This change adds a script to programatically group all includes in a
specific order. The script was used as a one time invocation to group
and sort all includes throught our formatted code. The grouping is as
follows:
- System includes (eg. `#include<...>`)
- Postgres.h (eg. `#include "postgres.h"`)
- Toplevel imports from postgres, not contained in a directory (eg.
`#include "miscadmin.h"`)
- General postgres includes (eg . `#include "nodes/..."`)
- Toplevel citus includes, not contained in a directory (eg. `#include
"citus_verion.h"`)
- Columnar includes (eg. `#include "columnar/..."`)
- Distributed includes (eg. `#include "distributed/..."`)
Because it is quite hard to understand the difference between toplevel
citus includes and toplevel postgres includes it hardcodes the list of
toplevel citus includes. In the same manner it assumes anything not
prefixed with `columnar/` or `distributed/` as a postgres include.
The sorting/grouping is enforced by CI. Since we do so with our own
script there are not changes required in our uncrustify configuration.
PG16 compatibility - Part 6
Check out part 1 42d956888d
part 2 0d503dd5ac
part 3 907d72e60d
part 4 7c6b4ce103
part 5 6056cb2c29
This commit is in the series of PG16 compatibility commits.
It handles the Permission Info changes in PG16. See below:
The main issue lies in the following entries of PlannedStmt: {
rtable
permInfos
}
Each rtable has an int perminfoindex, and its actual permission info is
obtained through the following:
permInfos[perminfoindex]
We had crashes because perminfoindexes were not updated in the finalized
planned statement after distributed planner hook.
So, basically, everywhere we set a query's or planned statement's rtable
entry, we need to set the rteperminfos/permInfos accordingly.
Relevant PG commits:
a61b1f7482
a61b1f74823c9c4f79c95226a461f1e7a367764b
b803b7d132
b803b7d132e3505ab77c29acf91f3d1caa298f95
More PG16 compatibility commits are coming soon ...
1) For distributed tables that are not colocated.
2) When joining on a non-distribution column for colocated tables.
3) When merging into a distributed table using reference or citus-local tables as the data source.
This is accomplished primarily through the implementation of the following two strategies.
Repartition: Plan the source query independently,
execute the results into intermediate files, and repartition the files to
co-locate them with the merge-target table. Subsequently, compile a final
merge query on the target table using the intermediate results as the data
source.
Pull-to-coordinator: Execute the plan that requires evaluation at the coordinator,
run the query on the coordinator, and redistribute the resulting rows to ensure
colocation with the target shards. Direct the MERGE SQL operation to the worker
nodes' target shards, using the intermediate files colocated with the data as the
data source.
We should do the sublink conversations at the end of the recursive
planning because earlier steps might have transformed the query into a
shape that needs recursively planning the sublinks.
DESCRIPTION: Fixes early sublink check at recursive planner.
Related to PR https://github.com/citusdata/citus/pull/6650
* Fix UNION not being pushdown
Postgres optimizes column fields that are not needed in the output. We
were relying on these fields to understand if it is safe to push down a
union query.
This fix looks at the parse query, which has the original column fields
to detect if it is safe to push down a union query.
* Add more tests
* Simplify code and make it more robust
* Process varlevelsup > 0 in FindReferencedTableColumn
* Only look for outers vars in union path
* Add more comments
* Remove UNION ALL specific logic for pulling up childvars
Instead of sending NULL's over a network, we now convert the subqueries
in the form of:
SELECT t.a, NULL, NULL FROM (SELECT a FROM table)t;
And we recursively plan the inner part so that we don't send the NULL's
over network. We still need the NULLs in the outer subquery because we
currently don't have an easy way of updating all the necessary places in
the query.
Add some documentation for how the conversion is done
Baseinfo also has pushed down filters etc, so it makes more sense to use
BaseRestrictInfo to determine what columns have constant equality
filters.
Also RteIdentity is used for removing conversion candidates instead of
rteIndex.
AllDataLocallyAccessible and ContainsLocalTableSubqueryJoin are removed.
We can possibly remove ModifiesLocalTableWithRemoteCitusLocalTable as
well. Though this removal has a side effect that now when all the data
is locally available, we could still wrap a relation into a subquery, I
guess that should be resolved in the router planner itself.
Add more tests
When we wrap an RTE to subquery we are updating the variables varno's as
1, however we should also update the varno's of vars in quals.
Also some other small code quality improvements are done.
The previous algorithm was not consistent and it could convert different
RTEs based on the table orders in the query. Now we convert local tables
if there is a distributed table which doesn't have a unique index. So if
there are 4 tables, local1, local2, dist1, dist2_with_pkey then we will
convert local1 and local2 in `auto` mode. Converting a distributed table
is not that logical because as there is a distributed table without a
unique index, we will need to convert the local tables anyway. So
converting the distributed table with pkey is redundant.
We should not recursively plan an already routable plannable query. An
example of this is (SELECT * FROM local JOIN (SELECT * FROM dist) d1
USING(a));
So we let the recursive planner do all of its work and at the end we
convert the final query to to handle unsupported joins. While doing each
conversion, we check if it is router plannable, if so we stop.
Only consider range table entries that are in jointree
If a range table is not in jointree then there is no point in
considering that because we are trying to convert range table entries to
subqueries for join use case.
Check equality in quals
We want to recursively plan distributed tables only if they have an
equality filter on a unique column. So '>' and '<' operators will not
trigger recursive planning of distributed tables in local-distributed
table joins.
Recursively plan distributed table only if the filter is constant
If the filter is not a constant then the join might return multiple rows
and there is a chance that the distributed table will return huge data.
Hence if the filter is not constant we choose to recursively plan the
local table.
When doing local-distributed table joins we convert one of them to
subquery. The current policy is that we convert distributed tables to
subquery if it has a unique index on a column that has unique
index(primary key also has a unique index).
The logical planner cannot handle joins between local and distributed table.
Instead, we can recursively plan one side of the join and let the logical
planner handle the rest.
Our algorithm is a little smart, trying not to recursively plan distributed
tables, but favors local tables.
FindNodeCheck is not clear about what the function is doing. They are
renamed to FindNodeMatchingCheckFunctionXXX. Also for choosing elements in these
functions, CheckNodeFunc type is introduced.
The codebase is updated to use varattnosync and varnosyn and we defined
the macros for older versions. This way we can just remove the macros
when we drop an older version.
The error message when index has opclassopts is improved and the commit
from postgres side is also included for future reference.
Also some minor style related changes are applied.
As the new planner and pg_plan_query_compat methods expect the query
string as well, macros are defined to be compatible in different
versions of postgres.
Relevant commit on Postgres:
6aba63ef3e606db71beb596210dd95fa73c44ce2
Command on Postgres:
git log --all --grep="pg_plan_query"
Onur Tirtir
Nils Dijk
Naisila Puka
Teja Mupparti
aykut-bozkurt
Marco Slot
Onder Kalaci
Jeff Davis
Halil Ozan Akgul
SaitTalhaNisanci
Marco Slot