With this change we add an option to add a node without replicating all reference
tables to that node. If a node is added with this option, we mark the node as
inactive and no queries will sent to that node.
We also added two new UDFs;
- master_activate_node(host, port):
- marks node as active and replicates all reference tables to that node
- master_add_inactive_node(host, port):
- only adds node to pg_dist_node
With this change, we start to error out if loaded citus binaries does not match
the available major version or installed citus extension version. In this case
we force user to restart the server or run ALTER EXTENSION depending on the
situation
Custom Scan is a node in the planned statement which helps external providers
to abstract data scan not just for foreign data wrappers but also for regular
relations so you can benefit your version of caching or hardware optimizations.
This sounds like only an abstraction on the data scan layer, but we can use it
as an abstraction for our distributed queries. The only thing we need to do is
to find distributable parts of the query, plan for them and replace them with
a Citus Custom Scan. Then, whenever PostgreSQL hits this custom scan node in
its Vulcano style execution, it will call our callback functions which run
distributed plan and provides tuples to the upper node as it scans a regular
relation. This means fewer code changes, fewer bugs and more supported features
for us!
First, in the distributed query planner phase, we create a Custom Scan which
wraps the distributed plan. For real-time and task-tracker executors, we add
this custom plan under the master query plan. For router executor, we directly
pass the custom plan because there is not any master query. Then, we simply let
the PostgreSQL executor run this plan. When it hits the custom scan node, we
call the related executor parts for distributed plan, fill the tuple store in
the custom scan and return results to PostgreSQL executor in Vulcano style,
a tuple per XXX_ExecScan() call.
* Modify planner to utilize Custom Scan node.
* Create different scan methods for different executors.
* Use native PostgreSQL Explain for master part of queries.
This UDF returns a shard placement from cache given shard id and placement id. At the
moment it iterates over all shard placements of given shard by ShardPlacementList and
searches given placement id in that list, which is not a good solution performance-wise.
However, currently, this function will be used only when there is a failed transaction.
If a need arises we can optimize this function in the future.
So far router planner had encapsulated different functionality in
MultiRouterPlanCreate. Modifications always go through router, selects
sometimes. Modifications always error out if the query is unsupported,
selects return NULL. Especially the error handling is a problem for
the upcoming extension of prepared statement support.
Split MultiRouterPlanCreate into CreateRouterPlan and
CreateModifyPlan, and change them to not throw errors.
Instead errors are now reported by setting the new
MultiPlan->plannigError.
Callers of router planner functionality now have to throw errors
themselves if desired, but also can skip doing so.
This is a pre-requisite for expanding prepared statement support.
While touching all those lines, improve a number of error messages by
getting them closer to the postgres error message guidelines.
It can be useful, e.g. in the upcoming prepared statement support, to
be able to return an error from a function that is not raised
immediately, but can later be thrown. That allows e.g. to attempt to
plan a statment using different methods and to create good error
messages in each planner, but to only error out after all planners
have been run.
To enable that create support for deferred error messages that can be
created (supporting errorcode, message, detail, hint) in one function,
and then thrown in different place.
This change adds support for serial columns to be used with MX tables.
Prior to this change, sequences of serial columns were created in all
workers (for being able to create shards) but never used. With MX, we
need to set the sequences so that sequences in each worker create
unique values. This is done by setting the MINVALUE, MAXVALUE and
START values of the sequence.
With this change, we start to delete placement of reference tables at given worker node
after master_remove_node UDF call. We remove placement metadata at master node but we do
not drop actual shard from the worker node. There are two reasons for that decision,
first, it is not critical to DROP the shards in the workers because Citus will ignore them
as long as node is removed from cluster and if we add that node back to cluster we will
DROP and recreate all reference tables. Second, if node is unreachable, it becomes
complicated to cover failure cases and have a transaction support.
Enables use views within distributed queries.
User can create and use a view on distributed tables/queries
as he/she would use with regular queries.
After this change router queries will have full support for views,
insert into select queries will support reading from views, not
writing into. Outer joins would have a limited support, and would
error out at certain cases such as when a view is in the inner side
of the outer join.
Although PostgreSQL supports writing into views under certain circumstances.
We disallowed that for distributed views.
So far we've reloaded them frequently. Besides avoiding that cost -
noticeable for some workloads with large shard counts - it makes it
easier to add information to ShardPlacements that help us make
placement_connection.c colocation aware.
Doing so requires adding a mapping from shardId to the cache
entries. For that metadata_cache.c now maintains an additional
hashtable. That hashtable only references shard intervals in the
dist table cache.
Previously the function was getting too large. Thus this splits the
function into separate parts for looking up the cache entry and
building the cache contents.
With this change, we start to replicate all reference tables to the new node when new node
is added to the cluster with master_add_node command. We also update replication factor
of reference table's colocation group.
With this change we introduce new UDF, upgrade_to_reference_table, which can be used to
upgrade existing broadcast tables reference tables. For upgrading, we require that given
table contains only one shard.
Renamed FindShardIntervalIndex() to ShardIndex() and added binary search
capability. It used to assume that hash partition tables are always
uniformly distributed which is not true if upcoming tenant isolation
feature is applied. This commit also reduces code duplication.
* Add get_distribution_value_shardid UDF
With this UDF users can now map given distribution value to shard id. We mostly hide
shardids from users to prevent unnecessary complexity but some power users might need
to know about which entry/value is stored in which shard for maintanence purposes.
Signature of this UDF is as follows;
bigint get_distribution_value_shardid(table_name regclass, distribution_value anyelement)
With this commit, we implemented some basic features of reference tables.
To start with, a reference table is
* a distributed table whithout a distribution column defined on it
* the distributed table is single sharded
* and the shard is replicated to all nodes
Reference tables follows the same code-path with a single sharded
tables. Thus, broadcast JOINs are applicable to reference tables.
But, since the table is replicated to all nodes, table fetching is
not required any more.
Reference tables support the uniqueness constraints for any column.
Reference tables can be used in INSERT INTO .. SELECT queries with
the following rules:
* If a reference table is in the SELECT part of the query, it is
safe join with another reference table and/or hash partitioned
tables.
* If a reference table is in the INSERT part of the query, all
other participating tables should be reference tables.
Reference tables follow the regular co-location structure. Since
all reference tables are single sharded and replicated to all nodes,
they are always co-located with each other.
Queries involving only reference tables always follows router planner
and executor.
Reference tables can have composite typed columns and there is no need
to create/define the necessary support functions.
All modification queries, master_* UDFs, EXPLAIN, DDLs, TRUNCATE,
sequences, transactions, COPY, schema support works on reference
tables as expected. Plus, all the pre-requisites associated with
distribution columns are dismissed.
Marco Slot
velioglu
Burak Yucesoy
Jason Petersen
Metin Doslu
Andres Freund
Murat Tuncer
Brian Cloutier
Onder Kalaci
Eren Basak