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8c2bf9769a
Added costs to all Exprs, which estimate the relative cost of evaluating an expression and all of its children. Costs are calculated during analysis. For now, these costs are intended as a simple way to order expressions from cheap to expensive, not necessarily to be a precise reflection of running times. In general, expressions that deal with variable length types like strings will have higher cost than those dealing with fixed length types like numbers and booleans. Additionally, expressions with complicated subexpressions will have higher cost than simpler expressions. Also added PlanNode.orderConjunctsByCost, which takes a list of Exprs and returns a new list sorted according to an estimate of the cheapest order to evaulate the conjuncts in, based on their cost and selectivity. The conjuncts are sorted by repeatedly iterating over them and choosing the conjunct that would result in the least total estimated work were it to be applied before the remaining conjuncts. Selectivities are exponentially backed off, and Exprs without selectivity estimates are given a reasonable default. Change-Id: I02279a26fbc6308ac5eb819d78345fc010469034 Reviewed-on: http://gerrit.cloudera.org:8080/2598 Reviewed-by: Thomas Tauber-Marshall <tmarshall@cloudera.com> Tested-by: Internal Jenkins
77 lines
3.2 KiB
Plaintext
77 lines
3.2 KiB
Plaintext
# Test implicit and explicit casts. Binary predicates containing an explicit cast
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# cannot be offered to the data source.
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select * from functional.alltypes_datasource
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where tinyint_col < 256 and
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float_col != 0 and
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cast(int_col as bigint) < 10
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---- PLAN
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00:SCAN DATA SOURCE [functional.alltypes_datasource]
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data source predicates: tinyint_col < 256
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predicates: float_col != 0, CAST(int_col AS BIGINT) < 10
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====
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# The first four predicates are in a form that can be offered to the data source
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# and the first and third will be accepted (it accepts every other conjunct).
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# The second and fourth will be evaluated by Impala. The negated predicates,
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# i.e. NOT <PREDICATE>, are not in a form able to be offered to the data source,
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# so they will always be evaluated by Impala.
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select * from functional.alltypes_datasource
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where 10 > int_col and
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5 > double_col and
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string_col != "Foo" and
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string_col != "Bar" and
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not true = bool_col and
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not 5.0 = double_col
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---- PLAN
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00:SCAN DATA SOURCE [functional.alltypes_datasource]
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data source predicates: 10 > int_col, string_col != 'Foo'
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predicates: 5 > double_col, NOT TRUE = bool_col, NOT 5.0 = double_col, string_col != 'Bar'
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====
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# The 3rd predicate is not in a form that can be offered to the data source so
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# the 4th will be offered and accepted instead.
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select * from functional.alltypes_datasource
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where int_col < 10 and
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double_col > 5 and
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string_col in ("Foo", "Bar") and
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bool_col != false
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---- PLAN
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00:SCAN DATA SOURCE [functional.alltypes_datasource]
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data source predicates: int_col < 10, bool_col != FALSE
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predicates: double_col > 5, string_col IN ('Foo', 'Bar')
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====
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# Tests that all predicates from the On-clause are applied (IMPALA-805)
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# and that slot equivalences are enforced at lowest possible plan node
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# for tables produced by a data source.
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select 1 from functional.alltypes_datasource a
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inner join functional.alltypes_datasource b
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# equivalence class
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on a.id = b.id and a.id = b.int_col and a.id = b.bigint_col
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and a.tinyint_col = b.id and a.smallint_col = b.id
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and a.int_col = b.id and a.bigint_col = b.id
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# redundant predicates to test minimal spanning tree of equivalent slots
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where a.tinyint_col = a.smallint_col and a.int_col = a.bigint_col
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---- PLAN
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02:HASH JOIN [INNER JOIN]
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| hash predicates: a.id = b.id
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| runtime filters: RF000 <- b.id
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|--01:SCAN DATA SOURCE [functional.alltypes_datasource b]
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|--predicates: b.id = b.int_col, b.id = b.bigint_col
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00:SCAN DATA SOURCE [functional.alltypes_datasource a]
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predicates: a.id = a.int_col, a.tinyint_col = a.smallint_col, a.int_col = a.bigint_col, a.id = a.tinyint_col
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====
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# Tests that <=>, IS DISTINCT FROM, and IS NOT DISTINCT FROM all can be offered to the
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# data source.
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select * from functional.alltypes_datasource
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where id <=> 1
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and bool_col <=> true
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and tinyint_col IS DISTINCT FROM 2
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and smallint_col IS DISTINCT FROM 3
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and int_col is not distinct from 4
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and bigint_col is not distinct from 5
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---- PLAN
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00:SCAN DATA SOURCE [functional.alltypes_datasource]
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data source predicates: id IS NOT DISTINCT FROM 1, tinyint_col IS DISTINCT FROM 2, int_col IS NOT DISTINCT FROM 4
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predicates: bool_col IS NOT DISTINCT FROM TRUE, smallint_col IS DISTINCT FROM 3, bigint_col IS NOT DISTINCT FROM 5
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====
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