Feature idea summary

Cgroups plugin supports only proportional and max Block IO policies. We should support BFQ scheduler as well. Disk stats for the scheduler are in blkio.bfq.io_service_bytes and blkio.bfq.io_serviced files.

Relevant telegraf.conf:

[[inputs.kinesis_consumer]]
  region = "eu-west-1"
  streamname = "telegrafStream"
  data_format = "influx"

System info:

Telegrad 1.17.2-alpine (running in Fargate)

Steps to reproduce:

it's becoming more time-consuming and error-prone to manually re-test all the demos following internal refactorings and API adjustments.

now that the API is fleshed out a bit, it's possible to test a large amount of code (non-granularly) without having to simulate all interactions via Puppeteer or similar.

a lot of code can already be regression-tested by simply running all the demos and val

Is your feature request related to a problem? Please describe.
Currently, window length parameters (e.g. window_length or initial_window in SlidingWindowSplitter) have to be integers and denote the absolute number of time points, similar to how scikit-learn handles fractions in their cross-validation functionality.

Describe the solution you'd like
Add support for floats denotin

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提建议？
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提修复PR？
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提Feature？
建议先将想法提出，不着急写代码，与社区同道沟通，大家觉得OK再做代码实现

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We should remove Guava as a dependency from the server module.

Most of the functionality we used from Guava are provided by the JDK by now.
The stuff that is missing from the JDK has mostly been added in the utilities we inherited from Elasticsearch, due to their decision to remove Guava completely.
Any functionality that we use which isn't present in the JDK can be co

Is your feature request related to a problem? Please describe.
When starting QuestDB, it's hard to tell the location of the server.conf file, and this becomes more complicated when running via Docker, from source or from Homebrew.

Describe the solution you'd like
The server should print out the location of the currently-used configuration file, and if possible, state which non-defa

Description

(A clear and concise description of what the feature is.)

• util.cumsum implementation https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/mx/util.py#L326 does not scale under mx.ndarray
• cumsum is 2-5 times slower than nd.cumsum under both mx.sym and mx.ndarray, and even fails for large 4-dim input

Sample test

Code

# import ...
def test_

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually