CS100.1x-lab0_student

这是CS100.1x第一个提交的作业，是给我们测试用的。相关ipynb文件见我github。本来没什么好说的。我在这里简单讲一下，后面会更详细的讲解。主要分成5个部分。

Part 1: Test Spark functionality

Parallelize, filter, and reduce

# Check that Spark is working
largeRange = sc.parallelize(xrange(100000))
reduceTest = largeRange.reduce(lambda a, b: a + b)
filterReduceTest = largeRange.filter(lambda x: x % 7 == 0).sum()

print reduceTest
print filterReduceTest

# If the Spark jobs don't work properly these will raise an AssertionError
assert reduceTest == 4999950000
assert filterReduceTest == 714264285

前三行代码的作用分别是，把一个python的集合转化为RDD，把列表里的值相加，把列表里对7整除的数相加

Loading a text file

# Check loading data with sc.textFile
import os.path
baseDir = os.path.join('data')
inputPath = os.path.join('cs100', 'lab1', 'shakespeare.txt')
fileName = os.path.join(baseDir, inputPath)

rawData = sc.textFile(fileName)
shakespeareCount = rawData.count()

print shakespeareCount

# If the text file didn't load properly an AssertionError will be raised
assert shakespeareCount == 122395

这段代码第一段是构造文件路径，第二段是读取文本文件，然后统计行数。

Part 2: Check class testing library

Compare with hash

# TEST Compare with hash (2a)
# Check our testing library/package
# This should print '1 test passed.' on two lines
from test_helper import Test

twelve = 12
Test.assertEquals(twelve, 12, 'twelve should equal 12')
Test.assertEqualsHashed(twelve, '7b52009b64fd0a2a49e6d8a939753077792b0554',
                        'twelve, once hashed, should equal the hashed value of 12')

测试哈希比较，没什么好说的

Compare lists

# TEST Compare lists (2b)
# This should print '1 test passed.'
unsortedList = [(5, 'b'), (5, 'a'), (4, 'c'), (3, 'a')]
Test.assertEquals(sorted(unsortedList), [(3, 'a'), (4, 'c'), (5, 'a'), (5, 'b')],
                  'unsortedList does not sort properly')

排序的操作

Part 3: Check plotting

Our first plot

# Check matplotlib plotting
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from math import log

# function for generating plot layout
def preparePlot(xticks, yticks, figsize=(10.5, 6), hideLabels=False, gridColor='#999999', gridWidth=1.0):
    plt.close()
    fig, ax = plt.subplots(figsize=figsize, facecolor='white', edgecolor='white')
    ax.axes.tick_params(labelcolor='#999999', labelsize='10')
    for axis, ticks in [(ax.get_xaxis(), xticks), (ax.get_yaxis(), yticks)]:
        axis.set_ticks_position('none')
        axis.set_ticks(ticks)
        axis.label.set_color('#999999')
        if hideLabels: axis.set_ticklabels([])
    plt.grid(color=gridColor, linewidth=gridWidth, linestyle='-')
    map(lambda position: ax.spines[position].set_visible(False), ['bottom', 'top', 'left', 'right'])
    return fig, ax

# generate layout and plot data
x = range(1, 50)
y = [log(x1 ** 2) for x1 in x]
fig, ax = preparePlot(range(5, 60, 10), range(0, 12, 1))
plt.scatter(x, y, s=14**2, c='#d6ebf2', edgecolors='#8cbfd0', alpha=0.75)
ax.set_xlabel(r'$range(1, 50)$'), ax.set_ylabel(r'$log_e(x^2)$')
pass

熟悉matplotlib的人应该知道，这个就是自己生成数据，然后画出来。
运行完代码后，得到如下图片。