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https://issues.apache.org/jira/browse/IGNITE-16430?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aleksey Plekhanov updated IGNITE-16430:
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Description: Currently, we have code in
{{FilterSpoolMergeToSortedIndexSpoolRule}} that creates a sorted spool even if
the input collation is empty. In this case, collation is created by index
condition and the new sort node is inserted before the spool. But such a plan
can never be chosen as the best plan since when we calculate the cumulative
cost for the nested loop correlated join, we multiply left side rows count to
right side commutative cost not taking into account rewind cost. Currently,
cumulative cost for filter + spool = {{CPU: n + n}}, memory: {{0 + n}}, for
sorted spool + sort = CPU: {{log n+ n*log n}}, memory: {{n + n}}. So, the cost
for filter + spool will always be better than the cost for sorted spool + sort
and sorted spool + sort never can be chosen. But for example, for sorted spool
with sort rewind CPU cost is only {{log n}} since sorting is required only once
and rewind CPU cost of filter + spool is {{n + n}}. So, starting from some
iteration count cost of {{iterations * rewind cost + cumulative cost}} will be
better than {{iterantions * cumulative cost}}, and sorted spool + sort will be
chosen in this case. (was: Currently, we have code in
{{FilterSpoolMergeToSortedIndexSpoolRule}} that creates a sorted spool even if
the input collation is empty. In this case, collation is created by index
condition and the new sort node is inserted before the spool. But such a plan
can never be chosen as the best plan since when we calculate the cumulative
cost for the nested loop correlated join, we multiply left side rows count to
right side commutative cost not taking into account rewind cost. Currently,
cumulative cost for filter + spool = {{{}CPU: n + n{}}}, memory: {{{}0 + n{}}},
for sorted spool + sort = CPU: {{{}log(n)+ n*log(n){}}}, memory: {{{}n + n{}}}.
So, the cost for filter + spool will always be better than the cost for sorted
spool + sort and sorted spool + sort never can be chosen. But for example, for
sorted spool with sort rewind CPU cost is only {{log(n)}} since sorting is
required only once and rewind CPU cost of filter + spool is {{{}n + n{}}}. So,
starting from some iteration count cost of {{iterations * rewind cost +
cumulative cost}} will be better than {{{}iterantions * cumulative cost{}}},
and sorted spool + sort will be chosen in this case.)
> Calcite engine. Sorted index spool with sorting can be planned
> --------------------------------------------------------------
>
> Key: IGNITE-16430
> URL: https://issues.apache.org/jira/browse/IGNITE-16430
> Project: Ignite
> Issue Type: Improvement
> Reporter: Aleksey Plekhanov
> Priority: Major
>
> Currently, we have code in {{FilterSpoolMergeToSortedIndexSpoolRule}} that
> creates a sorted spool even if the input collation is empty. In this case,
> collation is created by index condition and the new sort node is inserted
> before the spool. But such a plan can never be chosen as the best plan since
> when we calculate the cumulative cost for the nested loop correlated join, we
> multiply left side rows count to right side commutative cost not taking into
> account rewind cost. Currently, cumulative cost for filter + spool = {{CPU: n
> + n}}, memory: {{0 + n}}, for sorted spool + sort = CPU: {{log n+ n*log n}},
> memory: {{n + n}}. So, the cost for filter + spool will always be better than
> the cost for sorted spool + sort and sorted spool + sort never can be chosen.
> But for example, for sorted spool with sort rewind CPU cost is only {{log n}}
> since sorting is required only once and rewind CPU cost of filter + spool is
> {{n + n}}. So, starting from some iteration count cost of {{iterations *
> rewind cost + cumulative cost}} will be better than {{iterantions *
> cumulative cost}}, and sorted spool + sort will be chosen in this case.
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