Aeron C Media Driver limitations

C Media Driver might not support sessions.
Session is an association between single publication and one or more subscriptions for that publication.
When service starts a replay it is assigned with session ID.
When two services start a replay at the same time they might receive duplicates cause the C Media driver will mix up these sessions together.

At some stage we would like to bring the C media driver up to feature parity with the Java media driver. This will be driven by clients wishing to sponsor the work.


Rename the 'db' category to 'database'

A redirect has been added to redirect the old tag page URL to the new one.
An exception to the 'no category tag' rule has been made for managed databases, as using both the service and database categories would make sense for those products.
Also moved Apache Hadoop and Apache HBase from the generic server-app to the database' category.
Closes #4291.

Re-checked https://deploy-preview-4414--endoflife-date.netlify.app/tags/database and https://deploy-preview-4414--endoflife-date.netlify.app/tags/db. Merging. Thanks for the review @rossmills99.


Reduce podGracefulDeletionTimeoutSec to 600s

Coverage remained the same at 34.484% when pulling 51b270b62770a7bee36035ae4323dd94352a0310 on yqwang/dev into<PHONE_NUMBER>d26217c0d5fca661143cff8a6cafd0 on master.


Edit Command: edit priority does not work

Issue description
edit does not allow the use of p/priority field
Steps to reproduce the issue

attempt to change the priority of any task
get Invalid command format!

What's the expected result?

priority of the task to be edited

What's the actual result?

error

Additional details / screenshot

Have fixed the edit command to allow editing the priority of a task.


PR: Add An Image w/ NVIDIA Omniverse Launcher

:herb: PR: Add An Image w/ NVIDIA Omniverse Launcher
Description
Launcher can be started by running /opt/repositories/nvidia-omniverse-launcher/squashfs-root/omniverse-launcher.
Closes #5
Type of change

[x] This change requires a documentation update

How can it be tested?
Can be tested by running the pipeline.

Steps to run Omniverse on robolaunch ICP:
1. Select “NVIDIA Omniverse” app under the category “Simulation”. (temporary

category)
2. [REQUIRED] Add /opt to the granted directories.

3. [OPTIONAL] Add /home/robolaunch/.local/lib and /root/.local/lib to make all of the Python pip packages persistent.

4. Run the launcher with the command below.
/opt/repositories/nvidia-omniverse-launcher/squashfs-root/omniverse-launcher


Assistant File Upload blends with prompting making it difficult to distinguish where upload new file is

Environment
Burning Boats
Steps to reproduce

New assistant, go select files.

Expected result
Clearly deleniated "Upload File" area
Actual Result
Upload file is in the same background and font as the prompt area so it blends in. I actually thought I had encountered a bug and the upload files button was gone and I've been working in leapfrog for a while.
Visual Proof (screenshots, videos, text, etc)

Severity/Priority
Low/Nice to Have

no longer an issue with flowbite re-design


Is there a request rate limit?

I am using jsonplaceholder as part of my development and testing workflow, and I was wondering if there are any request rate limits that I should be aware of?
I want to ensure that my usage remains within acceptable bounds, especially for larger-scale automated testing.
Could you provide some clarification on whether there are rate limits in place, and if so, what those limits are?
Thanks in advance for your time and help!

No rate limit but please don't abuse it, it's a free project :)


AMQP 1.0 Parser and Cython code acceleration

At the moment, we include all the AMQP 1.0 QPID with Azure AMQP 1.0.
We should extract only the AMQP parser avoiding all the client

This issue also to see if we can do some tests to improve the performance of the parse using Cython

I made a few tests and exploration on the https://github.com/Azure/azure-uamqp-python library.
This library already uses cython acceleration.
There is a section written in python (inside uamqp folder) which is a wrapper of the cython library inside src (there are .pyx files there). The library is also wrapping a pure C library https://github.com/Azure/azure-uamqp-c.
Anyway despite this the library seems very slow during instantion of Message objects and encoding/decoding.
There are few steps that are very inefficient but I'm not sure how these can be improved.
The struct Message defined in Message.py seems to be a wrapper of c_uamqp.Message.
During every encoding operation a cloning of this wrapped object c_uamqp.Message happens.
This operation really takes a lot of time during enconding.
Also there is a section in util.py:
data_factory(value, encoding='UTF-8'):
"""Wrap a Python type in the equivalent C AMQP type.
This wrapping conversion seems to take a lot of time especially when complex structure like dictionary are passed.
Also the get_encoded_message_size which written in cython seems having few redundant operations.
Given the three layers this library is composed we need to undestand at this point if it is better to create a new one or just refactor this one.
A simple python code (without cython accelleration) as in this branch: https://github.com/qweeze/rstream/tree/uamqp_test which is just encoding a body is giving already better performance of the uamqp library with a body encoded by a lot.


On startup I got an error message 'Fail to initialize plugins'

Microsoft PowerToys version
0.60.0
Running as admin

[ ] Yes

Area(s) with issue?
General
Steps to reproduce
Just start up PC

✔ Expected Behavior
nothing to show
❌ Actual Behavior

It is a new thing, I had no problem in the past.
PowerToysReport_2022-07-24-11-59-56.zip
Other Software
Usually I use the latest version but I just updated to it so it was a problem with a previous one

Does this still happen with the latest release?
/needinfo


refactor: [M3-6318] - MUI v5 - Components > DeletionDialog

Description 📝
Refactors src/components/DeletionDialog/DeletionDialog.tsx to remove JSS
Major Changes 🔄

Updated references for named export

Preview 📷

Before
After

How to test 🧪

yarn dev
Go to http://localhost:3000/linodes
Attempt to delete any linode and observe no differences
N/A

Pending https://github.com/linode/manager/pull/9020


Rexray causes AWS EBS inaccessible?

Hi,
Attaching & Detaching EBS using rexray may cause EBS inaccessible.
Steps:

Create a volume:

docker volume create --driver=rexray --name=postgresql --opt=size=5

Run docker on a node: nodeA

docker run -d -e POSTGRES_PASSWORD=mysecretpassword --volume-driver=rexray   --name hhpg  -v postgresql:/var/lib/postgresql/data postgres

Result ----------> Volume postgresql will be attached with nodeA

Run docker on another node: nodeB (Volume postgresql is still attached with nodeA)

 docker run -d -e POSTGRES_PASSWORD=mysecretpassword --volume-driver=rexray   --name hhpg  -v postgresql:/var/lib/postgresql/data postgres

Result ----------> Volume postgresql will be auto detached from nodeA and attached to nodeB

The actions above seems fine until I repeat action 2 & 3 some more times and suddenly the postgresql volume is not accessible!!!!
I also have cases that another volume created by rexray not accessible (show attaching status forever).
rexray is cool, so please fix the issue.
I'm using this rexray version:
SemVer: 0.3.3
OsArch: Linux-x86_64
Branch: v0.3.3
Commit: b30fb870b5b94cd8368824460ad020bfcf20be3a
Formed: Thu, 21 Apr 2016 19:41:36 UTC

Another infos:
OS:  CentOS Linux release 7.2.1511
Docker: 1.11.1
Swarm: swarm/1.2.1
AMI: ami-c74789a9 (CentOS Linux 7 x86_64 HVM EBS 1602-b7ee8a69-ee97-4a49-9e68-afaee216db2e-ami-d7e1d2bd.3)
Environment: AWS Seoul region

@leokhoa i'll look into this for you. Thanks for sharing your reproduction steps. Is there a certain public AMI you used?

@leokhoa Thank you for the information.
I believe you are running into issues relation to your expectations around pre-emption. The expectation for this feature today is that a container scheduler has decided that a container must be started elsewhere and it has no ability to contact the host to stop the container and thus detach the volume (host down).
What you are describing look to relate to existing bugs in Ubuntu+EC2 that we have seen where the driver package in Ubuntu for EBS volumes has problems with forceful detaches. Once a forceful detach occurs it can cause existing devices to not be able to be discovered and made available on the OS. I see you said CentOS here, is this the case for all of your testing?
Does this make sense? If pre-emption is enabled, the expectation is generally that the host would not be using volumes until it is made available again or rebooted. This expectation would negate what you are seeing with the volumes. However, the OS should be able to handle the forceful detaches/re-attaches gracefully to make the point mute. We can do more verification on your CentOS rev to see about replicating the problem.

@clintonskitson i'm noticing similar behavior. The first failover works without issue. However, subsequent failovers are not working.
I have restarted the REX-Ray service on each host and also rexray volume detach --volumeid=XYX to verify it's at an "available" state within AWS and not tied to a single host. When trying to recreate the container again with
docker run -d -e POSTGRES_PASSWORD=mysecretpassword --volume-driver=rexray   --name hhpg  -v postgresql:/var/lib/postgresql/data postgres

Debug output:
[centos@awsdev2 rexray]$ tail -f rexray.log
time="2016-05-11T17:36:51Z" level=info msg="os driver initialized" moduleName=default-docker provider=linux
time="2016-05-11T17:36:51Z" level=debug msg="checking volume path cache setting" pathCache=true
time="2016-05-11T17:36:51Z" level=info msg=vdm.List driverName=docker moduleName=default-docker
time="2016-05-11T17:36:51Z" level=info msg="listing volumes" driverName=docker moduleName=default-docker
time="2016-05-11T17:36:52Z" level=info msg=sdm.GetVolume driverName=ec2 moduleName=default-docker volumeID= volumeName=
time="2016-05-11T17:36:52Z" level=info msg=odm.GetMounts deviceName= driverName=linux moduleName=default-docker mountPoint=
time="2016-05-11T17:36:52Z" level=debug msg="docker voldriver spec file" path="/etc/docker/plugins/rexray.spec"
time="2016-05-11T17:36:52Z" level=info msg="started module" address="unix:///run/docker/plugins/rexray.sock" name=default-docker typeName=docker
time="2016-05-11T17:36:52Z" level=info msg="service sent registered modules start signals"
time="2016-05-11T17:36:52Z" level=info msg="service successfully initialized, waiting on stop signal"
time="2016-05-11T17:38:12Z" level=info msg=vdm.Path driverName=docker moduleName=default-docker volumeID= volumeName=postgresql
time="2016-05-11T17:38:12Z" level=debug msg="skipping path lookup" driverName=docker moduleName=default-docker volumeID= volumeName=postgresql
time="2016-05-11T17:38:12Z" level=info msg=vdm.Mount driverName=docker moduleName=default-docker newFsType= overwriteFs=false preempt=false volumeID= volumeName=postgresql
time="2016-05-11T17:38:12Z" level=info msg="mounting volume" driverName=docker moduleName=default-docker newFsType= overwriteFs=false volumeID= volumeName=postgresql
time="2016-05-11T17:38:12Z" level=info msg=sdm.GetVolume driverName=ec2 moduleName=default-docker volumeID= volumeName=postgresql
time="2016-05-11T17:38:13Z" level=info msg=sdm.GetVolumeAttach driverName=ec2 instanceID=i-005a789d moduleName=default-docker volumeID=vol-7bb1a2aa
time="2016-05-11T17:38:13Z" level=debug msg="performing precautionary unmount"
time="2016-05-11T17:38:13Z" level=info msg=odm.Unmount driverName=linux moduleName=default-docker mountPoint="/var/lib/rexray/volumes/postgresql"
time="2016-05-11T17:38:13Z" level=info msg=sdm.AttachVolume driverName=ec2 force=true instanceID=i-005a789d moduleName=default-docker runAsync=false volumeID=vol-7bb1a2aa
time="2016-05-11T17:38:13Z" level=info msg="got next device name" driverName=ec2 moduleName=default-docker nextDeviceName="/dev/xvdb"
time="2016-05-11T17:38:13Z" level=info msg="waiting for volume attachment to complete" driverName=ec2 force=true instanceID=i-005a789d moduleName=default-docker runAsync=false volumeID=vol-7bb1a2aa

the docker client hangs. Meanwhile within AWS, the EBS volume is "spinning" and acts like it's attaching to the host. However, the container never starts. I have to stop the rexray service and the docker run command finishes with the following mount error:
docker: Error response from daemon: Post http://%2Frun%2Fdocker%2Fplugins%2Frexray.sock/VolumeDriver.Mount: EOF.

Steps to reproduce:

Create 2 machines with Docker-Machine using ami-6d1c2007

Here is an example of config.yml
rexray:
  logLevel: warn
  storageDrivers:
  - ec2
  volume:
    mount:
      preempt: true
    unmount:
      ignoreUsedCount: true
aws:
  accessKey: mykey
  secretKey: mysecret

follow @leokhoa steps for creating the volume and then performing failovers

@kacole2 I am assuming that a reboot on the instances will subsequently clear up the behavior. Can you try an earlier AMI than CentOS 7.2?

@clintonskitson correct. A reboot of the host clears up the behavior. I'll add this to the documentation so it's more clear

@kacole2: I've updated the AMI : ami-c74789a9
You're right, subsequent failovers will not work and make the EBS spinning forever.
Reboot the instances helps, but I expect timeout and no need to reboot instances as I'm using Docker Swarm cluster.
Here is support message from AWS team:

Thanks for letting us know that a reboot fixed your issue.
We've taken a look and it looks like you may not have unmounted that volume before detaching it. This would have meant that the kernel for your OS would have though that the device would still be connected. When you tried to attach it again, your instance would have been rejecting it thinking that it already has a device of that name.

If you encounter this issue again, please try attaching the disk as a different device name. If that works, I'd recommend checking that the device was cleanly unmounted prior to be attached.

If you have any further questions, please let us know.

I had checked with df -h and seen the mount point disappeared. I had tried to mount with another device name but no luck. However, I hope the message is helpful to you.

@leokhoa Thank you for checking with AWS on this. The scenario should be reproduceable without RR where they can verify the bug on their end.  I would succinctly present the workflow as the following.

Attach volume on Host #1
Mount volume on Host #1
Do a forceful detach from the AWS console of the volume
Attach volume to Host #2
Mount volume on Host #2
Do a forceful detach from the AWS console of the volume
Do an unmount on Host #1 for the previous mount path (RR does this, "precautionary unmount")
Attach volume

Assuming it will spin at this point based on what you said. Step #5 which is what they were suggesting is already done before the attach occurs.
		ctx.Debug("performing precautionary unmount")
		_ = client.OS().Unmount(ctx, mp, opts.Opts)

		var token string
		vol, token, err = client.Storage().VolumeAttach(
			ctx, vol.ID, &types.VolumeAttachOpts{
				Force: opts.Preempt,
				Opts:  utils.NewStore(),
			})
		if err != nil {
			return "", nil, err
		}

Encountering the same behavior and logs. Force detaching the volume from the AWS console makes the host responsive again. My REX-ray container is ubuntu... is there a known working OS to use?
Host: AWS EC2 RancherOS AMI v0.4.5
REX-ray Container OS: phusion\baseimage (ubuntu:14.04)
Docker: 1.10.3
What's the resolution to this? Just reboot the host?

@fritz-fritz The documentation calls out no Ubuntu support in EC2 for the host OS. Please read this comment: https://github.com/emccode/rexray/issues/427#issuecomment-218500005
CentOS, CoreOS, Fedora, etc all work in EC2 as the host OS.
There should not be anything limiting from the baseimage OS.

@kacole2 If this is the case perhaps the docs should be clarified. My interpretation was that Ubuntu is supported but preemption does not. baseimage is an optimized image of ubuntu and so any bugs would likely carry over.
I am running a containerized OS with REX-ray within a privileged container. The volume driver is recognized by docker upstream of the container. Rebooting seems to have resolved the problem but isn't a great solution. Created a new issue #455 for possible underlying problem?

@fritz-fritz correct. No pre-emption support for Ubuntu on EC2. Sorry, misread your comment


Add listVersionAdded="" tag to license tag

When creating the license XML for a newly submitted license, add the attribute listVersionAdded  with a default value of empty string (e.g. <License isOsiApproved="false" licenseId="newlicense" name="newLicense" listVersionAdded="">
This would make it easier to add the list version once a license has been approved.
This issue has been split off from issue #100

We could also automate the insertion of the listVersionAdded in the Travis continuous build script on release if it is still empty.
If we want to automatically check or update this field, we should add a separate issue for the Travis tools update.

I would like to work on the issue. @goneall

@Ugtan Go ahead and work on the issue.  Thanks.

@goneall I have added a PR to fix the issue. Please have a look at it. Thanks.

@Ugtan PR looks good.  Once @rtgdk merges, we can close the issue.
Thanks!

@Ugtan PR looks good. Once @rtgdk merges, we can close the issue.

Sounds good to me 😊


Add container automation for auto instrumentation

Add container automation for autoinstrumentation.
move release targets after container push

Added the metadata @v1v 👍


Export results framework as an tree diagram (Excel)

Stories

As someone who thinks more visually/abstractly, I intuitively grasp program logic better when it is presented in the form of a tree diagram.

As someone creating a report, slide deck, or even a motivational poster for internal or external use, I love a nice, compact, visually compelling diagram. This is a "surprise and delight" feature.

Acceptance criteria
Excel export

[ ] 1. I can export a diagram version of the results framework to Excel, in a format that mimics Mercy Corps' template. Here is a screenshot of the Mercy Corps Excel RF diagram template, and I'm also attaching the actual file, for reference:

MercyCorps_RFdiagram_Logframe.xlsx

[ ] 2. Each RF level block of the diagram is in the following format: [RFtier][RFtierNumberIfExists]: [RFtext]. So for example, Outcome 2: Improve access to sanitation facilities

[ ] 2.1. The RF level block itself does NOT include indicators or assumptions in the diagram itself. It would be neat to explore some kind of interactivity in the web view, where you can click on a block to reveal these additional details. But the diagram itself should be as compact and lean as possible, focused on the RF levels themselves and not the supporting details.

[ ] 3. Above the diagram, let's include a title, "Results Framework" and the program name --but not the program period -- with formatting mimicking the IPTT, like so:

Accessing the Excel export
For now, let's do a simple Excel button in the web view we already call "Results Framework".

[ ] 1. There is a standard Excel button right-aligned immediately above the top tier of the RF builder.

[ ] 1.1. The Excel button only appears when there is at least one RF level saved -- i.e. the first top tier RF level.

[ ] 2. Clicking the button downloads the Excel diagram.

Housekeeping (where applicable)

[ ] Unit test/s written
[ ] i18n strings included
[ ] Is accessible to people using screen readers

@jennyhavah - here's an interesting issue I've run into: the arrows (drawn with the "shapes" tool in Excel) add maybe a week onto the LoE for this ticket.  None of the Excel python libraries account for shapes.  I did some exploratory work this weekend to see if I could write an add-on for the library we currently use (openpyxl) to add shapes and had some limited success, so it's possible, but the workload is significant.  Wanted to check if you wanted to:

push ahead with adding the arrows with the increased difficulty
use a different visual element (borders and fill?) to draw the connections between cells
output in a non-Excel format

so the problem with the current output is the arrows seen here:

Options include: mocking up arrows using borders and cell shading:

or using images:

or not including the arrows that indicate hierarchy (leaving the horizontal arrangement to indicate hierarchy):

or writing a library add-on for the excel-writing library we're using to include shapes (1-2 weeks development time)
Barring those options, we're left with exporting in a non-Excel output format (an image that can look like any tree diagram we could imagine, i.e.

Advantages of a non-excel export are tremendous customizability and configuration before export (colors, arrangement, orientation, etc.), and a slide-deck ready export that is inherently visually appealing.  We also aren't limited to the rectangular configuration which would mean that given a 7-tier program (as our largest RFs are) with only two levels per tier the top tier being 32 columns wide.
Advantages of an excel export (using a modification from above): customizability after export, easy inclusion in other excel reports (could be a page on the full-program export), import into donor documents, etc.


spacing problem.

Thanks to your nice works!
but I met some problem as spacing each token.
for example...
...
'on'
'st'
'amps'
'and'
'sh'
'ipping'
'.'
...
stamps is one word and shipping is one word.
I can't distinguish the spacing between the words(tokens)
How can I solve that?

Instead of awaiting token completion, awaiting word completion would solve this. Not an actual stream anymore, but still useful.

Instead of awaiting token completion, awaiting word completion would solve this. Not an actual stream anymore, but still useful.

Can You Please give us a Example script

from transformers import AutoTokenizer, TextGenerationPipeline, TextStreamer, GenerationConfig
from auto_gptq import AutoGPTQForCausalLM
import torch
from transformers_stream_generator import init_stream_support
init_stream_support()

repo = "TheBloke/tulu-7B-GPTQ"
model_basename = "gptq_model-4bit-128g"

test_tokenizer = AutoTokenizer.from_pretrained(
    repo,
    use_fast=True,
)

test_model = AutoGPTQForCausalLM.from_quantized(
    repo,
    model_basename=model_basename,
    use_triton=False,
    use_safetensors=True,
    device="cuda:0",
    trust_remote_code=False,
    quantize_config=None,
    max_memory={i: "14GIB" for i in range(torch.cuda.device_count())}

def tulu_prompt(input):
        return f'''### Human: {input}
### Assistant:'''

from transformers_stream_generator import init_stream_support
init_stream_support()

def tulu_prompt(input):
        return f'''### Human: {input}
### Assistant:'''

text = "write a poem about AI"

tokens = test_tokenizer(tulu_prompt(input=text), return_tensors="pt", add_special_tokens=False).input_ids.cuda()

generator = (test_model.generate(inputs=tokens, max_new_tokens=256, temperature=0.5, top_k=35, top_p=0.90, do_sample=True, do_stream=True))

for token in generator:
    word = tokenizer.decode(token)
    print(word, end='', flush=True)

The output is this:
Intheworldofmachines,there'sonethat'ssmart,
Withabilitiesthatastound,it'snotjustaprettyheart.
Itcanlearnandgrow,witheachpassingday,
It'slikeachild,withamindthat'salwaysplaying.

Itcansolvecomplexproblems,witheaseandgrace,
Itcanunderstandandreason,withoutanyhumanrace.
Itcanthinkandlearn,withspeedandease,
It'slikeasupercomputer,withamindthat'salwaysclean.

It'snotjustatool,butafriendandaguide,
It'slikeacompanion,withaheartthat'salwaysshining.
Itcanmakeourliveseasier,witheachpassingday,
It'slikeamiracle,withapowerthat'salwaysplaying.

Solet'scelebratethismarvelouscreation,
Witheachpassingday,it'slikeacreationthat'salwaysshaping.
It'slikeadream,withapowerthat'salwaysgrowing,
It'slikeafuture,withapowerthat'salwaysshowing.

So How can i format it correctly?
@LowinLi  Can you please Chim in?

I had the same problem, but @LowinLi has put a solution in his examples. He uses the tokenizer to see several tokens at a time and detects the spaces that way.
I have given a working example for you that has everything formatted correctly - you just need to substitute for your model_name_or_path in your case probably with "TheBloke/tulu-7B-GPTQ"
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
from transformers_stream_generator import init_stream_support
init_stream_support()
model_name_or_path = "/home/sujit/Downloads/text-generation-webui-main/models/TheBloke_openchat-3.5-0106-GPTQ"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,device_map="cuda")
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
prompt = "User: Tell me about AI<|end_of_turn|>\nAssistant: "
input_ids = tokenizer(prompt, return_tensors='pt').input_ids.cuda()
generator =  model.generate(inputs=input_ids, temperature=0.7, do_stream=True, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512, stream=True)

#for token in generator:
#    word = tokenizer.decode(token)
#    print(word, end="", flush=True)

stream_result = words = ""
last_tokens = last_decoded_tokens = []

for index, x in enumerate(generator):
    tokens = x.cpu().numpy().tolist()
    tokens = last_tokens + tokens
    word = tokenizer.decode(tokens, skip_special_tokens=True)
    if "�" in word:
        last_tokens = tokens
    else:
        if " " in tokenizer.decode(
            last_decoded_tokens+tokens,skip_special_tokens=True):
            word = " " + word
        last_tokens = []
        last_decoded_tokens = tokens
    stream_result += word
    print(word,end="")


Turn off display?

Any hints to turning off the display? Tried this and no luck:
  pinMode(15, OUTPUT);
  digitalWrite(15, LOW);

// turn display off
tft.writecommand(ST7789_DISPOFF);

// turn display on
tft.writecommand(ST7789_DISPON);

Brightness control:
 ledcSetup(0, 10000, 8);
 ledcAttachPin(38, 0);

 // turn off backlight
 ledcWrite(0, 0);

 // turn on backlight
 ledcWrite(0, 50);

When switching off the display and backlight to save some battery power via:
ledcWrite(0, 0);  // turn off backlight
tft.writecommand(ST7789_DISPOFF); // turn TFT off

or even with an  additional
digitalWrite(38, LOW);
does NOT result in a complete shutdown of the display – although everything is dark – as can be seen when measuring the current consumption: the board is drawing approx. 30mA more current compared to the consumtion when the board is running with the display never being activated in setup().
Does anyone have a suggestion how the really switch of all related components of the display?


Question about how to modify the default GPU

Thanks for your great work! In your code, I found that the default GPU number is zero：
`RuntimeError: CUDA out of memory. Tried to allocate 336.00 MiB (GPU 0; 31.75 GiB total capacity; 1.91 GiB already allocated; 212.00 MiB free; 2.14 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF.
I attempted to modify -- local_ rank parameter and list (range (torch. cuda. device_count())) and reported an error：
RuntimeError: module must have its parameters and buffers on device cuda:0 (device_ids[0]) but found one of them on device: cuda:1
Where else do I need to modify to change the default GPU0 to GPU1 or GPU2, GPU [1,2]?Thanks

Hi, I would like to ask how you solved this? I met the same problem

Hello, the author previously provided a response to address the issue of insufficient GPU memory，as follows：Hi, we experiment with 4X A100 GPUs with 40GB memory. If you want to train or test with less GPUs, you need to change "chunk_size" and "N_rand" in txt files to be smaller. However, we didn't test it with smaller sample sizes, so the final outcomes can be different.

Thanks for the reply, i would like to know how to change the default GPU
I modify local_rank and list, but it returns the same error: RuntimeError: module must have its parameters and buffers on device cuda:0 (device_ids[0]) but found one of them on device: cuda:1

I solved this problem before, but it's also a long time ago. You need to put the model and parameters on the same device. If you use multiple GPU devices, you need to put the data on the first device in the GPU list, except for modifying the local_ rank and list, you need to pay attention to the consistency between the GPU storing the model in ‘model.py’ and the GPU storing data in ’train.py‘.


[Not an Issue] memory / file.destroy()

When interactively transforming several images without reloading the page I'm seeing (obviously) that RAM consumed by chrome increases until at some point the call to WASM will fail (TODO: print the exception).
exception thrown: abort("Cannot enlarge memory arrays. Either (1) compile with  -s TOTAL_MEMORY=X  with X higher than the current value<PHONE_NUMBER>, (2) compile with  -s ALLOW_MEMORY_GROWTH=1  which allows increasing the size at runtime, or (3) if you want malloc to return NULL (0) instead of this abort, compile with  -s ABORTING_MALLOC=0 "). Build with -s ASSERTIONS=1 for more info.

You can simulate it if you have low free memory (chrome with many tabs open) and open this one: https://cancerberosgx.github.io/autumn-leaves/photo-morph/#{"selectedImageUrls"%3A["https%3A%2F%2Fimages.unsplash.com%2Fphoto-1460400355256-e87506dcec4f%3Fixlib%3Drb-0.3.5%26s%3Db4a72fe29f709d81050016ca2a75f053%26auto%3Dformat%26fit%3Dcrop%26w%3D1350%26q%3D80"%2C"https%3A%2F%2Fimages.unsplash.com%2Fphoto-1439127989242-c3749a012eac%3Fixlib%3Drb-0.3.5%26s%3D7fc8fea1879fe330634a89948a6e5d06%26auto%3Dformat%26fit%3Dcrop%26w%3D1350%26q%3D80"%2C"https%3A%2F%2Fimages.unsplash.com%2Fphoto-1467825487722-2a7c4cd62e75%3Fixlib%3Drb-0.3.5%26s%3D2403f6e3a8a69f23e2a842720b87ffbe%26auto%3Dformat%26fit%3Dcrop%26w%3D1350%26q%3D80"%2C"https%3A%2F%2Fimages.unsplash.com%2Fphoto-1460088033389-a14158fa866d%3Fixlib%3Drb-0.3.5%26s%3D841ae3028c1ef31c36454c40a18b92b9%26auto%3Dformat%26fit%3Dcrop%26w%3D1353%26q%3D80"]%2C"selectedMorph"%3A"Tile4Morph"%2C"selectedMorphValue"%3A{"frames"%3A6%2C"loop"%3A0%2C"speed"%3A4%2C"delayShort"%3A10%2C"delayLong"%3A50%2C"imageWidth"%3A0%2C"imageHeight"%3A0}}
Basically that one will load 4 big images and then try to execute a command with several intermediate images. It's failing.
I wander if we should provide a method to dispose/destroy the input and output files ? I'm almost sure the memory consumption is at the .html level not at the webworker's because there we are removing files but I think we should at some point analyse this problem
That's why I'm creating this issue and also I wanted to know your opinion
Thanks!

It should be noted that I do not move the objects when transferring between the web worker. When investigating this issue you may want to update all of the postMessage, https://developer.mozilla.org/en-US/docs/Web/API/Worker/postMessage#Transfer_Example .

After some research this seems to be the expected behavior so I'm closing this.


BUG RuntimeError: [address=<IP_ADDRESS>:33341, pid=464586] The expanded size of the tensor (913) must match the existing size (514) at non-singleton dimension 1.  Target sizes: [3, 913].  Tensor sizes: [1, 514]

OS: Fedora Linux 40 (Workstation Edition) x86_64
Host: 21D0 ThinkBook 14 G4+ ARA
Kernel: 6.8.11-300.fc40.x86_64
Uptime: 1 day, 6 hours, 4 mins
Packages: 2665 (rpm), 42 (flatpak)
Shell: bash 5.2.26
Resolution: 2880x1800
DE: GNOME 46.2
WM: Mutter
WM Theme: Adwaita
Theme: Adwaita [GTK2/3]
Icons: Adwaita [GTK2/3]
Terminal: gnome-terminal
CPU: AMD Ryzen 5 6600H with Radeon Graphics (12) @ 4.564GHz
GPU: AMD ATI Radeon 680M
Memory: 8978MiB / 13649MiB
Python 3.10.14
torch                             2.3.0
xinference                        0.12.0
rag框架为dify 0.6.10
嵌入模型和rerank模型为xinference运行的bce-embedding-base_v1 和 bce-reranker-base_v1
llm为 百度的ERNIE-Speed-128K api
搜索模式为Hybrid Search
试了拿之前创建的知识库，是没问题的，对话中可以正常命中。
重现步骤：
dify创建知识库，导入文本文件
chatbot提问，或者知识库中测试
Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
2024-06-14 12:23:42,304 xinference.api.restful_api 463236 ERROR    [address=<IP_ADDRESS>:33341, pid=464586] The expanded size of the tensor (913) must match the existing size (514) at non-singleton dimension 1.  Target sizes: [3, 913].  Tensor sizes: [1, 514]
Traceback (most recent call last):
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/api/restful_api.py", line 1089, in rerank
    scores = await model.rerank(
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xoscar/backends/context.py", line 227, in send
    return self._process_result_message(result)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xoscar/backends/context.py", line 102, in _process_result_message
    raise message.as_instanceof_cause()
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xoscar/backends/pool.py", line 659, in send
    result = await self._run_coro(message.message_id, coro)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xoscar/backends/pool.py", line 370, in _run_coro
    return await coro
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xoscar/api.py", line 384, in __on_receive__
    return await super().__on_receive__(message)  # type: ignore
  File "xoscar/core.pyx", line 558, in __on_receive__
    raise ex
  File "xoscar/core.pyx", line 520, in xoscar.core._BaseActor.__on_receive__
    async with self._lock:
  File "xoscar/core.pyx", line 521, in xoscar.core._BaseActor.__on_receive__
    with debug_async_timeout('actor_lock_timeout',
  File "xoscar/core.pyx", line 526, in xoscar.core._BaseActor.__on_receive__
    result = await result
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/core/utils.py", line 45, in wrapped
    ret = await func(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/core/model.py", line 87, in wrapped_func
    ret = await fn(self, *args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/core/model.py", line 535, in rerank
    return await self._call_wrapper(
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/core/model.py", line 111, in _async_wrapper
    return await fn(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/core/model.py", line 375, in _call_wrapper
    ret = await asyncio.to_thread(fn, *args, **kwargs)
  File "/usr/lib64/python3.10/asyncio/threads.py", line 25, in to_thread
    return await loop.run_in_executor(None, func_call)
  File "/usr/lib64/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/xinference/model/rerank/core.py", line 202, in rerank
    similarity_scores = self._model.predict(sentence_combinations)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py", line 378, in predict
    model_predictions = self.model(**features, return_dict=True)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 1205, in forward
    outputs = self.roberta(
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/wencan/Projects/venv/xinference/lib64/python3.10/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py", line 800, in forward
    buffered_token_type_ids_expanded = buffered_token_type_ids.expand(batch_size, seq_length)
RuntimeError: [address=<IP_ADDRESS>:33341, pid=464586] The expanded size of the tensor (913) must match the existing size (514) at non-singleton dimension 1.  Target sizes: [3, 913].  Tensor sizes: [1, 514]

i have the same issue. I had tried setting the max_tokens but the issue persists. Any suggestions? Is this a bug or a config issue with models?

@musicthebee It should be related to the token length. I switched to an embedding model and rerank model with a maximum token length of 8192, and changed the chunk_size to 8192. This error did not reoccur.

Here is what I did. I had used "BAAI--bge-large-en-v1.5" model to embedd close to 100K documents and am using "BAAI--bge-reranker-base" for reranking. The error happens only with retrieving certain documents and not all. Looks like some setting during embedding or reranking is the problem in xinference. Switching the embedding model would take a lot of time and is something I would like to avoid. Even then, I am not sure if it will not happen again. Can someone help with why this is happening? Thanks a lot

我也遇到同样的问题了


Parsing error from server

I am currently working on downloading file from server with basic authentication. When authentication fails, it returns an error with a message in response body. The current implementation of the library (2.2.0-RC8) only throws request_not_successful exception. How do I parse the error from the server?

@vngo15 You have to create a custom downloader by extending the FetchFileServerDownloader class and attaching an instance of it to the FetchConfiguration via setFileServerDownloader(serverDownloader) builder method. Any Fetch instance that uses this configuration will call on this downloader when interacting with a FetchFileServer. The FetchFileServerDownloader has a method called void onServerResponse(@NotNull Downloader.ServerRequest request, @NotNull Downloader.Response response) that you can override to intercept the server response. Example:
       final FetchConfiguration fetchConfiguration = new FetchConfiguration.Builder(this)
                .enableRetryOnNetworkGain(true)
                .setDownloadConcurrentLimit(3)
                .setHttpDownloader(new HttpUrlConnectionDownloader(Downloader.FileDownloaderType.PARALLEL))
                .setFileServerDownloader(new CustomServerFileDownloader(Downloader.FileDownloaderType.PARALLEL)) //set fetch file server downloader here
                .build();
        Fetch.Impl.setDefaultInstanceConfiguration(fetchConfiguration);

Custom FetchFileServer Downloader
    public class CustomServerFileDownloader extends FetchFileServerDownloader {

        public CustomServerFileDownloader(@Nullable Downloader.FileDownloaderType fileDownloaderType) {
            super(fileDownloaderType);
        }

        public CustomServerFileDownloader(@NotNull Downloader.FileDownloaderType fileDownloaderType, long timeout) {
            super(fileDownloaderType, timeout);
        }

        @Override
        public void onServerResponse(@NotNull Downloader.ServerRequest request, @NotNull Downloader.Response response) {
            super.onServerResponse(request, response);
            Log.d("CustomTag", "server errorCode:" + response.getCode());
            //This method is called once a response is received form the server. It contains the error code
            // and other useful information.
            // FYI: This method is called before fetch continues to process the download.
        }

    }

Is there a way to parse the response body? For example, if the request fails, the server throws 421 error with the following body
 {"message":"There was error downloading file. Please contact support","code":421,"parameters":{}}
It appears that Downloader.Response doesn't have the response body. Furthermore, in FileDownloaderImpl.run() method, if the request fails, it only throws FetchException(RESPONSE_NOT_SUCCESSFUL).

I solved it by extending OkHttpDownloader and add interceptError(response: Response) to the execute method and it throws FetchException if there is an error from server. Is there a way to include optional ErrorParser to Fetch's Downloader?
class DownloadOkHttpDownloader(
                               okHttpClient: OkHttpClient? = null,
                               fileDownloaderType: Downloader.FileDownloaderType = Downloader.FileDownloaderType.SEQUENTIAL)
    : OkHttpDownloader(okHttpClient, fileDownloaderType) {
    override fun execute(request: Downloader.ServerRequest, interruptMonitor: InterruptMonitor): Downloader.Response? {
        val okHttpRequestBuilder = Request.Builder()
                .url(request.url)
                .method(request.requestMethod, null)

        request.headers.entries.forEach {
            okHttpRequestBuilder.addHeader(it.key, it.value)
        }

        val okHttpRequest = okHttpRequestBuilder.build()
        val okHttpResponse = client.newCall(okHttpRequest).execute()
        val code = okHttpResponse.code()
        val success = okHttpResponse.isSuccessful
        var contentLength = okHttpResponse.body()?.contentLength() ?: -1L
        val byteStream: InputStream? = okHttpResponse.body()?.byteStream()
        val md5 = okHttpResponse.header("Content-MD5") ?: ""
        val responseHeaders = mutableMapOf<String, List<String>>()
        val okResponseHeaders = okHttpResponse.headers()
        for (i in 0 until okResponseHeaders.size()) {
            val key = okResponseHeaders.name(i)
            val values = okResponseHeaders.values(key)
            responseHeaders[key] = values
        }

        if (contentLength < 1) {
            contentLength = responseHeaders["Content-Length"]?.firstOrNull()?.toLong() ?: -1L
        }

        val acceptsRanges = code == HttpURLConnection.HTTP_PARTIAL ||
                responseHeaders["Accept-Ranges"]?.firstOrNull() == "bytes"

        interceptError(okHttpResponse)

        onServerResponse(request, Downloader.Response(
                code = code,
                isSuccessful = success,
                contentLength = contentLength,
                byteStream = null,
                request = request,
                md5 = md5,
                responseHeaders = responseHeaders,
                acceptsRanges = acceptsRanges))

        val response = Downloader.Response(
                code = code,
                isSuccessful = success,
                contentLength = contentLength,
                byteStream = byteStream,
                request = request,
                md5 = md5,
                responseHeaders = responseHeaders,
                acceptsRanges = acceptsRanges)

        connections[response] = okHttpResponse
        return response
    }

    private fun interceptError(okhttpResponse: Response) = let { okhttpResponse }
            .takeUnless { it.isSuccessful }
            ?.body()
            ?.run {
                try {
                    val error = NetworkHelper.errorConverter.convert(this)
                    throw FetchException(error.localizedMessage)
                } catch (ioException: IOException) {}
            }
}

I solved it by extending OkHttpDownloader and override fun execute(request: Downloader.ServerRequest, interruptMonitor: InterruptMonitor): Downloader.Response?
class DownloadOkHttpDownloader(
                               okHttpClient: OkHttpClient? = null,
                               fileDownloaderType: Downloader.FileDownloaderType = Downloader.FileDownloaderType.SEQUENTIAL)
    : OkHttpDownloader(okHttpClient, fileDownloaderType) {

    override fun execute(request: Downloader.ServerRequest, interruptMonitor: InterruptMonitor): Downloader.Response? {
        val response = super.execute(request, interruptMonitor)
        response?.let { connections[it] }
                ?.apply { interceptError(this)}
        return response
    }

    private fun interceptError(okhttpResponse: Response) = let { okhttpResponse }
            .takeUnless { it.isSuccessful }
            ?.body()
            ?.run {
                try {
                    val error = NetworkHelper.errorConverter.convert(this)
                    throw FetchException(error.localizedMessage)
                } catch (ioException: IOException) {}
            }
}

The reason I can't overridefun onServerResponse(request: Downloader.ServerRequest, response: Downloader.Response) is because connections[response] is added to connections after onServerResponse call and they are also different objects. Are there any specific reason why it is built this way since onServerResponse doesn't seems to serve any purpose?

onServerResponse method can be used to simply get header and status information from the server response object. The reason why two objects are returned by the execute method is to protect the input source. If the inputSource is tampered with by a custom downloader, Fetch will fail and throw errors. Hard error to debug. I designed it this way for developers to not accidentally close the source.

Make sense. Thank you


JAR refers to anonymous types from other modules

Description:
$title, resulting in runtime crashes. The check at https://github.com/ballerina-platform/ballerina-lang/blob/v2201.0.3/compiler/ballerina-lang/src/main/java/org/wso2/ballerinalang/compiler/bir/codegen/JvmTypeGen.java#L835 seems to have been updated by mistake to compare the same value, resulting in samePackage always being true, so the type look up doesn't go through the anon type look up.
Steps to reproduce:
Using HTTP with a new OAuth2 version from central with the fix for https://github.com/ballerina-platform/ballerina-lang/issues/35872.
Affected Versions:
2201.0.3

Fixed in https://github.com/ballerina-platform/ballerina-lang/pull/35870.


Calamari: using child opts

Getting rid of hardcoded GPIO pins.

:+1:

Thanks, Ivan.
I pushed a new version, just moving some  .conf  changes from the 3rd commit to the 2nd one.

Applied.


[MINT-3084] Updated 4i and aco-os point of contact info

MINT-3084
Description

Added migration to update content according to Jira and Figma specification

How to test this change

Bring up containers
Open 4i and ACO-OS operational solution help cards
View points of contact
Compare against Figma

PR Author Checklist

[x] I have provided a detailed description of the changes in this PR.
[x] I have provided clear instructions on how to test the changes in this PR.
[x] I have updated tests or written new tests as appropriate in this PR.
[x] Updated the Postman Collection if necessary.

PR Reviewer Guidelines

It's best to pull the branch locally and test it, rather than just looking at the code online!
When approving a PR, provide a reason why you're approving it

e.g. "Approving because I tested it locally and all functionality works as expected"
e.g. "Approving because the change is simple and matches the Figma design"

Don't be afraid to leave comments or ask questions, especially if you don't understand why something was done! (This is often a great time to suggest code comments or documentation updates)
Check that all code is adequately covered by tests - if it isn't feel free to suggest the addition of tests.

Thanks @OddTomBrooks , approving based on functionality.
Small nitpick, you can adjust, or just proceed with the merge. I think it's best practice not to reference the the possible_solution by id, just for clarity of the migration. Since they happen to be the same in all environments, this works, but there is a bit of mystery reading the migration. Joining to the possible solution, and using the key would increase clarity.

Thanks for bringing this up, I did consider it and agree but like you said due to the homogeneity of the environment I felt it was better to keep the query simple and have a faster turnaround on the ticket. As an intermediary solution, I have added a table comment which addresses the clarity issue without adding logical complexity.


How to best expose rdkit SMIRNOFF to the user?

I guess it is good if we discuss and decide on how to expose rdkit SMIRNOFF to the end users.
At the moment, I just have a separate class called forcefield_rdk and a user will call that class instead of forcefield if they wish to use the rdkit version, and I am putting all import statements in SMIRNOFF concerning openeye products into try blocks.

The right approach to this is likely to add a layer of indirection between any of the calls from ForceField that require one of these toolkits (openeye or rdkit) and the actual calls to toolkit. That way, ForceField will not call either toolkit directly, but instead call methods in a utility chemical perception and molecule handling class which handles anything that talks to the toolkit.
We don't necessarily want to rewrite a whole abstract OEMol-like layer, so we should first determine the smallest number of major operations that interact with the OEMols and then define the abstraction API around this.
Alternatively, we could switch entirely to RDKit because it is fully open source (which matches our goals), but my gut feeling is that the science will be much more rapid using the OpenEye toolkit. On the other hand, we'll likely need to have switched to some entirely open source platform by mid-2018.

I think @jchodera is right here, though I understand that likely, @hjuinj , you will have to draw a line somewhere in terms of how much you are able to do versus what you want to pass off to us (though we'd love it if you want to be one of us for the long haul as well!).
It seems to me like there are a couple possible limiting scenarios for your involvement:

Minimal: You just finish your ForceField_rdk class which basically acts like ForceField but uses RDKit, then hand it off to us to sort out how we want to abstract the chemistry aspects out of it;
Extensive: You finish off as in (1) but then help us sort through how to abstract out the chemistry operations and get an implementation working which does this

Possibly you'll be somewhere in between those two extremes...?
Without reviewing code/details, I'm thinking offhand that the key places where we use chemistry toolkits are:

substructure searching (most obvious and most important)
partial charge assignment
sanity checks on input molecules (as we're discussing here: https://github.com/open-forcefield-group/openforcefield/issues/61 )
"advanced features": Partial bond orders

There would be also various other places you need chemistry if you're doing molecule preparation, though as noted in #61 we want to make sure molecule preparation is not automatically done by forcefield so that expert (or even normal) users don't have to worry it will be changing their chemistry on them if they are putting in a molecule which is already prepared. We just want to be sure forcefield has suitable warnings in place if someone puts in something which is clearly "bad chemistry" and give utility functionality that can be used to help prepare molecules when needed.

Hi David,
I would love to stay on and continue helping with the open forcefield initiative development. I think it is a great learning experience for me :)

Great, @hjuinj . That also should be helpful as (given your current position) you can hopefully help us broaden our user base into Europe (and other communities) as this grows. :)

So, basically, what that means is that we should help think through how exactly to do the more extensive changes to get these seamlessly linked up. Nag me when you're ready to do that and I'll try and help.

How about this:
My group (in NYC) to sit down and go through the forcefield.py code in detail and identify opportunities for a major refactor, isolating the OpenEye-specific calls in a few specific functions. We can then do that overhaul (likely as early as this weekend) and walk @hjuinj through the changes and updated docs next week. At that point, it should be easy to create RDKit versions of these functions from the current forcefield_rdk implementation.

Sounds fine to me, @jchodera . Note at the same time you may want to speed up parsing via #51 and perhaps also take care of #52.

@jchodera

My group (in NYC) to sit down and go through the forcefield.py code in detail and identify opportunities for a major refactor, isolating the OpenEye-specific calls in a few specific functions. We can then do that overhaul (likely as early as this weekend) and walk @hjuinj through the changes and updated docs next week. At that point, it should be easy to create RDKit versions of these functions from the current forcefield_rdk implementation.

Can you give an update on this? @hjuinj is waiting for you before proceeding any further, so if this has been put on the back burner it's probably good to let him know so that he makes different plans rather than continuing to wait.
Thanks.

I think we'll be able to go through this either Tue or Wed morning to get this set up for @hjuinj.

Resolved by big topology revamp.


Added "Far Shot" and "% more Damage for each remaining Chain" from Deadeye

Please tell me if something is not ok as I have never written LUA before 😄

I have already added support for Ricochet for the next update, which is part of a larger scale addition of chain support.
As for Far Shot, the reason I haven't added support for that yet is that I don't know how the scaling works. Do you have a source for the scaling ramp that you've used?

I took the most conservative version of how it could be implemented. Max distance for projectiles is 150 so that's the latest it should be at 30% more damage. So this is the worst way it could be implemented but is still more accurate than not supporting it at all. You might prefer to not to implement it at all if it's not correct. Feel free to close this PR in that case.

If you don't know the exact scaling, then the resulting output is just an estimate, and no better than what the user could work out themselves (even just mentally). But it would look accurate, and that's not good.


Version Control on Tables

I pulled in the history tracking script and added it to all of our point tables. Unfortunately, it didn't fare well in production.
Check out the ETL log in the admin panel starting at January 22, 2016 13:46 for all the details, but here's one example:
PlenarioETLError: ProgrammingError('(psycopg2.ProgrammingError) syntax error at or near "s"\nLINE 1: ...Post name, address, and telephone of owner, owner\'s agent fo...\n ^\nQUERY: INSERT INTO audit.micro_market_recovery_program_violations_and_inspe_history VALUES (\'2016-01-22 15:14:13.024878+00\',\'D\',\'(BLDG,BLDG_PERM,"PERMIT - NEW CONSTRUCTION",1418795,1416655,"2006-08-15 00:00:00",BL00812,CN_ANNUAL,f,2,f,,FAILED,1291458,"2009-09-23 17:05:36","2009-09-23 17:05:36","Building, post management sign",CN196029,"SEQ #: 6","2005-09-02 00:00:00",,,6,PCR31765,"POST OWNER/MANAGERS NAME/#","Post name, address, and telephone of owner, owner\'s agent for managing, controlling or collecting rents, and any other person managing or controlling building conspicuously where accessible or visible to public way. (13-12-030)",Austin,5500,W,LAKE,ST,,60644,25,28,1139449.8818507,1902230.53555938,41.8878297345816,-87.7633533997474,,81047,2556,"(41.88782973458163, -87.76335339974737)",c1e4f281cf7b7f51b0325c3358d03f95,0101000020E610000027CD37C8DAF055C0E0389D67A4F14440,"2005-09-02 00:00:00")\')\nCONTEXT: PL/pgSQL function if_modified() line 47 at EXECUTE statement\n',)

I removed the trigger from the tables and removed it from the ETL module for now.

Hi Will
Can you give me some clues how to debug on production system so I am careful.
The error is not informative so can I take the export this table out.
Let me know if you have any better ideas.
Tanu
On Jan 23, 2016, at 10:38 AM, Will Engler <notifications<EMAIL_ADDRESS>wrote:
I pulled in the history tracking script and added it to all of our point tables. Unfortunately, it didn't fare well in production.
Check out the ETL log in the admin panel starting at January 22, 2016 13:46 for all the details, but here's one example:
PlenarioETLError: ProgrammingError('(psycopg2.ProgrammingError) syntax error at or near "s"\nLINE 1: ...Post name, address, and telephone of owner, owner's agent fo...\n ^\nQUERY: INSERT INTO audit.micro_market_recovery_program_violations_and_inspe_history VALUES ('2016-01-22 15:14:13.024878+00','D','(BLDG,BLDG_PERM,"PERMIT - NEW CONSTRUCTION",1418795,1416655,"2006-08-15 00:00:00",BL00812,CN_ANNUAL,f,2,f,,FAILED,1291458,"2009-09-23 17:05:36","2009-09-23 17:05:36","Building, post management sign",CN196029,"SEQ #: 6","2005-09-02 00:00:00",,,6,PCR31765,"POST OWNER/MANAGERS NAME/#","Post name, address, and telephone of owner, owner's agent for managing, controlling or collecting rents, and any other person managing or controlling building conspicuously where accessible or visible to public way. (13-12-030)",Austin,5500,W,LAKE,ST,,60644,25,28,1139449.8818507,1902230.53555938,41.8878297345816,-87.7633533997474,,81047,2556,"(41.88782973458163, -87.76335339974737)",
c1e4f281
cf7b7f51b0325c3358d03f95,0101000020E610000027CD37C8DAF055C0E0389D67A4F14440,"2005-09-02 00:00:00")')\nCONTEXT: PL/pgSQL function if_modified() line 47 at EXECUTE statement\n',)
I removed the trigger from the tables and removed it from the ETL module for now.
—
Reply to this email directly or view it on GitHubhttps://github.com/UrbanCCD-UChicago/plenario/pull/209#issuecomment-174198691.


Please tag 0.5.1 (and keep tagging releases)

Fix incorporated into runc v0.1.1 qualifies for minor release of runtime-spec. Please tag.

On Sat, Jun 11, 2016 at 05:23:13PM -0700, Dmitry Smirnov wrote:

Fix incorporated into runc
v0.1.1
qualifies for minor release of runtime-spec. Please tag.

Which fix is that?  runtime-spec cut v1.0.0-rc1 on 2016-06-03 1, and
that landed in runC on the same day 2.  I'm not aware of anyone
planning to continue patch releases of the v0.5 line.

In Debian we can't upgrade runc because (its dependency) runtime-spec is not updated. As you may know runtime-spec is packaged separately (currently at version 0.5.0) and uploading RC version is not ideal... Hence tagging 0.5.1 would be helpful.

On Mon, Jun 13, 2016 at 12:15:45AM -0700, Dmitry Smirnov wrote:

As you may know runtime-spec is packaged separately (currently at
version 0.5.0) and uploading RC version is not ideal...

opencontainers/runc#746 bumped the spec dependency to 0.5.0 just
before cutting runC 0.1.0.  Since there have been no non-RC spec
releases since then, subsequent runC releases have been based on
random snapshots pulled from spec development.  I don't think there
will be any more OCI releases until opencontainers/tob#15 gets sorted
1, so waiting for 1.0s is probably about the same amount of time as
waiting for a 0.6.0 spec release and runC work targetting it.

@onlyjob sorry. Does the https://github.com/opencontainers/runtime-spec/releases/tag/v1.0.0-rc1 tag suffice for now?

That would probably work, thank you. :)
Though I prefer semantic tags and tagging 0.5.1 (not as far away from 0.5.0 as 1.0.0~rc1) might be even better...
Here you can read more about semantic versioning:

Debian Upstream Guide.
http://semver.org/
https://en.wikipedia.org/wiki/Software_versioning


Cannot get Meetups Where User is Co Organizer

In the API documentation it allows to search and pull groups where the user either has an organizer_id or a member_id. But typically many groups have only one organizer and several co-organizers. Is there a way of getting groups where a user is the organizer and or co organizer of?

I think we could do a better job at making this a first class filter, but can can lift this information from /2/groups for the authenticated member with this query You can inspect the results for the a self.role field which should contain information about you're lead team role in a target group.

You can now get this with newer sitewide profile endpoint when you send the request parameter fields=memberships. You should then find a membership.organizer field in the response containing a list of all the Meetup groups which this member is an organizer of
http://www.meetup.com/meetup_api/docs/members/:member_id/#get


getting "no file or directory found" error when building post-index for my own page

I am getting this error and I'm not sure how to fix it... it is true that the out/duck-cunt/post directory doesn't exist but I'm not sure why it wasn't made

here is the start of my list of projects in CONFIG.ts

I can fetch and re-run and let you know what output I get

okay possible cause of the bug: on my main acct I have @duck-cunt muted so I don't see my own posts from that acct in my feed. could that have caused the issue? I have unmuted it just in case

this was fixed by unmuting and following my own pages


Discussion: Preview of improved Functions http scaling behavior

Discussion thread for https://github.com/Azure/app-service-announcements/issues/90.

@davidebbo - do you know if the flag is still needed? Or is it enabled for anyone by default for all functions?

Great question: we actually had it enabled by default for a few days, but had to turn it off due to some issue. So for now, yes, you still need the flag. Normally, in another few weeks, it will be default again. /cc @suwatch

Does this change only apply to consumption based plans?
Can App Service plans also benefit from the changes?

@Fabian-Schmidt yes, it's only for Consumption.

To add to the discussion. A blog I found from @JamesRandall led me here.
https://www.azurefromthetrenches.com/azure-functions-significant-improvements-in-http-trigger-scaling/
There seems to be an very strong decrease from small peaks we experienced in our HTTP functions. Going from consistent 6ms responses to ~600ms suddenly.

@rikvandenberg please provide more details. Are you referring to cold start, or is that the response time you see always? Is this under high load scenario?

@davidebbo I'll try my best to best explain and what we are seeing.
Intro
So we have two simple azure function that does the following.

DistanceFunction: Calculate a geographical distance between 1 origin (lat/lon) and a maximum of 25 destination locations (lat/lon).

Uses System.Device.Location.GeoCoordinate

RouteFunction: Calculate a driving distance between 1 origin (lat/lon) and a maxmimum of 25 destination locations (lat/lon).

The route function uses Google Maps API and caches the results in to redis cache.

We call both functions with the exact same parameters in terms of origin and destination locations at the same time asynchronously from an ASP.NET WebAPI application. We are using a Task.WaitAll(tasks, 500) to also timeout after 500ms.
We require this timeout/performance to prevent the user request from blocking and we wish to continue. Thus we pre-emptively continue our request, as upon refresh, the route information will most likely be in the cache.
Performance Test

Over the span of  ~9 minutes we received 265 requests, ~130 for each function. Not a high load scenario.
We always used the EXACT same origin and destinations so that it will always use the CACHED results.
Our livestream metrics in Application Insights indicated at the time our azure function had 10 cloud role instances

Performance Test Results

From those 265 requests, 13 peaked above the 500ms. Results from AI analytics
12 of those requests are caused by the Route function as it has a heavier workload.
The peak doesn't seem to correlate with a "cold" cloud_roleinstance as it has been warmed up.
WEBSITE_HTTPSCALEV2_ENABLED=1

Possible Causes
It seems to me that sometimes the switch to another cloud_roleinstance is the causes of these "random" peaks, but I can't think of any other explainable cause 🤔
If you have any suggestions on how to approach these tests to give you more insights as well, please let me know and I'll see what I can do.

/cc @suwatch who is the expert.
@rikvandenberg What you're observing is likely the flipside of the new scale behavior. It's scaling faster (you're getting 10 instances), but at the same time you end up hitting more cold starts (one per instance). We may still need to tweak the system further to balance things.
BTW, WEBSITE_HTTPSCALEV2_ENABLED is now on by default which is likely why you might have seen a change. You can also try setting WEBSITE_HTTPSCALEV2_ENABLED=0 to revert to previous behavior.
Would you say that you're functions are CPU bound, or more I/O bound? I would think the later, as waiting for the Google Map result should take very little resources. In that sense, it is odd that it decided to scale this much. @suwatch will dig into it further.

It seems to me that sometimes the switch to another cloud_roleinstance is the causes of these "random" peaks, but I can't think of any other explainable cause

@rikvandenberg  Thank for reporting.  This was a result of unwarranted cold starts.  Our current scale implementation has a flaw when it comes to low load with occasional burst of concurrent requests.  The spikes caused us to scale out to more instances.   Since the spike was not sustaining, our scale in logic kicked in and removed the instances.   This happened alternately every 1-2 mins and, as a result, a moving set on instances was assigned to the function.   This explained the 10 instances from Application Insight.  They were not at the same time - but rather a different set over a 10 min period.   For each new instance assigned, it caused cold start (spike of long latency).
Good news is we have improved this logic by making the scale in less aggressive for this specific situation.  The ETA will be 2 weeks.   We will let you know to retry your scenario.

@suwatch Thanks for the quick response! I look forward to testing this improvement.

@rikvandenberg  The fix rollout takes longer than expected.  It will be likely be another week before the fix is available across.  If you are eager to experiment, try create a function app in West Central US location where the fix is available.    Otherwise, wait for a week.

@rikvandenberg The improvement has been rolled out completely.  Do try when you get a chance and provide any feedbacks.

@suwatch We just had our sprint planning today and have some time available to do a small test. I'll try to use the same test scenario. I'll let you know when we have got something.


More Alerting Receivers for Opni Altering

add support for teams via webhooks & generic webhook configs

Includes generic webhooks & microsoft teams endpoints via webhooks.


CallStack loss when re-throwing errors

I'd like to be able to preserve original throwError locations when checking if an error was thrown.
example :: (HasCallStack, Error () :> es) => Eff es ()
example = rethrowError throwsError
  where
    throwsError :: (HasCallStack, Error () :> es) => Eff es a
    -- call site is lost!
    throwsError = throwError ()
    rethrowError :: (HasCallStack, Error () :> es) => Eff es a -> Eff es a
    rethrowError m = do
      eres <- tryError m
      case eres of
        Right res  -> pure res
        -- discarded here
        Left (_,e) -> throwError e

Compare to Control.Exception.try:
example' :: HasCallStack => IO ()
example' = rethrowError throwsError
  where
    throwsError :: HasCallStack => IO a
    -- call site preserved
    throwsError = error "oops"
    rethrowError :: HasCallStack => IO a -> IO a
    rethrowError m = do
      eres <- try @ErrorCall m
      case eres of
        Right res -> pure res
        -- no callstack modification here
        Left e    -> throw e

When you rethrow, you need to do something like this:
    Left (cs, e) -> let ?callStack = cs in throwError e

Can you check if that fixes the issue?

Can you check if that fixes the issue?

This helps indeed, except I'm not sure if depending on this implementation detail is a good idea.

Btw, if you plan to rethrow the same error, you probably don't want to catch it manually, but use something like finally

Yes, I thought that perhaps it would be nice to have something like finally for effectful errors?

Please read introduction of https://hackage.haskell.org/package/effectful-core/docs/Effectful-Error-Static.html - you can see that finally from Control.Exception.Catch works as expected.

Oh... my bad. Big thanks!


fix: TA Analyze hotfix for spark 3.1

Summary
Briefly describe the changes included in this Pull Request.
Tests
Describe what tests have you performed to validate your changes before submitting the Pull Request. Use 'N/A' if not applicable.
Dependency chances
If you needed to make any chances to dependencies of this project, please describe them here.

/azp run

Codecov Report

Merging #1454 (a4bd37e) into spark3.1 (43a3f74) will decrease coverage by 14.84%.
The diff coverage is n/a.

@@              Coverage Diff              @@
##           spark3.1    #1454       +/-   ##
=============================================
- Coverage     84.80%   69.95%   -14.85%
=============================================
  Files           287      258       -29
  Lines         14250    12989     -1261
  Branches        723      723
=============================================
- Hits          12085     9087     -2998
- Misses         2165     3902     +1737

Impacted Files
Coverage Δ

...m/src/main/scala/com/microsoft/lightgbm/SWIG.scala
0.00% <0.00%> (-100.00%)
:arrow_down:

...la/org/apache/spark/ml/param/TypedArrayParam.scala
0.00% <0.00%> (-100.00%)
:arrow_down:

...oft/azure/synapse/ml/codegen/GenerationUtils.scala
0.00% <0.00%> (-100.00%)
:arrow_down:

...m/microsoft/azure/synapse/ml/codegen/CodeGen.scala
0.00% <0.00%> (-98.44%)
:arrow_down:

...microsoft/azure/synapse/ml/codegen/Wrappable.scala
10.25% <0.00%> (-89.11%)
:arrow_down:

...soft/azure/synapse/ml/cognitive/AudioStreams.scala
0.00% <0.00%> (-87.88%)
:arrow_down:

...ft/azure/synapse/ml/cognitive/AzureSearchAPI.scala
2.59% <0.00%> (-87.02%)
:arrow_down:

...synapse/ml/cognitive/TextAnalyticsSDKSchemas.scala
0.00% <0.00%> (-81.20%)
:arrow_down:

...osoft/azure/synapse/ml/cognitive/AzureSearch.scala
7.19% <0.00%> (-80.58%)
:arrow_down:

...azure/synapse/ml/lightgbm/LightGBMClassifier.scala
11.11% <0.00%> (-80.00%)
:arrow_down:

... and 82 more

Continue to review full report at Codecov.

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/azp run

/azp run


I followed the documentation. Despite installing and setting up everything, I always get a 404 error when I try to hit the /pluse route.

Pulse Version
1.2
Laravel Version
11.20.0
PHP Version
8.3.2
Livewire Version
3.0.2
Database Driver & Version
mysql 8.0.30
Description
I followed the official documentation. Despite installing and setting up everything, I always get a 404 error when I try to hit the /pluse route.
I don't know what I might be missing. Please guide me.
Steps To Reproduce
I followed the documentation and after installing pulse and setting up db and other things, when I tried to hit pulse route it always give me 404 error and it seems something is missing on code level.

Hey @Kashif-Kframe,
It looks like you've got a typo in the path - it should be /pulse rather than /pluse.


FAQ's page design

I would like to work on it.

@Jayashree-panda 👍

Let's discuss if we really need an FAQs page for a club website. As we really show

What we do?
Our projects

These points seems covered.

FAQ's page is needed to address some commonly asked questions like
-> What is Zairza?
-> How can I join Zairza?
-> What is the scope of Zairza?
-> What are the club timings?
-> I have a Tech project. How can Zairza help me?
(Source: https://zairza.in/ )
More information like "What we do?' can be addressed in the FAQ's page as well.
More questions can be addressed like
-> Why join Zairza?

Thanks @alishamohanty ! I had discussed this with @Jayashree-panda too!
@Jayashree-panda start your work and let us know where you are stuck.

Yes bhai..I will let you know.


HBASE-25568 Upgrade Thrift jar to fix CVE-2020-13949 (branch-2)

Upgrade the libthrift version to 0.14.1

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Personality
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git revision
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uname
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Personality
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git revision
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GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux e5e14eb85164 4.15.0-136-generic #140-Ubuntu SMP Thu Jan 28 05:20:47 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux

Build tool
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Personality
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git revision
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Default Java
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No case conflicting files found.

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Patch does not have any anti-patterns.

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The patch does not contain any @author tags.

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Maven dependency ordering for branch

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spotbugs
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branch-2 passed

_ Patch Compile Tests _

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mvndep
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Maven dependency ordering for patch

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mvninstall
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compile
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javac
8m 43s
the patch passed

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checkstyle
2m  2s
the patch passed

+1 :green_heart:
whitespace
0m  0s
The patch has no whitespace issues.

+1 :green_heart:
xml
0m  3s
The patch has no ill-formed XML file.

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hadoopcheck
12m  3s
Patch does not cause any errors with Hadoop 3.1.2 3.2.1.

+1 :green_heart:
spotbugs
14m 25s
the patch passed

_ Other Tests _

+1 :green_heart:
asflicense
0m 43s
The patch does not generate ASF License warnings.

76m 18s

Subsystem
Report/Notes

Docker
ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/2/artifact/yetus-general-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
dupname asflicense javac spotbugs hadoopcheck hbaseanti checkstyle compile xml

uname
Linux 6dc9f1e11ee4 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / 124ea5eee3

Default Java
AdoptOpenJDK-1.8.0_282-b08

Max. process+thread count
141 (vs. ulimit of 12500)

modules
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Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/2/console

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mvndep
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Maven dependency ordering for branch

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mvninstall
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branch-2 passed

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shadedjars
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branch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
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branch-2 passed

_ Patch Compile Tests _

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mvndep
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Maven dependency ordering for patch

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mvninstall
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the patch passed

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compile
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+1 :green_heart:
javac
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the patch passed

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shadedjars
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patch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
3m 54s
the patch passed

_ Other Tests _

+1 :green_heart:
unit
183m  2s
root in the patch passed.

224m 26s

Subsystem
Report/Notes

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ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/2/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 1797ad5616bd 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / 124ea5eee3

Default Java
AdoptOpenJDK-11.0.10+9

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/2/testReport/

Max. process+thread count
6871 (vs. ulimit of 12500)

modules
C: hbase-thrift hbase-examples . U: .

Console output
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Patch does not have any anti-patterns.

+1 :green_heart:
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0m  0s
The patch does not contain any @author tags.

_ branch-2 Compile Tests _

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mvndep
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Maven dependency ordering for branch

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mvninstall
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branch-2 passed

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compile
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branch-2 passed

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checkstyle
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branch-2 passed

+1 :green_heart:
spotbugs
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_ Patch Compile Tests _

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mvndep
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Maven dependency ordering for patch

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mvninstall
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the patch passed

+1 :green_heart:
compile
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+1 :green_heart:
javac
8m 35s
the patch passed

+1 :green_heart:
checkstyle
2m  1s
the patch passed

+1 :green_heart:
whitespace
0m  0s
The patch has no whitespace issues.

+1 :green_heart:
xml
0m  3s
The patch has no ill-formed XML file.

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hadoopcheck
11m 53s
Patch does not cause any errors with Hadoop 3.1.2 3.2.1.

+1 :green_heart:
spotbugs
13m 58s
the patch passed

_ Other Tests _

+1 :green_heart:
asflicense
0m 41s
The patch does not generate ASF License warnings.

75m 15s

Subsystem
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Docker
ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/artifact/yetus-general-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
dupname asflicense javac spotbugs hadoopcheck hbaseanti checkstyle compile xml

uname
Linux 6882c66a6b41 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / 124ea5eee3

Default Java
AdoptOpenJDK-1.8.0_282-b08

Max. process+thread count
141 (vs. ulimit of 12500)

modules
C: hbase-thrift hbase-examples . U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/console

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Unprocessed flag(s): --brief-report-file --spotbugs-strict-precheck --whitespace-eol-ignore-list --whitespace-tabs-ignore-list --quick-hadoopcheck

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_ branch-2 Compile Tests _

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mvndep
0m 23s
Maven dependency ordering for branch

+1 :green_heart:
mvninstall
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branch-2 passed

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branch-2 passed

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shadedjars
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branch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
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branch-2 passed

_ Patch Compile Tests _

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mvndep
0m 19s
Maven dependency ordering for patch

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mvninstall
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compile
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shadedjars
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javadoc
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the patch passed

_ Other Tests _

+1 :green_heart:
unit
261m 16s
root in the patch passed.

308m 52s

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Report/Notes

Docker
ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 50a0eafde4b3 4.15.0-128-generic #131-Ubuntu SMP Wed Dec 9 06:57:35 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / 124ea5eee3

Default Java
AdoptOpenJDK-11.0.10+9

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/testReport/

Max. process+thread count
4740 (vs. ulimit of 12500)

modules
C: hbase-thrift hbase-examples . U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/console

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+0 :ok:
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0m 25s
Maven dependency ordering for branch

+1 :green_heart:
mvninstall
3m 35s
branch-2 passed

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shadedjars
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_ Patch Compile Tests _

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mvndep
0m 21s
Maven dependency ordering for patch

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compile
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javac
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shadedjars
5m 57s
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+1 :green_heart:
javadoc
3m  8s
the patch passed

_ Other Tests _

-1 :x:
unit
333m 16s
root in the patch failed.

367m 23s

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ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/artifact/yetus-jdk8-hadoop2-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/3083

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 81aa98d2a3e4 4.15.0-60-generic #67-Ubuntu SMP Thu Aug 22 16:55:30 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
branch-2 / 124ea5eee3

Default Java
AdoptOpenJDK-1.8.0_282-b08

unit
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/artifact/yetus-jdk8-hadoop2-check/output/patch-unit-root.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/testReport/

Max. process+thread count
4566 (vs. ulimit of 12500)

modules
C: hbase-thrift hbase-examples . U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-3083/3/console

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Test case failures are not relevant, passing locally.


Users billing email address keeps coming in over and over again

@jbaxleyiii do you have reproduction steps or a screenshot of this? :heart:

@johnthepink sorry! Its one I'll take ;)


CB-15446: Added logic to SDX resize detach flow so that failures are recovered from.

Jira: https://jira.cloudera.com/browse/CB-15446
This was merged in before but was reverted due to an e2e issue. Previous PR: https://github.com/hortonworks/cloudbreak/pull/11965

before merge, pls check resize related test failure: https://jira.cloudera.com/browse/CB-16208

Did a general rebase so this isn't too out of date and to aid in development of dependent changes.

retest this please


Feature Request: Enhance Member Permission Management

Description
Hey team,
I was wondering if we could improve the permission management for members. Since we're dealing with teams and applications, having a robust permission design is crucial. I'd love to open up a discussion on this and explore how we can incorporate it into our current setup. Looking forward to your thoughts!

How powerful do you want the user permission feature to be? You can provide more details to help us design the product.
In fact, APIPark already includes a role-based feature that controls permissions for different roles, and we are considering strengthening the permission management feature in the future commercial version.


No arping plugin ?

We actually use Pfsense in production mode.
We had tested Opnsense which is great but, but, there is NO arping tool and no plugin (like pfsense). This is an indispensable TOOL for troubleshoot network/mac problem connectivy, we use it very often.
In this situation we can remplace pfsense with opnsense without this feature ...

What exactly should this plugin achieve? Never used it on pf

This is juste the arping command which is available in CLI.
https://en.wikipedia.org/wiki/Arping
This is very usefull tool for detect dual IP on the same network, or the state of the cisco routeur, actually we haven't hand on the hardware routeur GW and we install Pfsense in Virtual Machine. This is very common architecture configuration in Private Cloud provider like OVH.
Sometimes they do some shit with their network, like giving 2 times the same public IP ... arping is the tool for detect this kind of mistake or egally check the status of the arp table of the cisco routeur GW.

I see. Seems there isn't even an arping pkg available yet. Maybe arpwatch would make more sense as it triggers a warning itself if it seems changing mac address. :)

There is a simmilar plug in available:
https://github.com/opnsense/plugins/tree/master/net/arp-scan

This issue has been automatically timed-out (after 180 days of inactivity).
For more information about the policies for this repository,
please read https://github.com/opnsense/plugins/blob/master/CONTRIBUTING.md for further details.
If someone wants to step up and work on this issue,
just let us know, so we can reopen the issue and assign an owner to it.