Finally, game cartridges you can plug in to your smart phone

Downloading games directly to your smartphone and playing them immediately is convenient, I suppose. But this ephemeral, bloodless process is missing a familiar tangibility gamers might remember warmly from the last millennium: that comforting, solid, life-affirming feeling of jamming a game cartridge into a console slot.

Enter Pico Cassette, a Japanese outfit that says it’s bringing back “the next retro” with tiny game cartridges that plug in to a smartphone’s headphone jack. The tiny “cassettes” (the general Japanese term for cartridges) are built on PlugAir technology, which uses a specially designed iPhone or Android app to draw power from the headphone jack and send data using specially modulated audio signals.

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Finally, game cartridges you can plug in to your smart phone

Downloading games directly to your smartphone and playing them immediately is convenient, I suppose. But this ephemeral, bloodless process is missing a familiar tangibility gamers might remember warmly from the last millennium: that comforting, solid, life-affirming feeling of jamming a game cartridge into a console slot.

Enter Pico Cassette, a Japanese outfit that says it’s bringing back “the next retro” with tiny game cartridges that plug in to a smartphone’s headphone jack. The tiny “cassettes” (the general Japanese term for cartridges) are built on PlugAir technology, which uses a specially designed iPhone or Android app to draw power from the headphone jack and send data using specially modulated audio signals.

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What’s the correct way of using reduceByKey in Spark using Python

I’m new to apache spark and don’t know if I’m misunderstanding reduceByKey or am encountering a bug. I’m using the spark-1.4.1-bin-hadoop1 build, due to
issues with the python Cassandra interface in spark-1.4.1-bin-hadoop2.

reduceByKey(lambda x,y: y[0]) returns the first value of the last tuple,
but reduceByKey(lambda x,y: x[0]) throws an exception.

Trying to get to reduceByKey(lambda x,y: x[0]+y[0]), to sum values by key, but that statement throws the same exception as x[0].

Code Fragments:

import sys

from pyspark import SparkContext, SparkConf
from pyspark import StorageLevel
from pyspark.sql import SQLContext, Row
from pyspark.sql.types import *

import h5py
import sys
import numpy
import os
import datetime

if __name__ == "__main__":

  sc_conf = SparkConf().setAppName("VIIRS_QC").set("spark.default.parallelism", "49").set("spark.storage.memoryFraction", "0.75")
  sc = SparkContext(conf=sc_conf)

  sqlContext=SQLContext(sc)

  f=h5py.File("/mnt/NAS/pmacharr/sample_20130918/GMTCO_npp_d20130919_t0544413_e0546054_b09816_c20130919063740340635_noaa_ops.h5", 'r')
  result = f["/All_Data/VIIRS-MOD-GEO-TC_All/Latitude"]
  myLats = numpy.ravel(result).tolist()
  ...
  t1 = numpy.dstack((myLats, myLons, myArray, myM2_radiance, myDNP))

  t1 = t1.tolist()

  x=sc.parallelize(t1[0][123401:123410])

  print t1[0][123401:123410]
  print "input list=", t1[0][123401:123410]

  y=x.map(
      lambda (lat, lon, m6_rad, m2_rad, dn):
                    ((round(lat,0),round(lon,0),dn), (m2_rad,m6_rad))
       )

  print "map"
  print y.collect()

  print "reduceByKey(lambda x,y: x)=", y.reduceByKey(lambda x,y: x ).collect()
  print "reduceByKey(lambda x,y: y)=", y.reduceByKey(lambda x,y: y ).collect()
  print "reduceByKey(lambda x,y: y[0])=", y.reduceByKey(lambda x,y: y[0]).collect()
  print "reduceByKey(lambda x,y: x[0])=", y.reduceByKey(lambda x,y: x[0]).collect()

  sc.stop()
  exit()

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How do I set the version of IE used by an Outlook VSTO Add-in?

I’m having difficulty finding information on this. I have a Winforms Webbrowser control in my VSTO Outlook add-in.

In other .net projects using this control, I changed it’s IE version by setting a registry key at HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Internet Explorer\MAIN\FeatureControl\FEATURE_BROWSER_EMULATION specifying my exe with one of the ie values, but if I make one for OUTLOOK.exe nothing happens.

Anyone familiar with this?

How do I set the version of IE used by an Outlook VSTO Add-in?

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