* Change worker_hash_partition_table() such that the
divergence between Citus planner's hashing and
worker_hash_partition_table() becomes the same.
* Rename single partitioning to single range partitioning.
* Add single hash repartitioning. Basically, logical planner
treats single hash and range partitioning almost equally.
Physical planner, on the other hand, treats single hash and
dual hash repartitioning almost equally (except for JoinPruning).
* Add a new GUC to enable this feature
- 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
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 is the first of series of window function work.
We can now support window functions that can be pushed down to workers.
Window function must have distribution column in the partition clause
to be pushed down.
We push down order by to worker query when limit is specified
(with some other additional checks). If the query has an expression
on an aggregate or avg aggregate by itself, and there is an order
by on this particular target we may send wrong order by to worker
query with potential to affect query result.
The fix creates a auxilary target entry in the worker query and
uses that target entry for sorting.
With #1804 (and related PRs), Citus gained the ability to
plan subqueries that are not safe to pushdown.
There are two high-level requirements for pushing down subqueries:
* Individual subqueries that require a merge step (i.e., GROUP BY
on non-distribution key, or LIMIT in the subquery etc). We've
handled such subqueries via #1876.
* Combination of subqueries that are not joined on distribution keys.
This commit aims to recursively plan some of such subqueries to make
the whole query safe to pushdown.
The main logic behind non colocated subquery joins is that we pick
an anchor range table entry and check for distribution key equality
of any other subqueries in the given query. If for a given subquery,
we cannot find distribution key equality with the anchor rte, we
recursively plan that subquery.
We also used a hacky solution for picking relations as the anchor range
table entries. The hack is that we wrap them into a subquery. This is only
necessary since some of the attribute equivalance checks are based on
queries rather than range table entries.
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.
This commit provides the support for window functions in subquery and insert
into select queries. Note that our support for window functions is still limited
because it must have a partition by clause on the distribution key. This commit
makes changes in the files insert_select_planner and multi_logical_planner. The
required tests are also added with files multi_subquery_window_functions.out
and multi_insert_select_window.out.
This change adds support for SAVEPOINT, ROLLBACK TO SAVEPOINT, and RELEASE SAVEPOINT.
When transaction connections are not established yet, savepoints are kept in a stack and sent to the worker when the connection is later established. After establishing connections, savepoint commands are sent as they arrive.
This change fixes#1493 .
This GUC has two settings, 'always' and 'never'. When it's set to
'never' all behavior stays exactly as it was prior to this commit. When
it's set to 'always' only SELECT queries are allowed to run, and only
secondary nodes are used when processing those queries.
Add some helper functions:
- WorkerNodeIsSecondary(), checks the noderole of the worker node
- WorkerNodeIsReadable(), returns whether we're currently allowed to
read from this node
- ActiveReadableNodeList(), some functions (namely, the ones on the
SELECT path) don't require working with Primary Nodes. They should call
this function instead of ActivePrimaryNodeList(), because the latter
will error out in contexts where we're not allowed to write to nodes.
- ActiveReadableNodeCount(), like the above, replaces
ActivePrimaryNodeCount().
- EnsureModificationsCanRun(), error out if we're not currently allowed
to run queries which modify data. (Either we're in read-only mode or
use_secondary_nodes is set)
Some parts of the code were switched over to use readable nodes instead
of primary nodes:
- Deadlock detection
- DistributedTableSize,
- the router, real-time, and task tracker executors
- ShardPlacement resolution
This commit adds distributed transaction id infrastructure in
the scope of distributed deadlock detection.
In general, the distributed transaction id consists of a tuple
in the form of: `(databaseId, initiatorNodeIdentifier, transactionId,
timestamp)`.
Briefly, we add a shared memory block on each node, which holds some
information per backend (i.e., an array `BackendData backends[MaxBackends]`).
Later, on each coordinated transaction, Citus sends
`SELECT assign_distributed_transaction_id()` right after `BEGIN`.
For that backend on the worker, the distributed transaction id is set to
the values assigned via the function call.
The aim of the above is to correlate the transactions on the coordinator
to the transactions on the worker nodes.
This commit is intended to be a base for supporting declarative partitioning
on distributed tables. Here we add the following utility functions and their
unit tests:
* Very basic functions including differnentiating partitioned tables and
partitions, listing the partitions
* Generating the PARTITION BY (expr) and adding this to the DDL events
of partitioned tables
* Ability to generate text representations of the ranges for partitions
* Ability to generate the `ALTER TABLE parent_table ATTACH PARTITION
partition_table FOR VALUES value_range`
* Ability to apply add shard ids to the above command using
`worker_apply_inter_shard_ddl_command()`
* Ability to generate `ALTER TABLE parent_table DETACH PARTITION`
Adds support for PostgreSQL 10 by copying in the requisite ruleutils
and updating all API usages to conform with changes in PostgreSQL 10.
Most changes are fairly minor but they are numerous. One particular
obstacle was the change in \d behavior in PostgreSQL 10's psql; I had
to add SQL implementations (views, mostly) to mimic the pre-10 output.
Distributed query planning for subquery pushdown is done on the original
query. This prevents the usage of external parameters on the execution.
To overcome this, we manually replace the parameters on the original
query.
* Support for subqueries in WHERE clause
This commit enables subqueries in WHERE clause to be pushed down
by the subquery pushdown logic.
The support covers:
- Correlated subqueries with IN, NOT IN, EXISTS, NOT EXISTS,
operator expressions such as (>, <, =, ALL, ANY etc.)
- Non-correlated subqueries with (partition_key) IN (SELECT partition_key ..)
(partition_key) =ANY (SELECT partition_key ...)
Note that this commit heavily utilizes the attribute equivalence logic introduced
in the 1cb6a34ba8. In general, this commit mostly
adjusts the logical planner not to error out on the subqueries in WHERE clause.
* Improve error checks for subquery pushdown and INSERT ... SELECT
Since we allow subqueries in WHERE clause with the previous commit,
we should apply the same limitations to those subqueries.
With this commit, we do not iterate on each subquery one by one.
Instead, we extract all the subqueries and apply the checks directly
on those subqueries. The aim of this change is to (i) Simplify the
code (ii) Make it close to the checks on INSERT .. SELECT code base.
* Extend checks for unresolved paramaters to include SubLinks
With the presence of subqueries in where clause (i.e., SubPlans on the
query) the existing way for checking unresolved parameters fail. The
reason is that the parameters for SubPlans are kept on the parent plan not
on the query itself (see primnodes.h for the details).
With this commit, instead of checking SubPlans on the modified plans
we start to use originalQuery, where SubLinks represent the subqueries
in where clause. The unresolved parameters can be found on the SubLinks.
* Apply code-review feedback
* Remove unnecessary copying of shard interval list
This commit removes unnecessary copying of shard interval list. Note
that there are no copyObject function implemented for shard intervals.
- There was a crash when the table a shardid belonged to changed during
a session. Instead of crashing (a failed assert) we now throw an error
- Update the isolation test which was crashing to no longer exercise
that code path
- Add a regression test to check that the error is thrown
* Enabling physical planner for subquery pushdown changes
This commit applies the logic that exists in INSERT .. SELECT
planning to the subquery pushdown changes.
The main algorithm is followed as :
- pick an anchor relation (i.e., target relation)
- per each target shard interval
- add the target shard interval's shard range
as a restriction to the relations (if all relations
joined on the partition keys)
- Check whether the query is router plannable per
target shard interval.
- If router plannable, create a task
* Add union support within the JOINS
This commit adds support for UNION/UNION ALL subqueries that are
in the following form:
.... (Q1 UNION Q2 UNION ...) as union_query JOIN (QN) ...
In other words, we currently do NOT support the queries that are
in the following form where union query is not JOINed with
other relations/subqueries :
.... (Q1 UNION Q2 UNION ...) as union_query ....
* Subquery pushdown planner uses original query
With this commit, we change the input to the logical planner for
subquery pushdown. Before this commit, the planner was relying
on the query tree that is transformed by the postgresql planner.
After this commit, the planner uses the original query. The main
motivation behind this change is the simplify deparsing of
subqueries.
* Enable top level subquery join queries
This work enables
- Top level subquery joins
- Joins between subqueries and relations
- Joins involving more than 2 range table entries
A new regression test file is added to reflect enabled test cases
* Add top level union support
This commit adds support for UNION/UNION ALL subqueries that are
in the following form:
.... (Q1 UNION Q2 UNION ...) as union_query ....
In other words, Citus supports allow top level
unions being wrapped into aggregations queries
and/or simple projection queries that only selects
some fields from the lower level queries.
* Disallow subqueries without a relation in the range table list for subquery pushdown
This commit disallows subqueries without relation in the range table
list. This commit is only applied for subquery pushdown. In other words,
we do not add this limitation for single table re-partition subqueries.
The reasoning behind this limitation is that if we allow pushing down
such queries, the result would include (shardCount * expectedResults)
where in a non distributed world the result would be (expectedResult)
only.
* Disallow subqueries without a relation in the range table list for INSERT .. SELECT
This commit disallows subqueries without relation in the range table
list. This commit is only applied for INSERT.. SELECT queries.
The reasoning behind this limitation is that if we allow pushing down
such queries, the result would include (shardCount * expectedResults)
where in a non distributed world the result would be (expectedResult)
only.
* Change behaviour of subquery pushdown flag (#1315)
This commit changes the behaviour of the citus.subquery_pushdown flag.
Before this commit, the flag is used to enable subquery pushdown logic. But,
with this commit, that behaviour is enabled by default. In other words, the
flag is now useless. We prefer to keep the flag since we don't want to break
the backward compatibility. Also, we may consider using that flag for other
purposes in the next commits.
* Require subquery_pushdown when limit is used in subquery
Using limit in subqueries may cause returning incorrect
results. Therefore we allow limits in subqueries only
if user explicitly set subquery_pushdown flag.
* Evaluate expressions on the LIMIT clause (#1333)
Subquery pushdown uses orignal query, the LIMIT and OFFSET clauses
are not evaluated. However, logical optimizer expects these expressions
are already evaluated by the standard planner. This commit manually
evaluates the functions on the logical planner for subquery pushdown.
* Better format subquery regression tests (#1340)
* Style fix for subquery pushdown regression tests
With this commit we intented a more consistent style for the
regression tests we've added in the
- multi_subquery_union.sql
- multi_subquery_complex_queries.sql
- multi_subquery_behavioral_analytics.sql
* Enable the tests that are temporarily commented
This commit enables some of the regression tests that were commented
out until all the development is done.
* Fix merge conflicts (#1347)
- Update regression tests to meet the changes in the regression
test output.
- Replace Ifs with Asserts given that the check is already done
- Update shard pruning outputs
* Add view regression tests for increased subquery coverage (#1348)
- joins between views and tables
- joins between views
- union/union all queries involving views
- views with limit
- explain queries with view
* Improve btree operators for the subquery tests
This commit adds the missing comprasion for subquery composite key
btree comparator.
In this PR, we aim to deduce whether each of the RTE_RELATION
is joined with at least on another RTE_RELATION on their partition keys. If each
RTE_RELATION follows the above rule, we can conclude that all RTE_RELATIONs are
joined on their partition keys.
In order to do that, we invented a new equivalence class namely:
AttributeEquivalenceClass. In very simple words, a AttributeEquivalenceClass is
identified by an unique id and consists of a list of AttributeEquivalenceMembers.
Each AttributeEquivalenceMember is designed to identify attributes uniquely within the
whole query. The necessity of this arise since varno attributes are defined within
a single level of a query. Instead, here we want to identify each RTE_RELATION uniquely
and try to find equality among each RTE_RELATION's partition key.
Whenever we find an equality clause A = B, where both A and B originates from
relation attributes (i.e., not random expressions), we create an
AttributeEquivalenceClass to record this knowledge. If we later find another
equivalence B = C, we create another AttributeEquivalenceClass. Finally, we can
apply transitity rules and generate a new AttributeEquivalenceClass which includes
A, B and C.
Note that equality among the members are identified by the varattno and rteIdentity.
Each equality among RTE_RELATION is saved using an AttributeEquivalenceClass where
each member attribute is identified by a AttributeEquivalenceMember. In the final
step, we try generate a common attribute equivalence class that holds as much as
AttributeEquivalenceMembers whose attributes are a partition keys.
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.
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.
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.
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 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.
Previously, we errored out if non-user tries to SELECT query for some metadata tables. It
seems that we already GRANT SELECT access to some metadata tables but not others. With
this change, we GRANT SELECT access to all existing Citus metadata tables.
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.
This commit adds INSERT INTO ... SELECT feature for distributed tables.
We implement INSERT INTO ... SELECT by pushing down the SELECT to
each shard. To compute that we use the router planner, by adding
an "uninstantiated" constraint that the partition column be equal to a
certain value. standard_planner() distributes that constraint to all
the tables where it knows how to push the restriction safely. An example
is that the tables that are connected via equi joins.
The router planner then iterates over the target table's shards,
for each we replace the "uninstantiated" restriction, with one that
PruneShardList() handles. Do so by replacing the partitioning qual
parameter added in multi_planner() with the current shard's
actual boundary values. Also, add the current shard's boundary values to the
top level subquery to ensure that even if the partitioning qual is
not distributed to all the tables, we never run the queries on the shards
that don't match with the current shard boundaries. Finally, perform the
normal shard pruning to decide on whether to push the query to the
current shard or not.
We do not support certain SQLs on the subquery, which are described/commented
on ErrorIfInsertSelectQueryNotSupported().
We also added some locking on the router executor. When an INSERT/SELECT command
runs on a distributed table with replication factor >1, we need to ensure that
it sees the same result on each placement of a shard. So we added the ability
such that router executor takes exclusive locks on shards from which the SELECT
in an INSERT/SELECT reads in order to prevent concurrent changes. This is not a
very optimal solution, but it's simple and correct. The
citus.all_modifications_commutative can be used to avoid aggressive locking.
An INSERT/SELECT whose filters are known to exclude any ongoing writes can be
marked as commutative. See RequiresConsistentSnapshot() for the details.
We also moved the decison of whether the multiPlan should be executed on
the router executor or not to the planning phase. This allowed us to
integrate multi task router executor tasks to the router executor smoothly.
The necessity for this functionality comes from the fact that ruleutils.c is not supposed to be
used on "rewritten" queries (i.e. ones that have been passed through QueryRewrite()).
Query rewriting is the process in which views and such are expanded,
and, INSERT/UPDATE targetlists are reordered to match the physical order,
defaults etc. For the details of reordeing, see transformInsertRow().
With this change, we now push down foreign key constraints created during CREATE TABLE
statements. We also start to send foreign constraints during shard move along with
other DDL statements
With this change, master_copy_shard_placement and master_move_shard_placement functions
start to copy/move given shard along with its co-located shards.
This change adds the required infrastructure about metadata snapshot from MX
codebase into Citus, mainly metadata_sync.c file and master_metadata_snapshot UDF.
Two sets of tests are fixed by this change:
* multi_agg_approximate_distinct
* those in multi_task_tracker_extra_schedule
The first broke when we renamed stage to load in many files and was
never being run because the HyperLogLog extension wasn't easily
available in Debian. Now it's in our repo, so we install it and run
the test. I removed the distinct HLL target in favor of just always
running it and providing an output variant to handle when the extension
is absent. Basically, if PostgreSQL thinks HLL is available, the test
installs it and runs normally, otherwise the absent variant is used.
The second broke when I removed a test variant, erroneously believing
it to be related to an older Citus version. I've added a line in that
test to clarify why the variant is necessary (a practice we should
widely adopt).
Related to #786
This change adds the `pg_dist_node` table that contains the information
about the workers in the cluster, replacing the previously used
`pg_worker_list.conf` file (or the one specified with `citus.worker_list_file`).
Upon update, `pg_worker_list.conf` file is read and `pg_dist_node` table is
populated with the file's content. After that, `pg_worker_list.conf` file
is renamed to `pg_worker_list.conf.obsolete`
For adding and removing nodes, the change also includes two new UDFs:
`master_add_node` and `master_remove_node`, which require superuser
permissions.
'citus.worker_list_file' guc is kept for update purposes but not used after the
update is finished.
related to a table that might be distributed, allowing any name
that is within regular PostgreSQL length limits to be extended
with a shard ID for use in shards on workers. Handles multi-byte
character boundaries in identifiers when making prefixes for
shard-extended names. Includes tests.
Uses hash_any from PostgreSQL's access/hashfunc.c.
Removes AppendShardIdToStringInfo() as it's used only once
and arguably is best replaced there with a call to AppendShardIdToName().
Adds UDF shard_name(object_name, shard_id) to expose the shard-extended
name logic to other PL/PGSQL, UDFs and scripts.
Bumps version to 6.0-2 to allow for UDF to be created in migration script.
Fixescitusdata/citus#781 and citusdata/citus#179.
is now a `::regtype` using the qualified name of the column type,
not the column type OID which may differ between master/worker nodes.
Test coverage of a hash reparitition using a UDT as the join column.
Note that the UDFs `worker_hash_partition_table` and `worker_range_partition_table`
are unchanged, and rightly expect an OID for the column type; but the
planner code building the commands now allows for `::regtype` casting
to do its magic.
Fixescitusdata/citus#111.
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.
Allows the use of modification commands (INSERT/UPDATE/DELETE) within
transaction blocks (delimited by BEGIN and ROLLBACK/COMMIT), so long as
all modifications hit a subset of nodes involved in the first such com-
mand in the transaction. This does not circumvent the requirement that
each individual modification command must still target a single shard.
For instance, after sending BEGIN, a user might INSERT some rows to a
shard replicated on two nodes. Subsequent modifications can hit other
shards, so long as they are on one or both of these nodes.
SAVEPOINTs are supported, though if the user actually attempts to send
a ROLLBACK command that specifies a SAVEPOINT they will receive an
ERROR at the end of the topmost transaction.
Placements are only marked inactive if at least one replica succeeds
in a transaction where others fail. Non-atomic behavior is possible if
the shard targeted by the initial modification within a transaction has
a higher replication factor than another shard within the same block
and a node with the latter shard has a failure during the COMMIT phase.
Other methods of denoting transaction blocks (multi-statement commands
sent all at once and functions written in e.g. PL/pgSQL or other such
languages) are not presently supported; their treatment remains the
same as before.
- Enables using VOLATILE functions (like nextval()) in INSERT queries
- Enables using STABLE functions (like now()) targetLists and joinTrees
UPDATE and INSERT can now contain non-immutable functions. INSERT can contain any kind of
expression, while UPDATE can contain any STABLE function, so long as a Var is not passed
into the STABLE function, even indirectly. UPDATE TagetEntry's can now also include Vars.
There's an exception, CASE/COALESCE statements may not contain mutable functions.
Functions calls in master_modify_multiple_shards are also evaluated.
Fixes#78
With this change, it is possible to append a table in any schema to shard. The function
master_append_table_to_shard now supports schema names.
-Added 2 more schedules for task-tracker and multi-binary
instead of running multi_schedule 3 times
-set task-tracker-delay for each long running schedule
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.
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');
```
Citus' extension version now has a -$schemaversion appendix. When the
schema is changed, a new schema version has to be added; changes to the
same schema version several commits inside a single pull request are ok.
Schema migration scripts between each schema version have to be
added. To ensure upgrade scripts work correctly a new regression test
ensures that all steps work.
The extension scripts to-be-used for CREATE EXTENSION (i.e. not
extension updates) are generated by concatenating citus.sql and the
relevant migration scripts.
When we notice that pg_dist_partition is being invalidated we assume
that the citus extension is being dropped and drop state such as
extensionLoaded and the cached oids of all the metadata tables.
This frees the user from needing to reconnect after running DROP
EXTENSION, so we also no longer send a warning message.
Prior to this change, it was not possible to use UDFs in repartitioned
subqueries. The reason is that we were setting the search path explicitly
and omiting public schema from that path.
This change adds the public schema to the explicitly set search path.
Onder Kalaci
velioglu
Murat Tuncer
Murat Tuncer
Marco Slot
Markus Sintonen
mehmet furkan şahin
Hadi Moshayedi
Brian Cloutier
Burak Yucesoy
Andres Freund
Jason Petersen
Jason Petersen
Metin Doslu
Eren Basak
Robin Thomas
eren