org.apache.calcite.rel.rules.LoptOptimizeJoinRule Java Examples
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org.apache.calcite.rel.rules.LoptOptimizeJoinRule.
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Example #1
Source File: Programs.java From Bats with Apache License 2.0 | 5 votes |
/** Creates a program that invokes heuristic join-order optimization * (via {@link org.apache.calcite.rel.rules.JoinToMultiJoinRule}, * {@link org.apache.calcite.rel.rules.MultiJoin} and * {@link org.apache.calcite.rel.rules.LoptOptimizeJoinRule}) * if there are 6 or more joins (7 or more relations). */ public static Program heuristicJoinOrder( final Iterable<? extends RelOptRule> rules, final boolean bushy, final int minJoinCount) { return (planner, rel, requiredOutputTraits, materializations, lattices) -> { final int joinCount = RelOptUtil.countJoins(rel); final Program program; if (joinCount < minJoinCount) { program = ofRules(rules); } else { // Create a program that gathers together joins as a MultiJoin. final HepProgram hep = new HepProgramBuilder() .addRuleInstance(FilterJoinRule.FILTER_ON_JOIN) .addMatchOrder(HepMatchOrder.BOTTOM_UP) .addRuleInstance(JoinToMultiJoinRule.INSTANCE) .build(); final Program program1 = of(hep, false, DefaultRelMetadataProvider.INSTANCE); // Create a program that contains a rule to expand a MultiJoin // into heuristically ordered joins. // We use the rule set passed in, but remove JoinCommuteRule and // JoinPushThroughJoinRule, because they cause exhaustive search. final List<RelOptRule> list = Lists.newArrayList(rules); list.removeAll( ImmutableList.of(JoinCommuteRule.INSTANCE, JoinAssociateRule.INSTANCE, JoinPushThroughJoinRule.LEFT, JoinPushThroughJoinRule.RIGHT)); list.add(bushy ? MultiJoinOptimizeBushyRule.INSTANCE : LoptOptimizeJoinRule.INSTANCE); final Program program2 = ofRules(list); program = sequence(program1, program2); } return program.run( planner, rel, requiredOutputTraits, materializations, lattices); }; }
Example #2
Source File: Programs.java From calcite with Apache License 2.0 | 5 votes |
/** Creates a program that invokes heuristic join-order optimization * (via {@link org.apache.calcite.rel.rules.JoinToMultiJoinRule}, * {@link org.apache.calcite.rel.rules.MultiJoin} and * {@link org.apache.calcite.rel.rules.LoptOptimizeJoinRule}) * if there are 6 or more joins (7 or more relations). */ public static Program heuristicJoinOrder( final Iterable<? extends RelOptRule> rules, final boolean bushy, final int minJoinCount) { return (planner, rel, requiredOutputTraits, materializations, lattices) -> { final int joinCount = RelOptUtil.countJoins(rel); final Program program; if (joinCount < minJoinCount) { program = ofRules(rules); } else { // Create a program that gathers together joins as a MultiJoin. final HepProgram hep = new HepProgramBuilder() .addRuleInstance(FilterJoinRule.FILTER_ON_JOIN) .addMatchOrder(HepMatchOrder.BOTTOM_UP) .addRuleInstance(JoinToMultiJoinRule.INSTANCE) .build(); final Program program1 = of(hep, false, DefaultRelMetadataProvider.INSTANCE); // Create a program that contains a rule to expand a MultiJoin // into heuristically ordered joins. // We use the rule set passed in, but remove JoinCommuteRule and // JoinPushThroughJoinRule, because they cause exhaustive search. final List<RelOptRule> list = Lists.newArrayList(rules); list.removeAll( ImmutableList.of(JoinCommuteRule.INSTANCE, JoinAssociateRule.INSTANCE, JoinPushThroughJoinRule.LEFT, JoinPushThroughJoinRule.RIGHT)); list.add(bushy ? MultiJoinOptimizeBushyRule.INSTANCE : LoptOptimizeJoinRule.INSTANCE); final Program program2 = ofRules(list); program = sequence(program1, program2); } return program.run( planner, rel, requiredOutputTraits, materializations, lattices); }; }