tivrfoa

The fastest way to understand source code is to avoid reading it line-by-line. Instead, use a top-down, interactive approach focused on tracing a single feature.

Think of it like exploring a new city: you don't start by walking every single street. You look at a map, find the city center, and follow the main roads to a landmark.

## 1. Start High (The 10-Minute Map) 🗺️

Your first goal is to get a "map" of the project, not to understand every building.

https://www.youtube.com/watch?v=XRUMbGweHsY

-XX:CompileThreshold=1 -XX:-TieredCompilation is an interesting test.

Even then, the interpreted version ran 9969 times.

JVM Flags Explanation https://chatgpt.com/s/t_68fe297b69308191a32d33d5108e0a59

AOT

https://x.com/shipilev/status/1970805877545505108

Aleksey Shipilëv @shipilev Timings get way better for any AOT mode when there are only a few available cores to run JIT in background. Once aggressive JIT compiler starts to compete with the application, it hurts a lot, and residency graphs are a mess. There are 2-3x wins, though. Oh man.

https://www.reddit.com/r/microservices/comments/17p2zrk/does_microservices_architecture_requires_a/

https://stackoverflow.com/questions/44085454/join-table-between-different-microservices

https://stackoverflow.com/a/44104451/25118705

https://stackoverflow.com/questions/29761872/microservices-and-database-joins#comment47737622_29762027

https://www.reddit.com/r/golang/comments/1gpj9n7/comment/lwqmg9k/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Prompt: So to process different chunks of a file in parallel, is RandomAccessFile the only option is to use ?

ChatGPT:

No, RandomAccessFile is not the only option. There are several alternatives for processing different chunks of a file in parallel:

FileChannel and MappedByteBuffer:

Using a FileChannel, you can memory-map a file (or portions of it) into a MappedByteBuffer with the map() method.

Prompt: Write a Java benchmark program using JMH, that benchmarks TreeSet vs PriorityQueue.

Here is a complete Java benchmark program using JMH (Java Microbenchmark Harness) to compare the performance of TreeSet and PriorityQueue. The benchmark focuses on three key operations: adding elements, adding and removing the smallest element, and checking for element existence. Benchmark Overview We will measure the performance of TreeSet and PriorityQueue for the following operations:

Adding Elements:

	import speech_recognition as sr
	import sys
	import os
	import subprocess
	import tempfile

	def convert_to_wav(input_file):
	"""Convert input audio to a temporary WAV file using ffmpeg"""
	tmp_wav = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
	tmp_wav.close()

	package com.example.mandelbrot;

	import javafx.application.Application;
	import javafx.scene.Scene;
	import javafx.scene.canvas.Canvas;
	import javafx.scene.canvas.GraphicsContext;
	import javafx.scene.layout.Pane;
	import javafx.scene.paint.Color;
	import javafx.stage.Stage;
	import javafx.scene.image.PixelWriter;

	// using threads so it can read and write without blocking

	use std::io::{self, prelude::*, BufReader, BufWriter, Write};
	use std::net::TcpStream;
	use std::env;
	use std::thread;

	fn main() -> io::Result<()> {
	let args: Vec<String> = env::args().collect();


	# find files that contain the string STR and delete them

	find src/main/java -type f -exec grep -q "STR" {} \; -delete