gortiz commented on issue #12949:
URL: https://github.com/apache/pinot/issues/12949#issuecomment-2079590396
I was able to replicate a similar plan in MultiStageQuickStart using:
```sql
select
playerID,
numberOfGamesAsBatter,
playerName,
runs,
intentionalWalks,
CAST(hits as BIGINT) as Zeit
from baseballStats a
join dimBaseballTeams b on a.teamID = b.teamID
where not exists ( select 1 from baseballStats c where c.teamID = a.teamID
and c.yearID < a.yearID)
order by Zeit desc
```
Which generates
```
Execution Plan
LogicalSort(sort0=[$5], dir0=[DESC])
PinotLogicalSortExchange(distribution=[hash], collation=[[5 DESC]],
isSortOnSender=[false], isSortOnReceiver=[true])
LogicalProject(playerID=[$3], numberOfGamesAsBatter=[$2],
playerName=[$4], runs=[$5], intentionalWalks=[$1], Zeit=[CAST($0):BIGINT NOT
NULL])
LogicalFilter(condition=[IS NULL($11)])
LogicalJoin(condition=[AND(=($6, $9), =($7, $10))], joinType=[left])
PinotLogicalExchange(distribution=[hash[6, 7]])
LogicalJoin(condition=[=($6, $8)], joinType=[inner])
PinotLogicalExchange(distribution=[hash[6]])
LogicalProject(hits=[$9], intentionalWalks=[$12],
numberOfGamesAsBatter=[$15], playerID=[$16], playerName=[$17], runs=[$19],
teamID=[$25], yearID=[$27])
LogicalTableScan(table=[[default, baseballStats]])
PinotLogicalExchange(distribution=[hash[0]])
LogicalProject(teamID=[$3])
LogicalTableScan(table=[[default, dimBaseballTeams]])
PinotLogicalExchange(distribution=[hash[0, 1]])
LogicalAggregate(group=[{0, 1}], agg#0=[MIN($2)])
PinotLogicalExchange(distribution=[hash[0, 1]])
LogicalAggregate(group=[{0, 1}], agg#0=[MIN($2)])
LogicalProject(teamID0=[$2], yearID0=[$3], $f0=[true])
LogicalJoin(condition=[AND(=($0, $2), <($1, $3))],
joinType=[inner])
PinotLogicalExchange(distribution=[hash[0]])
LogicalProject(teamID=[$25], yearID=[$27])
LogicalTableScan(table=[[default, baseballStats]])
PinotLogicalExchange(distribution=[hash[0]])
LogicalAggregate(group=[{0, 1}])
PinotLogicalExchange(distribution=[hash[0, 1]])
LogicalAggregate(group=[{0, 1}])
LogicalJoin(condition=[=($0, $2)],
joinType=[inner])
PinotLogicalExchange(distribution=[hash[0]])
LogicalProject(teamID=[$25], yearID=[$27])
LogicalTableScan(table=[[default,
baseballStats]])
PinotLogicalExchange(distribution=[hash[0]])
LogicalProject(teamID=[$3])
LogicalTableScan(table=[[default,
dimBaseballTeams]])
```
But at lest with the numbers we have in this quickstart, the rows returned
by this version are smaller than the number returned without the where.
I'll take a look next week trying to understand the rules that have been
applied to generate that plan.
Meanwhile, can you try to use LAST_WITH_TIME instead? IICU your query, that
should be semantically equivalent to:
```
select a.acctuniquesessionid,
a.acctstatustype,
a.ts,
b.acctstatustype,
b.ts,
(cast(b.ts as BIGINT) - cast(a.ts as BIGINT)) / 1000 as Zeit
from (
select acctuniquesessionid,
LAST_WITH_TIME(acctstatustype, ts, "STRING") as acctstatustype,
MAX(ts) as ts
from radius_start
group by acctuniquesessionid
) as a
join radius_stop b on a.acctuniquesessionid = b.acctuniquesessionid
order by Zeit desc
```
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