alamb commented on code in PR #17088:
URL: https://github.com/apache/datafusion/pull/17088#discussion_r2265213324
##########
datafusion/sqllogictest/test_files/errors.slt:
##########
@@ -168,8 +168,9 @@ CREATE TABLE tab0(col0 INTEGER, col1 INTEGER, col2 INTEGER);
statement ok
INSERT INTO tab0 VALUES(83,0,38);
-query error DataFusion error: Arrow error: Divide by zero error
+query I
Review Comment:
This is an interesting change -- we short circuited the evaluation and now
the error doesn't happen
THis happens in other areas and so I think this change is consistent with
other parts of DataFusion as well
##########
datafusion/optimizer/src/simplify_expressions/expr_simplifier.rs:
##########
@@ -1947,6 +1858,53 @@ fn has_common_conjunction(lhs: &Expr, rhs: &Expr) ->
bool {
iter_conjunction(rhs).any(|e| lhs_set.contains(&e) && !e.is_volatile())
}
+fn binary_op_null_on_null(op: Operator) -> bool {
Review Comment:
I recommend making this a function on `Operator` so it is more discoverable
-- similar to
https://docs.rs/datafusion/latest/datafusion/logical_expr/enum.Operator.html#method.is_numerical_operators
##########
datafusion/sqllogictest/test_files/predicates.slt:
##########
@@ -777,6 +777,52 @@ physical_plan
16)--------------------RepartitionExec: partitioning=RoundRobinBatch(4),
input_partitions=1
17)----------------------DataSourceExec: file_groups={1 group:
[[WORKSPACE_ROOT/datafusion/core/tests/tpch-csv/part.csv]]},
projection=[p_partkey, p_brand], file_type=csv, has_header=true
+# Simplification of a binary operator with a NULL value
+
+statement ok
+create table t(x int) as values (1), (2), (3);
+
+query TT
+EXPLAIN FORMAT INDENT SELECT x > NULL FROM t;
+----
+logical_plan
+01)Projection: Boolean(NULL) AS t.x > NULL
+02)--TableScan: t projection=[]
+physical_plan
+01)ProjectionExec: expr=[NULL as t.x > NULL]
+02)--DataSourceExec: partitions=1, partition_sizes=[1]
+
+query TT
+EXPLAIN FORMAT INDENT SELECT * FROM t WHERE x > NULL;
+----
+logical_plan EmptyRelation
+physical_plan EmptyExec
+
+query TT
+EXPLAIN FORMAT INDENT SELECT * FROM t WHERE x < 5 AND (10 * NULL < x);
+----
+logical_plan
+01)Filter: t.x < Int32(5) AND Boolean(NULL)
+02)--TableScan: t projection=[x]
+physical_plan
+01)CoalesceBatchesExec: target_batch_size=8192
+02)--FilterExec: x@0 < 5 AND NULL
Review Comment:
Isn't `<expr> AND NULL` always `NULL` too? -- maybe a potential future
optimization or I forget the boolean tristate logic rules in this case
##########
datafusion/sqllogictest/test_files/predicates.slt:
##########
@@ -777,6 +777,52 @@ physical_plan
16)--------------------RepartitionExec: partitioning=RoundRobinBatch(4),
input_partitions=1
17)----------------------DataSourceExec: file_groups={1 group:
[[WORKSPACE_ROOT/datafusion/core/tests/tpch-csv/part.csv]]},
projection=[p_partkey, p_brand], file_type=csv, has_header=true
+# Simplification of a binary operator with a NULL value
+
+statement ok
+create table t(x int) as values (1), (2), (3);
+
+query TT
+EXPLAIN FORMAT INDENT SELECT x > NULL FROM t;
+----
+logical_plan
+01)Projection: Boolean(NULL) AS t.x > NULL
+02)--TableScan: t projection=[]
+physical_plan
+01)ProjectionExec: expr=[NULL as t.x > NULL]
+02)--DataSourceExec: partitions=1, partition_sizes=[1]
+
+query TT
+EXPLAIN FORMAT INDENT SELECT * FROM t WHERE x > NULL;
+----
+logical_plan EmptyRelation
+physical_plan EmptyExec
+
+query TT
+EXPLAIN FORMAT INDENT SELECT * FROM t WHERE x < 5 AND (10 * NULL < x);
+----
+logical_plan
+01)Filter: t.x < Int32(5) AND Boolean(NULL)
+02)--TableScan: t projection=[x]
+physical_plan
+01)CoalesceBatchesExec: target_batch_size=8192
+02)--FilterExec: x@0 < 5 AND NULL
+03)----DataSourceExec: partitions=1, partition_sizes=[1]
+
+query TT
+EXPLAIN FORMAT INDENT SELECT * FROM t WHERE x < 5 OR (10 * NULL < x);
+----
+logical_plan
+01)Filter: t.x < Int32(5) OR Boolean(NULL)
+02)--TableScan: t projection=[x]
+physical_plan
+01)CoalesceBatchesExec: target_batch_size=8192
+02)--FilterExec: x@0 < 5 OR NULL
Review Comment:
Yes, the difference between Filters and Projections for null semantics has
come up before. I think currently there is no way to differentiate
There is a ticket that tracks this idea too:
- https://github.com/apache/datafusion/issues/6179
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