本文整理汇总了Java中org.apache.calcite.rel.rules.JoinPushThroughJoinRule类的典型用法代码示例。如果您正苦于以下问题:Java JoinPushThroughJoinRule类的具体用法?Java JoinPushThroughJoinRule怎么用?Java JoinPushThroughJoinRule使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
JoinPushThroughJoinRule类属于org.apache.calcite.rel.rules包,在下文中一共展示了JoinPushThroughJoinRule类的4个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: getJoinPermRules
import org.apache.calcite.rel.rules.JoinPushThroughJoinRule; //导入依赖的package包/类
public static RuleSet getJoinPermRules(OptimizerRulesContext optimizerRulesContext) {
return new DrillRuleSet(ImmutableSet.<RelOptRule> builder().add( //
JoinPushThroughJoinRule.RIGHT,
JoinPushThroughJoinRule.LEFT
).build());
}
示例2: register
import org.apache.calcite.rel.rules.JoinPushThroughJoinRule; //导入依赖的package包/类
@Override
public void register(RelOptPlanner planner) {
// force clear the query context before traversal relational operators
OLAPContext.clearThreadLocalContexts();
// register OLAP rules
addRules(planner, kylinConfig.getCalciteAddRule());
planner.addRule(OLAPToEnumerableConverterRule.INSTANCE);
planner.addRule(OLAPFilterRule.INSTANCE);
planner.addRule(OLAPProjectRule.INSTANCE);
planner.addRule(OLAPAggregateRule.INSTANCE);
planner.addRule(OLAPJoinRule.INSTANCE);
planner.addRule(OLAPLimitRule.INSTANCE);
planner.addRule(OLAPSortRule.INSTANCE);
planner.addRule(OLAPUnionRule.INSTANCE);
planner.addRule(OLAPWindowRule.INSTANCE);
// Support translate the grouping aggregate into union of simple aggregates
planner.addRule(AggregateMultipleExpandRule.INSTANCE);
planner.addRule(AggregateProjectReduceRule.INSTANCE);
// CalcitePrepareImpl.CONSTANT_REDUCTION_RULES
planner.addRule(ReduceExpressionsRule.PROJECT_INSTANCE);
planner.addRule(ReduceExpressionsRule.FILTER_INSTANCE);
planner.addRule(ReduceExpressionsRule.CALC_INSTANCE);
planner.addRule(ReduceExpressionsRule.JOIN_INSTANCE);
// the ValuesReduceRule breaks query test somehow...
// planner.addRule(ValuesReduceRule.FILTER_INSTANCE);
// planner.addRule(ValuesReduceRule.PROJECT_FILTER_INSTANCE);
// planner.addRule(ValuesReduceRule.PROJECT_INSTANCE);
removeRules(planner, kylinConfig.getCalciteRemoveRule());
// since join is the entry point, we can't push filter past join
planner.removeRule(FilterJoinRule.FILTER_ON_JOIN);
planner.removeRule(FilterJoinRule.JOIN);
// since we don't have statistic of table, the optimization of join is too cost
planner.removeRule(JoinCommuteRule.INSTANCE);
planner.removeRule(JoinPushThroughJoinRule.LEFT);
planner.removeRule(JoinPushThroughJoinRule.RIGHT);
// keep tree structure like filter -> aggregation -> project -> join/table scan, implementOLAP() rely on this tree pattern
planner.removeRule(AggregateJoinTransposeRule.INSTANCE);
planner.removeRule(AggregateProjectMergeRule.INSTANCE);
planner.removeRule(FilterProjectTransposeRule.INSTANCE);
planner.removeRule(SortJoinTransposeRule.INSTANCE);
planner.removeRule(JoinPushExpressionsRule.INSTANCE);
planner.removeRule(SortUnionTransposeRule.INSTANCE);
planner.removeRule(JoinUnionTransposeRule.LEFT_UNION);
planner.removeRule(JoinUnionTransposeRule.RIGHT_UNION);
planner.removeRule(AggregateUnionTransposeRule.INSTANCE);
planner.removeRule(DateRangeRules.FILTER_INSTANCE);
planner.removeRule(SemiJoinRule.JOIN);
planner.removeRule(SemiJoinRule.PROJECT);
// distinct count will be split into a separated query that is joined with the left query
planner.removeRule(AggregateExpandDistinctAggregatesRule.INSTANCE);
// see Dec 26th email @ http://mail-archives.apache.org/mod_mbox/calcite-dev/201412.mbox/browser
planner.removeRule(ExpandConversionRule.INSTANCE);
}
示例3: heuristicJoinOrder
import org.apache.calcite.rel.rules.JoinPushThroughJoinRule; //导入依赖的package包/类
/** 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 new Program() {
public RelNode run(RelOptPlanner planner, RelNode rel,
RelTraitSet requiredOutputTraits,
List<RelOptMaterialization> materializations,
List<RelOptLattice> 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);
}
};
}
示例4: heuristicJoinOrder
import org.apache.calcite.rel.rules.JoinPushThroughJoinRule; //导入依赖的package包/类
/** 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 new Program() {
public RelNode run(RelOptPlanner planner, RelNode rel,
RelTraitSet requiredOutputTraits,
List<RelOptMaterialization> materializations,
List<RelOptLattice> 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);
}
};
}