ExpandingMan

#include <alloca.h>
#include <errno.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
// anari
#include "anari/anari.h"
#define ANARI_EXTENSION_UTILITY_IMPL
#include "anari/frontend/anari_extension_utility.h"

ExpandingMan

Computer Information:
    Manufacturer:  ASUSTeK COMPUTER INC.
    Model:  TUF GAMING X570-PLUS (WI-FI)
    Form Factor: Desktop
    No Touch Input Detected

Processor Information:
    CPU Vendor:  AuthenticAMD
    CPU Brand:  AMD Ryzen 7 3800X 8-Core Processor             
    CPU Family:  0x17

ExpandingMan

using AbstractTrees, BenchmarkTools, Random
using AbstractTrees: PreOrderState, next

using Base: @kwdef


@kwdef struct RandTreeParams
    max_generations::Int = 5
    max_children::Int = 3
end

ExpandingMan

======================
Proton: 1636976115 experimental-6.3-20211115
SteamGameId: 780310
Command: ['/home/expandingman/.local/share/Steam/steamapps/common/Riftbreaker/bin/Launcher.exe']
Options: {'forcelgadd'}
depot: 0.20211014.30
pressure-vessel: 0.20210906.2
scripts: v0.20210917.0-0-g1cf127d
soldier: 0.20211013.0 soldier 0.20211013.0
Kernel: Linux 5.14.10-1-MANJARO #1 SMP PREEMPT Thu Oct 7 06:43:34 UTC 2021 x86_64

ExpandingMan

Computer Information:
    Manufacturer:  Unknown
    Model:  Unknown
    Form Factor: Desktop
    No Touch Input Detected

Processor Information:
    CPU Vendor:  AuthenticAMD
    CPU Brand:  AMD Ryzen 7 3800X 8-Core Processor             
    CPU Family:  0x17

ExpandingMan

The Plan

The ultimate goal is to have a package or set of packages for large-scale distributed computing on tabular data in Julia that works "out of the box". We would like to be able to replace processes that run in e.g. Apache Spark or Python's dask.

Examples of things we'd like to be able to do:

• Get table metadata for a table that is spread across a hundred CSV files in HDFS.
• Join a 10^10 row table which is stored as parquet files on S3 buckets with a 100 row table that we create locally in memory, perform a groupby operation and save to a new table as parquet files on S3.

ExpandingMan

using DifferentialEquations, LinearAlgebra, ThreadsX, DiffEqGPU, StaticArrays, ThreadsX, BenchmarkTools

struct DnegWormhole
    ρ::Float64
    a::Float64
    M::Float64
end

const DEFAULT_WORMHOLE = Ref{DnegWormhole}(DnegWormhole(1.0, 0.5, 0.5))
default_wormhole() = DEFAULT_WORMHOLE[]

ExpandingMan

function hacked_jlopts(jlopts::Base.JLOptions, str::String)
    f = (n, arg) -> n == :trace_compile ? pointer(str) : arg
    GC.@preserve str Base.JLOptions((f(n, getproperty(jlopts, n)) for n ∈ fieldnames(Base.JLOptions))...)
end

function hack_jlopts(str::String)
    ptr = convert(Ptr{Base.JLOptions}, cglobal(:jl_options))
    jlopts = hacked_jlopts(Base.JLOptions(), str)
    unsafe_store!(ptr, jlopts)
    jlopts

ExpandingMan

import pyarrow as pa

v = pa.array([1,2,3,4])

batch = pa.RecordBatch.from_arrays([v], ["this_is_the_column_name"])

sink = pa.BufferOutputStream()

writer = pa.RecordBatchStreamWriter(sink, batch.schema)

ExpandingMan

let searchengine duckduckgo = "https://duckduckgo.com/?q=%s&t=vivaldi"
let defaultengine = "duckduckgo"

" key bindings
map d x