This happens only when we have a "<" or "<=" filter on distribution
column of a range distributed table and that filter falls in between
two shards.
When the filter falls in between two shards:
If the filter is ">" or ">=", then UpperShardBoundary was
returning "upperBoundIndex - 1", where upperBoundIndex is
exclusive shard index used during binary seach.
This is expected since upperBoundIndex is an exclusive
index.
If the filter is "<" or "<=", then LowerShardBoundary was
returning "lowerBoundIndex + 1", where lowerBoundIndex is
inclusive shard index used during binary seach.
On the other hand, since lowerBoundIndex is an inclusive
index, we should just return lowerBoundIndex instead of
doing "+ 1". Before this commit, we were missing leftmost
shard in such queries.
* Remove useless conditional branches
The branch that we delete from UpperShardBoundary was obviously useless.
The other one in LowerShardBoundary became useless after we remove "+ 1"
from there.
This indeed is another proof of what & how we are fixing with this pr.
* Improve comments and add more
* Add some tests for upper bound calculation too
DESCRIPTION: Replace the query planner for the coordinator part with the postgres planner
Closes#2761
Citus had a simple rule based planner for the query executed on the query coordinator. This planner grew over time with the addigion of SQL support till it was getting close to the functionality of the postgres planner. Except the code was brittle and its complexity rose which made it hard to add new SQL support.
Given its resemblance with the postgres planner it was a long outstanding wish to replace our hand crafted planner with the well supported postgres planner. This patch replaces our planner with a call to postgres' planner.
Due to the functionality of the postgres planner we needed to support both projections and filters/quals on the citus custom scan node. When a sort operation is planned above the custom scan it might require fields to be reordered in the custom scan before returning the tuple (projection). The postgres planner assumes every custom scan node implements projections. Because we controlled the plan that was created we prevented reordering in the custom scan and never had implemented it before.
A same optimisation applies to having clauses that could have been where clauses. Instead of applying the filter as a having on the aggregate it will push it down into the plan which could reach a custom scan node.
For both filters and projections we have implemented them when tuples are read from the tuple store. If no projections or filters are required it will directly return the tuple from the tuple store. Otherwise it will loop tuples from the tuple store through the filter and projection until a tuple is found and returned.
Besides filters being pushed down a side effect of having quals that could have been a where clause is that a call to read intermediate result could be called before the first tuple is fetched from the custom scan. This failed because the intermediate result would only be pulled to the coordinator on the first tuple fetch. To overcome this problem we do run the distributed subplans now before we run the postgres executor. This ensures the intermediate result is present on the coordinator in time. We do account for total time instrumentation by removing the instrumentation before handing control to the psotgres executor and update the timings our self.
For future SQL support it is enough to create a valid query structure for the part of the query to be executed on the query coordinating node. As a utility we do serialise and print the query at debug level4 for engineers to inspect what kind of query is being planned on the query coordinator.
Fixes#271
This change sets ShardIds and JobIds for each test case. Before this change,
when a new test that somehow increments Job or Shard IDs is added, then
the tests after the new test should be updated.
ShardID and JobID sequences are set at the beginning of each file with the
following commands:
```
ALTER SEQUENCE pg_catalog.pg_dist_shardid_seq RESTART 290000;
ALTER SEQUENCE pg_catalog.pg_dist_jobid_seq RESTART 290000;
```
ShardIds and JobIds are multiples of 10000. Exceptions are:
- multi_large_shardid: shardid and jobid sequences are set to much larger values
- multi_fdw_large_shardid: same as above
- multi_join_pruning: Causes a race condition with multi_hash_pruning since
they are run in parallel.
This change fixes the problem with joins with VARCHAR columns. Prior to
this change, when we tried to do large table joins on varchar columns, we got
an error of the form:
ERROR: cannot perform local joins that involve expressions
DETAIL: local joins can be performed between columns only.
This is because we have a check in CheckJoinBetweenColumns() which requires the
join clause to have only 'Var' nodes (i.e. columns). Postgres adds a relabel t
ype cast to cast the varchar to text; hence the type of the node is not T_Var
and the join fails.
The fix involves calling strip_implicit_coercions() to the left and right
arguments so that RELABELTYPE is stripped to VAR.
Fixes#76.
All citusdb references in
- extension, binary names
- file headers
- all configuration name prefixes
- error/warning messages
- some functions names
- regression tests
are changed to be citus.