Previously, we were wrapping targetlist nodes with Vars that reference
to the result of the worker query, if the node itself is not `Const` or
not a `Param`. Indeed, we should not do that unless the node itself is
a `Var` node or contains a `Var` within it (e.g.: `OpExpr(Var(column_a) > 2)`).
Otherwise, when worker query returns empty result set, then combine
query exec would crash since the `Var` would be pointing to an empty
tuple slot, which is not desirable for the node-executor methods.
With this commit, rebalancer backends are identified by application_name = citus_rebalancer
and the regular internal backends are identified by application_name = citus_internal
BEGIN/COMMIT transaction block or in a UDF calling another UDF.
(2) Prohibit/Limit the delegated function not to do a 2PC (or any work on a
remote connection).
(3) Have a safety net to ensure the (2) i.e. we should block the connections
from the delegated procedure or make sure that no 2PC happens on the node.
(4) Such delegated functions are restricted to use only the distributed argument
value.
Note: To limit the scope of the project we are considering only Functions(not
procedures) for the initial work.
DESCRIPTION: Introduce a new flag "force_delegation" in create_distributed_function(),
which will allow a function to be delegated in an explicit transaction block.
Fixes#3265
Once the function is delegated to the worker, on that node during the planning
distributed_planner()
TryToDelegateFunctionCall()
CheckDelegatedFunctionExecution()
EnableInForceDelegatedFuncExecution()
Save the distribution argument (Constant)
ExecutorStart()
CitusBeginScan()
IsShardKeyValueAllowed()
Ensure to not use non-distribution argument.
ExecutorRun()
AdaptiveExecutor()
StartDistributedExecution()
EnsureNoRemoteExecutionFromWorkers()
Ensure all the shards are local to the node in the remoteTaskList.
NonPushableInsertSelectExecScan()
InitializeCopyShardState()
EnsureNoRemoteExecutionFromWorkers()
Ensure all the shards are local to the node in the placementList.
This also fixes a minor issue: Properly handle expressions+parameters in distribution arguments
PostgreSQL does not need calling this function since 7.4 release, and it
is a NOOP.
For more details, check PostgreSQL commit below :
commit dd04e958c8b03c0f0512497651678c7816af3198
Author: Tom Lane <tgl@sss.pgh.pa.us>
Date: Sun Mar 9 03:34:10 2003 +0000
tuplestore_donestoring() isn't needed anymore, but provide a no-op
macro definition so as not to create compatibility problems.
diff --git a/src/include/utils/tuplestore.h b/src/include/utils/tuplestore.h
index b46babacd1..76fe9fb428 100644
--- a/src/include/utils/tuplestore.h
+++ b/src/include/utils/tuplestore.h
@@ -17,7 +17,7 @@
* Portions Copyright (c) 1996-2002, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
- * $Id: tuplestore.h,v 1.8 2003/03/09 02:19:13 tgl Exp $
+ * $Id: tuplestore.h,v 1.9 2003/03/09 03:34:10 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -41,6 +41,9 @@ extern Tuplestorestate *tuplestore_begin_heap(bool randomAccess,
extern void tuplestore_puttuple(Tuplestorestate *state, void *tuple);
+/* tuplestore_donestoring() used to be required, but is no longer used */
+#define tuplestore_donestoring(state) ((void) 0)
+
/* backwards scan is only allowed if randomAccess was specified 'true' */
extern void *tuplestore_gettuple(Tuplestorestate *state, bool forward,
bool *should_free);
We've both allowed delegating functions and procedures from worker nodes
and also prevented delegation if a function/procedure has already been
propagated from another node.
We re-define the meaning of active shard placement. It used
to only be defined via shardstate == SHARD_STATE_ACTIVE.
Now, we also add one more check. The worker node that the
placement is on should be active as well.
This is a preparation for supporting citus_disable_node()
for MX with multiple failures at the same time.
With this change, the maintanince daemon only needs to
sync the "node metadata" (e.g., pg_dist_node), not the
shard metadata.
With Citus 9.0, we introduced `citus.single_shard_commit_protocol` which
defaults to 2PC.
With this commit, we prevent any user to set it to 1PC and drop support
for `citus.single_shard_commit_protocol`.
Although this might add some overhead for users, it is already the default
behaviour (so less likely) and marking placements as INVALID is much
worse.
When queryId is not 0 and verbose is true, the query identifier is
emitted to the explain output. This is breaking Postgres outputs.
We disable de query identifier calculation in the tests.
Commit on PG that introduced the query identifier in the explain output:
4f0b0966c866ae9f0e15d7cc73ccf7ce4e1af84b
Relevant PG commit:
9e38c2bb5093ceb0c04d6315ccd8975bd17add66
fix array_cat_agg for pg upgrades
array_cat_agg now needs to take anycompatiblearray instead of anyarray
because array_cat changed its type from anyarray to anycompatiblearray
with pg14.
To handle upgrades correctly, we drop the aggregate in
citus_pg_prepare_upgrade. To be able to drop it, we first remove the
dependency from pg_depend.
Then we create the right aggregate in citus_finish_pg_upgrade and we
also add the dependency back to pg_depend.
Postgres doesn't accept NULL for queryStrings in explain plans anymore.
Internally, there are some places in Postgres where they modified the
NULLS to ""(the empty string). So we do the same on citus side.
Commit on Postgres:
1111b2668d89bfcb6f502789158b1233ab4217a6
SetTuplestoreDestReceiverParams function now has two new parameters
This new macro give us the ability to use this new parameter for PG14 and it doesn't give the parameter for previous versions
Existing parameters are set to NULL to keep previous behavior
Relevant PG commit:
2f48ede080f42b97b594fb14102c82ca1001b80c
New macros: FuncnameGetCandidates_compat and expand_function_arguments_compat
The functions (the ones without _compat) now have a new bool include_out_arguments parameter
These new macros give us the ability to use this new parameter for PG14 and it doesn't give the parameter for previous versions
Existing include_out_arguments parameters are set to 'false' to keep current behavior
Relevant PG commit:
e56bce5d43789cce95d099554ae9593ada92b3b7
* 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
Before this commit, we always synced the metadata with superuser.
However, that creates various edge cases such as visibility errors
or self distributed deadlocks or complicates user access checks.
Instead, with this commit, we use the current user to sync the metadata.
Note that, `start_metadata_sync_to_node` still requires super user
because accessing certain metadata (like pg_dist_node) always require
superuser (e.g., the current user should be a superuser).
However, metadata syncing operations regarding the distributed
tables can now be done with regular users, as long as the user
is the owner of the table. A table owner can still insert non-sense
metadata, however it'd only affect its own table. So, we cannot do
anything about that.
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
Ignore orphaned shards in more places
Only use active shard placements in RouterInsertTaskList
Use IncludingOrphanedPlacements in some more places
Fix comment
Add tests
The name and comment of this function did not indicate that it only
really could detect locally accessible citus local tables. This fixes
that, while also cleaning up the function a bit.
With local query caching, we try to avoid deparse/parse stages as the
operation is too costly.
However, we can do deparse/parse operations once per cached queries, right
before we put the plan into the cache. With that, we avoid edge
cases like (4239) or (5038).
In a sense, we are making the local plan caching behave similar for non-cached
local/remote queries, by forcing to deparse the query once.
DESCRIPTION: introduce `citus.local_hostname` GUC for connections to the current node
Citus once in a while needs to connect to itself for some systems operations. This used to be hardcoded to `localhost`. The hardcoded hostname causes some issues, for example in environments where `sslmode=verify-full` is required. It is not always desirable or even feasible to get `localhost` as an alt name on the certificate.
By introducing a GUC to use when connecting to the current instance the user has more control what network path is used and what hostname is required to be present in the server certificate.
As long as the VALUES clause contains constant values, we should not
recursively plan the queries/CTEs.
This is a follow-up work of #1805. So, we can easily apply OUTER join
checks as if VALUES clause is a reference table/immutable function.
With this commit, we make sure to prevent infinite recursion for queries
in the format: [subquery with a UNION ALL] JOIN [table or subquery]
Also, fixes a bug where we pushdown UNION ALL below a JOIN even if the
UNION ALL is not safe to pushdown.
* Use translated vars in postgres 13 as well
Postgres 13 removed translated vars with pg 13 so we had a special logic
for pg 13. However it had some bug, so now we copy the translated vars
before postgres deletes it. This also simplifies the logic.
* fix rtoffset with pg >= 13
/*
* The physical planner assumes that all worker queries would have
* target list entries based on the fact that at least the column
* on the JOINs have to be on the target list. However, there is
* an exception to that if there is a cartesian product join and
* there is no additional target list entries belong to one side
* of the JOIN. Once we support cartesian product join, we should
* remove this error.
*/
It seems that we need to consider only pseudo constants while doing some
shortcuts in planning. For example there could be a false clause but it
can contribute to the result in which case it will not be a pseudo
constant.
We would exclude tables without relationRestriction from conversion
candidates in local-distributed table joins. This could leave a leftover
local table which should have been converted to a subquery.
Ideally I would expect that in each call to CreateDistributedPlan we
would pass a new plan id, but that seems like a bigger change.
We do not include dummy column if original task didn't return any
columns.
Otherwise, number of columns that original task returned wouldn't
match number of columns returned by worker_save_query_explain_analyze.
It seems that we were not considering the case where coordinator was
added to the cluster as a worker in the optimization of intermediate
results.
This could lead to errors when coordinator was added as a worker.
* Fix partition column index issue
We send column names to worker_hash/range_partition_table methods, and
in these methods we check the column name index from tuple descriptor.
Then this index is used to decide the bucket that the current row will
be sent for the repartition.
This becomes a problem when there are the same column names in the
tupleDescriptor. Then we can choose the wrong index. Hence the
partitioned data will be put to wrong workers. Then the result could
miss some data because workers might contain different range of data.
An example:
TupleDescriptor contains "trip_id", "car_id", "car_id" for one table.
It contains only "car_id" for the other table. And assuming that the
tables will be partitioned by car_id, it is not certain what should be
used for deciding the bucket number for the first table. Assuming value
2 goes to bucket 2 and value 3 goes to bucket 3, it is not certain which
bucket "1 2 3" (trip_id, car_id, car_id) row will go to.
As a solution we send the index of partition column in targetList
instead of the column name.
The old API is kept so that if workers upgrade work, it still works
(though it will have the same bug)
* Use the same method so that backporting is easier
Attribute number in a subquery RTE and relation RTE means different
things. In a relation attribute number will point to the column number
in the table definition including the dropped columns as well however in
subquery, it means the index in the target list. When we convert a
relation RTE to subquery RTE we should either correct all the relevant
attribute numbers or we can just add a dummy column for the dropped
columns. We choose the latter in this commit because it is practically
too vulnerable to update all the vars in a query.
Another thing this commit fixes is that in case a join restriction
clause list contains a false clause, we should just returns a false
clause instead of the whole list, because the whole list will contain
restrictions from other RTEs as well and this breaks the query, which
can be seen from the output changes, now it is much simpler.
Also instead of adding single tests for dropped columns, we choose to
run the whole mixed queries with tables with dropped columns, this
revealed some bugs already, which are fixed in this commit.
It seems that there are only very few cases where that is useful, and
for now we prefer not having that check. This means that we might
perform some unnecessary checks, but that should be rare and not
performance critical.
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.
It seems that most of the updates were broken, we weren't aware of it
because there wasn't any data in the tables. They are broken mostly
because local tables do not have a shard id and some code paths should
be updated with that information, currently when there is an invalid
shard id, it is assumed to be pruned.
Consider local tables in router planner
In case there is a local table, the shard id will not be valid and there
are some checks that rely on shard id, we should skip these in case of
local tables, which is handled with a dummy placement.
Add citus local table dist table join tests
add local-dist table mixed joins tests
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.
Remove FillLocalAndDistributedRTECandidates and use
ShouldConvertLocalTableJoinsToSubqueries, which simplifies things as we
rely on a single function to decide whether we should continue
converting RTE to subquery.
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.
The name of the function is different than the implemantation. Because
the function is designed to only consider SELECT queries. Also this
changes the assert with an error.
It seems that we forgot to pass the revelant
flag to enable Postgres' parallel query
capabilities on the shards when user does
EXPLAIN ANALYZE on a distributed table.
When a relation is used on an OUTER JOIN with FALSE filters,
set_rel_pathlist_hook may not be called for the table.
There might be other cases as well, so do not rely on the hook
for classification of the tables.
RemoveDuplicateJoinRestrictions() function was introduced with the aim of decrasing the overall planning times by eliminating the duplicate JOIN restriction entries (#1989). However, it turns out that the function itself is so CPU intensive with a very high algorithmic complexity, it hurts a lot more than it helps. The function is a clear example of premature optimization.
The table below shows the difference clearly:
"distributed query planning
time master" RemoveDuplicateJoinRestrictions() execution time on master "Remove the function RemoveDuplicateJoinRestrictions()
this PR"
5 table INNER JOIN 9 msec 2msec 7 msec
10 table INNER JOIN 227 msec 194 msec 29 msec
20 table INNER JOIN 1 sec 235 msec 1 sec 139 msec 90 msecs
50 table INNER JOIN 24 seconds 21 seconds 1.5 seconds
100 table INNER JOIN 2 minutes 16 secods 1 minute 53 seconds 23 seconds
250 table INNER JOIN Bottleneck on JoinClauseList 18 minutes 52 seconds Bottleneck on JoinClauseList
5 table INNER JOIN in subquery 9 msec 0 msec 6 msec
10 table INNER JOIN subquery 33 msec 10 msec 32 msec
20 table INNER JOIN subquery 132 msec 67 msec 123 msec
50 table INNER JOIN subquery 1.2 seconds 900 msec 500 msec
100 table INNER JOIN subquery 6 seconds 5 seconds 2 seconds
250 table INNER JOIN subquery 54 seconds 37 seconds 20 seconds
5 table LEFT JOIN 5 msec 0 msec 5 msec
10 table LEFT JOIN 11 msec 0 msec 13 msec
20 table LEFT JOIN 26 msec 2 msec 30 msec
50 table LEFT JOIN 150 msec 15 msec 193 msec
100 table LEFT JOIN 757 msec 71 msec 722 msec
250 table LEFT JOIN 8 seconds 600 msec 8 seconds
5 JOINs among 2 table JOINs 37 msec 11 msec 25 msec
10 JOINs among 2 table JOINs 536 msec 306 msec 352 msec
20 JOINs among 2 table JOINs 794 msec 181 msec 640 msec
50 JOINs among 2 table JOINs 25 seconds 2 seconds 22 seconds
100 JOINs among 2 table JOINs Bottleneck on JoinClauseList 9 seconds Bottleneck on JoinClauseList
150 JOINs among 2 table JOINs Bottleneck on JoinClauseList 46 seconds Bottleneck on JoinClauseList
On top of the performance penalty, the function had a critical bug #4255, and with #4254 we hit one more important bug. It should be fixed by adding the followig check to the ContextCoversJoinRestriction():
```
static bool
JoinRelIdsSame(JoinRestriction *leftRestriction, JoinRestriction *rightRestriction)
{
Relids leftInnerRelIds = leftRestriction->innerrel->relids;
Relids rightInnerRelIds = rightRestriction->innerrel->relids;
if (!bms_equal(leftInnerRelIds, rightInnerRelIds))
{
return false;
}
Relids leftOuterRelIds = leftRestriction->outerrel->relids;
Relids rightOuterRelIds = rightRestriction->outerrel->relids;
if (!bms_equal(leftOuterRelIds, rightOuterRelIds))
{
return false;
}
return true;
}
```
However, adding this eliminates all the benefits tha RemoveDuplicateJoinRestrictions() brings.
I've used the commands here to generate the JOINs mentioned in the PR: https://gist.github.com/onderkalaci/fe8654f9df5916c7af4c7c5eb892561e#file-gistfile1-txt
Inner and outer JOINs behave roughly the same, to simplify the table only added INNER joins.
* Fix incorrect join related fields
Ruleutils expect to give the original index of join columns hence we
should consider the dropped columns while setting the fields in
SetJoinRelatedFieldsCompat.
* add some more tests for joins
* Move tests to join.sql and create a utility function
Disallow `ON TRUE` outer joins with reference & distributed tables
when reference table is outer relation by fixing the logic bug made
when calling `LeftListIsSubset` function.
Also, be more defensive when removing duplicate join restrictions
when join clause is empty for non-inner joins as they might still
contain useful information for non-inner joins.
It seems like Postgres could call set_rel_pathlist() for
the same relation multiple times. This breaks the logic
where we assume relationCount eqauls to the number of
entries in relationRestrictionList.
In summary, relationRestrictionList may contain duplicate
entries.
We should not access CurrentLocalExecutionStatus directly because that
would mean that we could also set it directly, which we shouldn't
because we have checks to see if the new state is possible, otherwise we
error.
Before this commit, the logic was:
- As long as the outer side of the JOIN is not a JOIN (e.g., relation
or subquery etc.), we check for the existence of any recurring
tuples. There were two implications of this decision.
First, even if a subquery which is on the outer side contains
distributed table JOIN reference table, Citus would unnecessarily throw
an error. Note that, the JOIN inside the subquery would already
be going to be tested recursively. But, as long as that check
passes, there is no reason for the upper JOIN to fail. An example, which
used to fail and now works:
SELECT * FROM (SELECT * FROM dist JOIN ref) as foo LEFT JOIN dist;
Second, certain JOINs, especially with ON (true) conditions were not
represented as Citus expects the JOINs to be in the format
DeferredErrorIfUnsupportedRecurringTuplesJoin().
Multi-row & router INSERT's were crashing with local execution if at
least one of the DEFAULT columns were not specified in VALUES list.
This was because, the changes we make on query->values_lists and
query->targetList was sufficient for deparsing given INSERT for remote
execution but not sufficient for local execution.
With this commit, DEFAULT value normalization for multi-row & router
INSERT's is fixed by adding dummy column references for unspecified
DEFAULT columns.
We currently do not support volatile functions in update/delete statements
because the function evaluation logic does not know how to distinguish
volatile functions (that need to be evaluated per row) from stable functions
(that need to be evaluated per query), and it is also not safe to push the
volatile functions down on replicated tables.
Add sort method parameter for regression tests
Fix check-style
Change sorting method parameters to enum
Polish
Add task fields to OutTask
Add test into multi_explain
Fix isolation test
Pushing down the CALLs to the node that the CALL is executed is
dangerous and could lead to infinite recursion.
When the coordinator added as worker, Citus was by chance preventing
this. The coordinator was marked as "not metadatasynced" node
in pg_dist_node, which prevented CALL/function delegation to happen.
With this commit, we do the following:
- Fix metadatasynced column for the coordinator on pg_dist_node
- Prevent pushdown of function/procedure to the same node that
the function/procedure is being executed. Today, we do not sync
pg_dist_object (e.g., distributed functions metadata) to the
worker nodes. But, even if we do it now, the function call delegation
would prevent the infinite recursion.
Introduce table entry utility functions
Citus table cache entry utilities are introduced so that we can easily
extend existing functionality with minimum changes, specifically changes
to these functions. For example IsNonDistributedTableCacheEntry can be
extended for citus local tables without the need to scan the whole
codebase and update each relevant part.
* Introduce utility functions to find the type of tables
A table type can be a reference table, a hash/range/append distributed
table. Utility methods are created so that we don't have to worry about
how a table is considered as a reference table etc. This also makes it
easy to extend the table types.
* Add IsCitusTableType utilities
* Rename IsCacheEntryCitusTableType -> IsCitusTableTypeCacheEntry
* Change citus table types in some checks
create_distributed_function(function_name,
distribution_arg_name,
colocate_with text)
This UDF did not allow colocate_with parameters when there were no
disttribution_arg_name supplied. This commit changes the behaviour to
allow missing distribution_arg_name parameters when the function should
be colocated with a reference table.
RemoveCoordinatorPlacement does not do what it says. It removes the
coordinator placement only if there are other placements, so it is not a
single node, and only if the coordinator has a placement.
AllTargetExpressionsAreColumnReferences would return false if a query
had an entry that is referencing the outer query. It seems safe to not
have this for non-distributed tables, such as reference tables. We
already have separate checks for other cases such as having limits.
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.
It seems that currently we process even postgres tables in explain
commands. This is because we register a hook for explain and we don't
have any check to see if the query has any citus table.
With this commit, we now send the buffer usage as well to the relevant
API. There is some duplicate in the code but it is because of the
existing structure, we can refactor this separately.
Onur Tirtir
Teja Mupparti
Marco Slot
Ahmet Gedemenli
Talha Nisanci
Hanefi Onaldi
Burak Velioglu
Onder Kalaci
Philip Dubé
Önder Kalacı
Teja Mupparti
Halil Ozan Akgul
Jelte Fennema
Nils Dijk
Naisila Puka
Marco Slot
Hadi Moshayedi