miyagawa

#!/usr/bin/env perl
use strict;
use File::Find::Rule;
use Capture::Tiny qw(capture);

sub atomic {
    my($file, @cmd) = @_;
    capture {
        system "atomicparsley", $file, @cmd;
    };

tobyhede

 -- PostgreSQL 9.2 beta (for the new JSON datatype)
 --   You can actually use an earlier version and a TEXT type too
 -- PL/V8 http://code.google.com/p/plv8js/wiki/PLV8

 -- Inspired by 
 -- http://people.planetpostgresql.org/andrew/index.php?/archives/249-Using-PLV8-to-index-JSON.html
 -- http://ssql-pgaustin.herokuapp.com/#1

  -- JSON Types need to be mapped into corresponding PG types 
  -- 

marcelcaraciolo

#-*-coding: utf-8 -*-

'''

    This module represents the FriendsRecommender system for recommending
    new friends based on friendship similarity and state similarity.

'''
__author__ = 'Marcel Caraciolo <[email protected]>'

mbostock

license: gpl-3.0
height: 2000
border: no
redirect: https://beta.observablehq.com/@mbostock/d3-cluster-dendrogram

bcantrill

From bmc Mon Oct  2 15:12:34 2000
Subject: Undergrad systems curriculum
To: [email protected]
Date: Mon, 2 Oct 2000 15:12:34 -0700 (PDT)
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Status: RO

pbailis

A friend asked me for a few pointers to interesting, mostly recent papers on data warehousing and "big data" database systems, with an eye towards real-world deployments. I figured I'd share the list. It's biased and rather incomplete but maybe of interest to someone. While many are obvious choices (I've omitted several, like MapReduce), I think there are a few underappreciated gems.

###Dataflow Engines:

Dryad--general-purpose distributed parallel dataflow engine
http://research.microsoft.com/en-us/projects/dryad/eurosys07.pdf

Spark--in memory dataflow
http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf

hadley

Notes:

• I've tried to break up in to separate pieces, but it's not always possible: e.g. knowledge of data structures and subsetting are tidy intertwined.

• Level of Bloom's taxonomy listed in square brackets, e.g. http://bit.ly/15gqPEx. Few categories currently assess components higher in the taxonomy.

Programming R curriculum

Data structures

avibryant

Recent versions of Cloudera's Impala added NDV, a "number of distinct values" aggregate function that uses the HyperLogLog algorithm to estimate this number, in parallel, in a fixed amount of space.

This can make a really, really big difference: in a large table I tested this on, which had roughly 100M unique values of mycolumn, using NDV(mycolumn) got me an approximate answer in 27 seconds, whereas the exact answer using count(distinct mycolumn) took ... well, I don't know how long, because I got tired of waiting for it after 45 minutes.

It's fun to note, though, that because of another recent addition to Impala's dialect of SQL, the fnv_hash function, you don't actually need to use NDV; instead, you can build HyperLogLog yourself from mathematical primitives.

HyperLogLog hashes each value it sees, and then assigns them to a bucket based on the low order bits of the hash. It's common to use 1024 buckets, so we can get the bucket by using a bitwise & with 1023:

select

octocat

# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so

# Packages #

P7h

#####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####   #####

### Shell script to download Oracle JDK / JRE / Java binaries from Oracle website using terminal / command / shell prompt using wget.
### You can download all the binaries one-shot by just giving the BASE_URL.
### Script might be useful if you need Oracle JDK on Amazon EC2 env.
### Script is updated for every JDK release.

### Features:-
# 1. Resumes a broken / interrupted [previous] download, if any.
# 2. Renames the file to a proper name with including platform info.