tim-patterson

Hive partitioning scheme for dealing with late arriving data etc.

Over the last few years I've been quite involved with using hive for big data analysis.

I've read many web tutorials and blogs about using hadoop/hive/pig for data analysis but all them seem to be over simplified and targeted as a "my first hive query" kind of audience instead of showing how to structure hive tables and queries for real word use cases eg years of data, reoccurring batch jobs to build aggregate/reporting tables and having to deal with late arriving data etc.

Most of these tutorials look something like this

Twitter Data -> hdfs/external hive table external hive table -> hive query -> results.

tim-patterson

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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tim-patterson

include /usr/share/nano/c.nanorc
include /usr/share/nano/html.nanorc
include /usr/share/nano/makefile.nanorc
include /usr/share/nano/python.nanorc
include /usr/share/nano/xml.nanorc
include /usr/share/nano/java.nanorc
include /usr/share/nano/sh.nanorc
set autoindent
set nowrap
set tabsize 4

tim-patterson

import wx
import sys
from wx._core import EVT_LEFT_UP

class MainWindow(wx.Frame):
    def __init__(self):
        wx.Frame.__init__(self, None, title='Python Listbox test')
        self.setup_menu()
        self.setup_list()