stream-processing

I figured out a way to get the (x,y,z) data points for each frame from one hand previously. but im not sure how to do that for the new holistic model that they released. I am trying to get the all landmark data points for both hands as well as parts of the chest and face. does anyone know how to extract the holistic landmark data/print it to a text file? or at least give me some directions as to h

Bug description

Header in Top Endpoint section overflows in browser with reduced width

Expected behavior

Header shouldn't overflow

How to reproduce

1. Go to SigNoz dashboard metrics page with reduced browser window width
2. Open any application
3. Top Endpoint panel header appears overflowing

Version information

• Signoz version: v0.7.1
• *Browser version

I have a use case where I need to create a new stream containing the bearing between two consecutive points in a pre-existing lat/lon stream. Normally bearing would be available in a standard lib but in a pinch can easily be implemented through sin, cos, and atan2 funcs, none of which are currently available in ksql.

Basic trig functions have a range of use cases in geometric and geographic co

Add --add-exports jdk.management/com.ibm.lang.management.internal only when OpenJ9 detected.

Otherwise we got WARNING: package com.ibm.lang.management.internal not in jdk.management in logs

Under the hood, Benthos csv input uses the standard encoding/csv packages's csv.Reader struct.

The current implementation of csv input doesn't allow setting the LazyQuotes field.

We have a use case where we need to set the LazyQuotes field in order to make things work correctly.

I have this implemented in a custom marshaler now but wondering if it makes sense to push back upstream - when we are integrating with legacy services we find it useful to use the correlation ID as the message ID when first brought into watermill - from there they get sent on headers to subsequent services and work normally.

Its a simple change if it would make sense for other users.

I would like to convert a DataFrame to a JSON object the same way that Pandas does with to_dict().

toJSON() treats rows as elements in an array, and ignores the index labels. But to_dict() uses the index as keys.

Here is an example of what I have in mind:

function to_dict(df) {
    const rows = df.toJSON();
    const entries = df.index.map((e, i) => ({ [e]: rows[i] }));
  

It can be very difficult to piece together a reasonably estimate of a history of events from the current workers logs because none of them have timestamps.

So for that end, I think we should add timestamps to the logs.

This has some cons:

1. We can't just use @printf like we have been until now. We need to either include a timestamp in every @printf call (laborious and error prone) or c

For example, given a simple pipeline such as:

Pipeline p = Pipeline.create();
p.readFrom(TestSources.items("the", "quick", "brown", "fox"))
 .aggregate(aggregator)
 .writeTo(Sinks.logger());

I'd like aggregator to be something requiring a non-serialisable dependency to do its work.

I know I can do this:

Pipeline p = Pipeline.create();
p.readFrom(TestSource

The mapcat function seems to choke if you pass in a mapping function that returns a stream instead of a sequence:

user> (s/stream->seq (s/mapcat (fn [x] (s/->source [x])) (s/->source [1 2 3])))
()
Aug 18, 2019 2:23:39 PM clojure.tools.logging$eval5577$fn__5581 invoke
SEVERE: error in message propagation
java.lang.IllegalArgumentException: Don't know how to create ISeq from: manifold.