kaijianding opened a new pull request #11380:
URL: https://github.com/apache/druid/pull/11380
### Description
I noticed that `timestamp_floor("__time",'P1D',null,'Asia/Shanghai')` is
extremely slower(_**more than 3x in my case**_) than
`timestamp_floor("__time",'P1D','','Asia/Shanghai')` when I test this sql
```sql
select
sum("count") as c,
Floor(__time to DAY) as __time
from
"sms_normal"
where
__time >= TIMESTAMP '2021-05-19 00:00:00'
and __time < TIMESTAMP '2021-05-20 23:59:59'
group by
Floor(__time to DAY)
having
c>0
```
This is due to
```java
if (args.stream().skip(1).allMatch(Expr::isLiteral)) {
return new TimestampFloorExpr(args);
} else {
return new TimestampFloorDynamicExpr(args);
}
```
in `TimestampFloorExprMacro.java`
The "null" expr doesn't match `Expr::isLiteral()`, then
TimestampFloorDynamicExpr is used, and `TimestampFloorDynamicExpr.eval()`
create PeriodGranularity every time not like that only one time in
`TimestampFloorExpr`'s constructor.
```java
public ExprEval eval(final ObjectBinding bindings)
{
final PeriodGranularity granularity = computeGranularity(args,
bindings);
return
ExprEval.of(granularity.bucketStart(args.get(0).eval(bindings).asLong()));
}
```
This patch modifies the translation to
`timestamp_floor("__time",'P1D','','Asia/Shanghai')` rather than
`timestamp_floor("__time",'P1D',null,'Asia/Shanghai')`
<hr>
##### Key changed/added classes in this PR
* `TimeFloorOperatorConversion`
* `DruidExpression`
<hr>
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