dcp | distributed file copy program | Architecture library

so I'm in a new internship position and I was told to modernize a JEE applciation. I've migrated the code in my machine in both .rar , .tar.gz and raw source code , and I sotill get the same problem. so here is the full stack trace of the problem :

We had a rogue producer setting a Kafka Header __TypeId__ to a class that was part of the producer, but not of a consumer implemented within a Spring Cloud Stream application using Kafka Streams binder. It resulted in an exception java.lang.IllegalArgumentException: The class 'com.bad.MyClass' is not in the trusted packages: [java.util, java.lang, de.datev.pws.loon.dcp.foreignmodels.*]. If you believe this class is safe to deserialize, please provide its name. If the serialization is only done by a trusted source, you can also enable trust all (*).

How can we ensure within the consumer that this TypeId header is ignored?

Some stackoverflow answers point to spring.json.use.type.headers=false, but it seems to be an "old" property, that is no more valid.

application.yaml:

I want to solve linear regression in the following way

When I try with minimizing the sum of cost it works fine,

It's not entirely lasso because I add an extra constraint but I'm not sure how I'm supposed to solve a problem like the following using cvxpy

After filtering out the inverse duplicates, I have to count how many actual duplicates there are. Here is my (working example) code, it's too slow though, for 90 000+ rows.. using iterrows:

This is my MacBook Pro details overview:

• Model Name: MacBook Pro
• Chip: Apple M1
• Total Number of Cores: 8 (4 performance and 4 efficiency)
• Memory: 8 GB
• System Version: macOS 11.2.2 (20D80) -- macOS Big Sur

Andriod Studio Preview for Arm64 M1 Chip details are as shown in below image:

Crash Error report page after computer restarted:

I am using the CVXR modelling package to solve a convex optimization problem. I know for sure that the problem is convex and that it follows the DCP rules, but if I check the DCP rules using CVXR it returns False. However, if I take the exact same problem and check it using CVXPY it returns True (as expected)

What is happening here? I attach a minimal reproducible example of this behavior in R and Python:

I am trying to run the following optimization using CVXPY:

Problem: I have 50 text files, each with thousands of lines of text, each line has a value on it. I am only interesting in a small section near the middle (lines 757-827 - it is actually lines 745-805 I'm interested in, but the first 12 lines of every file is irrelevant stuff). I would like to read each file in. And then total the values between those lines. In the end I would like it to print off a pair of numbers in the format (((n+1)*18),total count), where n is the number of the file (since they are numbered starting at zero). Then repeat for all 50 files, giving 50 pairs of numbers, looking something like:

(18,77),(36,63),(54,50),(72,42),...

Code: