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我試圖跟隨this Codelab一起，告訴你如何從你的谷歌應用引擎數據存儲中獲取數據，並通過谷歌雲存儲和通過設置一個MapReduce管道。我建立了一個Google App Engine數據存儲實體，並且有一個過程來收集關於某些我想收集數據的股票的推文。我相信我已經遵循了示例中列出的所有內容，但是分解數據並將其加載到雲存儲中的所有工作的碎片引發了UnicodeEncodeErrors。下面是從我測試的應用dev的應用服務器上的日誌：UnicodeEncodeError谷歌應用引擎數據存儲到BigQuery過程
INFO 2012-12-18 20:41:07,645 dev_appserver.py:3103] "POST /mapreduce/worker_callback HTTP/1.1" 500 -
WARNING 2012-12-18 20:41:07,648 taskqueue_stub.py:1981] Task appengine-mrshard-1582400592541472B07B9-0-0 failed to execute. This task will retry in 0.100 seconds
ERROR 2012-12-18 20:41:09,453 webapp2.py:1552] 'ascii' codec can't encode character u'\u2019' in position 80: ordinal not in range(128)
Traceback (most recent call last):
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 1535, in __call__
rv = self.handle_exception(request, response, e)
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 1529, in __call__
rv = self.router.dispatch(request, response)
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 1278, in default_dispatcher
return route.handler_adapter(request, response)
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 1102, in __call__
return handler.dispatch()
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 572, in dispatch
return self.handle_exception(e, self.app.debug)
File "C:\Program Files (x86)\Google\google_appengine\lib\webapp2\webapp2.py", line 570, in dispatch
return method(*args, **kwargs)
File "C:\Users\Tank\Documents\Aptana Studio 3 Workspace\jibdantest-bq\mapreduce\base_handler.py", line 65, in post
self.handle()
File "C:\Users\Tank\Documents\Aptana Studio 3 Workspace\jibdantest-bq\mapreduce\handlers.py", line 181, in handle
entity, input_reader, ctx, tstate)
File "C:\Users\Tank\Documents\Aptana Studio 3 Workspace\jibdantest-bq\mapreduce\handlers.py", line 298, in process_data
output_writer.write(output, ctx)
File "C:\Users\Tank\Documents\Aptana Studio 3 Workspace\jibdantest-bq\mapreduce\output_writers.py", line 659, in write
ctx.get_pool("file_pool").append(self._filename, str(data))
UnicodeEncodeError: 'ascii' codec can't encode character u'\u2019' in position 80: ordinal not in range(128)
下面的代碼：
import json
import webapp2
import urllib2
import time
import calendar
import datetime
import httplib2
from google.appengine.ext import db
from google.appengine.api import taskqueue
from google.appengine.ext import blobstore
from google.appengine.ext.webapp.util import run_wsgi_app
from google.appengine.ext.webapp import blobstore_handlers
from google.appengine.ext.webapp import util
from google.appengine.ext.webapp import template
from google.appengine.api import urlfetch
from mapreduce.lib import files
from mapreduce import base_handler
from mapreduce import mapreduce_pipeline
from apiclient.discovery import build
from oauth2client.appengine import AppAssertionCredentials
SCOPE = 'https://www.googleapis.com/auth/bigquery'
PROJECT_ID = 'project_id' # Your Project ID here
BQ_DATASET_ID = 'datastore_data'
GS_BUCKET = 'bucketname'
ENTITY_KIND = 'main.streamdata'
class streamdata(db.Model):
querydate = db.DateTimeProperty(auto_now_add = True)
ticker = db.StringProperty()
created_at = db.StringProperty()
tweet_id = db.StringProperty()
text = db.TextProperty()
source = db.StringProperty()
class DatastoreMapperPipeline(base_handler.PipelineBase):
def run(self, entity_type):
output = yield mapreduce_pipeline.MapperPipeline(
"Datastore Mapper %s" % entity_type,
"main.datastore_map",
"mapreduce.input_readers.DatastoreInputReader",
output_writer_spec="mapreduce.output_writers.FileOutputWriter",
params={
"input_reader":{
"entity_kind": entity_type,
},
"output_writer":{
"filesystem": "gs",
"gs_bucket_name": GS_BUCKET,
"output_sharding":"none",
}
},
shards=10)
yield CloudStorageToBigQuery(output)
class CloudStorageToBigQuery(base_handler.PipelineBase):
def run(self, csv_output):
credentials = AppAssertionCredentials(scope=SCOPE)
http = credentials.authorize(httplib2.Http())
bigquery_service = build("bigquery", "v2", http=http)
jobs = bigquery_service.jobs()
table_name = 'datastore_data_%s' % datetime.datetime.utcnow().strftime(
'%m%d%Y_%H%M%S')
files = [str(f.replace('/gs/', 'gs://')) for f in csv_output]
result = jobs.insert(projectId=PROJECT_ID,
body=build_job_data(table_name,files))
result.execute()
def build_job_data(table_name, files):
return {"projectId": PROJECT_ID,
"configuration":{
"load": {
"sourceUris": files,
"schema":{
"fields":[
{
"name":"querydate",
"type":"INTEGER",
},
{
"name":"ticker",
"type":"STRING",
},
{
"name":"created_at",
"type":"STRING",
},
{
"name":"tweet_id",
"type":"STRING",
},
{ "name":"text",
"type":"TEXT",
},
{
"name":"source",
"type":"STRING",
}
]
},
"destinationTable":{
"projectId": PROJECT_ID,
"datasetId": BQ_DATASET_ID,
"tableId": table_name,
},
"maxBadRecords": 0,
}
}
}
def datastore_map(entity_type):
data = db.to_dict(entity_type)
resultlist = [timestamp_to_posix(data.get('querydate')),
data.get('ticker'),
data.get('created_at'),
data.get('tweet_id'),
data.get('text'),
data.get('source')]
result = ','.join(['"%s"' % field for field in resultlist])
yield("%s\n" % result)
def timestamp_to_posix(timestamp):
return int(time.mktime(timestamp.timetuple()))
class DatastoretoBigQueryStart(webapp2.RequestHandler):
def get(self):
pipeline = DatastoreMapperPipeline(ENTITY_KIND)
pipeline.start()
path = pipeline.base_path + "/status?root=" + pipeline.pipeline_id
self.redirect(path)
class StreamHandler(webapp2.RequestHandler):
def get(self):
tickers = ['AAPL','GOOG', 'IBM', 'BAC', 'INTC',
'DELL', 'C', 'JPM', 'WFM', 'WMT',
'AMZN', 'HOT', 'SPG', 'SWY', 'HTSI',
'DUK', 'CEG', 'XOM', 'F', 'WFC',
'CSCO', 'UAL', 'LUV', 'DAL', 'COST', 'YUM',
'TLT', 'HYG', 'JNK', 'LQD', 'MSFT',
'GE', 'LVS', 'MGM', 'TWX', 'DIS', 'CMCSA',
'TWC', 'ORCL', 'WPO', 'NYT', 'GM', 'JCP',
'LNKD', 'OPEN', 'NFLX', 'SBUX', 'GMCR',
'SPLS', 'BBY', 'BBBY', 'YHOO', 'MAR',
'L', 'LOW', 'HD', 'HOV', 'TOL', 'NVR', 'RYL',
'GIS', 'K', 'POST', 'KRFT', 'CHK', 'GGP',
'RSE', 'RWT', 'AIG', 'CB', 'BRK.A', 'CAT']
for i in set(tickers):
url = 'http://search.twitter.com/search.json?q='
resultcount = '&rpp=100'
language = '&lang=en'
encoding = '%40%24'
tickerstring = url + encoding + i + resultcount + language
tickurl = urllib2.Request(tickerstring)
tweets = urllib2.urlopen(tickurl)
code = tweets.getcode()
if code == 200:
results = json.load(tweets, 'utf-8')
if "results" in results:
entries = results["results"]
for entry in entries:
tweet = streamdata()
created = entry['created_at']
tweetid = entry['id_str']
tweettxt = entry['text']
tweet.ticker = i
tweet.created_at = created
tweet.tweet_id = tweetid
tweet.text = tweettxt
tweet.source = "Twitter"
tweet.put()
class MainHandler(webapp2.RequestHandler):
def get(self):
self.response.out.write('<a href="/start">Click here</a> to start the Datastore to BigQuery pipeline. ')
self.response.out.write('<a href="/add_data">Click here</a> to start adding data to the datastore. ')
app = webapp2.WSGIApplication([
('/', MainHandler),
('/start', DatastoretoBigQueryStart),
('/add_data', StreamHandler)],
debug=True)
任何見解的人可能會是一個很大的幫助。
很多謝謝。