConfigImpl calciteConnectionConfig = new CalciteConnectionConfigImpl(prop);return new CalciteCatalogReader(CalciteSchema.from(rootSchema),CalciteSchema.from(rootSchema).path("csv"),new JavaTypeFactoryImpl(),calciteConnectionConfig);}
}
PlannerTest
import cn.com.ptpress.cdm.optimization.RelBuilder.Utils.SqlToRelNode;
import cn.com.ptpress.cdm.optimization.RelBuilder.optimizer.CSVProjectRule;
import cn.com.ptpress.cdm.optimization.RelBuilder.optimizer.CSVProjectRuleWithCost;
import org.apache.calcite.plan.RelOptPlanner;
import org.apache.calcite.plan.RelOptUtil;
import org.apache.calcite.plan.hep.HepPlanner;
import org.apache.calcite.plan.hep.HepProgram;
import org.apache.calcite.plan.hep.HepProgramBuilder;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.rules.FilterJoinRule;
import org.apache.calcite.sql.parser.SqlParseException;
import org.junit.jupiter.api.Test;class PlannerTest {@Testpublic void testCustomRule() throws SqlParseException {final String sql = "select Id from data ";HepProgramBuilder programBuilder = HepProgram.builder();// 测试交换 CSVProjectRule 和 CSVProjectRuleWithCost 的顺序HepPlanner hepPlanner =new HepPlanner(programBuilder.addRuleInstance(CSVProjectRule.Config.DEFAULT.toRule()).addRuleInstance(CSVProjectRuleWithCost.Config.DEFAULT.toRule()).build());// HepPlanner hepPlanner =
// new HepPlanner(
// programBuilder
// .addRuleInstance(CSVProjectRuleWithCost.Config.DEFAULT.toRule())
// .addRuleInstance(CSVProjectRule.Config.DEFAULT.toRule())
// .build());RelNode relNode = SqlToRelNode.getSqlNode(sql, hepPlanner);System.out.println(RelOptUtil.toString(relNode));RelOptPlanner planner = relNode.getCluster().getPlanner();planner.setRoot(relNode);RelNode bestExp = planner.findBestExp();System.out.println(RelOptUtil.toString(bestExp));RelOptPlanner relOptPlanner = relNode.getCluster().getPlanner();relOptPlanner.addRule(CSVProjectRule.Config.DEFAULT.toRule());relOptPlanner.addRule(CSVProjectRuleWithCost.Config.DEFAULT.toRule());relOptPlanner.setRoot(relNode);RelNode exp = relOptPlanner.findBestExp();System.out.println(RelOptUtil.toString(exp));}/*** 未优化算子树结构* LogicalProject(ID=[$0])* LogicalFilter(condition=[>(CAST($0):INTEGER NOT NULL, 1)])* LogicalJoin(condition=[=($0, $3)], joinType=[inner])* LogicalTableScan(table=[[csv, data]])* LogicalTableScan(table=[[csv, data]])** 优化后接结果* LogicalProject(ID=[$0])* LogicalJoin(condition=[=($0, $3)], joinType=[inner])* LogicalFilter(condition=[>(CAST($0):INTEGER NOT NULL, 1)])* LogicalTableScan(table=[[csv, data]])* LogicalTableScan(table=[[csv, data]])*/@Testpublic void testHepPlanner() throws SqlParseException {final String sql = "select a.Id from data as a join data b on a.Id = b.Id where a.Id>1";HepProgramBuilder programBuilder = HepProgram.builder();HepPlanner hepPlanner =new HepPlanner(programBuilder.addRuleInstance(FilterJoinRule.FilterIntoJoinRule.Config.DEFAULT.toRule()).build());RelNode relNode = SqlToRelNode.getSqlNode(sql, hepPlanner);//未优化算子树结构System.out.println(RelOptUtil.toString(relNode));RelOptPlanner planner = relNode.getCluster().getPlanner();planner.setRoot(relNode);RelNode bestExp = planner.findBestExp();//优化后接结果System.out.println(RelOptUtil.toString(bestExp));}/*** 未转化Dag算子树结构* LogicalProject(Id=[$0], Name=[$1], Score=[$2])* LogicalFilter(condition=[=(CAST($0):INTEGER NOT NULL, 1)])* LogicalTableScan(table=[[csv, data]])** 转化为Dag图* Breadth-first from root: {* rel#8:HepRelVertex(rel#7:LogicalProject.(input=HepRelVertex#6,inputs=0..2)) = rel#7:LogicalProject.(input=HepRelVertex#6,inputs=0..2), rowcount=15.0, cumulative cost=130.0* rel#6:HepRelVertex(rel#5:LogicalFilter.(input=HepRelVertex#4,condition==(CAST($0):INTEGER NOT NULL, 1))) = rel#5:LogicalFilter.(input=HepRelVertex#4,condition==(CAST($0):INTEGER NOT NULL, 1)), rowcount=15.0, cumulative cost=115.0* rel#4:HepRelVertex(rel#1:LogicalTableScan.(table=[csv, data])) = rel#1:LogicalTableScan.(table=[csv, data]), rowcount=100.0, cumulative cost=100.0* }*/@Testpublic void testGraph() throws SqlParseException {final String sql = "select * from data where Id=1";HepProgramBuilder programBuilder = HepProgram.builder();HepPlanner hepPlanner =new HepPlanner(programBuilder.build());RelNode relNode = SqlToRelNode.getSqlNode(sql, hepPlanner);//未转化Dag算子树结构System.out.println("未转化Dag算子树结构");System.out.println(RelOptUtil.toString(relNode));//转化为Dag图System.out.println("转化为Dag图");hepPlanner.setRoot(relNode);//查看需要把log4j.properties级别改为trace}
}
data.csv
Id:VARCHAR Name:VARCHAR Score:INTEGER
1,小明,90
2,小红,98
3,小亮,95
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