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.
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.
We remove schema name parameter from worker_fetch_foreign_file and
worker_fetch_regular_table functions. We now send schema name
concatanated with table name.
Fixes#676
We added old versions (i.e. without schema name) of worker_apply_shard_ddl_command,
worker_fetch_foreign_file and worker_fetch_regular_table back. During function call
of one of these functions, we set schema name as public schema and call the newer
version of the functions.
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.
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.
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.
Marco Slot
Andres Freund
Robin Thomas
Burak Yucesoy
Jason Petersen
Brian Cloutier
Murat Tuncer
Onder Kalaci