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
Fixes#496
Previously we do not check whether table is foreign or not while creating empty
shards, and set storage type to 't'(Standard table) or 'c'(Columnar table). Now
if the table is foreign table(but not CStore foreign table) we set storage
type to 'f'(Foreign table). If it is CStore foreign table, we set its storage
type to 'c', i.e. columnar table have priority over foreign table.
Please note that 'c' is only used for CStore tables not for other possible
columnar stores at the moment. Possible improvement could be checking for other
columnar stores, though I am not sure if there is a way to check it for all
other columnar stores.
Since we now short-circuit on certain remote errors, we want to ensure
we preserve the old behavior of not modifying any placement states if
a non-short-circuiting error occurs on all placements.
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.
Fixes#475
With this change we prevent addition of ONLY clause to queries prepared for
worker nodes. When we add ONLY clause we may miss the inherited tables in
worker nodes created by users manually.
When executing queries with citus.task_executor = 'real-time', query
execution could, so far, spend a significant amount of time
sleeping. That's because we were
a) sleeping after several phases of query execution, even if we're not
waiting for network IO
b) sleeping for a fixed amount of time when waiting for network IO;
often a lot longer than actually required.
Just reducing the amount of time slept isn't a real solution, because
that just increases CPU usage.
Instead have the real-time executor's ManageTaskExecution return whether
a task is currently being processed, waiting for reads or writes, or
failed. When all tasks are waiting for IO use poll() to wait for IO
readyness.
That requires to slightly redefine how connection timeouts are handled:
before we counted the number of times ManageTaskExecution() was called,
and compared that with the timeout divided by the task check
interval. That, if processing of tasks took a while, could significantly
increase the time till a timeout occurred. Because it was based on the
ManageTaskExecution() being called on a constant interval, this approach
isn't feasible anymore. Instead measure the actual time since
connection establishment was started. That could in theory, if task
processing takes a very long time, lead to few passes over
PQconnectPoll().
The problem of sleeping too much also exists for the 'task-tracker'
executor, but is generally less problematic there, as processing the
individual tasks usually will take longer. That said, for e.g. the
regression tests it'd be helpful to use a similar approach.
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');
```
Make's $(wildcard) does not sort the glob result, but returns filenames
in filesystem ordering. This makes the build result vary and hence
unreproducible on the binary level. Fix by adding $(sort).
Spotted by Debian's reproducible builds project.
Murat Tuncer
Murat Tuncer
Jason Petersen
Amos Bird
Burak Yücesoy
Jason Petersen
Metin Doslu
Ahmet Eren Basak
Eren
Burak Yucesoy
Andres Freund
Matthew Seaman
Christoph Berg