Processes/dlpredictor/tests/scripts/fact_data_count.py

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from pyspark import SparkContext
from pyspark.sql import HiveContext
from pyspark.sql.functions import udf
from pyspark.sql.types import IntegerType
from operator import add
import time
from datetime import datetime, timedelta


"""
Author: Eric Tsai

This script reads the fact data Hive table and print the impression totals 
for all the uckeys.
"""

def get_day_list(yesterday, prepare_past_days):
    day = datetime.strptime(yesterday, '%Y-%m-%d')
    day_list = []
    for _ in range(0, prepare_past_days):
        day_list.append('\"{}\"'.format(datetime.strftime(day, '%Y-%m-%d')))
        day = day + timedelta(days=-1)
    day_list.sort()
    return day_list

def run(cfg):
    start_time = time.time()
    sc = SparkContext()
    hive_context = HiveContext(sc)
    sc.setLogLevel(cfg['log_level'])

    fact_data_table = cfg['fact_data_table']

    num_buckets = cfg['num_buckets']
    bucket_increment = cfg['bucket_increment']

    yesterday = cfg['yesterday']
    prepare_past_days = cfg['prepare_past_days']
    day_list = get_day_list(yesterday, prepare_past_days)
    # day_list = [ '\"2020-04-01\"' ]

    total = 0
    for i in range(0, num_buckets, bucket_increment):
        print('Bucket {} of {}: {}'.format(i+1, num_buckets, fact_data_table))

        # Load the distribution detail table.
        command = 'select count_array, day, bucket_id from {} where day in ({}) and bucket_id between {} and {}'.format(
            fact_data_table, ','.join(day_list), i, i + bucket_increment)
        # print(command)
        df = hive_context.sql(command)

        _udf = udf(
            lambda x: sum([int(list(i.split(':'))[1]) for i in x if i and ':' in i]) if x else 0, IntegerType())
        df = df.withColumn('imp', _udf(df.count_array))
        # df.show(10)

        increment = df.rdd.map(lambda x: (1,x['imp'])).reduceByKey(add).collect()
        # print('increment: {}'.format(increment))
        total += increment[0][1]

        # Print the results.
        print('Total impressions: {:>16,}'.format(total))
        lap_time = int(time.time() - start_time)
        print('Total elapsed time: {}m {:02}s'.format(lap_time/60, lap_time%60))

    sc.stop()


if __name__ == '__main__':

    cfg = {
        'fact_data_table': 'dlpm_05182021_1500_tmp_area_map',
        'yesterday': '2020-05-31',
        'prepare_past_days': 90,
        'num_buckets': 10,
        'bucket_increment': 1,
        'log_level': 'WARN'
    }

    run(cfg)