This is a refactoring PR that starts using our new hash table creation
helper function. It adds a few more macros for ease of use, because C
doesn't have default arguments. It also adds a macro to check if a
struct contains automatic padding bytes. No struct that is hashed using
tag_hash should have automatic padding bytes, because those bytes are
undefined and thus using them to create a hash will result in undefined
behaviour (usually a random hash).
**Intro**
This adds support to Citus to change the CPU priority values of
backends. This is created with two main usecases in mind:
1. Users might want to run the logical replication part of the shard moves
or shard splits at a higher speed than they would do by themselves.
This might cause some small loss of DB performance for their regular
queries, but this is often worth it. During high load it's very possible
that the logical replication WAL sender is not able to keep up with the
WAL that is generated. This is especially a big problem when the
machine is close to running out of disk when doing a rebalance.
2. Users might have certain long running queries that they don't impact
their regular workload too much.
**Be very careful!!!**
Using CPU priorities to control scheduling can be helpful in some cases
to control which processes are getting more CPU time than others.
However, due to an issue called "[priority inversion][1]" it's possible that
using CPU priorities together with the many locks that are used within
Postgres cause the exact opposite behavior of what you intended. This
is why this PR only allows the PG superuser to change the CPU priority
of its own processes. Currently it's not recommended to set `citus.cpu_priority`
directly. Currently the only recommended interface for users is the setting
called `citus.cpu_priority_for_logical_replication_senders`. This setting
controls CPU priority for a very limited set of processes (the logical
replication senders). So, the dangers of priority inversion are also limited
with when using it for this usecase.
**Background**
Before reading the rest it's important to understand some basic
background regarding process CPU priorities, because they are a bit
counter intuitive. A lower priority value, means that the process will
be scheduled more and whatever it's doing will thus complete faster. The
default priority for processes is 0. Valid values are from -20 to 19
inclusive. On Linux a larger difference between values of two processes
will result in a bigger difference in percentage of scheduling.
**Handling the usecases**
Usecase 1 can be achieved by setting `citus.cpu_priority_for_logical_replication_senders`
to the priority value that you want it to have. It's necessary to set
this both on the workers and the coordinator. Example:
```
citus.cpu_priority_for_logical_replication_senders = -10
```
Usecase 2 can with this PR be achieved by running the following as
superuser. Note that this is only possible as superuser currently
due to the dangers mentioned in the "Be very carefull!!!" section.
And although this is possible it's **NOT** recommended:
```sql
ALTER USER background_job_user SET citus.cpu_priority = 5;
```
**OS configuration**
To actually make these settings work well it's important to run Postgres
with more a more permissive value for the 'nice' resource limit than
Linux will do by default. By default Linux will not allow a process to
set its priority lower than it currently is, even if it was lower when
the process originally started. This capability is necessary to reset
the CPU priority to its original value after a transaction finishes.
Depending on how you run Postgres this needs to be done in one of two
ways:
If you use systemd to start Postgres all you have to do is add a line
like this to the systemd service file:
```conf
LimitNice=+0 # the + is important, otherwise its interpreted incorrectly as 20
```
If that's not the case you'll have to configure `/etc/security/limits.conf`
like so, assuming that you are running Postgres as the `postgres` OS user:
```
postgres soft nice 0
postgres hard nice 0
```
Finally you'd have add the following line to `/etc/pam.d/common-session`
```
session required pam_limits.so
```
These settings would allow to change the priority back after setting it
to a higher value.
However, to actually allow you to set priorities even lower than the
default priority value you would need to change the values in the
config to something lower than 0. So for example:
```conf
LimitNice=-10
```
or
```
postgres soft nice -10
postgres hard nice -10
```
If you use WSL2 you'll likely have to do another thing. You have to
open a new shell, because when PAM is only used during login, and
WSL2 doesn't actually log you in. You can force a login like this:
```
sudo su $USER --shell /bin/bash
```
Source: https://stackoverflow.com/a/68322992/2570866
[1]: https://en.wikipedia.org/wiki/Priority_inversion
The long description of the `citus.distributed_deadlock_detection_factor`
setting was incorrectly stating that 1000 would disable it. Instead -1
is the value that disables distributed deadlock detection.
When introducing non-blocking shard split functionality it was based
heavily on the non-blocking shard moves. However, differences between
usage was slightly to big to be able to reuse the existing functions
easily. So, most logical replication code was simply copied to dedicated
shard split functions and modified for that purpose.
This PR tries to create a more generic logical replication
infrastructure that can be used by both shard splits and shard moves.
There's probably more code sharing possible in the future, but I believe
this is at least a good start and addresses the lowest hanging fruit.
This also adds a CreateSimpleHash function that makes creating the
most common type of hashmap common.
When using `citus.replicate_reference_tables_on_activate = off`,
reference tables need to be replicated later. This can be done using the
`replicate_reference_tables()` UDF. However, this function only allowed
blocking replication. This changes the function to default to logical
replication instead, and allows choosing any of our existing shard
transfer modes.
DESCRIPTION: Use faster custom copy logic for non-blocking shard moves
Non-blocking shard moves consist of two main phases:
1. Initial data copy
2. Catchup phase
This changes the first of these phases significantly. Previously we used the
copy logic provided by postgres subscriptions. This meant we didn't have
to implement it ourselves, but it came with the downside of little control.
When implementing shard splits we needed more control to even make it
work, so we implemented our own logic for copying data between nodes.
This PR starts using that logic for non-blocking shard moves. Doing so
has four main advantages:
1. It uses COPY in binary format when possible, which is cheaper to encode
and decode. Furthermore it very often results in less data that needs to
be sent over the network.
2. It allows us to create the primary key (or other replica identity) after doing
the initial data copy. This should give some speed up over the total run,
because creating an index is bulk is much faster than incrementally building it.
3. It doesn't require a replication slot per parallel copy. Increasing the maximum
number of replication slots uses resources in postgres, even if they are not used.
So reducing the number of replication slots that shard moves need is nice.
4. Logical replication table_sync workers are slow to start up, so if lots of shards
need to be copied that can make it quite slow. This can happen easily when
combining Postgres partitioning with Citus.
The new shard copy code that was created for shard splits has some
advantages over the old shard copy code. The old code was using
worker_append_table_to_shard, which wrote to disk twice. And it also
didn't use binary copy when that was possible. Both of these issues
were fixed in the new copy code. This PR starts using this new copy
logic also for shard moves, not just for shard splits.
On my local machine I created a single shard table like this.
```sql
set citus.shard_count = 1;
create table t(id bigint, a bigint);
select create_distributed_table('t', 'id');
INSERT into t(id, a) SELECT i, i from generate_series(1, 100000000) i;
```
I then turned `fsync` off to make sure I wasn't bottlenecked by disk.
Finally I moved this shard between nodes with `citus_move_shard_placement`
with `block_writes`.
Before this PR a move took ~127s, after this PR it took only ~38s. So for this
small test this resulted in spending ~70% less time.
And I also tried the same test for a table that contained large strings:
```sql
set citus.shard_count = 1;
create table t(id bigint, a bigint, content text);
select create_distributed_table('t', 'id');
INSERT into t(id, a, content) SELECT i, i, 'aunethautnehoautnheaotnuhetnohueoutnehotnuhetncouhaeohuaeochgrhgd.athbetndairgexdbuhaobulrhdbaetoausnetohuracehousncaoehuesousnaceohuenacouhancoexdaseohusnaetobuetnoduhasneouhaceohusnaoetcuhmsnaetohuacoeuhebtokteaoshetouhsanetouhaoug.lcuahesonuthaseauhcoerhuaoecuh.lg;rcydabsnetabuesabhenth' from generate_series(1, 20000000) i;
```
While testing 5670dffd33, I realized
that we have a missing RecordNonDistTableAccessesForTask() for
local utility commands.
Although we don't have to record the relation access for local
only cases, we really want to keep the behaviour for scale-out
be the same with single node on all aspects. We wouldn't want
any single node complex transaction to work on single machine,
but not on multi node cluster. Hence, we apply the same restrictions.
For example, on a distributed cluster, the following errors, and
after this commit this errors locally as well
```SQL
CREATE TABLE ref(a int primary key);
INSERT INTO ref VALUES (1);
CREATE TABLE dist(a int REFERENCES ref(a));
SELECT create_reference_table('ref');
SELECT create_distributed_table('dist', 'a');
BEGIN;
SELECT * FROM dist;
TRUNCATE ref CASCADE;
ERROR: cannot execute DDL on table "ref" because there was a parallel SELECT access to distributed table "dist" in the same transaction
HINT: Try re-running the transaction with "SET LOCAL citus.multi_shard_modify_mode TO 'sequential';"
COMMIT;
```
We also add the comprehensive test suite and run the same locally.
naisila
Jelte Fennema
aykut-bozkurt
Marco Slot
Teja Mupparti
Ahmet Gedemenli
Sameer Awasekar
aykutbozkurt
Onder Kalaci
Naisila Puka