def join_time_series():
get_db_instance().time_series.drop()
get_db_instance().emotions_aggregation.aggregate(pipeline)
def aggregate_vad():
get_db_instance().vad_aggregate.drop()
TweetRepo.aggregate(pipeline)
def aggregate_tweet_emotions_by_houre():
get_db_instance().emotions_aggregation.drop()
TweetRepo.aggregate(pipelineHourly)
def create_emotions_aggregation_view(hourly=False):
config = {'create': 'emotions_by_houre',
'viewOn': 'tweets', 'pipeline': pipelineHourly}
get_db_instance().command(config)
def count_tweets():
get_db_instance().tweetCount.drop()
TweetRepo.aggregate(pipeline)
def generate_word_count():
get_db_instance().word_count.drop()
get_db_instance().tweets.aggregate(pipeline)
def generate_user_post_counts():
get_db_instance().user_post_count.drop()
get_db_instance().tweets.aggregate(pipeline, allowDiskUse=True, cursor={})