This document lays out the ways in which a few prominent SQL-on-Hadoop systems read and write decimal values from and to parquet files, and their respective in-memory formats.
Parquet's logical DECIMAL type can to be represented by the following
physical types.
| // This file is MIT Licensed. | |
| // | |
| // Copyright 2017 Christian Reitwiessner | |
| // Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: | |
| // The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. | |
| // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF O |
| #!/usr/bin/env python | |
| import ctypes, re, sys | |
| c_ptrace = ctypes.CDLL("libc.so.6").ptrace | |
| c_pid_t = ctypes.c_int32 | |
| c_ptrace.argtypes = [ctypes.c_int, c_pid_t, ctypes.c_void_p, ctypes.c_void_p] | |
| def ptrace(attach, pid): | |
| op = ctypes.c_int(16 if attach else 17) |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
| trait RankN { | |
| type TransformRank1[CC[X]] = CC ~> CC | |
| type TransformRank0[CC[X]] = CC[_] => CC[_] | |
| def liftRank[CC[X]](f: TransformRank0[CC]): TransformRank1[CC] = | |
| new TransformRank1[CC] { | |
| def apply[A](x: CC[A]): CC[A] = f(x).castTo[CC[A]] | |
| } | |
| } |