yashmayya commented on code in PR #15263:
URL: https://github.com/apache/pinot/pull/15263#discussion_r2000856836
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pinot-query-planner/src/test/resources/queries/JoinPlans.json:
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@@ -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 resultant 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))))`
So this unexpected value does seem to be because we're using the same max
and default value for scale and precision, but I'm not convinced that this is
an issue given the large values we're using. For reference, Calcite seems to be
using 0 as the default scale for `DECIMAL` types and max precision for default
precision (which is 19 in Calcite).
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