Dataflow 中的 Apache Beam 获取与生成器对象相关的错误不可下标

Question

我正在尝试在数据流中创建我的第一个管道，当我使用交互式光束运行器执行时，我有相同的代码运行，但在数据流上我得到了各种各样的错误，这对我来说没有多大意义。

我从 pub sub 获取 json，格式如下。

{"timestamp":1589992571906,"lastPageVisited":"https://kickassdataprojects.com/simple-and-complete-tutorial-on-simple-linear-regression/","pageUrl":"https://kickassdataprojects.com/","pageTitle":"Helping%20companies%20and%20developers%20create%20awesome%20data%20projects%20%7C%20Data%20Engineering/%20Data%20Science%20Blog","eventType":"Pageview","landingPage":0,"referrer":"direct","uiud":"31af5f22-4cc4-48e0-9478-49787dd5a19f","sessionId":322371}

这是我的管道代码。

from __future__ import absolute_import
import apache_beam as beam
#from apache_beam.runners.interactive import interactive_runner
#import apache_beam.runners.interactive.interactive_beam as ib
import google.auth
from datetime import timedelta
import json
from datetime import datetime
from apache_beam import window
from apache_beam.transforms.trigger import AfterWatermark, AfterProcessingTime, AccumulationMode, AfterCount
from apache_beam.options.pipeline_options import GoogleCloudOptions
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.options.pipeline_options import SetupOptions
from apache_beam.options.pipeline_options import StandardOptions
import argparse
import logging
from time import mktime

def setTimestamp(elem):
     from apache_beam import window
     yield window.TimestampedValue(elem, elem['timestamp'])

def createTuples(elem):
     yield (elem["sessionId"], elem)

class WriteToBigQuery(beam.PTransform):
  """Generate, format, and write BigQuery table row information."""
  def __init__(self, table_name, dataset, schema, project):
    """Initializes the transform.
    Args:
      table_name: Name of the BigQuery table to use.
      dataset: Name of the dataset to use.
      schema: Dictionary in the format {'column_name': 'bigquery_type'}
      project: Name of the Cloud project containing BigQuery table.
    """
    # TODO(BEAM-6158): Revert the workaround once we can pickle super() on py3.
    #super(WriteToBigQuery, self).__init__()
    beam.PTransform.__init__(self)
    self.table_name = table_name
    self.dataset = dataset
    self.schema = schema
    self.project = project

  def get_schema(self):
    """Build the output table schema."""
    return ', '.join('%s:%s' % (col, self.schema[col]) for col in self.schema)

  def expand(self, pcoll):
    return (
        pcoll
        | 'ConvertToRow' >>
        beam.Map(lambda elem: {col: elem[col]
                               for col in self.schema})
        | beam.io.WriteToBigQuery(
            self.table_name, self.dataset, self.project, self.get_schema()))


class ParseSessionEventFn(beam.DoFn):
  """Parses the raw game event info into a Python dictionary.
  Each event line has the following format:
    username,teamname,score,timestamp_in_ms,readable_time
  e.g.:
    user2_AsparagusPig,AsparagusPig,10,1445230923951,2015-11-02 09:09:28.224
  The human-readable time string is not used here.
  """
  def __init__(self):
    # TODO(BEAM-6158): Revert the workaround once we can pickle super() on py3.
    #super(ParseSessionEventFn, self).__init__()
    beam.DoFn.__init__(self)

  def process(self, elem):
          #timestamp = mktime(datetime.strptime(elem["timestamp"], "%Y-%m-%d %H:%M:%S").utctimetuple())
          elem['sessionId'] = int(elem['sessionId'])
          elem['landingPage'] = int(elem['landingPage'])
          yield elem

class AnalyzeSessions(beam.DoFn):
  """Parses the raw game event info into a Python dictionary.
  Each event line has the following format:
    username,teamname,score,timestamp_in_ms,readable_time
  e.g.:
    user2_AsparagusPig,AsparagusPig,10,1445230923951,2015-11-02 09:09:28.224
  The human-readable time string is not used here.
  """
  def __init__(self):
    # TODO(BEAM-6158): Revert the workaround once we can pickle super() on py3.
    #super(AnalyzeSessions, self).__init__()
    beam.DoFn.__init__(self)

  def process(self, elem, window=beam.DoFn.WindowParam):
          sessionId = elem[0]
          uiud = elem[1][0]["uiud"]
          count_of_events = 0
          pageUrl = []
          window_end = window.end.to_utc_datetime()
          window_start = window.start.to_utc_datetime()
          session_duration = window_end - window_start
          for rows in elem[1]:
             if rows["landingPage"] == 1:
                    referrer = rows["refererr"]
             pageUrl.append(rows["pageUrl"])       

          return {
             "pageUrl":pageUrl,
             "eventType":"pageview",
             "uiud":uiud,
             "sessionId":sessionId,
             "session_duration": session_duration,
              "window_start" : window_start
               }

def run(argv=None, save_main_session=True):
    parser = argparse.ArgumentParser()
    parser.add_argument('--topic', type=str, help='Pub/Sub topic to read from')
    parser.add_argument(
          '--subscription', type=str, help='Pub/Sub subscription to read from')
    parser.add_argument(
          '--dataset',
          type=str,
          required=True,
          help='BigQuery Dataset to write tables to. '
          'Must already exist.')
    parser.add_argument(
          '--table_name',
          type=str,
          default='game_stats',
          help='The BigQuery table name. Should not already exist.')
    parser.add_argument(
          '--fixed_window_duration',
          type=int,
          default=60,
          help='Numeric value of fixed window duration for user '
          'analysis, in minutes')
    parser.add_argument(
          '--session_gap',
          type=int,
          default=5,
          help='Numeric value of gap between user sessions, '
          'in minutes')
    parser.add_argument(
          '--user_activity_window_duration',
          type=int,
          default=30,
          help='Numeric value of fixed window for finding mean of '
          'user session duration, in minutes')
    args, pipeline_args = parser.parse_known_args(argv)
    session_gap = args.session_gap * 60
    options = PipelineOptions(pipeline_args)
    # Set the pipeline mode to stream the data from Pub/Sub.
    options.view_as(StandardOptions).streaming = True

    options.view_as( StandardOptions).runner= 'DataflowRunner'
    options.view_as(SetupOptions).save_main_session = save_main_session
    p = beam.Pipeline(options=options)
    lines = (p
                | beam.io.ReadFromPubSub(
              subscription="projects/phrasal-bond-274216/subscriptions/rrrr")
             | 'decode' >> beam.Map(lambda x: x.decode('utf-8'))
             | beam.Map(lambda x: json.loads(x))
             | beam.ParDo(ParseSessionEventFn())
             )

    next = ( lines
                | 'AddEventTimestamps' >> beam.Map(setTimestamp)
                | 'Create Tuples' >> beam.Map(createTuples)
                | beam.Map(print) 
                | 'Window' >> beam.WindowInto(window.Sessions(15))
                | 'group by key' >> beam.GroupByKey()          
                | 'analyze sessions' >> beam.ParDo(AnalyzeSessions())         
                | 'WriteTeamScoreSums' >> WriteToBigQuery(
                args.table_name,
               {

               "uiud":'STRING',
               "session_duration": 'INTEGER',
               "window_start" : 'TIMESTAMP'
                          },
                options.view_as(GoogleCloudOptions).project)
             )

    next1 = ( next
             | 'Create Tuples' >> beam.Map(createTuples)
             | beam.Map(print) 

             )

    result = p.run()
#    result.wait_till_termination()

if __name__ == '__main__':
  logging.getLogger().setLevel(logging.INFO)
  run()

在以下代码中，当我尝试在管道中创建元组时，我收到以下错误“生成器”对象不可下标。我使用 yield 来创建生成器对象，即使 return 也不起作用，它只会破坏我的管道。

apache_beam.coders.coder_impl.SequenceCoderImpl.get_estimated_size_and_observables File "sessiontest1.py", line 23, in createTuples TypeError: 'generator' object is not subscriptable [while running 'generatedPtransform-148']

这是我用来执行管道的代码。

python3 sessiontest1.py     --project phrasal-bond-xxxxx     --region us-central1     --subscription projects/phrasal-bond-xxxxx/s
ubscriptions/xxxxxx     --dataset sessions_beam     --runner DataflowRunner     --temp_location gs://webevents/sessions --service_account_email-xxxxxxxx-
compute@developer.gserviceaccount.com  

对此的任何帮助将不胜感激。谢谢大家，再次第一次处理数据流，所以不确定我在这里缺少什么。

我之前遇到的其他错误现在已排序：-

a) 我得到错误，widow is not defined from the line name beam.Map(lambda elem: window.TimestampedValue(elem, elem['timestamp'])) 。

如果我去 beam.window 那么它说梁没有定义，据我说梁应该由数据流提供，

NameError: name 'window' is not defined [while running 'generatedPtransform-3820']

您只需要在函数本身中导入模块。

Answer 1

在 createTuples 上获得 'generator' object is not subscriptable 错误表明当您尝试执行 elem["sessionID"] 时，elem 已经是一个生成器。您之前所做的转换是 setTimestamp，它也使用了yield，因此输出了一个生成器，该生成器作为元素传递给 createTuples。

这里的解决方案是使用return 而不是yield 来实现setTimestamp 和createTuples。在下面的变换中返回你想要接收的元素。

Answer 2

您应该在代码中设置 save_main_session = True。 （尝试在您的代码中取消注释该行）。在此处查看有关 NameError 的更多信息：https://cloud.google.com/dataflow/docs/resources/faq