This reverts commit dbb3a90fe6.
The org.apache.activemq.artemis.core.server.Queue#getRate method is for
slow-consumer detection and is designed for internal use only.
Furthermore, it's too opaque to be trusted by a remote user as it only
returns the number of message added to the queue since *the last time
it was called*. The problem here is that the user calling it doesn't
know when it was invoked last. Therefore, they could be getting the
rate of messages added for the last 5 minutes or the last 5
milliseconds. This can lead to inconsistent and misleading results.
There are three main ways for users to track rates of message
production and consumption:
1. Use a metrics plugin. This is the most feature-rich and flexible
way to track broker metrics, although it requires tools (e.g.
Prometheus) to store the metrics and display them (e.g. Grafana).
2. Invoke the getMessageCount() and getMessagesAdded() management
methods and store the returned values along with the time they were
retrieved. A time-series database is a great tool for this job. This is
exactly what tools like Prometheus do. That data can then be used to
create informative graphs, etc. using tools like Grafana. Of course, one
can skip all the tools and just do some simple math to calculate rates
based on the last time the counts were retrieved.
3. Use the broker's message counters. Message counters are the broker's
simple way of providing historical information about the queue. They
provide similar results to the previous solutions, but with less
flexibility since they only track data while the broker is up and
there's not really any good options for graphing.
Both authentication and authorization will hit the underlying security
repository (e.g. files, LDAP, etc.). For example, creating a JMS
connection and a consumer will result in 2 hits with the *same*
authentication request. This can cause unwanted (and unnecessary)
resource utilization, especially in the case of networked configuration
like LDAP.
There is already a rudimentary cache for authorization, but it is
cleared *totally* every 10 seconds by default (controlled via the
security-invalidation-interval setting), and it must be populated
initially which still results in duplicate auth requests.
This commit optimizes authentication and authorization via the following
changes:
- Replace our home-grown cache with Google Guava's cache. This provides
simple caching with both time-based and size-based LRU eviction. See more
at https://github.com/google/guava/wiki/CachesExplained. I also thought
about using Caffeine, but we already have a dependency on Guava and the
cache implementions look to be negligibly different for this use-case.
- Add caching for authentication. Both successful and unsuccessful
authentication attempts will be cached to spare the underlying security
repository as much as possible. Authenticated Subjects will be cached
and re-used whenever possible.
- Authorization will used Subjects cached during authentication. If the
required Subject is not in the cache it will be fetched from the
underlying security repo.
- Caching can be disabled by setting the security-invalidation-interval
to 0.
- Cache sizes are configurable.
- Management operations exist to inspect cache sizes at runtime.
HumanReadableByteCountTest test is no longer failing under environments with locales defining different number format.
The function now returns values according to the Locale.ROOT locale specification.
- when sending messages to DLQ or Expiry we now use x-opt legal names
- we now support filtering thorugh annotations if using m. as a prefix.
- enabling hyphenated_props: to allow m. as a prefix
This commit does the following:
- Deprecates existing overloaded createQueue, createSharedQueue,
createTemporaryQueue, & updateQueue methods for ClientSession,
ServerSession, ActiveMQServer, & ActiveMQServerControl where
applicable.
- Deprecates QueueAttributes, QueueConfig, & CoreQueueConfiguration.
- Deprecates existing overloaded constructors for QueueImpl.
- Implements QueueConfiguration with JavaDoc to be the single,
centralized configuration object for both client-side and broker-side
queue creation including methods to convert to & from JSON for use in
the management API.
- Implements new createQueue, createSharedQueue & updateQueue methods
with JavaDoc for ClientSession, ServerSession, ActiveMQServer, &
ActiveMQServerControl as well as a new constructor for QueueImpl all
using the new QueueConfiguration object.
- Changes all internal broker code to use the new methods.
KMPNeedle::searchInto has been specialized and copied
to handle ReadableBuffer in order to save polymorphic
calls on it that would make it slower on hot paths.
This is a Large commit where I am refactoring largeMessage Body out of CoreMessage
which is now reused with AMQP.
I had also to fix Reference Counting to fix how Large Messages are Acked
And I also had to make sure Large Messages are transversing correctly when in cluster.
- Avoid some Properties Decoding, checking if we need certain properties like scheduled delivery
- Avoid creating some unnecessary SimpleString instances
- Removed some intermediate ActiveMQBuffer allocation
- Removed some intermediate UnreleasableByteBuf allocation
This is a surprisingly large change just to fix some log messages, but
the changes were necessary in order to get the relevant data to where it
was being logged. The fact that the data wasn't readily available is
probably why it wasn't logged in the first place.
This commit introduces the ability to configure a downstream connection
for federation. This works by sending information to the remote broker
and that broker will parse the message and create a new upstream back
to the original broker.
A new feature to preserve messages sent to an address for queues that will be
created on the address in the future. This is essentially equivalent to the
"retroactive consumer" feature from 5.x. However, it's implemented in a way
that fits with the address model of Artemis.
The core server session tracks details about producers like what
addresses have had messages sent to them, the most recent message ID
sent to each address, and the number of messages sent to each address.
This information is made available to users via the
listProducersInfoAsJSON method on the various management interfaces
(JMX, web console, etc.). However, in situations where a server session
is long lived (e.g. in a pool) and is used to send to many different
addresses (e.g. randomly named temporary JMS queues) this info can
accumulate to a problematic degree. Therefore, we should limit the
amount of producer details saved by the session.
Wait netty event loop group shutdown to avoid too many opened FDs after
server stops, when netty configuration is used. Clear server
activateCallbacks to avoid reactivation of previous nodeManager and
consequent FD leaks on restart. Fix LargeServerMessageImpl.copy to avoid
FD leaks when a large message expiry or it is sent to DLA. Terminate
HawtDispatcher global queue to avoid pipes and eventpolls leaks after a
MQTT test.
cherry-picking commit 9617058ba0649af4eea15ce8793f86de827c4b7f
NO-JIRA adding check for open FD on the testsuite
cherry-picking commit 0facb7ddf4d3baa14a3add4290684aff7fd46053
NO-JIRA addressing connections leaks on integration tests
If a jms client (be it openwire, amqp, or core jms) receives a message that
is from a different protocol, the JMSMessageID maybe null when the
jms client expects it.
* Upgrading versions
* Adding wildfly-common dependency as jboss-logmanager now depends on it
for simple common operations such as getting hostname or process id
* Updating bootclasspath with wildfly-common
gtully
Clebert Suconic
Justin Bertram
Andy Taylor
Domenico Francesco Bruscino
Michael Pearce
Francesco Nigro
Jan Šmucr
Robbie Gemmell
Emmanuel Hugonnet
brusdev
Atri Sharma
Christopher L. Shannon (cshannon)
Tom
Tomas Hofman
Dmitry Volodin
Howard Gao
Emmanuel Hugonnet