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import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.io.{LongWritable, Text}
import org.apache.hadoop.mapreduce.lib.input.{FileSplit, TextInputFormat}
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.rdd.NewHadoopRDD

object Program {
  def main(args: Array[String]): Unit = {
    val srcFile = "hdfs://sandbox/Numbers.txt"
    val conf = new SparkConf().setAppName("spark-numbers")

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section .text
global _start

_start:

	mov rdi, 42
	mov rax, 60 ; sys_exit
	syscall
  
; assemble the elf64 object file with nasm:

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namespace Collections

module RiderReproTests =

    open FsCheck.Xunit
    open Xunit

    [<Property>]
    let repro_test_pass (_:int) = true

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"""Implements a simple expression evaluator.

Supported syntax:
1. Balanced parenthesis for grouping.
2. Numbers. Can include a decimal point.
3. Negation ('-' as a prefix unary operator)
4. Binary operators for '*', '/', '+', and '-'.

Order of operations follow typical rules:
1. Grouping. (1+2)

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#include <stdbool.h>
#include <stddef.h>
#include <string.h>
#include <stdio.h>

typedef struct thing thing_t;

struct thing {
    long num;
    int cnt;

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Bash array usage cheatsheet

• Create array
• Get elements
• Append element
• Get length
• Iteration
• Pass to function
• Reference

Create array

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//! Proof of concept for a reference counted [str]
//! Primary innovation over a plain Rc<str> is that is one less level of
//! indirection and heap allocation

#![feature(const_alloc_layout)]


use core::ptr::NonNull;
use std::alloc::Layout;
use std::alloc::{GlobalAlloc, System};