slidingwindow | Sliding Window library for image processing in Python | Computer Vision library

Having trouble with CUDA + Pytorch this is the error. I reinstalled CUDA and cudnn multiple times.

Conda env is detecting GPU but its giving errors with pytorch and certain cuda libraries. I tried with Cuda 10.1 and 10.0, and cudnn version 8 and 7.6.5, Added cuda to path and everything.

However anaconda is showing cuda tool kit 9.0 is installed, whilst I clearly installed 10.0, so I am not entirely sure what's the deal with that.

I am trying to write an unbounded ping pipeline that takes output from a ping command and parses it to determine some statistics about the RTT (avg/min/max) and for now, just print the results.

I have already written an unbounded ping source that outputs each line as it comes in. The results are windowed every second for every 5 seconds of pings. The windowed data is fed to a Combine.globally call to statefully process the string outputs. The problem is that the accumulators are never merged and the output is never extracted. This means that the pipeline never continues past this point. What am I doing wrong here?

I'm quite new to Apache Beam and implemented my first pipelines.

But now I got to a point, where I am confused how to combine windowing and joining.

Problem definition:

I have two streams of data, one with pageviews of users, and another with requests of the users. They share the key session_id which describes the users session, but each have other additional data.

The goal is to compute the number of pageviews in a session before a request happened. That means, I want to have a stream of data that has every request together with the number of pageviews before the request. It suffices to have the pageviews of lets say the last 5 minutes.

What I tried

To load the requests I use this snippet, which loads the requests from a pubsub subscription and then extracts the session_id as key. Lastly, I apply a window which emits every request directly when it is received.

My goal is to provide an interface for a stream processing module in Flink 1.10. The pipeline contains an AggregateFunction among other operators. All operators have generic types but the problem lies within the AggregateFunction, which cannot determine the output type.

Note: The actual pipeline has a slidingEventTimeWindow assigner and a WindowFunction passed along with the AggregateFunction, but the error can be reproduced much easier with the code below.

This is a simple test case that reproduces the error:

I have a problem with deriving variables from input file names - especially if you want to split based on a delimiter. I have tried different approaches (which I can't get to work) and the only one that works so far, fails in the end, because its looking for all possible variations of variables (and hence input files that don't exist).

My problem - the input files are named in the following pattern: 18AR1376_S57_R2_001.fastq.gz

My initial definition of variables at the beginning:
SAMPLES, = glob_wildcards("../run_links/{sample}_R1_001.fastq.gz")

but that ends up with my files all being named 18AR1376_S57 subsequently and I'd like to remove _S57 (which refers to the sample sheet id).

An approach that I have found while searching and which works is this:
SAMPLES,SHEETID, = glob_wildcards("../run_links/{sample}_{SHEETID}_R1.001.fastq.gz"}
but it looks for all possible combinations of sample and sheetid, and hence looks for input files that don't exist.

I then tried a more basic python approach:

I have the following input (testing in the Azure portal) that I have uploaded:

I am trying to remove duplicate events from an unbounded stream of data. I tried using sliding windows (60 seconds window with 30 seconds period) along with grouping events by unique key but it seems to be not working since the events that belong to multiple windows are emitted multiple times (more details).

I have the following code:

I have this simple code

I am trying to define a custom trigger for a sliding window that triggers repeatedly for every element, but also triggers finally at the end of the watermark. I've looked around documentation for almost an hour now but have yet to find any example :(.