0
もう一度私です。これは、私がやっているプロジェクトに関連するコードで、Twitterデータに対する感情分析と呼ばれています。次のコードは、基本的に、以下のエラーが発生している正と負のつぶやきの数を表示するために使用されます。'cairo.Context'の外部構造体コンバーターが見つかりません
from pyspark import SparkConf, SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
import operator
import numpy as np
import matplotlib.pyplot as plt
def main():
conf = SparkConf().setMaster("local[2]").setAppName("Streamer")
sc = SparkContext(conf=conf)
# Creating a streaming context with batch interval of 10 sec
ssc = StreamingContext(sc, 10)
ssc.checkpoint("checkpoint")
pwords = load_wordlist("positive.txt")
nwords = load_wordlist("negative.txt")
counts = stream(ssc, pwords, nwords, 100)
make_plot(counts)
def make_plot(counts):
"""
This function plots the counts of positive and negative words for each timestep.
"""
positiveCounts = []
negativeCounts = []
time = []
for val in counts:
positiveTuple = val[0]
positiveCounts.append(positiveTuple[1])
negativeTuple = val[1]
negativeCounts.append(negativeTuple[1])
for i in range(len(counts)):
time.append(i)
posLine = plt.plot(time, positiveCounts,'bo-', label='Positive')
negLine = plt.plot(time, negativeCounts,'go-', label='Negative')
plt.axis([0, len(counts), 0, max(max(positiveCounts), max(negativeCounts))+50])
plt.xlabel('Time step')
plt.ylabel('Word count')
plt.legend(loc = 'upper left')
plt.show()
def load_wordlist(filename):
"""
This function returns a list or set of words from the given filename.
"""
words = {}
f = open(filename, 'rU')
text = f.read()
text = text.split('\n')
for line in text:
words[line] = 1
f.close()
return words
def wordSentiment(word,pwords,nwords):
if word in pwords:
return ('positive', 1)
elif word in nwords:
return ('negative', 1)
def updateFunction(newValues, runningCount):
if runningCount is None:
runningCount = 0
return sum(newValues, runningCount)
def sendRecord(record):
connection = createNewConnection()
connection.send(record)
connection.close()
def stream(ssc, pwords, nwords, duration):
kstream = KafkaUtils.createDirectStream(
ssc, topics = ['twitterstream'], kafkaParams = {"metadata.broker.list": 'localhost:9092'})
tweets = kstream.map(lambda x: x[1].encode("ascii", "ignore"))
# Each element of tweets will be the text of a tweet.
# We keep track of a running total counts and print it at every time step.
words = tweets.flatMap(lambda line:line.split(" "))
positive = words.map(lambda word: ('Positive', 1) if word in pwords else ('Positive', 0))
negative = words.map(lambda word: ('Negative', 1) if word in nwords else ('Negative', 0))
allSentiments = positive.union(negative)
sentimentCounts = allSentiments.reduceByKey(lambda x,y: x+y)
runningSentimentCounts = sentimentCounts.updateStateByKey(updateFunction)
runningSentimentCounts.pprint()
# The counts variable hold the word counts for all time steps
counts = []
sentimentCounts.foreachRDD(lambda t, rdd: counts.append(rdd.collect()))
# Start the computation
ssc.start()
ssc.awaitTerminationOrTimeout(duration)
ssc.stop(stopGraceFully = True)
return counts
if __name__=="__main__":
main()
次のようにエラーがあることを起こる：
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_gtk3.py", line 343, in idle_draw
self.draw()
File "/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_gtk3.py", line 336, in draw
self.get_property("window").process_updates (False)
TypeError: Couldn't find foreign struct converter for 'cairo.Context'