hqx871 commented on a change in pull request #2363:
URL: https://github.com/apache/calcite/pull/2363#discussion_r591577136
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File path: core/src/main/java/org/apache/calcite/rel/core/Sort.java
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@@ -124,11 +126,24 @@ public abstract Sort copy(RelTraitSet traitSet, RelNode
newInput,
@Override public @Nullable RelOptCost computeSelfCost(RelOptPlanner planner,
RelMetadataQuery mq) {
+ double rowCount = mq.getRowCount(this);
+ if (collation.getFieldCollations().isEmpty()) {
+ return planner.getCostFactory().makeCost(rowCount, 0, 0);
+ }
+ final double inCount = mq.getRowCount(input);
// Higher cost if rows are wider discourages pushing a project through a
// sort.
- final double rowCount = mq.getRowCount(this);
final double bytesPerRow = getRowType().getFieldCount() * 4;
Review comment:
I use log2 to replace logE, this obviously increase the cpu cost. and
the test JdbcTest.testAlmostBushy failed.
```
/** Just short of bushy. */
@Test void testAlmostBushy() {
CalciteAssert.that()
.with(CalciteAssert.Config.FOODMART_CLONE)
.query("select *\n"
+ "from \"sales_fact_1997\" as s\n"
+ "join \"customer\" as c\n"
+ " on s.\"customer_id\" = c.\"customer_id\"\n"
+ "join \"product\" as p\n"
+ " on s.\"product_id\" = p.\"product_id\"\n"
+ "where c.\"city\" = 'San Francisco'\n"
+ "and p.\"brand_name\" = 'Washington'")
.explainMatches("including all attributes ",
CalciteAssert.checkMaskedResultContains(""
+ "EnumerableMergeJoin(condition=[=($0, $38)],
joinType=[inner]): rowcount = 7.050660528307499E8, cumulative cost =
{7.656040129282498E8 rows, 5.0023949296644424E10 cpu, 0.0 io}\n"
+ " EnumerableSort(sort0=[$0], dir0=[ASC]): rowcount =
2.0087351932499997E7, cumulative cost = {4.044858016499999E7 rows,
5.0023896255644424E10 cpu, 0.0 io}\n"
+ " EnumerableMergeJoin(condition=[=($2, $8)],
joinType=[inner]): rowcount = 2.0087351932499997E7, cumulative cost =
{2.0361228232499994E7 rows, 3.232400376004586E7 cpu, 0.0 io}\n"
+ " EnumerableSort(sort0=[$2], dir0=[ASC]): rowcount =
86837.0, cumulative cost = {173674.0 rows, 3.168658076004586E7 cpu, 0.0 io}\n"
+ " EnumerableTableScan(table=[[foodmart2,
sales_fact_1997]]): rowcount = 86837.0, cumulative cost = {86837.0 rows,
86838.0 cpu, 0.0 io}\n"
+ " EnumerableCalc(expr#0..28=[{inputs}], expr#29=['San
Francisco':VARCHAR(30)], expr#30=[=($t9, $t29)], proj#0..28=[{exprs}],
$condition=[$t30]): rowcount = 1542.1499999999999, cumulative cost = {11823.15
rows, 637423.0 cpu, 0.0 io}\n"
+ " EnumerableTableScan(table=[[foodmart2,
customer]]): rowcount = 10281.0, cumulative cost = {10281.0 rows, 10282.0 cpu,
0.0 io}\n"
+ " EnumerableCalc(expr#0..14=[{inputs}],
expr#15=['Washington':VARCHAR(60)], expr#16=[=($t2, $t15)],
proj#0..14=[{exprs}], $condition=[$t16]): rowcount = 234.0, cumulative cost =
{1794.0 rows, 53041.0 cpu, 0.0 io}\n"
+ " EnumerableTableScan(table=[[foodmart2, product]]):
rowcount = 1560.0, cumulative cost = {1560.0 rows, 1561.0 cpu, 0.0 io}\n"));
}
```
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