forked from hrucinska/cwiczenia
41 lines
1.5 KiB
Python
41 lines
1.5 KiB
Python
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from pyspark.sql import SparkSession
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import logging
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import datetime
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import time
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import pyspark.sql.functions as f
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spark = SparkSession \
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.builder \
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.appName("too_few_partitions") \
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.enableHiveSupport() \
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.getOrCreate()
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log4jLogger = spark._jvm.org.apache.log4j
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logger = log4jLogger.LogManager.getLogger(__name__)
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try:
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logger.info("SPARKAPP START")
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start = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S')
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orders_skew = spark.sql("select * from hrucinska.uam_orders")
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orders_partial_reduce = orders_skew.groupBy("seller_id", "buyer_id").agg(f.count("order_offer_id").alias("order_offer_id"))
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orders = orders_partial_reduce.groupBy("seller_id").agg(f.count("order_offer_id").alias("order_offer_id")).withColumnRenamed("seller_id", "seller_id_order")
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offers = spark.sql("select * from hrucinska.uam_offers")
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user_offers_orders = offers.join(orders, offers.seller_id == orders.seller_id_order, "left")
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res = user_offers_orders.groupBy(user_offers_orders.seller_id).agg(f.count(user_offers_orders.offer_id).alias("user_offers"), f.count(user_offers_orders.order_offer_id).alias("user_orders"))
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res.write.mode("overwrite").saveAsTable("hrucinska.data_skew2")
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stop = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S')
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print "czas rozpoczecia obliczen2: ", start
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print "czas zakonczenia obliczen2: ", stop
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time.sleep(180)
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except Exception as inst:
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logger.info("SPARKAPP ERROR {0}".format(inst))
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raise
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finally:
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logger.info("SPARKAPP STOP")
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