We acquire distributed lock on all mx nodes for truncated
tables before actually doing truncate operation.
This is needed for distributed serialization of the truncate
command without causing a deadlock.
Reason for the failure is that PG11 introduced a new relation kind
RELKIND_PARTITIONED_INDEX to be used for partitioned indices.
We expanded our check to cover that case.
Make sure that the coordinator sends the commands when the search
path synchronised with the coordinator's search_path. This is only
important when Citus sends the commands that are directly relayed
to the worker nodes. For example, the deparsed DLL commands or
queries always adds schema qualifications to the queries. So, they
do not require this change.
When a hash distributed table have a foreign key to a reference
table, there are few restrictions we have to apply in order to
prevent distributed deadlocks or reading wrong results.
The necessity to apply the restrictions arise from cascading
nature of foreign keys. When a foreign key on a reference table
cascades to a distributed table, a single operation over a single
connection can acquire locks on multiple shards of the distributed
table. Thus, any parallel operation on that distributed table, in the
same transaction should not open parallel connections to the shards.
Otherwise, we'd either end-up with a self-distributed deadlock or
read wrong results.
As briefly described above, the restrictions that we apply is done
by tracking the distributed/reference relation accesses inside
transaction blocks, and act accordingly when necessary.
The two main rules are as follows:
- Whenever a parallel distributed relation access conflicts
with a consecutive reference relation access, Citus errors
out
- Whenever a reference relation access is followed by a
conflicting parallel relation access, the execution mode
is switched to sequential mode.
There are also some other notes to mention:
- If the user does SET LOCAL citus.multi_shard_modify_mode
TO 'sequential';, all the queries should simply work with
using one connection per worker and sequentially executing
the commands. That's obviously a slower approach than Citus'
usual parallel execution. However, we've at least have a way
to run all commands successfully.
- If an unrelated parallel query executed on any distributed
table, we cannot switch to sequential mode. Because, the essense
of sequential mode is using one connection per worker. However,
in the presence of a parallel connection, the connection manager
picks those connections to execute the commands. That contradicts
with our purpose, thus we error out.
- COPY to a distributed table cannot be executed in sequential mode.
Thus, if we switch to sequential mode and COPY is executed, the
operation fails and there is currently no way of implementing that.
Note that, when the local table is not empty and create_distributed_table
is used, citus uses COPY internally. Thus, in those cases,
create_distributed_table() will also fail.
- There is a GUC called citus.enforce_foreign_key_restrictions
to disable all the checks. We added that GUC since the restrictions
we apply is sometimes a bit more restrictive than its necessary.
The user might want to relax those. Similarly, if you don't have
CASCADEing reference tables, you might consider disabling all the
checks.
-[x] drop constraint
-[x] drop column
-[x] alter column type
-[x] truncate
are sequentialized if there is a foreign constraint from
a distributed table to a reference table on the affected relations
by the above commands.
Make sure that intermediate results use a connection that is
not associated with any placement. That is useful in two ways:
- More complex queries can be executed with CTEs
- Safely use the same connections when there is a foreign key
to reference table from a distributed table, which needs to
use the same connection for modifications since the reference
table might cascade to the distributed table.
We're relying on multi_shard_modify_mode GUC for real-time SELECTs.
The name of the GUC is unfortunate, but, adding one more GUC
(or renaming the GUC) would make the UX even worse. Given that this
mode is mostly important for transaction blocks that involve modification
/DDL queries along with real-time SELECTs, we can live with the confusion.
After this commit DDL commands honour `citus.multi_shard_modify_mode`.
We preferred using the code-path that executes single task router
queries (e.g., ExecuteSingleModifyTask()) in order not to invent
a new executor that is only applicable for DDL commands that require
sequential execution.
utilityStmt sometimes (such as when it's inside of a plpgsql function)
comes from a cached plan, which is kept in a child of the
CacheMemoryContext. When we naively call copyObject we're copying it into
a statement-local context, which corrupts the cached plan when it's
thrown away.
- changes in ruleutils_11.c is reflected
- vacuum statement api change is handled. We now allow
multi-table vacuum commands.
- some other function header changes are reflected
- api conflicts between PG11 and earlier versions
are handled by adding shims in version_compat.h
- various regression tests are fixed due output and
functionality in PG1
- no change is made to support new features in PG11
they need to be handled by new commit
Without this change multi_real_time_transaction blocks forever (on
Windows) in the block where it repeatedly calls pg_advisory_lock(15).
This happens because the deadlock detector tries to cancel the backend
but the backend never processes that signal.
We recently added partitionin support to Citus MX. We should not execute
DROP table commands from MX workers but at the moment we try to execute
such commands for partitioned tables. This PR fixes that problem by
adding check.
Previously, we prevented creation of partitioned tables on Citus MX.
We decided to not focus on this feature until there is a need. Since
now there are requests for this feature, we are implementing support
for partitioned tables on Citus MX.
After this change all the logic related to shard data fetch logic
will be removed. Planner won't plan any ShardFetchTask anymore.
Shard fetch related steps in real time executor and task-tracker
executor have been removed.
This commit checks the connection status right after any IO happens
on the socket.
This is necessary since before this commit we didn't pass any information
to the higher level functions whether we're done with the connection
(e.g., no IO required anymore) or an errors happened during the IO.
PostgreSQL implements support for several relation kinds in a single
statement, such as in the AlterTableStmt case, which supports both tables
and indexes and more (see ATExecSetRelOptions in PostgreSQL source code file
src/backend/commands/tablecmds.c for an example of that).
As a consequence, this patch implements support for setting and resetting
storage parameters on both relation kinds.
The command is now distributed among the shards when the table is
distributed. To that effect, we fill in the DDLJob's targetRelationId with
the OID of the table for which the index is defined, rather than the OID of
the index itself.
The implementation was already mostly in place, but the code was protected
by a principled check against the operation. Turns out there's a nasty
concurrency bug though with long identifier names, much as in #1664.
To prevent deadlocks from happening, we could either review the DDL
transaction management in shards and placements, or we can simply reject
names with (NAMEDATALEN - 1) chars or more — that's because of the
PostgreSQL array types being created with a one-char prefix: '_'.
This commit introduces a new GUC to limit the intermediate
result size which we handle when we use read_intermediate_result
function for CTEs and complex subqueries.
Postgres provides OS agnosting formatting macros for
formatting 64 bit numbers. Replaced %ld %lu with
INT64_FORMAT and UINT64_FORMAT respectively.
Also found some incorrect usages of formatting
flags and fixed them.
While attaching a partition to a distributed table in schema, we mistakenly
used unqualified name to find partitioned table's oid. This caused problems
while using partitioned tables with schemas. We are fixing this issue in
this PR.