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.
Add a call to RemoteTransactionBeginIfNecessary so that BEGIN is
actually sent to the remote connections. This means that ROLLBACK and
Ctrl-C are respected and don't leave the table in a partial state.
With this change DropShards function started to use new connection API. DropShards
function is used by DROP TABLE, master_drop_all_shards and master_apply_delete_command,
therefore all of these functions now support transactional operations. In DropShards
function, if we cannot reach a node, we mark shard state of related placements as
FILE_TO_DELETE and continue to drop remaining shards; however if any error occurs after
establishing the connection, we ROLLBACK whole operation.
We changed error message which appears when user tries to execute outer join command and
that command requires repartitioning. Old error message mentioned about 1-to-1 shard
partitioning which may not be clear to user.
This enables proper transactional behaviour for copy and relaxes some
restrictions like combining COPY with single-row modifications. It
also provides the basis for relaxing restrictions further, and for
optionally allowing connection caching.
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.
Since we will now replicate reference tables each time we add node, we need to ensure
that test space is clean in terms of reference tables before any add node operation.
For this purpose we had to change order of multi_drop_extension test which caused
change of some of the colocation ids.
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.
We used to disable router planner and executor
when task executor is set to task-tracker.
This change enables router planning and execution
at all times regardless of task execution mode.
We are introducing a hidden flag enable_router_execution
to enable/disable router execution. Its default value is
true. User may disable router planning by setting it to false.
With this PR, we add foreign key support to ALTER TABLE commands. For now,
we only support foreign constraint creation via ALTER TABLE query, if it
is only subcommand in ALTER TABLE subcommand list.
We also only allow foreign key creation if replication factor is 1.
Adds support for PostgreSQL 9.6 by copying in the requisite ruleutils
file and refactoring the out/readfuncs code to flexibly support the
old-style copy/pasted out/readfuncs (prior to 9.6) or use extensible
node APIs (in 9.6 and higher).
Most version-specific code within this change is only needed to set new
fields in the AggRef nodes we build for aggregations. Version-specific
test output files were added in certain cases, though in most they were
not necessary. Each such file begins by e.g. printing the major version
in order to clarify its purpose.
The comment atop citus_nodes.h details how to add support for new nodes
for when that becomes necessary.
So far placements were assigned an Oid, but that was just used to track
insertion order. It also did so incompletely, as it was not preserved
across changes of the shard state. The behaviour around oid wraparound
was also not entirely as intended.
The newly introduced, explicitly assigned, IDs are preserved across
shard-state changes.
The prime goal of this change is not to improve ordering of task
assignment policies, but to make it easier to reference shards. The
newly introduced UpdateShardPlacementState() makes use of that, and so
will the in-progress connection and transaction management changes.
Before this change, count on a distributed returned NULL if all shards
were pruned away, because on the master we replace with count(..) call
with a sum(..) call to sum the counts from the shards. However, sum
returns NULL when there are no rows, whereas count is expected to return
0.
UNIQUE or PRIMARY KEY constraints. Also, properly propagate valid
EXCLUDE constraints to worker shard tables.
If an EXCLUDE constraint includes the distribution column,
the operator must be an equality operator.
Tests in regression suite for exclusion constraints that include
the partition column, omit it, and include it but with non-equality
operator. Regression tests also verify that valid exclusion constraints
are propagated to the shard tables. And the tests work in different
timezones now.
Fixescitusdata/citus#748 and citusdata/citus#778.
pg_toast_* oids are constantly changing, and this causes regression tests to
fail time to time. With this commit, we remove all of the pg_toast_* references
from regression test outputs.
Three changes here to get to true multi-statement, multi-relation DDL
transactions (same functionality pre-5.2, with benefits of atomicity):
1. Changed the multi-shard utility hook to always run (consistency
with router executor hook, removes ad-hoc "installed" boolean)
2. Change the global connection list in multi_shard_transaction to
instead be a hash; update related functions to operate on global
hash instead of local hash/global list
3. Remove check within DDL code to prevent subsequent DDL commands;
place unset/reset guard around call to ConnectToNode to permit
connecting to additional nodes after DDL transaction has begun
In addition, code has been added to raise an error if a ROLLBACK TO
SAVEPOINT is attempted (similar to router executor), and comprehensive
tests execute all multi-DDL scenarios (full success, user ROLLBACK, any
actual errors (say, duplicate index), partial failure (duplicate index
on one node but not others), partial COMMIT (one node fails), and 2PC
partial PREPARE (one node fails)). Interleavings with other commands
(DML, \copy) are similarly all covered.
Recent changes to DDL and transaction logic resulted in a "regression"
from the viewpoint of users. Previously, DDL commands were allowed in
multi-command transaction blocks, though they were not processed in any
actual transactional manner. We improved the atomicity of our DDL code,
but added a restriction that DDL commands themselves must not occur in
any BEGIN/END transaction block.
To give users back the original functionality (and improved atomicity)
we now keep track of whether a multi-command transaction has modified
data (DML) or schema (DDL). Interleaving the two modification types in
a single transaction is disallowed.
This first step simply permits a single DDL command in such a block,
admittedly an incomplete solution, but one which will permit us to add
full multi-DDL command support in a subsequent commit.
"Staging table" will be the only valid use of 'stage' from now on, we
will now say "load" when talking about data ingestion. If creation of
shards is its own step, we'll just say "shard creation".
Fixes#547
This change removes all references to \stage in the regression tests
and puts \COPY instead. Doing so changed shard counts, min/max
values on some test tables (lineitem, orders, etc.).
Fixes#679
This change sets the default commit protocol for distributed DDL
commands to '1pc'. If the user issues a distributed DDL command with
this default setting, then once in a session, a NOTICE message is
shown about using '2pc' being extra safe.
This adds support for SERIAL/BIGSERIAL column types. Because we now can
evaluate functions on the master (during execution), adding this is a
matter of ensuring the table creation step works properly.
To accomplish this, I've added some logic to detect sequences owned by
a table (i.e. those related to its columns). Simply creating a sequence
and using it in a default value is insufficient; users who do so must
ensure the sequence is owned by the column using it.
Fortunately, this is exactly what SERIAL and BIGSERIAL do, which is the
use case we're targeting with this feature. While testing this, I found
that worker_apply_shard_ddl_command actually adds shard identifiers to
sequence names, though I found no places that use or test this path. I
removed that code so that sequence names are not mutated and will match
those used by a SERIAL default value expression.
Our use of the new-to-9.5 CREATE SEQUENCE IF NOT EXISTS syntax means we
are dropping support for 9.4 (which is being done regardless, but makes
this change simpler). I've removed 9.4 from the Travis build matrix.
Some edge cases are possible in ALTER SEQUENCE, COPY FROM (on workers),
and CREATE SEQUENCE OWNED BY. I've added errors for each so that users
understand when and why certain operations are prohibited.
We can now support richer set of queries in router planner.
This allow us to support CTEs, joins, window function, subqueries
if they are known to be executed at a single worker with a single
task (all tables are filtered down to a single shard and a single
worker contains all table shards referenced in the query).
Fixes : #501
Fixes#132
We hook into ALTER ... SET SCHEMA and warn out if user tries to change schema of a
distributed table.
We also hook into ALTER TABLE ALL IN TABLE SPACE statements and warn out if citus has
been loaded.
Fixes#513
This change modifies the DDL Propagation logic so that DDL queries
are propagated via 2-Phase Commit protocol. This way, failures during
the execution of distributed DDL commands will not leave the table in
an intermediate state and the pending prepared transactions can be
commited manually.
DDL commands are not allowed inside other transaction blocks or functions.
DDL commands are performed with 2PC regardless of the value of
`citus.multi_shard_commit_protocol` parameter.
The workflow of the successful case is this:
1. Open individual connections to all shard placements and send `BEGIN`
2. Send `SELECT worker_apply_shard_ddl_command(<shardId>, <DDL Command>)`
to all connections, one by one, in a serial manner.
3. Send `PREPARE TRANSCATION <transaction_id>` to all connections.
4. Sedn `COMMIT` to all connections.
Failure cases:
- If a worker problem occurs before sending of all DDL commands is finished, then
all changes are rolled back.
- If a worker problem occurs after all DDL commands are sent but not after
`PREPARE TRANSACTION` commands are finished, then all changes are rolled back.
However, if a worker node is failed, then the prepared transactions in that worker
should be rolled back manually.
- If a worker problem occurs during `COMMIT PREPARED` statements are being sent,
then the prepared transactions on the failed workers should be commited manually.
- If master fails before the first 'PREPARE TRANSACTION' is sent, then nothing is
changed on workers.
- If master fails during `PREPARE TRANSACTION` commands are being sent, then the
prepared transactions on workers should be rolled back manually.
- If master fails during `COMMIT PREPARED` or `ROLLBACK PREPARED` commands are being
sent, then the remaining prepared transactions on the workers should be handled manually.
This change also helps with #480, since failed DDL changes no longer mark
failed placements as inactive.
Fixes#463
OID of user-defined types may be different in master and worker nodes. This causes errors
while sending data between nodes with binary nodes. Because binary copy format adds OID
of the element if it is in an array. The code adding OID is in PostgreSQL code, therefore
we cannot change it. Instead we decided to use text format if we try to send array of
user-defined type.
It turns out some tests exercised this behavior, but removing it should
have no ill effects. Besides, both copy and INSERT disallow NULLs in a
table's partition column.
Fixes a bug where anti-joins on hash-partitioned distributed tables
would incorrectly prune shards early, result in incorrect results (test
included).
Fixes#550, fixes#545
If table name contains special characters, it needs to be escaped. However in some cases,
we escape table name before appending shardId, which causes syntax error in the queries
sent to worker nodes. With this change we now append shardId before escaping table names.
now copies all column references in count distinct aggreagete
to worker target list and group by. Master target list is
also updated to reflect changes in attribute order.
Fixes 569
There's not a ton of documentation about what CONTEXT lines should look
like, but this seems like the most dominant pattern. Similarly, users
should expect lowercase, non-period strings.
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.
Fixes#302
Since our previous syntax did not allow creating hash partitioned tables,
some of the previous tests manually changed partition method to hash to
be able to test it. With this change we remove unnecessary workaround and
create hash distributed tables instead. Also in some tests metadata was
created manually. With this change we also fixed this issue.
Single table repartition subqueries now support count(distinct column)
and count(distinct (case when ...)) expressions. Repartition query
extracts column used in aggregate expression and adds them to target
list and group by list, master query stays the same (count (distinct ...))
but attribute numbers inside the aggregate expression is modified to
reflect changes in repartition query.
Now, master_create_empty_shard() will create shards according to the
value of citus.shard_placement_policy which also makes default round-robin
instead of random.
Fixes#10
This change creates a new UDF: master_modify_multiple_shards
Parameters:
modify_query: A simple DELETE or UPDATE query as a string.
The UDF is similar to the existing master_apply_delete_command UDF.
Basically, given the modify query, it prunes the shard list, re-constructs
the query for each shard and sends the query to the placements.
Depending on the value of citus.multi_shard_commit_protocol, the commit
can be done in one-phase or two-phase manner.
Limitations:
* It cannot be called inside a transaction block
* It only be called with simple operator expressions (like Single Shard Modify)
Sample Usage:
```
SELECT master_modify_multiple_shards(
'DELETE FROM customer_delete_protocol WHERE c_custkey > 500 AND c_custkey < 500');
```
Now, we can copy to an append-partitioned distributed relation from
any worker node by providing master options such as;
COPY relation_name FROM file_path WITH (delimiter '|', master_host 'localhost', master_port 5432);
where master_port is optional and default is 5432.
This commit adds a fast shard pruning path for INSERTs on
hash-partitioned tables. The rationale behind this change is
that if there exists a sorted shard interval array, a single
index lookup on the array allows us to find the corresponding
shard interval. As mentioned above, we need a sorted
(wrt shardminvalue) shard interval array. Thus, this commit
updates shardIntervalArray to sortedShardIntervalArray in the
metadata cache. Then uses the low-level API that is defined in
multi_copy to handle the fast shard pruning.
The performance impact of this change is more apparent as more
shards exist for a distributed table. Previous implementation
was relying on linear search through the shard intervals. However,
this commit relies on constant lookup time on shard interval
array. Thus, the shard pruning becomes less dependent on the
shard count.
Fixes#379
Varchar VAR struct is wrapped in RELABELTYPE struct inside PostgreSQL code and
IsPartitionColumnRecursive function considers only VAR types so returning false
for varchar.
This change adds strip_implicit_coercions() call to the columnExpression in
IsPartitionColumnRecursive function so that we get rid of implicit coercions like
RELABELTYPE are stripped to VAR.
Fixes#375
Prior to this change, shard pruning couldn't be done if:
- Table is hash-distributed
- Partition column of is VARCHAR
- Query to be pruned is a subquery
There were two problems:
- A bug in left-side/right-side checks for the partition column
- We were not considering relabeled types (VARCHAR was relabeled as TEXT)
The previous form of the test, utilizing DEBUG2, included too much
output dependent on the specifc system and version. Reformulate it to
explicitly connect to workers and show the schema there, when necessary.
The only remaining difference in some of the remaining alternate
regression test files was due to an older minor version release
change. Remove those as well.
The default staging policy is now round-robin, though tests were still
configured to use local-first. Testing with the shipping default seems
like the best option, correctness-wise, and since local-first has some
issues with OSes where connecting from localhost doesn't always resolve
to 'localhost', just going with the default is a win-win.
After this change, shards and associated metadata are automatically
dropped when running DROP TABLE on a distributed table, which fixes#230.
It also adds schema support for master_apply_delete_command, which
fixes#73.
Dropping the shards happens in the master_drop_all_shards UDF, which is
called from the SQL_DROP trigger. Inside the trigger, the table is no
longer visible and calling master_apply_delete_command directly wouldn't
work and oid <-> name mappings are not available. The
master_drop_all_shards function therefore takes the relation id, schema
name, and table name as parameters, which can be obtained from
pg_event_trigger_dropped_objects() in the SQL_DROP trigger. If the user
calls master_drop_all_shards while the table still exists, the schema
name and table name are ignored.
Author: Marco Slot
Reviewed-By: Andres Freund
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.
Metin Doslu
Andres Freund
Murat Tuncer
Marco Slot
Brian Cloutier
Eren Basak
Burak Yucesoy
Onder Kalaci
Sumedh Pathak
Robin Thomas
Jason Petersen
Eren Basak
Amos Bird