yashmayya commented on code in PR #15263:
URL: https://github.com/apache/pinot/pull/15263#discussion_r2000856836
##########
pinot-query-planner/src/test/resources/queries/JoinPlans.json:
##########
@@ -405,10 +405,10 @@
"\nLogicalProject(col1=[$0])",
"\n LogicalJoin(condition=[AND(=($0, $3), =($1, $4), >($2, $5))],
joinType=[inner])",
"\n PinotLogicalExchange(distribution=[hash[0, 1]])",
- "\n LogicalProject(col1=[$0], col2=[$1], col4=[$3])",
+ "\n LogicalProject(col1=[$0], col2=[$1],
EXPR$0=[CAST($3):DECIMAL(1000, 982) NOT NULL])",
Review Comment:
The scale is 982 btw, the precision is 1000 here.
I found out that this is actually coming from type coercion during the SQL
-> Rel conversion phase, where the casts are being applied because the
comparison (`>`) is being made on different types. One is `DECIMAL(1000, 1000)`
(the `BigDecimal` column using default scale / precision) and the other is
`DECIMAL(19, 1)` (`0.5` is `DECIMAL(2, 1)` and we're multiplying it with a
`BIGINT` value). The logic that computes the precision and scale when coercing
two decimal types is here -
https://github.com/apache/calcite/blob/9b51667eebc825d5d3ece72cfcdb5d2efaa2d56f/core/src/main/java/org/apache/calcite/sql/type/SqlTypeFactoryImpl.java#L460-L498.
It's a little convoluted, but the resultant scale of 982 is arrived at like
this:
`Math.min(maxScale, Math.min(Math.max(s1, s2), maxPrecision -
Math.min(maxPrecision, Math.max(p1 - s1, p2 - s2))))`
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