- created new subproject akka-protobuf (and added COPYING and LICENSE)
- renamed com.google.protobuf -> akka.protobuf everywhere
- also added such renaming step to the results of protoc compilation in
project/Protobuf.scala
- had to include transcriptions of Netty’s ProtobufEncoder/Decoder to
make multi-node-testkit compile again
It works, but the stack trace is very annoying since it will always be printed by Sigar itself
(so stupid of such a library to use stderr and stdout).
[error] org.hyperic.sigar.SigarException: no libsigar-universal64-macosx.dylib in java.library.path
[error] at org.hyperic.sigar.Sigar.loadLibrary(Sigar.java:174)
[error] at org.hyperic.sigar.Sigar.<clinit>(Sigar.java:102)
A workaround is to run with `-Djava.library.path=./target/native`, then it will only print
the stack trace when it is not provisioned and next time it's silent.
Also updated to latest sigar-loader, but that did not make
any difference for this issue
Future.successful(Nil) is an alternative way to signal all good
in the happy case, for reduced allocations.
fix test failure
benchJmh leveldb dependency
revert leveldb change
+ per plugin scoped adapters
+ could be swapped during runtime
+per EventAdapter now has manifest and is configurable ai la serializers
+ json examples in docs
+ including "completely manual" example in case one wants to add
metadata TO the persisted event
+ better error reporting when misconfigured bindings
+ manifest is handled by in memory plugin
- did not check if it works with LevelDB plugin yet
> TODO: json example uses Gson, as that's simplest to do, can we use
+per allows 1:n adapters, multiple adapters can be bound to 1 class
Previously know as [patriknw/akka-data-replication](https://github.com/patriknw/akka-data-replication),
which was originally inspired by [jboner/akka-crdt](https://github.com/jboner/akka-crdt).
The functionality is very similar to akka-data-replication 0.11.
Here is a list of the most important changes:
* The package name changed to `akka.cluster.ddata`
* The extension was renamed to `DistributedData`
* The keys changed from strings to classes with unique identifiers and type information of the data values,
e.g. `ORSetKey[Int]("set2")`
* The optional read consistency parameter was removed from the `Update` message. If you need to read from
other replicas before performing the update you have to first send a `Get` message and then continue with
the ``Update`` when the ``GetSuccess`` is received.
* `BigInt` is used in `GCounter` and `PNCounter` instead of `Long`
* Improvements of java api
* Better documentation
* changed zeromq-scala-binding library
* modified build-release task to include distributions from cross builds
* removed tar-zip step from release script, because tgz package is not used from the website
* release script now releases for all crossScalaVersions
* dry run is the default now
* load sample builds from their definitions and replace library dependencies with project ones
* remove redefined sample build definitions
* test osgi sample by running a maven command
Original here: https://github.com/krasserm/akka-persistence-testkit
New features:
* merged martin's tests
* usable from java (junit 4)
* simple bench test, which helps checking if ordering is perserved under
bigger workloads and simple perf checking
* does NOT include tests for already deprecated features (deleteMessages)
* docs
Resolves#13815
Conflicts:
project/AkkaBuild.scala
The report() call can come from multiple threads in our code,
yet it was opening/closing a shared graphite client instance in this
method, causing NPE when periodic reporting kicked in during a manual
report() call. We want to be able to do this - thus rewrite to safe impl
Removed metrics-graphite dependency, replaced by in house impl.
The previous was using discrete write() calls, which could be entangled
when called from multiple threads, and produce invalid metric lines.
Current impl is simpler and threadsafe, as the lock for write(String) to
aquired for the entire string lenght's write (unlike multiple write calls).
Resolves#15165
Note: This is NOT aimed to provide an micro-benchmarking solution.
The goal is to provide data for broad trend analysis. For techniques
that fight the inliner and other specialised techniques, refer to JMH.
+ custom console and graphite reporters
- had to be custom because it's not possible to add custom metric
types to the existing reporters
+ initial hdr.Histogram histogram() provider, see
http://latencyutils.github.io/LatencyUtils/
+ Not using timers provided by Metrics, instead use the above histogram
+ Added average Actor size measurement
+ Measuring the "blocking time" when an actor is created, before we fire
of the async part of this process; Measures in loop and will fluctuate
a lot. Times are in `us` -- System.nanoTime should provide good enough
resolution.
+ Measuring total actor creation time by using
`KnownOpsInTimespanTimer`, which given a known number of ops, in a
large amount of time, roughtly estimates time per one operation.
// Yes, we are aware of the possibility of GC pauses and other horrors
+ All classes are `private[akka]`, we should not encourage people to use
this yet
+ Counters use Java 8's `LongAdder`, which is metric's private;
The new trend in Java land will be copy paste-ing this class ;)
+ Metrics are logged to Graphite, so we can long-term analyse these
+ Reporters are configurable using typesafe-config
! I'm not very happy about how I work around Metrics not being too open
for adding additional custom metrics. Seems like a hack at places.
I will consider removing the Metrics dependency all together.
numbers
Example output:
```
-- KnownOpsInTimespanTimer-------------------------------------------
actor-creation.total.creating-100000-actors.Props|new-EmptyArgsActor|…||-same
ops = 100000
time = 1.969 s
ops/s = 50782.22
avg = 19.69 μs
-- AveragingGauge---------------------------------------------------
actor-creation.Props|new-EmptyArgsActor|…||-same.avg-mem-per-actor
avg = 439.67
```
