125 lines
3.7 KiB
Python
125 lines
3.7 KiB
Python
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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DISPLAY_ID_COLUMN = "display_id"
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BASE_CONT_COLUMNS = [
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"publish_time",
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"publish_time_promo",
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"timestamp",
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"document_id_promo_clicked_sum_ctr",
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"publisher_id_promo_clicked_sum_ctr",
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"source_id_promo_clicked_sum_ctr",
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"document_id_promo_count",
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"publish_time_days_since_published",
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"ad_id_clicked_sum_ctr",
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"advertiser_id_clicked_sum_ctr",
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"campaign_id_clicked_sum_ctr",
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"ad_id_count",
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"publish_time_promo_days_since_published",
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]
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SIM_COLUMNS = [
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"doc_event_doc_ad_sim_categories",
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"doc_event_doc_ad_sim_topics",
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"doc_event_doc_ad_sim_entities",
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]
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CONTINUOUS_COLUMNS = BASE_CONT_COLUMNS + SIM_COLUMNS + [DISPLAY_ID_COLUMN]
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exclude_conts = ["publish_time", "publish_time_promo", "timestamp"]
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NUMERIC_COLUMNS = [col for col in CONTINUOUS_COLUMNS if col not in exclude_conts]
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CATEGORICAL_COLUMNS = [
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"ad_id",
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"document_id",
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"platform",
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"document_id_promo",
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"campaign_id",
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"advertiser_id",
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"source_id",
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"publisher_id",
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"source_id_promo",
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"publisher_id_promo",
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]
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CTR_INPUTS = [
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"ad_id",
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"source_id_promo",
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"document_id_promo",
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"publisher_id_promo",
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"advertiser_id",
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"campaign_id",
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]
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EXCLUDE_COLUMNS = [
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"publish_time",
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"publish_time_promo",
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"timestamp",
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"ad_id_clicked_sum",
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"source_id_promo_count",
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"source_id_promo_clicked_sum",
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"document_id_promo_clicked_sum",
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"publisher_id_promo_count",
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"publisher_id_promo_clicked_sum",
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"advertiser_id_count",
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"advertiser_id_clicked_sum",
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"campaign_id_count",
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"campaign_id_clicked_sum",
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"uuid",
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"day_event",
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]
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nvt_to_spark = {
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"ad_id": "ad_id",
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"clicked": "label",
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"display_id": "display_id",
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"document_id": "doc_event_id",
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"platform": "event_platform",
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"document_id_promo": "doc_id",
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"campaign_id": "campaign_id",
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"advertiser_id": "ad_advertiser",
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"source_id": "doc_event_source_id",
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"publisher_id": "doc_event_publisher_id",
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"source_id_promo": "doc_ad_source_id",
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"publisher_id_promo": "doc_ad_publisher_id",
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"geo_location": "event_geo_location",
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"geo_location_country": "event_country",
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"geo_location_state": "event_country_state",
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"document_id_promo_ctr": "pop_document_id",
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"publisher_id_promo_ctr": "pop_publisher_id",
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"source_id_promo_ctr": "pop_source_id",
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"document_id_promo_count": "doc_views_log_01scaled",
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"publish_time_days_since_published": "doc_event_days_since_published_log_01scaled",
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"ad_id_ctr": "pop_ad_id",
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"advertiser_id_ctr": "pop_advertiser_id",
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"campaign_id_ctr": "pop_campain_id",
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"ad_id_count": "ad_views_log_01scaled",
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"publish_time_promo_days_since_published": "doc_ad_days_since_published_log_01scaled",
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"document_id_document_id_promo_sim_categories": "doc_event_doc_ad_sim_categories",
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"document_id_document_id_promo_sim_topics": "doc_event_doc_ad_sim_topics",
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"document_id_document_id_promo_sim_entities": "doc_event_doc_ad_sim_entities",
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}
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spark_to_nvt = {item: key for key, item in nvt_to_spark.items()}
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def transform_nvt_to_spark(column):
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return nvt_to_spark[column]
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def transform_spark_to_nvt(column):
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return spark_to_nvt[column]
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