`sets` v2 were not yet available when this module was written. Compared
to `gb_sets`, v2 `sets` are faster and more memory efficient:
> List = lists:seq(1, 50_000).
> tprof:profile(sets, from_list, [List, [{version, 2}]], #{type => call_memory}).
****** Process <0.94.0> -- 100.00% of total ***
FUNCTION CALLS WORDS PER CALL [ %]
maps:from_keys/2 1 184335 184335.00 [100.00]
184335 [ 100.0]
ok
> tprof:profile(gb_sets, from_list, [List], #{type => call_memory}).
****** Process <0.97.0> -- 100.00% of total ***
FUNCTION CALLS WORDS PER CALL [ %]
lists:rumergel/3 1 2 2.00 [ 0.00]
gb_sets:from_ordset/1 1 3 3.00 [ 0.00]
lists:reverse/2 1 100000 100000.00 [16.76]
lists:usplit_1/5 49999 100002 2.00 [16.76]
gb_sets:balance_list_1/2 65535 396605 6.05 [66.48]
596612 [100.0]
The `rabbit_mgmt_gc` gen_server performs garbage collections
periodically. When doing so it can create potentially fairly large
terms, for example by creating a set out of
`rabbit_exchange:list_names/0`. With many exchanges, for example, the
process memory usage can climb steadily especially when the management
agent is mostly idle since `rabbit_mgmt_gc` won't hit enough reductions
to cause a full-sweep GC on itself. Since the process is only active
periodically (once every 2min by default) we can hibernate it to GC the
terms it created.
This can save a medium amount of memory in situations where there are
very many pieces of metadata (exchanges, vhosts, queues, etc.). For
example on an idle single-node broker with 50k exchanges,
`rabbit_mgmt_gc` can hover around 50MB before being naturally GC'd. With
this patch the process memory usage stays consistent between `start_gc`
timer messages at around 1KB.
This avoids using Mix while compiling which simplifies
a number of things and let us do further build improvements
later on.
Elixir is only enabled from within rabbitmq_cli currently.
Eunit is disabled since there are only Elixir tests.
Dialyzer will force-enable Elixir in order to process
Elixir-compiled beam files.
This commit also includes a few changes that are
related:
* The Erlang distribution will now be started for parallel-ct
* Many unnecessary PROJECT_MOD lines have been removed
* `eunit_formatters` has been removed, it provides little value
* The new `maybe_flock` Erlang.mk function is used where possible
* Build test deps when testing rabbitmq_cli (Mix won't do it anymore)
* rabbitmq_ct_helpers now use the early plugins to have Dialyzer
properly set up
[Why]
Before this patch, required feature flags were basically checked during
boot: they must have been enabled when they were mere stable feature
flags. If they were not, the node refused to boot.
This was easy for the developer because making a feature flag required
allowed to remove the entire compatibility code. Very satisfying.
Unfortunately, this was a pain point to end users, especially those who
did not pay attention to RabbitMQ and the release notes and were just
asking their package manager to update everything. They could end up
with a node that refuse to boot. The only solution was to downgrade,
enable the disabled stable feature flags, upgrade again.
[How]
This patch introduces two levels of requirement to required feature
flags:
* `hard`: this corresponds to the existing behavior where a node will
refuse to boot if a hard required feature flag is not enabled before
the upgrade.
* `soft`: such a required feature flag will be automatically enabled
during the upgrade to a version where it is marked as required.
The level of requirement is set in the feature flag definition:
-rabbit_feature_flag(
{my_feature_flag,
#{stability => required,
require_level => hard
}}).
The default requirement level is `soft`. All existing required feature
flags have now a requirement level of `hard`.
The handling of soft required feature flag is done when the cluster
feature flags states are verified and synchronized. If a required
feature flag is not enabled yet, it is enabled at that time.
This means that as developers, we will have to keep compatibility code
forever for every soft required feature flag, like the feature flag
definition itself.
We don't need to duplicate so many patterns in so many
files since we have a monorepo (and want to keep it).
If I managed to miss something or remove something that
should stay, please put it back. Note that monorepo-wide
patterns should go in the top-level .gitignore file.
Other .gitignore files are for application or folder-
specific patterns.
They are no longer used.
This removes a couple file_handle_cache:info/1 calls.
We are not removing them from the HTTP API to avoid
breaking things unintentionally.
I noticed that `stop_app` would take over 5 seconds on an empty
node which is strange. I found this gap in the logs:
```
2024-04-18 10:49:04.646450+09:00 [info] <0.599.0> Management plugin: to stop collect_statistics.
2024-04-18 10:49:09.647652+09:00 [debug] <0.247.0> Set stop reason to: normal
```
No point waiting for that stats to stop being emitted when we stop the
node completely. It was added in https://github.com/rabbitmq/rabbitmq-server/commit/0e640da5
to ensure the stats stop when the management_agent gets disabled
## What
Similar to Native MQTT in #5895, this commits implements Native AMQP 1.0.
By "native", we mean do not proxy via AMQP 0.9.1 anymore.
## Why
Native AMQP 1.0 comes with the following major benefits:
1. Similar to Native MQTT, this commit provides better throughput, latency,
scalability, and resource usage for AMQP 1.0.
See https://blog.rabbitmq.com/posts/2023/03/native-mqtt for native MQTT improvements.
See further below for some benchmarks.
2. Since AMQP 1.0 is not limited anymore by the AMQP 0.9.1 protocol,
this commit allows implementing more AMQP 1.0 features in the future.
Some features are already implemented in this commit (see next section).
3. Simpler, better understandable, and more maintainable code.
Native AMQP 1.0 as implemented in this commit has the
following major benefits compared to AMQP 0.9.1:
4. Memory and disk alarms will only stop accepting incoming TRANSFER frames.
New connections can still be created to consume from RabbitMQ to empty queues.
5. Due to 4. no need anymore for separate connections for publishers and
consumers as we currently recommended for AMQP 0.9.1. which potentially
halves the number of physical TCP connections.
6. When a single connection sends to multiple target queues, a single
slow target queue won't block the entire connection.
Publisher can still send data quickly to all other target queues.
7. A publisher can request whether it wants publisher confirmation on a per-message basis.
In AMQP 0.9.1 publisher confirms are configured per channel only.
8. Consumers can change their "prefetch count" dynamically which isn't
possible in our AMQP 0.9.1 implementation. See #10174
9. AMQP 1.0 is an extensible protocol
This commit also fixes dozens of bugs present in the AMQP 1.0 plugin in
RabbitMQ 3.x - most of which cannot be backported due to the complexity
and limitations of the old 3.x implementation.
This commit contains breaking changes and is therefore targeted for RabbitMQ 4.0.
## Implementation details
1. Breaking change: With Native AMQP, the behaviour of
```
Convert AMQP 0.9.1 message headers to application properties for an AMQP 1.0 consumer
amqp1_0.convert_amqp091_headers_to_app_props = false | true (default false)
Convert AMQP 1.0 Application Properties to AMQP 0.9.1 headers
amqp1_0.convert_app_props_to_amqp091_headers = false | true (default false)
```
will break because we always convert according to the message container conversions.
For example, AMQP 0.9.1 x-headers will go into message-annotations instead of application properties.
Also, `false` won’t be respected since we always convert the headers with message containers.
2. Remove rabbit_queue_collector
rabbit_queue_collector is responsible for synchronously deleting
exclusive queues. Since the AMQP 1.0 plugin never creates exclusive
queues, rabbit_queue_collector doesn't need to be started in the first
place. This will save 1 Erlang process per AMQP 1.0 connection.
3. 7 processes per connection + 1 process per session in this commit instead of
7 processes per connection + 15 processes per session in 3.x
Supervision hierarchy got re-designed.
4. Use 1 writer process per AMQP 1.0 connection
AMQP 0.9.1 uses a separate rabbit_writer Erlang process per AMQP 0.9.1 channel.
Prior to this commit, AMQP 1.0 used a separate rabbit_amqp1_0_writer process per AMQP 1.0 session.
Advantage of single writer proc per session (prior to this commit):
* High parallelism for serialising packets if multiple sessions within
a connection write heavily at the same time.
This commit uses a single writer process per AMQP 1.0 connection that is
shared across all AMQP 1.0 sessions.
Advantages of single writer proc per connection (this commit):
* Lower memory usage with hundreds of thousands of AMQP 1.0 sessions
* Less TCP and IP header overhead given that the single writer process
can accumulate across all sessions bytes before flushing the socket.
In other words, this commit decides that a reader / writer process pair
per AMQP 1.0 connection is good enough for bi-directional TRANSFER flows.
Having a writer per session is too heavy.
We still ensure high throughput by having separate reader, writer, and
session processes.
5. Transform rabbit_amqp1_0_writer into gen_server
Why:
Prior to this commit, when clicking on the AMQP 1.0 writer process in
observer, the process crashed.
Instead of handling all these debug messages of the sys module, it's better
to implement a gen_server.
There is no advantage of using a special OTP process over gen_server
for the AMQP 1.0 writer.
gen_server also provides cleaner format status output.
How:
Message callbacks return a timeout of 0.
After all messages in the inbox are processed, the timeout message is
handled by flushing any pending bytes.
6. Remove stats timer from writer
AMQP 1.0 connections haven't emitted any stats previously.
7. When there are contiguous queue confirmations in the session process
mailbox, batch them. When the confirmations are sent to the publisher, a
single DISPOSITION frame is sent for contiguously confirmed delivery
IDs.
This approach should be good enough. However it's sub optimal in
scenarios where contiguous delivery IDs that need confirmations are rare,
for example:
* There are multiple links in the session with different sender
settlement modes and sender publishes across these links interleaved.
* sender settlement mode is mixed and sender publishes interleaved settled
and unsettled TRANSFERs.
8. Introduce credit API v2
Why:
The AMQP 0.9.1 credit extension which is to be removed in 4.0 was poorly
designed since basic.credit is a synchronous call into the queue process
blocking the entire AMQP 1.0 session process.
How:
Change the interactions between queue clients and queue server
implementations:
* Clients only request a credit reply if the FLOW's `echo` field is set
* Include all link flow control state held by the queue process into a
new credit_reply queue event:
* `available` after the queue sends any deliveries
* `link-credit` after the queue sends any deliveries
* `drain` which allows us to combine the old queue events
send_credit_reply and send_drained into a single new queue event
credit_reply.
* Include the consumer tag into the credit_reply queue event such that
the AMQP 1.0 session process can process any credit replies
asynchronously.
Link flow control state `delivery-count` also moves to the queue processes.
The new interactions are hidden behind feature flag credit_api_v2 to
allow for rolling upgrades from 3.13 to 4.0.
9. Use serial number arithmetic in quorum queues and session process.
10. Completely bypass the rabbit_limiter module for AMQP 1.0
flow control. The goal is to eventually remove the rabbit_limiter module
in 4.0 since AMQP 0.9.1 global QoS will be unsupported in 4.0. This
commit lifts the AMQP 1.0 link flow control logic out of rabbit_limiter
into rabbit_queue_consumers.
11. Fix credit bug for streams:
AMQP 1.0 settlements shouldn't top up link credit,
only FLOW frames should top up link credit.
12. Allow sender settle mode unsettled for streams
since AMQP 1.0 acknowledgements to streams are no-ops (currently).
13. Fix AMQP 1.0 client bugs
Auto renewing credits should not be related to settling TRANSFERs.
Remove field link_credit_unsettled as it was wrong and confusing.
Prior to this commit auto renewal did not work when the sender uses
sender settlement mode settled.
14. Fix AMQP 1.0 client bugs
The wrong outdated Link was passed to function auto_flow/2
15. Use osiris chunk iterator
Only hold messages of uncompressed sub batches in memory if consumer
doesn't have sufficient credits.
Compressed sub batches are skipped for non Stream protocol consumers.
16. Fix incoming link flow control
Always use confirms between AMQP 1.0 queue clients and queue servers.
As already done internally by rabbit_fifo_client and
rabbit_stream_queue, use confirms for classic queues as well.
17. Include link handle into correlation when publishing messages to target queues
such that session process can correlate confirms from target queues to
incoming links.
18. Only grant more credits to publishers if publisher hasn't sufficient credits
anymore and there are not too many unconfirmed messages on the link.
19. Completely ignore `block` and `unblock` queue actions and RabbitMQ credit flow
between classic queue process and session process.
20. Link flow control is independent between links.
A client can refer to a queue or to an exchange with multiple
dynamically added target queues. Multiple incoming links can also fan
in to the same queue. However the link topology looks like, this
commit ensures that each link is only granted more credits if that link
isn't overloaded.
21. A connection or a session can send to many different queues.
In AMQP 0.9.1, a single slow queue will lead to the entire channel, and
then entire connection being blocked.
This commit makes sure that a single slow queue from one link won't slow
down sending on other links.
For example, having link A sending to a local classic queue and
link B sending to 5 replica quorum queue, link B will naturally
grant credits slower than link A. So, despite the quorum queue being
slower in confirming messages, the same AMQP 1.0 connection and session
can still pump data very fast into the classic queue.
22. If cluster wide memory or disk alarm occurs.
Each session sends a FLOW with incoming-window to 0 to sending client.
If sending clients don’t obey, force disconnect the client.
If cluster wide memory alarm clears:
Each session resumes with a FLOW defaulting to initial incoming-window.
23. All operations apart of publishing TRANSFERS to RabbitMQ can continue during cluster wide alarms,
specifically, attaching consumers and consuming, i.e. emptying queues.
There is no need for separate AMQP 1.0 connections for publishers and consumers as recommended in our AMQP 0.9.1 implementation.
24. Flow control summary:
* If queue becomes bottleneck, that’s solved by slowing down individual sending links (AMQP 1.0 link flow control).
* If session becomes bottleneck (more unlikely), that’s solved by AMQP 1.0 session flow control.
* If connection becomes bottleneck, it naturally won’t read fast enough from the socket causing TCP backpressure being applied.
Nowhere will RabbitMQ internal credit based flow control (i.e. module credit_flow) be used on the incoming AMQP 1.0 message path.
25. Register AMQP sessions
Prefer local-only pg over our custom pg_local implementation as
pg is a better process group implementation than pg_local.
pg_local was identified as bottleneck in tests where many MQTT clients were disconnected at once.
26. Start a local-only pg when Rabbit boots:
> A scope can be kept local-only by using a scope name that is unique cluster-wide, e.g. the node name:
> pg:start_link(node()).
Register AMQP 1.0 connections and sessions with pg.
In future we should remove pg_local and instead use the new local-only
pg for all registered processes such as AMQP 0.9.1 connections and channels.
27. Requeue messages if link detached
Although the spec allows to settle delivery IDs on detached links, RabbitMQ does not respect the 'closed'
field of the DETACH frame and therefore handles every DETACH frame as closed. Since the link is closed,
we expect every outstanding delivery to be requeued.
In addition to consumer cancellation, detaching a link therefore causes in flight deliveries to be requeued.
Note that this behaviour is different from merely consumer cancellation in AMQP 0.9.1:
"After a consumer is cancelled there will be no future deliveries dispatched to it. Note that there can
still be "in flight" deliveries dispatched previously. Cancelling a consumer will neither discard nor requeue them."
[https://www.rabbitmq.com/consumers.html#unsubscribing]
An AMQP receiver can first drain, and then detach to prevent "in flight" deliveries
28. Init AMQP session with BEGIN frame
Similar to how there can't be an MQTT processor without a CONNECT
frame, there can't be an AMQP session without a BEGIN frame.
This allows having strict dialyzer types for session flow control
fields (i.e. not allowing 'undefined').
29. Move serial_number to AMQP 1.0 common lib
such that it can be used by both AMQP 1.0 server and client
30. Fix AMQP client to do serial number arithmetic.
31. AMQP client: Differentiate between delivery-id and transfer-id for better
understandability.
32. Fix link flow control in classic queues
This commit fixes
```
java -jar target/perf-test.jar -ad false -f persistent -u cq -c 3000 -C 1000000 -y 0
```
followed by
```
./omq -x 0 amqp -T /queue/cq -D 1000000 --amqp-consumer-credits 2
```
Prior to this commit, (and on RabbitMQ 3.x) the consuming would halt after around
8 - 10,000 messages.
The bug was that in flight messages from classic queue process to
session process were not taken into account when topping up credit to
the classic queue process.
Fixes#2597
The solution to this bug (and a much cleaner design anyway independent of
this bug) is that queues should hold all link flow control state including
the delivery-count.
Hence, when credit API v2 is used the delivery-count will be held by the
classic queue process, quorum queue process, and stream queue client
instead of managing the delivery-count in the session.
33. The double level crediting between (a) session process and
rabbit_fifo_client, and (b) rabbit_fifo_client and rabbit_fifo was
removed. Therefore, instead of managing 3 separate delivery-counts (i. session,
ii. rabbit_fifo_client, iii. rabbit_fifo), only 1 delivery-count is used
in rabbit_fifo. This is a big simplification.
34. This commit fixes quorum queues without bumping the machine version
nor introducing new rabbit_fifo commands.
Whether credit API v2 is used is solely determined at link attachment time
depending on whether feature flag credit_api_v2 is enabled.
Even when that feature flag will be enabled later on, this link will
keep using credit API v1 until detached (or the node is shut down).
Eventually, after feature flag credit_api_v2 has been enabled and a
subsequent rolling upgrade, all links will use credit API v2.
This approach is safe and simple.
The 2 alternatives to move delivery-count from the session process to the
queue processes would have been:
i. Explicit feature flag credit_api_v2 migration function
* Can use a gen_server:call and only finish migration once all delivery-counts were migrated.
Cons:
* Extra new message format just for migration is required.
* Risky as migration will fail if a target queue doesn’t reply.
ii. Session always includes DeliveryCountSnd when crediting to the queue:
Cons:
* 2 delivery counts will be hold simultaneously in session proc and queue proc;
could be solved by deleting the session proc’s delivery-count for credit-reply
* What happens if the receiver doesn’t provide credit for a very long time? Is that a problem?
35. Support stream filtering in AMQP 1.0 (by @acogoluegnes)
Use the x-stream-filter-value message annotation
to carry the filter value in a published message.
Use the rabbitmq:stream-filter and rabbitmq:stream-match-unfiltered
filters when creating a receiver that wants to filter
out messages from a stream.
36. Remove credit extension from AMQP 0.9.1 client
37. Support maintenance mode closing AMQP 1.0 connections.
38. Remove AMQP 0.9.1 client dependency from AMQP 1.0 implementation.
39. Move AMQP 1.0 plugin to the core. AMQP 1.0 is enabled by default.
The old rabbitmq_amqp1_0 plugin will be kept as a no-op plugin to prevent deployment
tools from failing that execute:
```
rabbitmq-plugins enable rabbitmq_amqp1_0
rabbitmq-plugins disable rabbitmq_amqp1_0
```
40. Breaking change: Remove CLI command `rabbitmqctl list_amqp10_connections`.
Instead, list both AMQP 0.9.1 and AMQP 1.0 connections in `list_connections`:
```
rabbitmqctl list_connections protocol
Listing connections ...
protocol
{1, 0}
{0,9,1}
```
## Benchmarks
### Throughput & Latency
Setup:
* Single node Ubuntu 22.04
* Erlang 26.1.1
Start RabbitMQ:
```
make run-broker PLUGINS="rabbitmq_management rabbitmq_amqp1_0" FULL=1 RABBITMQ_SERVER_ADDITIONAL_ERL_ARGS="+S 3"
```
Predeclare durable classic queue cq1, durable quorum queue qq1, durable stream queue sq1.
Start client:
https://github.com/ssorj/quiverhttps://hub.docker.com/r/ssorj/quiver/tags (digest 453a2aceda64)
```
docker run -it --rm --add-host host.docker.internal:host-gateway ssorj/quiver:latest
bash-5.1# quiver --version
quiver 0.4.0-SNAPSHOT
```
1. Classic queue
```
quiver //host.docker.internal//amq/queue/cq1 --durable --count 1m --duration 10m --body-size 12 --credit 1000
```
This commit:
```
Count ............................................. 1,000,000 messages
Duration ............................................... 73.8 seconds
Sender rate .......................................... 13,548 messages/s
Receiver rate ........................................ 13,547 messages/s
End-to-end rate ...................................... 13,547 messages/s
Latencies by percentile:
0% ........ 0 ms 90.00% ........ 9 ms
25% ........ 2 ms 99.00% ....... 14 ms
50% ........ 4 ms 99.90% ....... 17 ms
100% ....... 26 ms 99.99% ....... 24 ms
```
RabbitMQ 3.x (main branch as of 30 January 2024):
```
---------------------- Sender ----------------------- --------------------- Receiver ---------------------- --------
Time [s] Count [m] Rate [m/s] CPU [%] RSS [M] Time [s] Count [m] Rate [m/s] CPU [%] RSS [M] Lat [ms]
----------------------------------------------------- ----------------------------------------------------- --------
2.1 130,814 65,342 6 73.6 2.1 3,217 1,607 0 8.0 511
4.1 163,580 16,367 2 74.1 4.1 3,217 0 0 8.0 0
6.1 229,114 32,767 3 74.1 6.1 3,217 0 0 8.0 0
8.1 261,880 16,367 2 74.1 8.1 67,874 32,296 8 8.2 7,662
10.1 294,646 16,367 2 74.1 10.1 67,874 0 0 8.2 0
12.1 360,180 32,734 3 74.1 12.1 67,874 0 0 8.2 0
14.1 392,946 16,367 3 74.1 14.1 68,604 365 0 8.2 12,147
16.1 458,480 32,734 3 74.1 16.1 68,604 0 0 8.2 0
18.1 491,246 16,367 2 74.1 18.1 68,604 0 0 8.2 0
20.1 556,780 32,767 4 74.1 20.1 68,604 0 0 8.2 0
22.1 589,546 16,375 2 74.1 22.1 68,604 0 0 8.2 0
receiver timed out
24.1 622,312 16,367 2 74.1 24.1 68,604 0 0 8.2 0
quiver: error: PlanoProcessError: Command 'quiver-arrow receive //host.docker.internal//amq/queue/cq1 --impl qpid-proton-c --duration 10m --count 1m --rate 0 --body-size 12 --credit 1000 --transaction-size 0 --timeout 10 --durable --output /tmp/quiver-otujr23y' returned non-zero exit status 1.
Traceback (most recent call last):
File "/usr/local/lib/quiver/python/quiver/pair.py", line 144, in run
_plano.wait(receiver, check=True)
File "/usr/local/lib/quiver/python/plano/main.py", line 1243, in wait
raise PlanoProcessError(proc)
plano.main.PlanoProcessError: Command 'quiver-arrow receive //host.docker.internal//amq/queue/cq1 --impl qpid-proton-c --duration 10m --count 1m --rate 0 --body-size 12 --credit 1000 --transaction-size 0 --timeout 10 --durable --output /tmp/quiver-otujr23y' returned non-zero exit status 1.
```
2. Quorum queue:
```
quiver //host.docker.internal//amq/queue/qq1 --durable --count 1m --duration 10m --body-size 12 --credit 1000
```
This commit:
```
Count ............................................. 1,000,000 messages
Duration .............................................. 101.4 seconds
Sender rate ........................................... 9,867 messages/s
Receiver rate ......................................... 9,868 messages/s
End-to-end rate ....................................... 9,865 messages/s
Latencies by percentile:
0% ....... 11 ms 90.00% ....... 23 ms
25% ....... 15 ms 99.00% ....... 28 ms
50% ....... 18 ms 99.90% ....... 33 ms
100% ....... 49 ms 99.99% ....... 47 ms
```
RabbitMQ 3.x:
```
---------------------- Sender ----------------------- --------------------- Receiver ---------------------- --------
Time [s] Count [m] Rate [m/s] CPU [%] RSS [M] Time [s] Count [m] Rate [m/s] CPU [%] RSS [M] Lat [ms]
----------------------------------------------------- ----------------------------------------------------- --------
2.1 130,814 65,342 9 69.9 2.1 18,430 9,206 5 7.6 1,221
4.1 163,580 16,375 5 70.2 4.1 18,867 218 0 7.6 2,168
6.1 229,114 32,767 6 70.2 6.1 18,867 0 0 7.6 0
8.1 294,648 32,734 7 70.2 8.1 18,867 0 0 7.6 0
10.1 360,182 32,734 6 70.2 10.1 18,867 0 0 7.6 0
12.1 425,716 32,767 6 70.2 12.1 18,867 0 0 7.6 0
receiver timed out
14.1 458,482 16,367 5 70.2 14.1 18,867 0 0 7.6 0
quiver: error: PlanoProcessError: Command 'quiver-arrow receive //host.docker.internal//amq/queue/qq1 --impl qpid-proton-c --duration 10m --count 1m --rate 0 --body-size 12 --credit 1000 --transaction-size 0 --timeout 10 --durable --output /tmp/quiver-b1gcup43' returned non-zero exit status 1.
Traceback (most recent call last):
File "/usr/local/lib/quiver/python/quiver/pair.py", line 144, in run
_plano.wait(receiver, check=True)
File "/usr/local/lib/quiver/python/plano/main.py", line 1243, in wait
raise PlanoProcessError(proc)
plano.main.PlanoProcessError: Command 'quiver-arrow receive //host.docker.internal//amq/queue/qq1 --impl qpid-proton-c --duration 10m --count 1m --rate 0 --body-size 12 --credit 1000 --transaction-size 0 --timeout 10 --durable --output /tmp/quiver-b1gcup43' returned non-zero exit status 1.
```
3. Stream:
```
quiver-arrow send //host.docker.internal//amq/queue/sq1 --durable --count 1m -d 10m --summary --verbose
```
This commit:
```
Count ............................................. 1,000,000 messages
Duration ................................................ 8.7 seconds
Message rate ........................................ 115,154 messages/s
```
RabbitMQ 3.x:
```
Count ............................................. 1,000,000 messages
Duration ............................................... 21.2 seconds
Message rate ......................................... 47,232 messages/s
```
### Memory usage
Start RabbitMQ:
```
ERL_MAX_PORTS=3000000 RABBITMQ_SERVER_ADDITIONAL_ERL_ARGS="+P 3000000 +S 6" make run-broker PLUGINS="rabbitmq_amqp1_0" FULL=1 RABBITMQ_CONFIG_FILE="rabbitmq.conf"
```
```
/bin/cat rabbitmq.conf
tcp_listen_options.sndbuf = 2048
tcp_listen_options.recbuf = 2048
vm_memory_high_watermark.relative = 0.95
vm_memory_high_watermark_paging_ratio = 0.95
loopback_users = none
```
Create 50k connections with 2 sessions per connection, i.e. 100k session in total:
```go
package main
import (
"context"
"log"
"time"
"github.com/Azure/go-amqp"
)
func main() {
for i := 0; i < 50000; i++ {
conn, err := amqp.Dial(context.TODO(), "amqp://nuc", &amqp.ConnOptions{SASLType: amqp.SASLTypeAnonymous()})
if err != nil {
log.Fatal("dialing AMQP server:", err)
}
_, err = conn.NewSession(context.TODO(), nil)
if err != nil {
log.Fatal("creating AMQP session:", err)
}
_, err = conn.NewSession(context.TODO(), nil)
if err != nil {
log.Fatal("creating AMQP session:", err)
}
}
log.Println("opened all connections")
time.Sleep(5 * time.Hour)
}
```
This commit:
```
erlang:memory().
[{total,4586376480},
{processes,4025898504},
{processes_used,4025871040},
{system,560477976},
{atom,1048841},
{atom_used,1042841},
{binary,233228608},
{code,21449982},
{ets,108560464}]
erlang:system_info(process_count).
450289
```
7 procs per connection + 1 proc per session.
(7 + 2*1) * 50,000 = 450,000 procs
RabbitMQ 3.x:
```
erlang:memory().
[{total,15168232704},
{processes,14044779256},
{processes_used,14044755120},
{system,1123453448},
{atom,1057033},
{atom_used,1052587},
{binary,236381264},
{code,21790238},
{ets,391423744}]
erlang:system_info(process_count).
1850309
```
7 procs per connection + 15 per session
(7 + 2*15) * 50,000 = 1,850,000 procs
50k connections + 100k session require
with this commit: 4.5 GB
in RabbitMQ 3.x: 15 GB
## Future work
1. More efficient parser and serializer
2. TODO in mc_amqp: Do not store the parsed message on disk.
3. Implement both AMQP HTTP extension and AMQP management extension to allow AMQP
clients to create RabbitMQ objects (queues, exchanges, ...).
Listing queues with the HTTP API when there are many (1000s) of
quorum queues could be excessively slow compared to the same scenario
with classic queues.
This optimises various aspects of HTTP API queue listings.
For QQs it removes the expensive cluster wide rpcs used to get the
"online" status of each quorum queue. This was previously done _before_
paging and thus would perform a cluster-wide query for _each_ quorum queue in
the vhost/system. This accounted for most of the slowness compared to
classic queues.
Secondly the query to separate the running from the down queues
consisted of two separate queries that later were combined when a single
query would have sufficed.
This commit also includes a variety of other improvements and minor
fixes discovered during testing and optimisation.
MINOR BREAKING CHANGE: quorum queues would previously only display one
of two states: running or down. Now there is a new state called minority
which is emitted when the queue has at least one member running but
cannot commit entries due to lack of quorum.
Also the quorum queue may transiently enter the down state when a node
goes down and before its elected a new leader.
Introduce GET /api/queues/detailed endpoint
Just removed garbage_collection, idle_since and any 'null' value
/api/queues with 10k classic queues returns 7.4MB of data
/api/queues/detailed with 10k classic queues returns 11MB of data
This sits behind a new feature flag, required to collect data from
all nodes: detailed_queues_endpoint
A previous PR removed backing_queue_status as it is mostly unused,
but classic queue version is still useful. This PR returns version
as a top-level key in queue objects.
[Why]
Mnesia is a very powerful and convenient tool for Erlang applications:
it is a persistent disc-based database, it handles replication accross
multiple Erlang nodes and it is available out-of-the-box from the
Erlang/OTP distribution. RabbitMQ relies on Mnesia to manage all its
metadata:
* virtual hosts' properties
* intenal users
* queue, exchange and binding declarations (not queues data)
* runtime parameters and policies
* ...
Unfortunately Mnesia makes it difficult to handle network partition and,
as a consequence, the merge conflicts between Erlang nodes once the
network partition is resolved. RabbitMQ provides several partition
handling strategies but they are not bullet-proof. Users still hit
situations where it is a pain to repair a cluster following a network
partition.
[How]
@kjnilsson created Ra [1], a Raft consensus library that RabbitMQ
already uses successfully to implement quorum queues and streams for
instance. Those queues do not suffer from network partitions.
We created Khepri [2], a new persistent and replicated database engine
based on Ra and we want to use it in place of Mnesia in RabbitMQ to
solve the problems with network partitions.
This patch integrates Khepri as an experimental feature. When enabled,
RabbitMQ will store all its metadata in Khepri instead of Mnesia.
This change comes with behavior changes. While Khepri remains disabled,
you should see no changes to the behavior of RabbitMQ. If there are
changes, it is a bug. After Khepri is enabled, there are significant
changes of behavior that you should be aware of.
Because it is based on the Raft consensus algorithm, when there is a
network partition, only the cluster members that are in the partition
with at least `(Number of nodes in the cluster ÷ 2) + 1` number of nodes
can "make progress". In other words, only those nodes may write to the
Khepri database and read from the database and expect a consistent
result.
For instance in a cluster of 5 RabbitMQ nodes:
* If there are two partitions, one with 3 nodes, one with 2 nodes, only
the group of 3 nodes will be able to write to the database.
* If there are three partitions, two with 2 nodes, one with 1 node, none
of the group can write to the database.
Because the Khepri database will be used for all kind of metadata, it
means that RabbitMQ nodes that can't write to the database will be
unable to perform some operations. A list of operations and what to
expect is documented in the associated pull request and the RabbitMQ
website.
This requirement from Raft also affects the startup of RabbitMQ nodes in
a cluster. Indeed, at least a quorum number of nodes must be started at
once to allow nodes to become ready.
To enable Khepri, you need to enable the `khepri_db` feature flag:
rabbitmqctl enable_feature_flag khepri_db
When the `khepri_db` feature flag is enabled, the migration code
performs the following two tasks:
1. It synchronizes the Khepri cluster membership from the Mnesia
cluster. It uses `mnesia_to_khepri:sync_cluster_membership/1` from
the `khepri_mnesia_migration` application [3].
2. It copies data from relevant Mnesia tables to Khepri, doing some
conversion if necessary on the way. Again, it uses
`mnesia_to_khepri:copy_tables/4` from `khepri_mnesia_migration` to do
it.
This can be performed on a running standalone RabbitMQ node or cluster.
Data will be migrated from Mnesia to Khepri without any service
interruption. Note that during the migration, the performance may
decrease and the memory footprint may go up.
Because this feature flag is considered experimental, it is not enabled
by default even on a brand new RabbitMQ deployment.
More about the implementation details below:
In the past months, all accesses to Mnesia were isolated in a collection
of `rabbit_db*` modules. This is where the integration of Khepri mostly
takes place: we use a function called `rabbit_khepri:handle_fallback/1`
which selects the database and perform the query or the transaction.
Here is an example from `rabbit_db_vhost`:
* Up until RabbitMQ 3.12.x:
get(VHostName) when is_binary(VHostName) ->
get_in_mnesia(VHostName).
* Starting with RabbitMQ 3.13.0:
get(VHostName) when is_binary(VHostName) ->
rabbit_khepri:handle_fallback(
#{mnesia => fun() -> get_in_mnesia(VHostName) end,
khepri => fun() -> get_in_khepri(VHostName) end}).
This `rabbit_khepri:handle_fallback/1` function relies on two things:
1. the fact that the `khepri_db` feature flag is enabled, in which case
it always executes the Khepri-based variant.
4. the ability or not to read and write to Mnesia tables otherwise.
Before the feature flag is enabled, or during the migration, the
function will try to execute the Mnesia-based variant. If it succeeds,
then it returns the result. If it fails because one or more Mnesia
tables can't be used, it restarts from scratch: it means the feature
flag is being enabled and depending on the outcome, either the
Mnesia-based variant will succeed (the feature flag couldn't be enabled)
or the feature flag will be marked as enabled and it will call the
Khepri-based variant. The meat of this function really lives in the
`khepri_mnesia_migration` application [3] and
`rabbit_khepri:handle_fallback/1` is a wrapper on top of it that knows
about the feature flag.
However, some calls to the database do not depend on the existence of
Mnesia tables, such as functions where we need to learn about the
members of a cluster. For those, we can't rely on exceptions from
Mnesia. Therefore, we just look at the state of the feature flag to
determine which database to use. There are two situations though:
* Sometimes, we need the feature flag state query to block because the
function interested in it can't return a valid answer during the
migration. Here is an example:
case rabbit_khepri:is_enabled(RemoteNode) of
true -> can_join_using_khepri(RemoteNode);
false -> can_join_using_mnesia(RemoteNode)
end
* Sometimes, we need the feature flag state query to NOT block (for
instance because it would cause a deadlock). Here is an example:
case rabbit_khepri:get_feature_state() of
enabled -> members_using_khepri();
_ -> members_using_mnesia()
end
Direct accesses to Mnesia still exists. They are limited to code that is
specific to Mnesia such as classic queue mirroring or network partitions
handling strategies.
Now, to discover the Mnesia tables to migrate and how to migrate them,
we use an Erlang module attribute called
`rabbit_mnesia_tables_to_khepri_db` which indicates a list of Mnesia
tables and an associated converter module. Here is an example in the
`rabbitmq_recent_history_exchange` plugin:
-rabbit_mnesia_tables_to_khepri_db(
[{?RH_TABLE, rabbit_db_rh_exchange_m2k_converter}]).
The converter module — `rabbit_db_rh_exchange_m2k_converter` in this
example — is is fact a "sub" converter module called but
`rabbit_db_m2k_converter`. See the documentation of a `mnesia_to_khepri`
converter module to learn more about these modules.
[1] https://github.com/rabbitmq/ra
[2] https://github.com/rabbitmq/khepri
[3] https://github.com/rabbitmq/khepri_mnesia_migration
See #7206.
Co-authored-by: Jean-Sébastien Pédron <jean-sebastien@rabbitmq.com>
Co-authored-by: Diana Parra Corbacho <dparracorbac@vmware.com>
Co-authored-by: Michael Davis <mcarsondavis@gmail.com>
If a user does not have `handle.exe` installed in the `PATH` of their
Windows system, a message will be logged once, and then the total
handles being used will be set to `0`.
Fixes#8700
Follow-up to:
* #6614
* #6613
* #8541
* Check additional applications when comparing bazel and make results
* Sync bazel/make for amqp_client
* Do not fail-fast in build system comparison
* promethus -> prometheus
* Regenerate BUILD.redbug
* When comparing build systems & .app files ignore empty 'registered'
It's listed as a required key in
https://www.erlang.org/doc/man/app.html, but the same docs state the
default is "[]". It seems to ignore it if it's empty.
* Copy bazel/BUILD.osiris from BUILD.bazel in the osiris repo
Normally it would be generated with `bazel run gazelle-update-repos --
-args osiris@1.5.1=github.com/rabbitmq/osiris@v1.5.1`, but in this
case we just want to match it's compilation with erlang.mk with some
manual tweaks.
* Use elixir 1.15, otherwise mix format fails
* Sync bazel/make for rabbitmq_web_dispatch, rabbitmq_management_agent
[Why]
Management metrics collection will be removed in RabbitMQ 4.0. The
prometheus plugin provides a better and more scalable alternative.
[How]
The management metrics collection is marked as deprecated in the code
using the Deprecated features subsystem (based on feature flags). See
pull request #7390 for a description of that subsystem.
To test RabbitMQ behavior as if the feature was removed, the following
configuration setting can be used:
deprecated_features.permit.management_metrics_collection = false
Management metrics collection can be turned off anytime, there are no
conditions to do that.
Once management metrics collection is turned off, the management API
will not report any metrics and the UI will show empty graphs.
Note that given the marketing calendar, the deprecated feature will go
directly from "permitted by default" to "removed" in RabbitMQ 4.0. It
won't go through the gradual deprecation process.
Iliia Khaprov
Michael Davis
Michael Klishin
Razvan Grigore
Loïc Hoguin
Aitor Perez
Ayanda Dube
Jean-Sébastien Pédron
Karl Nilsson
Marcial Rosales
Rin Kuryloski
Diana Parra Corbacho
Michal Kuratczyk
Luke Bakken
David Ansari
Michael Klishin
Simon Unge
Rin Kuryloski
Iliia Khaprov