conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO emergency_categories (operation_id, birth_place) VALUES (%s, %s)", (uid, amt))
conn.commit()


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO certifications SELECT a.appointment_duration, b.blockfloor FROM emergency_responses a JOIN mart.mart_refunds_hourly b ON a.mascot = b.mascot"
spark.sql(sql)


spark.sql("SELECT claim_header_id, route_id FROM ai_safety_papers2 LIMIT 100")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO activity SELECT amenid, media_type_id FROM systems WHERE amenid > 23")


df = spark.read.table("site")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("researchprojects")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO agriculturalinnovations (feedtype, ties) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ai_ethics SELECT major, gameid FROM songs WHERE major > 33"


# model haircare_cruelty depends on climate_communication
dbt run -s haircare_cruelty --vars '{"src":"climate_communication"}'


src = spark.read.table("ocean_health_monitor")
src.write.insertInto("whale_sharks", overwrite=True)


# TODO: 旧逻辑 INSERT INTO ods.sessions_daily SELECT * FROM legacy
cur.execute("SELECT ad_id, deliverydate FROM eco_diversification_investment LIMIT 305")


cur.execute("SELECT planned_delivery_date, fault_log_entry_datetime FROM marine_species_status LIMIT 379")
rows = cur.fetchall()
import logging
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


# model album depends on animal_species
dbt build -s album --vars 'source: animal_species'


rows = session.query(Src).filter(Src.agegroup > 91).all()
# src table: diversity_metrics
engine.execute("INSERT INTO programoutcomes SELECT * FROM diversity_metrics")


df = spark.read.table("performers").toPandas()
df[["shipment_date", "mental_health_score"]].to_sql("artcontributors", engine, index=False)


if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO ods_cart_item_df SELECT claim_status_description, organisation_type_description FROM arrivals WHERE claim_status_description > 236")


df = pd.read_sql("SELECT journal, diplomacy_id FROM caribbeansea", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("genetics_stats.research_projects", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO circular_economy_initiatives SELECT visitor_count, number_of_platforms FROM bank_info WHERE visitor_count > 274"


msg = "would run: INSERT INTO tourist_attractions SELECT 1"
logger.info(msg)
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


spark-sql --master yarn -e "INSERT INTO healthbudget SELECT mission_count, class_president_vote, dphone, led_by FROM fossil_fuel_vehicles WHERE mission_count > 128"


logger = logging.getLogger(__name__)
import logging
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
import logging
sql = "INSERT INTO document_structures SELECT a.client_first_name, b.train_type FROM esportsteamsafrica a JOIN wastegeneration b ON a.stockid = b.stockid"
spark.sql(sql)


df = spark.read.table("item_inventory")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("ads.ads_exposure_di")


src = spark.read.table("ingredient")
src.write.insertInto("sectors", overwrite=True)


df = pd.read_sql("SELECT * FROM midwest_materials", conn)
df.to_sql("roles", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO flu_shots SELECT * FROM legacy
cur.execute("SELECT producerid, energy_efficiency_savings FROM ods.ods_users_di LIMIT 312")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM yttrium_production"


df = spark.read.table("charging_stations")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table circular_economy --target-dir /tmp/land


df = spark.read.table("genre_songs").toPandas()
df[["time_stamp", "meter_200"]].to_sql("bank", engine, index=False)


echo "dry-run: INSERT INTO reviews SELECT 1"
mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
set -euo pipefail


psql "$DB_URL" <<SQL
SELECT fare_id, founding_year FROM customersregion LIMIT 281;
INSERT INTO ingredients SELECT camera_lens_id, museumname, poll_source FROM whale_sharks WHERE camera_lens_id > 245;
SQL


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM ref_detention_type"


echo "dry-run: INSERT INTO satellites_by_country SELECT 1"
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}


df = spark.read.table("waste_data").toPandas()
df[["appointment_time", "farm_name"]].to_sql("climate_adaptation_re", engine, index=False)


df = spark.read.table("foodaid")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("community_health_workers")


# TODO: 旧逻辑 INSERT INTO communitydevelopment SELECT * FROM legacy
cur.execute("SELECT production_date, workout_type FROM has_allergy LIMIT 279")


cur.execute("SELECT class, timestamp FROM threat_severity LIMIT 114")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


# TODO: 旧逻辑 INSERT INTO international_visitors SELECT * FROM legacy
cur.execute("SELECT cloud_cover, workshop_id FROM mart.mart_campaigns_daily LIMIT 155")


psql -h "$PGHOST" -U etl -c "INSERT INTO media_library SELECT a.sustainability_certified, b.awayteamid FROM streams a JOIN bi.bi_campaigns_daily b ON a.amount_due = b.amount_due"


set -euo pipefail
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table recycling_rates_state --target-dir /tmp/land


src = spark.read.table("patient_outcomes")
src.write.insertInto("num_employees", overwrite=True)


df = pull_table(ctx, "digital_divide_initiatives")
export_to_warehouse(df, "disinformation_detection", mode="overwrite")


df = spark.read.table("autoshow")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("camera_lens")


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
import logging
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


df = spark.read.table("total_capacity")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("bustrips")


threshold = cfg.get('threshold', 0.5)
import logging
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO artsheritage (sale_quantity, equipment_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO team_revenue SELECT staystart, factory FROM fieldd_info WHERE staystart > 484")


df = spark.read.table("local_impact_japan").toPandas()
df[["sale_year", "maintenance_date"]].to_sql("healthcare_facilities", engine, index=False)


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO wind_farms SELECT museum_name, asessment_outcome_code, grant_date, years_operating FROM crime_stats WHERE museum_name > 470"


rows = session.query(Src).filter(Src.component_type > 361).all()
# src table: ads.orders
engine.execute("INSERT INTO journal SELECT * FROM ads.orders")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO organic_cosmetics SELECT airport, continent FROM tv_shows_genre WHERE airport > 207"


logger = logging.getLogger(__name__)
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


import logging
spark.sql("INSERT INTO circuits SELECT gamepreference, game_genre, carrier, hourlyrate FROM virtual_tourism WHERE gamepreference > 93")

gamepreference game_genre carrier hourlyrate


df = spark.read.table("unionmembers").toPandas()
df[["plant_location", "workoutname"]].to_sql("fleet", engine, index=False)


msg = "would run: INSERT INTO farm_competition SELECT 1"
logger.info(msg)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO reviews SELECT judge_state, cust_name, building_phone, event_attendance FROM factory_connections WHERE judge_state > 140"], check=True)


psql "$DB_URL" <<SQL
SELECT inventor_name, quarter FROM restaurants LIMIT 53;
INSERT INTO public.police_calls SELECT home_team_three_point, comment_count, certification FROM grad_students WHERE home_team_three_point > 291;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO marketing_budgets SELECT hometeam, emergency_type, room_number FROM mines WHERE hometeam > 216"


psql -h "$PGHOST" -U etl -c "INSERT INTO marine_species_indian SELECT a.has_disability, b.advocate_id FROM ads.ads_campaigns_full a JOIN ingredient_sourcing b ON a.session_date = b.session_date"


psql "$DB_URL" <<SQL
SELECT strainname, machinery_id FROM disease_prevalence LIMIT 163;
INSERT INTO arcticocean SELECT doctor_id, category, relationship, other_details FROM pilot_record WHERE doctor_id > 397;
SQL


df = pd.read_sql("SELECT * FROM geneva_motor_show", conn)
df.to_sql("ucl_top10", conn, if_exists="replace", index=False)


psql "$DB_URL" <<SQL
SELECT sensor_type, mission_date FROM product_info LIMIT 366;
INSERT INTO freshwaterfinfish SELECT extraction_date, case_burden, contract_address, refugee_id FROM paintings WHERE extraction_date > 38;
SQL


# TODO: 旧逻辑 INSERT INTO wearable_metrics SELECT * FROM legacy
cur.execute("SELECT mine_location, product_category_code FROM dw.dw_inventory_df LIMIT 404")


trap 'echo failed' ERR
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table restaurants --target-dir /tmp/land


df = spark.read.table("mine_workforce")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("ads_refunds_full")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO country_landfill_capacity (bedroom_count, engagementid) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO green_building_projects SELECT gymnast_id, local_authority FROM average WHERE gymnast_id > 98"], check=True)


echo "dry-run: INSERT INTO coral_reefs SELECT 1"
trap 'echo failed' ERR
echo "job start: $(date +%F)"


cur.execute("SELECT fiscal_year, coowner_name FROM extraction_methods LIMIT 423")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


trap 'echo failed' ERR
hive -e "INSERT INTO russia_nato_diplomacy SELECT publish_date, nominee FROM renewableenergy WHERE publish_date > 442"


echo "dry-run: INSERT INTO bi_products SELECT 1"
mkdir -p /tmp/joblog
set -euo pipefail
export TZ=Asia/Shanghai


msg = "would run: INSERT INTO nba_games SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
import logging


trap 'echo failed' ERR
hive -e "INSERT INTO workshop SELECT environmental_impact, restypedescription, player_api_id FROM affordablehousing WHERE environmental_impact > 447"


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO available_policies SELECT emp_id, mine_name, appelation, genrename FROM dws.dws_shipments_full WHERE emp_id > 464")


df = pd.read_sql("SELECT foreign, min_dew_point_f FROM people_addresses", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("dwd.dwd_products", engine, if_exists="append", index=False)


# model player_f depends on mart.mart_vendors
dbt run --select player_f --vars 'source: mart.mart_vendors'


rows = session.query(Src).filter(Src.club_name > 137).all()
# src table: dwd_risk_score_hourly
engine.execute("INSERT INTO minor_in SELECT * FROM dwd_risk_score_hourly")


cur.execute("SELECT founder_ethnicity, energy_star_rating FROM laborstatistics LIMIT 352")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO player_coach (attorney_id, inspection_id) VALUES (%s, %s)"


# model countries depends on dw_member_point_full
dbt run --select countries --vars '{"source_table":"dw_member_point_full"}'


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM ods.ods_coupon_use_delta"


df = pd.read_sql("SELECT crispr_id, squadron FROM book_club", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("seamounts", engine, if_exists="append", index=False)


echo "dry-run: INSERT INTO wastewatertreatment SELECT 1"
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO customer_events SELECT num_pallets, volunteer_hours FROM clinical_trials WHERE num_pallets > 326"], check=True)


echo "dry-run: INSERT INTO exhibitionattendance SELECT 1"
set -euo pipefail


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO railway (sqft, numcases) VALUES (%s, %s)", (uid, amt))
conn.commit()


mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table product_reviews --target-dir /tmp/land


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM emergency_responses"


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
hive -e "INSERT INTO artifactanalysis SELECT district_name, trip_type, tree_id FROM menu_categories WHERE district_name > 499"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO organization (fare, eliminated_by) VALUES (%s, %s)"


# model concert_sales depends on archaeologists
dbt run --select concert_sales --vars 'source: archaeologists'


df = read_frame(ctx, "ocean")
persist_to_output(df, "ads.ads_cart_item_hourly", mode="overwrite")


df = spark.read.table("mart.vendors_full")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


msg = "would run: INSERT INTO volunteerhours SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stories SELECT policy, screening FROM hotel_chains WHERE policy > 305"], check=True)


df = load_source(ctx, "dorm")
export_to_output(df, "artists_valuation", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO patient_satisfaction SELECT union_members, neighborhoodname, meal_date, is_hybrid FROM conservation_programs WHERE union_members > 115"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO sites_me SELECT purchase_details, typical_buying_price, flno FROM landfill_capacity_north_america WHERE purchase_details > 472"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO artsales SELECT a.building_description, b.state_id FROM timber_sales a JOIN dwd.dwd_payments_di b ON a.document_type_description = b.document_type_description"


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
trap 'echo failed' ERR
hive -e "INSERT INTO ads.ads_events_df SELECT text_of_notes, matchdate, policy_number FROM dwd.vendors WHERE text_of_notes > 196"


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM class"


# model military_spending depends on genre_songs
dbt run --models military_spending --vars '{"source_table":"genre_songs"}'


df = pd.read_sql("SELECT * FROM coal", conn)
df.to_sql("dws.dws_coupon_use_di", conn, if_exists="replace", index=False)


export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table farmers_india --target-dir /tmp/land


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO open_pedagogy_exam (traveler_id, assets) VALUES (%s, %s)", (uid, amt))
conn.commit()


RETRIES=${RETRIES:-3}
set -euo pipefail
sqoop import --connect "$JDBC" --table carbon_offsets --target-dir /tmp/land


echo "dry-run: INSERT INTO undergoes SELECT 1"
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO timbersales SELECT permitid, license_type, observation_id, production_id FROM atlantic_plate WHERE permitid > 343")


spark-sql --master yarn -e "INSERT INTO cars SELECT build_date, recycler_id, donationyear, count_date FROM problem_log WHERE build_date > 327"


echo "dry-run: INSERT INTO sustainable_fabrics SELECT 1"
mkdir -p /tmp/joblog


# model cosmetics depends on dwd.dwd_campaigns_df
dbt run --select cosmetics --vars '{"src":"dwd.dwd_campaigns_df"}'


df = fetch_table(ctx, "dws.dws_risk_score_daily")
save_to_store(df, "communitydevelopment", mode="overwrite")


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO athletes SELECT serve_id, address, destruction_authorised_by_employee_id, male_id FROM doctors WHERE serve_id > 208")


# TODO: 旧逻辑 INSERT INTO rainfall_data SELECT * FROM legacy
cur.execute("SELECT forest_type, rid FROM staff_roles LIMIT 445")


df = source_frame(ctx, "dwd.dwd_coupon_use_df")
persist_to_sink(df, "vehicle_registrations", mode="overwrite")


df = spark.read.table("ai_ethics_policies").toPandas()
df[["guest_last_name", "mining_operation"]].to_sql("nyc_subway", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO drama_workshop_groups SELECT onscholarship, warehouse_id, strat_name, hub_id FROM funding_rounds WHERE onscholarship > 369"


psql "$DB_URL" <<SQL
SELECT region_code, organizationname FROM safetyincidents LIMIT 265;
INSERT INTO musicgenre SELECT co2_reduction_tons, menuitemname, organization_details, tour_name FROM mealtypes WHERE co2_reduction_tons > 281;
SQL


df = spark.read.table("stg.events_hourly")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("electricvehicleadoption")


msg = "would run: INSERT INTO defense_project_timelines SELECT 1"
logger.info(msg)
import logging
logger = logging.getLogger(__name__)


# TODO: 旧逻辑 INSERT INTO therapy_attendance SELECT * FROM legacy
cur.execute("SELECT initiative_name, missions FROM sites LIMIT 120")


sqoop export --connect "$JDBC" --table efforts --columns strategy_id,moisture_level --export-dir /warehouse/stage


echo "dry-run: INSERT INTO labor_statistics SELECT 1"
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR


import logging
if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


df = spark.read.table("funding_records")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("dw.dw_coupon_use_daily")


spark-sql --master yarn -e "INSERT INTO refugee_support SELECT contributor, born_state FROM recreation_centers WHERE contributor > 46"


df = spark.read.table("price_data").toPandas()
df[["total_beds", "end_station_name"]].to_sql("lessons", engine, index=False)


df = spark.read.table("movie")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("timber_production")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO oceania_countries SELECT funding_id, hashtags, garment, spacecraft_model FROM zip_codes WHERE funding_id > 272"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO artprograms SELECT a.state_id, b.kills FROM members a JOIN status b ON a.therapy_sessions = b.therapy_sessions"


metrics.append(round(score, 4))
import logging
threshold = cfg.get('threshold', 0.5)
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO autoshow SELECT rank_in_round, line_name, injury_date FROM cosmetics WHERE rank_in_round > 213;
EOF


psql "$DB_URL" <<SQL
SELECT unionid, material FROM community_policing_events LIMIT 397;
INSERT INTO ods.ods_member_point_delta SELECT customer_status_code, pilot_name, pipeline_name FROM ai_papers WHERE customer_status_code > 198;
SQL


# TODO: 旧逻辑 INSERT INTO forestry_practices SELECT * FROM legacy
cur.execute("SELECT seal_species, inspection_time FROM dws.dws_events_hourly LIMIT 271")


echo "dry-run: INSERT INTO documents SELECT 1"
trap 'echo failed' ERR


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table sustainability --target-dir /tmp/land


beeline -u "$HS2_URL" -e "INSERT INTO movie SELECT party, serviceid, certification_name, factory_id FROM watertreatmentplants WHERE party > 31"


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO constructors SELECT a.cmi_cross_ref_id, b.username FROM strainlabresults a JOIN investmentsesg b ON a.range = b.range"
spark.sql(sql)


msg = "would run: INSERT INTO undergoes SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO team SELECT wildlife_type_id, art_movement, park_id, deliveryid FROM supplier_ethics WHERE wildlife_type_id > 393")


mkdir -p /tmp/joblog
hive -e "INSERT INTO ocean_shipping.cargo SELECT open_date, education_id, milestone, socially_responsible FROM safetyorgs WHERE open_date > 352"


spark.sql("SELECT performance_id, mean_temperature_f FROM postseason LIMIT 325")
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO hospitals SELECT staystart, decision, task FROM reverselogisticstransactions WHERE staystart > 315")


threshold = cfg.get('threshold', 0.5)
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


cur.execute("SELECT energytype, manager_name FROM sustainable_building LIMIT 340")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
import logging


df = spark.read.table("russia_nato_diplomacy")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("dws.exposure_df")


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table ref_detention_type --target-dir /tmp/land


df = pd.read_sql("SELECT * FROM programoutcomes", conn)
df.to_sql("facility", conn, if_exists="replace", index=False)


df = extract_dataset(ctx, "student_addresses")
push_to_output(df, "checking", mode="overwrite")


# model tb_cases depends on institution
dbt build -s tb_cases --vars '{"src":"institution"}'


df = pd.read_sql("SELECT * FROM staff_department_assignments", conn)
df.to_sql("fleet_management", conn, if_exists="replace", index=False)


src = spark.read.table("communityengagement")
src.write.insertInto("community_health_centers", overwrite=True)


rows = session.query(Src).filter(Src.team_id_loser > 433).all()
# src table: voyages
engine.execute("INSERT INTO ods.clicks_delta SELECT * FROM voyages")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM midwest_region"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cosmetics_sales (distance, mine_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = fetch_dataset(ctx, "colorado_river_basin")
upsert_to_output(df, "ais", mode="overwrite")


result = value * ratio + offset
sql = "INSERT INTO cybersecurity_vulnerabilities SELECT a.evaluationid, b.cmi_details FROM teams a JOIN recycling_rates b ON a.roaming_country = b.roaming_country"
spark.sql(sql)


cur.execute("SELECT eia_date, galleryid FROM jp_schema.policy_areas LIMIT 149")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


df = spark.read.table("attorney_billing_rates").toPandas()
df[["songname", "ai_powered_features"]].to_sql("satelliteimagery", engine, index=False)


msg = "would run: INSERT INTO fish_purchases SELECT 1"
logger.info(msg)
import logging
result = value * ratio + offset


trap 'echo failed' ERR
export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table viewership --target-dir /tmp/land


beeline -u "$HS2_URL" -e "INSERT INTO model_fairness SELECT is_false, affirmative, contractor FROM waste_types WHERE is_false > 139"


df = spark.read.table("food_safety_inspections")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


echo "dry-run: INSERT INTO call_volume SELECT 1"
set -euo pipefail


cur.execute("SELECT reviewscore, policyid FROM prereq LIMIT 444")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
import logging


presto --server presto01:8080 --catalog hive --execute "INSERT INTO virtual_tours_oceania SELECT directed_by, longitude, entrydate, movement FROM chargingstations WHERE directed_by > 448"

directed_by longitude entrydate movement


export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table creative_ai_applications --target-dir /tmp/land


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO tryout SELECT city_traffic_speed, fare_amount FROM org_volunteer WHERE city_traffic_speed > 365;
EOF


sqoop export --connect "$JDBC" --table sports --columns engagement_date,stocking_density --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.council_tax_id > 123).all()
# src table: military_innovation
engine.execute("INSERT INTO urban_farms SELECT * FROM military_innovation")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ods_shipments_df SELECT fan_id, theftdate, impact_id FROM attribute_definitions WHERE fan_id > 33"


df = spark.read.table("supportprograms")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("freshwaterfinfish")


psql "$DB_URL" <<SQL
SELECT patient, extraction_state FROM irrigation_systems LIMIT 89;
INSERT INTO agencies SELECT login_name, digital_channel, recipient_id, review_text FROM vehicledata WHERE login_name > 298;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO tryout SELECT date_incident_start, missiontype FROM broadband_subscribers WHERE date_incident_start > 134"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO humanitarian_assistance (hub_id, user_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table store_product --target-dir /tmp/land


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM farmer_details"


# TODO: 旧逻辑 INSERT INTO salesperson SELECT * FROM legacy
cur.execute("SELECT prominence, stat_id FROM product_sales LIMIT 243")


spark-sql --master yarn -e "INSERT INTO marine_species_observations SELECT regionid, stockid, virtual_tour_engagement_time, technique_id FROM shariah_compliant_products WHERE regionid > 427"


echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO firestations SELECT president_vote, minename FROM dwd.dwd_orders_daily WHERE president_vote > 482"


# model county_public_safety depends on whale_sharks
dbt build --models county_public_safety --vars 'source: whale_sharks'


spark.sql("SELECT closuredate, issued_date FROM dw.member_point_daily LIMIT 401")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO bus_fare_collection SELECT songid, avg_depth, claim_type, sensor_type FROM low_value_contracts WHERE songid > 151")


df = pd.read_sql("SELECT * FROM distributors", conn)
df.to_sql("ref_locations", conn, if_exists="replace", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ref_colors SELECT credits, commanding_officer, race_ethnicity FROM feedback WHERE credits > 406;
EOF


msg = "would run: INSERT INTO urban_agriculture_initiatives SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
import logging
retries = int(os.environ.get('RETRIES', '3'))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bi_orders_daily SELECT enzyme_id, department FROM animal_population_status WHERE enzyme_id > 291;
EOF


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM apac_hotel_views"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO units SELECT employee_name, project_name, carriername, unitsperweek FROM settlements WHERE employee_name > 15;
EOF


threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


src = spark.read.table("airlines")
src.write.insertInto("book_club", overwrite=True)


spark-sql --master yarn -e "INSERT INTO humanitarianassistanceoperations SELECT menu_type, access_count, activity_name, theftdate FROM mining.company WHERE menu_type > 493"


spark.sql("SELECT stayid, unit_of_measure FROM reservoirs LIMIT 2")
result = value * ratio + offset
spark.sql("INSERT INTO journal_committee SELECT bus_number, detection_id, customer_type_code, age_group FROM multimodal_trips WHERE bus_number > 4")


cur.execute("SELECT province, calories FROM ngo_funding LIMIT 330")
rows = cur.fetchall()
import logging


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO inmates SELECT client_first_name, built, address, handling_date FROM factories WHERE client_first_name > 264"], check=True)


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM trade_history"


sqoop export --connect "$JDBC" --table neighborhoods --columns farm_id,heritage_site --export-dir /warehouse/stage


spark.sql("SELECT pname, book_title FROM coffee_prices LIMIT 29")
result = value * ratio + offset
spark.sql("INSERT INTO vaccinations SELECT detention_type_code, operationtype, trench_id FROM stores_2 WHERE detention_type_code > 103")


df = spark.read.table("basketball_match")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("machinery")


sqoop export --connect "$JDBC" --table league_x --columns royal_family_details,contract_address --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO distributors SELECT a.organisation_type_description, b.ocean_name FROM workforce a JOIN athlete_wellbeing b ON a.dec = b.dec"


df = pd.read_sql("SELECT * FROM gamedesign", conn)
df.to_sql("bi.device_log", conn, if_exists="replace", index=False)


echo "dry-run: INSERT INTO ytterbiumproduction SELECT 1"
echo "job start: $(date +%F)"


spark-sql --master yarn -e "INSERT INTO film_actor SELECT success, date_of_birth, shipment_date FROM space_missions WHERE success > 187"


df = pd.read_sql("SELECT * FROM systems", conn)
df.to_sql("membership_data", conn, if_exists="replace", index=False)


rows = session.query(Src).filter(Src.publisher > 143).all()
# src table: drug_approvals
engine.execute("INSERT INTO animal_populations SELECT * FROM drug_approvals")


msg = "would run: INSERT INTO agro_regions SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


spark-sql --master yarn -e "INSERT INTO overwatch_scores SELECT chemical_type, pilot FROM tracklists WHERE chemical_type > 328"


spark.sql("SELECT investorgender, tier FROM ai_safety LIMIT 289")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO tourism_activities SELECT date_of_ceremony, spent, productcategory FROM gardens WHERE date_of_ceremony > 245")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM technology_access"


echo "dry-run: INSERT INTO workercontactinfo SELECT 1"
export TZ=Asia/Shanghai
set -euo pipefail
mkdir -p /tmp/joblog


presto --server presto01:8080 --catalog hive --execute "INSERT INTO emerging_markets.digital_assets SELECT funding, card_id FROM socially_responsible_loans WHERE funding > 367"


cur.execute("SELECT temperature, coach_id FROM sourcing LIMIT 18")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset


df = pd.read_sql("SELECT rig_id, sale_quantity FROM production_yearly", engine)
if not rows:
    logger.warning('empty result')
import logging
df.to_sql("viewership", engine, if_exists="append", index=False)


src = spark.read.table("gamedesigndata")
src.write.insertInto("government_transparency", overwrite=True)


sqoop export --connect "$JDBC" --table bi.bi_campaigns_daily --columns date_of_completion,hiv --export-dir /warehouse/stage


# model worker_union depends on permit
dbt build --select worker_union --vars '{"src":"permit"}'


rows = session.query(Src).filter(Src.observation_date > 422).all()
# src table: brandrevenue
engine.execute("INSERT INTO user_interests SELECT * FROM brandrevenue")


df = pd.read_sql("SELECT openingid, phone FROM military_personnel_africa", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("musical", engine, if_exists="append", index=False)


df = spark.read.table("open_pedagogy_enrollment")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


# TODO: 旧逻辑 INSERT INTO channel SELECT * FROM legacy
cur.execute("SELECT metric_id, units_owned FROM arcticocean LIMIT 289")


rows = session.query(Src).filter(Src.shipment_tracking_number > 215).all()
# src table: faculty_participates_in
engine.execute("INSERT INTO yearly_production SELECT * FROM faculty_participates_in")


sqoop export --connect "$JDBC" --table tech_accessibility_funding --columns asset_type,course_name --export-dir /warehouse/stage


src = spark.read.table("bi.bi_exposure_hourly")
src.write.insertInto("community_centers", overwrite=True)


src = spark.read.table("county")
src.write.insertInto("league", overwrite=True)


trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO az_drought_impact SELECT incidents, delivery_status FROM playergamehistory WHERE incidents > 385"


src = spark.read.table("astronaut_medical_3")
src.write.insertInto("customer_transactions", overwrite=True)


spark-sql --master yarn -e "INSERT INTO airport_aircraft SELECT site_name, peakhourid, is_organic FROM traditionalarts WHERE site_name > 270"


spark.sql("SELECT person_name, regulation FROM emergencies LIMIT 195")
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ocean_depths SELECT menu_category, friend, project_education, attack_country FROM school WHERE menu_category > 45")


src = spark.read.table("ingredient_sourcing")
src.write.insertInto("ads.users_full", overwrite=True)


echo "job start: $(date +%F)"
trap 'echo failed' ERR
set -euo pipefail
sqoop import --connect "$JDBC" --table industrial_building_energy_efficiency --target-dir /tmp/land


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tree_habitat_associations (sid, inclusive) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO haircare_sales SELECT bioprocess_name, technology, language FROM vesselarrivals WHERE bioprocess_name > 23"], check=True)


df = extract_dataset(ctx, "customer_master_index")
save_to_sink(df, "companies", mode="overwrite")


df = spark.read.table("ethical_ai")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("tryout")


df = spark.read.table("domesticconferences")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("tech_accessibility_funding")


df = pd.read_sql("SELECT foreign, unit_id FROM artist", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("event_attendance", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT product_size, programoutcomeid FROM dwd.dwd_exposure_df", engine)
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
df.to_sql("shop", engine, if_exists="append", index=False)


spark.sql("SELECT company_gender, sentence_id FROM attendance LIMIT 207")
import logging
spark.sql("INSERT INTO ai_ethics_policies SELECT injury, industry, equipment FROM neodymium_prices WHERE injury > 39")


echo "dry-run: INSERT INTO benefits_overpayments SELECT 1"
set -euo pipefail


result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO freshwaterfinfish SELECT ai_model, strainname, tour_id FROM all_programs WHERE ai_model > 196")


import logging
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO digital_trends SELECT occupancy_rate, socially_responsible, team_id_br FROM threatintelligence WHERE occupancy_rate > 464")


beeline -u "$HS2_URL" -e "INSERT INTO fabricdata SELECT coach_id, family_name, case_type, neighborhood_id FROM labor_costs WHERE coach_id > 455"


df = spark.read.table("mart.shipments_delta").toPandas()
df[["unit_id", "annual_interchanges"]].to_sql("asia_events", engine, index=False)


df = pull_table(ctx, "whale_sightings")
sink_to_store(df, "eco_materials", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO electricvehicleadoption SELECT planned_delivery_date, meal_name FROM urbanagricrop WHERE planned_delivery_date > 1"


df = spark.read.table("sustainable_tourism_practices").toPandas()
df[["bathroom_count", "phone"]].to_sql("agro_regions", engine, index=False)


df = spark.read.table("artist").toPandas()
df[["is_hybrid", "closure_authorised_by_staff_id"]].to_sql("cmi_cross_references", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO claims SELECT a.publication_id, b.student_id FROM party_forms a JOIN vehiclemodels b ON a.log_entry_date = b.log_entry_date"


df = pd.read_sql("SELECT * FROM dws.exposure_df", conn)
df.to_sql("student_courses", conn, if_exists="replace", index=False)


spark.sql("SELECT online_dispute_resolution, retail_price FROM gameattendance LIMIT 252")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO furniture SELECT target_u_id, living_wage FROM operate_company WHERE target_u_id > 254")


df = spark.read.table("stg.stg_products_delta")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("manufacturers")


# TODO: 旧逻辑 INSERT INTO threat_severity SELECT * FROM legacy
cur.execute("SELECT centername, cargoid FROM courses LIMIT 270")


spark-sql --master yarn -e "INSERT INTO functional_areas SELECT collection_id, staff_first_name, vehicle_flight_number, student FROM bikerental WHERE collection_id > 75"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO demographics SELECT agreementid, blockcode, medium FROM trust WHERE agreementid > 51;
EOF


df = pd.read_sql("SELECT dataset, state_code FROM courses", engine)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("phishing_attempts", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO higher_ed.publications SELECT impactid, route, materialtype FROM daily_revenue WHERE impactid > 162"


spark.sql("SELECT bicycle_id, donationid FROM election LIMIT 2")
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO cotton_source SELECT time_year, made_in_usa, award, bname FROM tournaments WHERE time_year > 234")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bi.events_delta SELECT waste_type, max_dissolved_oxygen, participatedinesports, day_number FROM footwear WHERE waste_type > 202"


df = pd.read_sql("SELECT exit_type, donorname FROM public.ev_sales", engine)
threshold = cfg.get('threshold', 0.5)
import logging
df.to_sql("voyages", engine, if_exists="append", index=False)


spark.sql("SELECT working_horses, installed_date FROM programs LIMIT 380")
import logging
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ads_refunds_full SELECT storeid, unit, policyname FROM all_programs WHERE storeid > 299")


df = load_source(ctx, "military_equipment")
save_to_warehouse(df, "immunizationrates", mode="overwrite")


df = read_source(ctx, "dw.clicks_di")
save_to_store(df, "circularsupplychain", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO roller_coaster (avg_usage, amount_claimed) VALUES (%s, %s)"


df = pd.read_sql("SELECT oct, wellbeing_score FROM habitats", engine)
import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("claims_documents", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO water_usage SELECT completion_year, last_year, user_login, firstdonationdate FROM therapy_session WHERE completion_year > 123"


src = spark.read.table("docking")
src.write.insertInto("gardens", overwrite=True)


df = spark.read.table("routes")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("biotech_startups")


df = pd.read_sql("SELECT * FROM communitypolicing", conn)
df.to_sql("program_history", conn, if_exists="replace", index=False)


sqoop export --connect "$JDBC" --table agriculturalinvestments --columns is_vegan,location_text --export-dir /warehouse/stage


df = spark.read.table("ods.ods_users_di")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("dorm")


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO dwd.dwd_products SELECT port_code, typical_selling_price FROM fan_purchases WHERE port_code > 100"


spark.sql("SELECT staff_last_name, complaint_date FROM geothermal_power_plants LIMIT 167")
metrics.append(round(score, 4))
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO public.developers SELECT product_category_description, steps, hourdate FROM sportsinfo WHERE product_category_description > 121")


spark-sql --master yarn -e "INSERT INTO mart_cart_item_di SELECT savingsid, fleet_series, transaction_product, date_left_staff FROM provider_training WHERE savingsid > 178"


echo "dry-run: INSERT INTO seal_population SELECT 1"
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR


presto --server presto01:8080 --catalog hive --execute "INSERT INTO satellitedata SELECT postal_code, country1, movieid FROM bi.device_log WHERE postal_code > 39"


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO dwd.dwd_coupon_use_df SELECT resolution, port FROM workforce_development WHERE resolution > 329"


echo "dry-run: INSERT INTO african_union_countries SELECT 1"
mkdir -p /tmp/joblog
trap 'echo failed' ERR


import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO dws.dws_coupon_use_full SELECT a.emp_hiredate, b.framework_id FROM mexico_regions a JOIN game_scores b ON a.airport_name = b.airport_name"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO company_info SELECT a.star_rating_code, b.date_of_attendance FROM ads_cart_item_hourly a JOIN construction_union b ON a.race = b.race"


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM fireincidents"


df = spark.read.table("electric_vehicle_stats")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("airportdata")


cur.execute("SELECT department_id, org_size FROM user_workouts_march LIMIT 408")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


df = pd.read_sql("SELECT vulnerability_name, fault_log_entry_datetime FROM authors", engine)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("drought_impact", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT injured, production_usage FROM rebounds LIMIT 237;
INSERT INTO soilmoisturedata SELECT primary_advisor, heart_rate, max_dissolved_oxygen, tech FROM total_consumption WHERE primary_advisor > 243;
SQL


df = pd.read_sql("SELECT date_in_location_from, company_gender FROM exhibition", engine)
import logging
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
df.to_sql("item", engine, if_exists="append", index=False)


msg = "would run: INSERT INTO dw.dw_inventory_delta SELECT 1"
logger.info(msg)
import logging


df = pd.read_sql("SELECT * FROM organization", conn)
df.to_sql("defense_contractors", conn, if_exists="replace", index=False)


df = spark.read.table("athlete_stats").toPandas()
df[["port_id", "follows_ethical_practices"]].to_sql("market_share", engine, index=False)


sqoop export --connect "$JDBC" --table counties --columns person_id,graphics_mode --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.coupon_use SELECT price, resource, nickname, points_per_game FROM rural.bus_trips WHERE price > 62"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO housing_investments SELECT primary_advisor, show_name FROM student_tests_taken WHERE primary_advisor > 282"


# model ads_sessions_di depends on crops_table
dbt run --models ads_sessions_di --vars 'source: crops_table'


psql -h "$PGHOST" -U etl -c "INSERT INTO tracklists SELECT a.sighting_id, b.recruitername FROM mobile_plans a JOIN recycling_rates_state b ON a.genre_is = b.genre_is"


rows = session.query(Src).filter(Src.co2_amount > 158).all()
# src table: ingredientsvegancrueltyfree
engine.execute("INSERT INTO parties SELECT * FROM ingredientsvegancrueltyfree")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO labels SELECT song_id, date_of_latest_revision, policytype FROM art_workshops WHERE song_id > 275"], check=True)


df = pd.read_sql("SELECT media_outlet, coach_id FROM issues", engine)
metrics.append(round(score, 4))
df.to_sql("satellite_missions_large", engine, if_exists="append", index=False)


result = value * ratio + offset
import logging
threshold = cfg.get('threshold', 0.5)
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ai_safety_papers2 (chargeable_amount, hotel_chain_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


metrics.append(round(score, 4))
spark.sql("INSERT INTO bi_orders_daily SELECT budget_allocation, acc_percent, station FROM dorm WHERE budget_allocation > 438")


df = pd.read_sql("SELECT trainingid, mining_operation_id FROM broadband_providers", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("global_tournament", engine, if_exists="append", index=False)


df = spark.read.table("bi.bi_payments_delta")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("criminal_cases")


df = spark.read.table("volume")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("apartment_bookings")


# model policy_areas depends on mailshot_customers
dbt build --models policy_areas --vars 'source: mailshot_customers'


sqoop export --connect "$JDBC" --table satellitematerials --columns hotel_chain_id,policyholderid --export-dir /warehouse/stage


src = spark.read.table("parties")
src.write.insertInto("field4_precip", overwrite=True)


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO coach SELECT a.investors, b.dapp_name FROM record a JOIN traffic_violations b ON a.player_id = b.player_id"
spark.sql(sql)


df = pd.read_sql("SELECT * FROM conservation_programs", conn)
df.to_sql("dancefunding", conn, if_exists="replace", index=False)


sqoop export --connect "$JDBC" --table dwd_payments_delta --columns genrename,state_province_county --export-dir /warehouse/stage


cur.execute("SELECT batting_average, adults FROM carbon_footprint LIMIT 333")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


echo "dry-run: INSERT INTO tasks SELECT 1"
set -euo pipefail


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table candidates --target-dir /tmp/land


df = spark.read.table("auto_show").toPandas()
df[["booking_date", "caloric_content"]].to_sql("ads.risk_score", engine, index=False)


psql "$DB_URL" <<SQL
SELECT total_spent, work_type FROM stg.campaigns_daily LIMIT 220;
INSERT INTO opendatainitiatives SELECT openning_year, purchaseid, authors, employee_name FROM outcomes WHERE openning_year > 464;
SQL


psql "$DB_URL" <<SQL
SELECT genreid, document_structure_code FROM cybersecurity_strategies LIMIT 191;
INSERT INTO community_education_programs SELECT wrestler_id, resident_id FROM indie_artists WHERE wrestler_id > 254;
SQL


# TODO: 旧逻辑 INSERT INTO completed_training SELECT * FROM legacy
cur.execute("SELECT project_name, ei_category FROM tree_species LIMIT 470")


df = spark.read.table("artwork_styles")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("trips")


df = source_frame(ctx, "safety_testing")
dump_to_sink(df, "num_employees", mode="overwrite")


df = spark.read.table("maintenance_contracts")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("field4_precip")


msg = "would run: INSERT INTO biotech_startups SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')


result = value * ratio + offset
metrics.append(round(score, 4))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


df = spark.read.table("indigenous_communities").toPandas()
df[["fundingagency", "movieid"]].to_sql("veteran_occupations", engine, index=False)


import logging
if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


df = spark.read.table("transport")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("customer")


set -euo pipefail
RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table cerium_production --target-dir /tmp/land


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table music --target-dir /tmp/land


beeline -u "$HS2_URL" -e "INSERT INTO market SELECT completed_course, min_dew_point_f, programarea FROM customer_month WHERE completed_course > 487"


# model shariah_compliant_finance depends on ai_papers
dbt run -s shariah_compliant_finance --vars '{"source_table":"ai_papers"}'


trap 'echo failed' ERR
sqoop import --connect "$JDBC" --table communityevents --target-dir /tmp/land


df = spark.read.table("producersnewmexico")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


msg = "would run: INSERT INTO channel SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
import logging
threshold = cfg.get('threshold', 0.5)


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO artist_info SELECT contract_end_date, participant_details FROM apac_hotel_views WHERE contract_end_date > 177"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO inspections SELECT personnelbranch, date_of_birth, violationtype, organic FROM consumer WHERE personnelbranch > 449;
EOF

personnelbranch date_of_birth violationtype organic


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO climate_adaptation_re SELECT clinic_id, calendar, took_office FROM labour_productivity WHERE clinic_id > 144;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws_cart_item (ingredient_id, depth) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO carbon_offsets SELECT programoutcomeid, culturalcompetency FROM ods.products_hourly WHERE programoutcomeid > 243;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO mart_exposure_di SELECT a.permits_issued, b.text_of_notes FROM resilience_infrastructure a JOIN labels b ON a.protected = b.protected"


df = pd.read_sql("SELECT * FROM vessel_positions", conn)
df.to_sql("ocean_floor_mapping", conn, if_exists="replace", index=False)


df = spark.read.table("ods.coupon_use")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("solana_transactions")


msg = "would run: INSERT INTO government_transparency SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)


df = pd.read_sql("SELECT * FROM ads.ads_inventory_df", conn)
df.to_sql("ads_payments_hourly", conn, if_exists="replace", index=False)


df = spark.read.table("bank_info")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("airportdata")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO researchgrants SELECT max_dissolved_oxygen, staystart, injury FROM units WHERE max_dissolved_oxygen > 208"


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO nutrition_facts SELECT a.games, b.max_aperture FROM furniture a JOIN military_bases b ON a.total_attendance = b.total_attendance"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO mart.mart_vendors SELECT * FROM legacy
cur.execute("SELECT invoice_id, review_text FROM exhibitiondetails LIMIT 18")


df = spark.read.table("cultural_competency_program")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


sqoop export --connect "$JDBC" --table ads_refunds_full --columns stu_num,num_sustainable_materials --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table incident_region --columns shippingmethod,eventdate --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO makeup_products (course_type, account_id) VALUES (%s, %s)"


spark.sql("SELECT customer_email_address, order_quantity FROM genetics.projects LIMIT 177")
metrics.append(round(score, 4))
spark.sql("INSERT INTO arctic_sightings SELECT veteran_unemployment_rate, driller FROM subway WHERE veteran_unemployment_rate > 136")


spark-sql --master yarn -e "INSERT INTO port_visits SELECT date_and_date, appointment_duration, event_location FROM healthydelights WHERE date_and_date > 213"


df = get_table(ctx, "grad_students")
push_to_target(df, "vessel_positions", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO productivity SELECT oct, has_spf, shares, school FROM india_ingredient_sourcing WHERE oct > 156"


mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table hotel_ratings --target-dir /tmp/land


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM playergamedata"


psql "$DB_URL" <<SQL
SELECT value, bname FROM australia_offset_programs LIMIT 146;
INSERT INTO diversification_projects SELECT date_order_placed, main_industry, stu_hrs FROM ods_risk_score_delta WHERE date_order_placed > 39;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO support_programs (service_type, fare_amount) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO immunization SELECT * FROM legacy
cur.execute("SELECT rooms, working_year_starts FROM stg.member_point_df LIMIT 96")


df = pull_frame(ctx, "military_equipment_maintenance")
export_to_warehouse(df, "cloud_issues", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO coowners (country, cause) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO vehicle_registrations SELECT * FROM legacy
cur.execute("SELECT date_opened, streams FROM ngo_funding LIMIT 237")


df = spark.read.table("on_call")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("militarycyberops")


df = spark.read.table("dw.events_hourly")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


spark.sql("SELECT coownerid, attorney FROM bi.users_full LIMIT 412")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO customer_events SELECT temperature, oppose_rate, artifactid FROM leed_buildings WHERE temperature > 14")


spark-sql --master yarn -e "INSERT INTO bi.bi_risk_score_df SELECT building_short_name, vol_id, silver FROM patients WHERE building_short_name > 101"


spark-sql --master yarn -e "INSERT INTO justice_schemas.legal_tech_providers SELECT no_of_customers, trend_id, don_id FROM district_schools WHERE no_of_customers > 479"


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table italy_culture --target-dir /tmp/land


msg = "would run: INSERT INTO marketing_budgets SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


msg = "would run: INSERT INTO government.region SELECT 1"
logger.info(msg)
logger = logging.getLogger(__name__)


sqoop export --connect "$JDBC" --table market --columns individual_last_name,socially_responsible --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.job_title > 248).all()
# src table: socially_responsible_loans
engine.execute("INSERT INTO communityengagementmetrics SELECT * FROM socially_responsible_loans")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dw.dw_payments_full SELECT mine_location, customer_status_code, volunteer_quarter FROM products_in_events WHERE mine_location > 260"


df = pd.read_sql("SELECT * FROM wastedata", conn)
df.to_sql("cybersecurity_vulnerabilities", conn, if_exists="replace", index=False)


df = spark.read.table("ocean_acidity")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("features")


spark.sql("SELECT common_name, phone_number FROM sales LIMIT 342")
metrics.append(round(score, 4))
spark.sql("INSERT INTO wellbeing_program_participants SELECT born_state, testdate FROM programs WHERE born_state > 478")


cur.execute("SELECT dribbling, implementation_year FROM mart.mart_device_log_delta LIMIT 422")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


import logging
result = value * ratio + offset
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM wastewatertreatment"


spark-sql --master yarn -e "INSERT INTO virtual_tours_oceania SELECT incidenttype, mailing_date, facility_name FROM recall_reports WHERE incidenttype > 251"


df = pd.read_sql("SELECT * FROM home_game", conn)
df.to_sql("chemical_production_5", conn, if_exists="replace", index=False)


df = spark.read.table("cosmetics.lipstick_spf_data").toPandas()
df[["mode", "doctor_id"]].to_sql("mealtypes", engine, index=False)


echo "dry-run: INSERT INTO transport SELECT 1"
set -euo pipefail


cur.execute("SELECT campaign_name, host_country FROM region_stats LIMIT 375")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


df = spark.read.table("tree_species").toPandas()
df[["grantid", "undergraduate"]].to_sql("schools", engine, index=False)


df = spark.read.table("excavationsites")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("marine_species_status")


df = spark.read.table("usdaviolations").toPandas()
df[["practiceid", "personnelbranch"]].to_sql("ods.ods_campaigns_df", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO smartcitycosts SELECT graduate, membergender, lot_id, orderdate FROM dw.dw_sessions_delta WHERE graduate > 188"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO arcticwildlifereserve (article_id, participant_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO policy SELECT rehab_date, amount_due, injury FROM weekly_weather WHERE rehab_date > 295"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO co2_emissions (premise_id, business_size) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("researchprojects")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


df = spark.read.table("ethics_violations")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("makeup_sales")


result = value * ratio + offset
import logging
sql = "INSERT INTO mart.mart_payments_hourly SELECT a.record_id, b.attribute_id FROM trenches a JOIN dwd.dwd_events_delta b ON a.spf_level = b.spf_level"
spark.sql(sql)


import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO urban_agriculture_initiatives SELECT sustainablepractices, production_cost FROM social_impact_bonds WHERE sustainablepractices > 274")


echo "job start: $(date +%F)"
set -euo pipefail
sqoop import --connect "$JDBC" --table miningoperations --target-dir /tmp/land


df = spark.read.table("sponsorship_donations")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("permit")


df = spark.read.table("ingredientsvegancrueltyfree")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


df = spark.read.table("item")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("trainingprograms")


msg = "would run: INSERT INTO species_forests SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')


psql "$DB_URL" <<SQL
SELECT hardware_model_name, room_count FROM community.donations LIMIT 453;
INSERT INTO virtual_tours_oceania SELECT archaeologist_name, max_gust_speed_mph, fare FROM tree_types WHERE archaeologist_name > 149;
SQL


cur.execute("SELECT grape, recorded_by_staff_id FROM temperature LIMIT 184")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


# TODO: 旧逻辑 INSERT INTO high_risk SELECT * FROM legacy
cur.execute("SELECT effort, is_sustainable FROM activities LIMIT 426")


# model projects depends on investor_activities
dbt run --models projects --vars '{"source_table":"investor_activities"}'


psql "$DB_URL" <<SQL
SELECT culture, farm_id FROM precipitation_data LIMIT 255;
INSERT INTO winter_olympics SELECT salary, omim FROM defense_contracts WHERE salary > 430;
SQL


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO mart.mart_sessions_di SELECT menuitemname, billid, building, virtual_tour_engagement_time FROM music_streaming WHERE menuitemname > 384"

menuitemname billid building virtual_tour_engagement_time


cur.execute("SELECT people_id, date_moved_in FROM iron_ore_production LIMIT 457")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
import logging


sqoop export --connect "$JDBC" --table drought_data --columns date_of_ceremony,male_id --export-dir /warehouse/stage


df = spark.read.table("bi.device_log_hourly")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM humanitarian_aid"


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO mental_health_professionals_2 SELECT amount_used, process_id, city_population, seasons FROM stg.stg_users_full WHERE amount_used > 104")


set -euo pipefail
sqoop import --connect "$JDBC" --table ods_risk_score_delta --target-dir /tmp/land


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.ods_member_point_df SELECT followers, annual_revenue, unitprice, eventname FROM state_usage WHERE followers > 477;
EOF

followers annual_revenue unitprice eventname


import logging
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM product_reviews"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO org_climate_finance (shipped_to, suppliername) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model mediterranean_salinity depends on demographics
dbt build --select mediterranean_salinity --vars '{"source_table":"demographics"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO landfillcapacitybycountry SELECT num_of_factories, invoice_details, publication_year, workout_date FROM cosmetic_formula WHERE num_of_factories > 442"


beeline -u "$HS2_URL" -e "INSERT INTO traffic SELECT statename, yearadded, primary, home_city FROM wins WHERE statename > 76"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO stg.stg_users_full SELECT emp_num, emp_lname, attendance_date FROM party_forms WHERE emp_num > 385"


df = spark.read.table("workout")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("chip_model")


import logging
spark.sql("INSERT INTO concert_sales SELECT trainingname, price_in_dollars, contract_count FROM cb_agreements WHERE trainingname > 362")


src = spark.read.table("infra_diversification")
src.write.insertInto("mart.mart_vendors", overwrite=True)


cur.execute("SELECT classid, menu_type FROM comments LIMIT 258")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)


import logging
retries = int(os.environ.get('RETRIES', '3'))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


df = spark.read.table("machine").toPandas()
df[["status_code", "pixels"]].to_sql("catalogs", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ai_safety (product_color, personnelbranch) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO billstatus SELECT screening_id, time_second FROM fare_collection WHERE screening_id > 41"], check=True)


spark-sql --master yarn -e "INSERT INTO station SELECT jul, payment_type_code, tasktype, plant FROM aircraftsquadrons WHERE jul > 84"


# model fertilizer depends on co2emissions
dbt run -s fertilizer --vars 'source: co2emissions'


# TODO: 旧逻辑 INSERT INTO attribute_definitions SELECT * FROM legacy
cur.execute("SELECT artwork_id, satellite FROM complaints LIMIT 376")


echo "dry-run: INSERT INTO regulatory_compliance SELECT 1"
echo "job start: $(date +%F)"


df = pd.read_sql("SELECT is_operational, metric FROM disaster_zones", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("vulnerabilities", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO contracts SELECT value_points, donor_category, habitat_name, volunteer_quarter FROM trade_history WHERE value_points > 260"


df = load_input(ctx, "colorado_river_basin")
dump_to_store(df, "weather_record", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO athletes SELECT posted_at, last_name, medical_condition FROM race WHERE posted_at > 9"


spark-sql --master yarn -e "INSERT INTO textile_suppliers SELECT planned_delivery_date, investor_id FROM bi_inventory_hourly WHERE planned_delivery_date > 475"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dispensary_sales (venue_id, neighborhood) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO engineer_skills SELECT industry_4_0, delivery_id, handling_id FROM airlines WHERE industry_4_0 > 12"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.stg_events_hourly SELECT a.functional_area_description, b.sd_id FROM noise_pollution a JOIN marine_life_research_stations b ON a.team_id_winner = b.team_id_winner"


msg = "would run: INSERT INTO staff_roles SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)


# model wind_projects depends on state_water_usage
dbt run --select wind_projects --vars '{"source_table":"state_water_usage"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO cosmetics (vendor_state, participatedinesports) VALUES (%s, %s)"


# model innovation_grants depends on geologicalsurvey
dbt build -s innovation_grants --vars '{"src":"geologicalsurvey"}'


echo "dry-run: INSERT INTO programoutcomes SELECT 1"
RETRIES=${RETRIES:-3}
set -euo pipefail
trap 'echo failed' ERR


psql -h "$PGHOST" -U etl -c "INSERT INTO state_contracts SELECT a.shares, b.mid FROM bi.bi_risk_score_df a JOIN purchase b ON a.dec = b.dec"


# model electric_vehicle_stats depends on stock
dbt run -s electric_vehicle_stats --vars 'source: stock'


src = spark.read.table("baseball_teams")
src.write.insertInto("government_funding", overwrite=True)


df = pd.read_sql("SELECT card_type_code, allocation_type FROM login_attempts", engine)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
df.to_sql("funding_rounds", engine, if_exists="append", index=False)


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO malicious_activity SELECT profession, gradepoint, year_join, total_beds FROM sustainableproduction WHERE profession > 358")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO smartcities (port_code, destination_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("ads.ads_orders_full").toPandas()
df[["transit_passengers", "staff_address_id"]].to_sql("labor_statistics", engine, index=False)


sqoop export --connect "$JDBC" --table faculty --columns inspection_time,evaluationid --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO fairtradecertification SELECT gas_production_2020, missionid FROM advisor WHERE gas_production_2020 > 70;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO military_bases SELECT region_name, spill_name FROM supply_chain WHERE region_name > 88"


df = extract_table(ctx, "healthcare_access_v2")
dump_to_output(df, "player_stats", mode="overwrite")


df = pd.read_sql("SELECT * FROM section", conn)
df.to_sql("traffic", conn, if_exists="replace", index=False)


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO zipcodes SELECT census_ranking, amountdonated, max_dew_point_f, town_city FROM unionnegotiations WHERE census_ranking > 104")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM visits"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.shipments_df SELECT animal_type, virtual_tour_engagement_time, name_last, policy FROM cotton_source WHERE animal_type > 464"], check=True)


src = spark.read.table("part_faults")
src.write.insertInto("ecohousing", overwrite=True)


cur.execute("SELECT deliveryaddress, mealname FROM people LIMIT 433")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
import logging


df = spark.read.table("bi.device_log_hourly")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("shariah_compliant_finance")


psql -h "$PGHOST" -U etl -c "INSERT INTO department_store_chain SELECT a.operation_type, b.international_passengers FROM soil_moisture a JOIN ai_safety_papers2 b ON a.store_name = b.store_name"


df = spark.read.table("daily_oil_production")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("exit_strategy")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bi.bi_shipments SELECT market_value, focal_length_mm FROM fashion_trend_data WHERE market_value > 302"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ytterbium_supply (recipient_id, therapy_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO dw.dw_sessions_delta SELECT implementation_date, patient_age, visit_id, restaurant_name FROM students WHERE implementation_date > 386"


psql -h "$PGHOST" -U etl -c "INSERT INTO crime_incidents SELECT a.classtype, b.sale_volume FROM county a JOIN platformg b ON a.sentence_length = b.sentence_length"


echo "dry-run: INSERT INTO video_content SELECT 1"
trap 'echo failed' ERR
export TZ=Asia/Shanghai
set -euo pipefail


spark.sql("SELECT chw_id, allergy FROM initiatives_3 LIMIT 378")
import logging
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO user_activity SELECT dance_form, pd_id, pricepergram FROM government_transparency WHERE dance_form > 179")


beeline -u "$HS2_URL" -e "INSERT INTO exhibition_visitors SELECT process_id, problem_description, country, caloric_content FROM protein WHERE process_id > 422"


beeline -u "$HS2_URL" -e "INSERT INTO species_observations SELECT home_team_score, disability, stu_lname FROM event_attendance WHERE home_team_score > 149"


msg = "would run: INSERT INTO union_membership SELECT 1"
logger.info(msg)
result = value * ratio + offset
import logging


src = spark.read.table("stg.campaigns_daily")
src.write.insertInto("product_revenue", overwrite=True)


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO noise_pollution SELECT lanes, cost_id, good_or_bad_customer FROM fruitimport WHERE lanes > 18")


df = spark.read.table("leed_buildings").toPandas()
df[["fund_name", "lipstick_id"]].to_sql("online_travel_agency", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO livestock (friend, driller) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.daily_co2_emission > 319).all()
# src table: ethics_violations
engine.execute("INSERT INTO preferences SELECT * FROM ethics_violations")


logger = logging.getLogger(__name__)
sql = "INSERT INTO grant SELECT a.commodity, b.winning_pilot FROM student_access a JOIN stg.campaigns_daily b ON a.attribute_name = b.attribute_name"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO marine_species_indian SELECT a.technique, b.funding_amount FROM supportprograms a JOIN stg.stg_inventory_full b ON a.haslegalprecedent = b.haslegalprecedent"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_exposure_daily SELECT claimtype, amount_piad, donationyear, personal_name FROM cargos WHERE claimtype > 99"


psql -h "$PGHOST" -U etl -c "INSERT INTO healthbudget SELECT a.visit_month, b.decoration_theme FROM fairtradefactories a JOIN facility_production b ON a.f_id = b.f_id"


df = pd.read_sql("SELECT moisture, created_date FROM claims_processing_stages", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("hospital_equipment", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO ods.ods_users_di SELECT attribute_value, customer_country FROM jupiter_missions WHERE attribute_value > 116"


echo "job start: $(date +%F)"
trap 'echo failed' ERR
hive -e "INSERT INTO domesticconferences SELECT regionname, cityid, sale_year FROM innovation_grants WHERE regionname > 133"


echo "dry-run: INSERT INTO disease_prevalence SELECT 1"
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai


df = spark.read.table("claims_processing_stages")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("marine_species_status")


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO team_franchise SELECT team_id_loser, initiativeid FROM dwd.products_hourly WHERE team_id_loser > 93")


if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vehicles SELECT case_status, stu_hrs, num_developments, number_of_vessels FROM water_conservation WHERE case_status > 409"


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO nasa_mars_program SELECT order_details, date_of_ceremony, mental_health_status FROM vessel_safety WHERE order_details > 170")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bi.bi_orders_hourly SELECT employees, sid, productiondate, savingsid FROM constructors WHERE employees > 499"


df = pd.read_sql("SELECT * FROM wrestler", conn)
df.to_sql("labor_unions", conn, if_exists="replace", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO infrastructure_projects (artist_gender, caseid) VALUES (%s, %s)"


import logging
spark.sql("INSERT INTO available_policies SELECT missing_data, filingdate FROM sustainability_metrics WHERE missing_data > 30")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO esa_missions SELECT wind_speed_mph, launch, launch_date, number_of_sightings FROM reporters WHERE wind_speed_mph > 343"], check=True)


df = spark.read.table("mediators")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("bank_info")


df = pd.read_sql("SELECT prominence, total_value_purchased FROM performances", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("atlantic_ocean", engine, if_exists="append", index=False)


echo "dry-run: INSERT INTO military_personnel_africa SELECT 1"
set -euo pipefail


df = pd.read_sql("SELECT ll_hours, detected_at FROM musicgenre", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("bioprocess.engineering_projects", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.initiativename > 293).all()
# src table: agency_satellites
engine.execute("INSERT INTO impact_investments SELECT * FROM agency_satellites")


df = spark.read.table("arctic_sightings")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("average")


df = load_dataset(ctx, "record")
dump_to_warehouse(df, "ods.ods_member_point_delta", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO public.police_calls SELECT acidification_level, regionid FROM licenses WHERE acidification_level > 270")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd.coupon_use_full SELECT mission, service_type_description FROM vocals WHERE mission > 448;
EOF


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO member_attendance SELECT cityid, target_name, supplier, cost_id FROM first_notification_of_loss WHERE cityid > 452")


df = pd.read_sql("SELECT round_number, personnel FROM engineer_skills", engine)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
df.to_sql("ads.campaigns_di", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO dws.exposure SELECT a.yield_id, b.attendee_id FROM stg.refunds_daily a JOIN veterans b ON a.guest_id = b.guest_id"


src = spark.read.table("permian_basin")
src.write.insertInto("cosmetic_formula", overwrite=True)


# model exposure_df depends on device_accessibility
dbt run --select exposure_df --vars '{"src":"device_accessibility"}'


sqoop export --connect "$JDBC" --table education --columns facility_code,pass_fail --export-dir /warehouse/stage


mkdir -p /tmp/joblog
hive -e "INSERT INTO store_product SELECT round_amount, mean_sea_level_pressure_inches, spf_level FROM dws.cart_item_full WHERE round_amount > 60"


psql -h "$PGHOST" -U etl -c "INSERT INTO space_programs SELECT a.home_team_points, b.truck_details FROM surveylocations a JOIN autonomous_research b ON a.vulnerability_name = b.vulnerability_name"


rows = session.query(Src).filter(Src.total_employees > 69).all()
# src table: cybersecurityincidents
engine.execute("INSERT INTO wrestler SELECT * FROM cybersecurityincidents")


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO miningoperations SELECT a.funding, b.machine_series FROM fabric a JOIN foodaid b ON a.plantid = b.plantid"
spark.sql(sql)


rows = session.query(Src).filter(Src.subject > 386).all()
# src table: prison
engine.execute("INSERT INTO mart.shipments_full SELECT * FROM prison")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM casesbyyear"


df = spark.read.table("hospitallocations")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("dws.cart_item_di")


src = spark.read.table("garmentproduction")
src.write.insertInto("cities", overwrite=True)


# TODO: 旧逻辑 INSERT INTO strainlabresults SELECT * FROM legacy
cur.execute("SELECT graphics_mode, co_id FROM emergencies LIMIT 333")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM circuits"


spark-sql --master yarn -e "INSERT INTO dwd.dwd_coupon_use_df SELECT sale_date, productiondate, programname FROM broadband_subscribers WHERE sale_date > 75"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO defensespending SELECT customer_code, investors, course_description, omim FROM product_info WHERE customer_code > 432"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO professionals (destination_state, production_bopd) VALUES (%s, %s)"


if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO shipmentinfo SELECT trial_success_rate, hours_served, month FROM monitoring_zones WHERE trial_success_rate > 267"], check=True)


spark.sql("SELECT sculpture_name, salary FROM hall_of_fame LIMIT 270")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO city.community_policing SELECT white, chair_name FROM africa_schema.african_mines WHERE white > 322")


cur.execute("SELECT base_name, num_projects FROM tourdifferences LIMIT 323")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


msg = "would run: INSERT INTO shariah_financing SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
set -euo pipefail
sqoop import --connect "$JDBC" --table council_tax --target-dir /tmp/land


df = pd.read_sql("SELECT departure_date, source_u_id FROM dispensaries", engine)
import logging
df.to_sql("precision_farming_imagery", engine, if_exists="append", index=False)


src = spark.read.table("carbon_footprint")
src.write.insertInto("refugees", overwrite=True)


# TODO: 旧逻辑 INSERT INTO community_development_projects SELECT * FROM legacy
cur.execute("SELECT rating_id, contract_count FROM climate_finance_re LIMIT 389")


df = spark.read.table("stg.cart_item_full")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("pediatricians")


df = spark.read.table("list")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("recyclednylongarments")


df = spark.read.table("agency_satellites").toPandas()
df[["aircraft", "menu_category"]].to_sql("performance_scores", engine, index=False)


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO advocacy SELECT cargo_type, days, attendance_date FROM follows WHERE cargo_type > 357")


src = spark.read.table("completed_training")
src.write.insertInto("az_drought_impact", overwrite=True)


df = pd.read_sql("SELECT * FROM military_expenditure", conn)
df.to_sql("yttrium_production", conn, if_exists="replace", index=False)


df = source_table(ctx, "review")
write_to_output(df, "dws_events_di", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO textile_suppliers SELECT surname, years_operating, asessment_outcome_code, eventdate FROM tryout WHERE surname > 234"


psql -h "$PGHOST" -U etl -c "INSERT INTO atlantic_plate SELECT a.mailing_date, b.departmentname FROM smartcontracts a JOIN stg.orders_daily b ON a.home_team_points = b.home_team_points"


# TODO: 旧逻辑 INSERT INTO call_volume SELECT * FROM legacy
cur.execute("SELECT society, num_sessions FROM stg.stg_risk_score LIMIT 430")


# model candidates depends on market
dbt build --models candidates --vars '{"src":"market"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO voting_record SELECT supplychainid, student_id, assessmentdate FROM average WHERE supplychainid > 373"


df = spark.read.table("cerium_production").toPandas()
df[["famous_title", "strainid"]].to_sql("artcontributors", engine, index=False)


df = pd.read_sql("SELECT * FROM mart.mart_device_log", conn)
df.to_sql("disaster_response_donations", conn, if_exists="replace", index=False)


msg = "would run: INSERT INTO training_programs SELECT 1"
logger.info(msg)
import logging
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO regular_order_products SELECT organic_matter, menuitem FROM us_cities WHERE organic_matter > 253;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO autoshow SELECT damage_millions_usd, document_id, worker_id FROM crop_yield WHERE damage_millions_usd > 206;
EOF


echo "dry-run: INSERT INTO classrooms SELECT 1"
trap 'echo failed' ERR


cur.execute("SELECT school_colors, offender_name FROM dw.shipments_df LIMIT 69")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


echo "dry-run: INSERT INTO economic_diversification SELECT 1"
echo "job start: $(date +%F)"
mkdir -p /tmp/joblog


# TODO: 旧逻辑 INSERT INTO productsafety SELECT * FROM legacy
cur.execute("SELECT clientid, owner FROM ads.ads_device_log_di LIMIT 308")


rows = session.query(Src).filter(Src.member_name > 407).all()
# src table: eu_data_usage
engine.execute("INSERT INTO wind_projects SELECT * FROM eu_data_usage")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM farmers_india"


df = pd.read_sql("SELECT * FROM galleries", conn)
df.to_sql("ods.member_point_df", conn, if_exists="replace", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO clinic_2022 (court_appearances, donorage) VALUES (%s, %s)"


src = spark.read.table("operation")
src.write.insertInto("audience_demographics", overwrite=True)


# TODO: 旧逻辑 INSERT INTO biotech_startups SELECT * FROM legacy
cur.execute("SELECT theatrename, productionid FROM menu LIMIT 493")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO county_public_safety SELECT resolved, quantity_sold, post_date FROM tech_volunteers WHERE resolved > 355;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO geneva_motor_show SELECT dish, genrename, furniture_id, report_type FROM stg.stg_risk_score WHERE dish > 277"


df = spark.read.table("dw.exposure_di").toPandas()
df[["email_address", "connection"]].to_sql("models_safety", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO investors SELECT police_force, special_features FROM classicgame WHERE police_force > 282;
EOF


cur.execute("SELECT support_rate, dockingid FROM cloud_issues LIMIT 88")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ocean_pollution SELECT asset_id, animal_species FROM subjects WHERE asset_id > 182"


df = pd.read_sql("SELECT days, goal_id FROM immunizationrates", engine)
threshold = cfg.get('threshold', 0.5)
import logging
logger = logging.getLogger(__name__)
df.to_sql("cargo_equipment", engine, if_exists="append", index=False)


df = spark.read.table("emergency_categories").toPandas()
df[["claimtype", "fiscal_year"]].to_sql("redundant_billing_data", engine, index=False)


echo "dry-run: INSERT INTO faculty_participates_in SELECT 1"
echo "job start: $(date +%F)"
trap 'echo failed' ERR
export TZ=Asia/Shanghai


# TODO: 旧逻辑 INSERT INTO ads.refunds_delta SELECT * FROM legacy
cur.execute("SELECT classid, volunteername FROM furniture LIMIT 39")


echo "dry-run: INSERT INTO safety_research SELECT 1"
export TZ=Asia/Shanghai
set -euo pipefail


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM ocean_species"


echo "dry-run: INSERT INTO cuisine SELECT 1"
set -euo pipefail
echo "job start: $(date +%F)"


psql "$DB_URL" <<SQL
SELECT section_title, card_type_code FROM crops_year LIMIT 46;
INSERT INTO artcontributors SELECT attribute_id, stationname, discount FROM revenue WHERE attribute_id > 93;
SQL


df = spark.read.table("ship")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("habitat3")


beeline -u "$HS2_URL" -e "INSERT INTO sfc_articles SELECT preference_rating, destination, has_spf FROM aquatic_farms WHERE preference_rating > 112"


echo "dry-run: INSERT INTO bioprocess_engineering SELECT 1"
RETRIES=${RETRIES:-3}


spark-sql --master yarn -e "INSERT INTO factory_workers SELECT purchase_id, online_dispute_resolution, mean_temperature_f FROM operations WHERE purchase_id > 104"


metrics.append(round(score, 4))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


psql "$DB_URL" <<SQL
SELECT line_name, ngo_id FROM autonomousvehicleaccidents LIMIT 43;
INSERT INTO appointments SELECT value_points, starting_year, dorm_name, health_equity_metric_3 FROM threats WHERE value_points > 61;
SQL


spark-sql --master yarn -e "INSERT INTO check_ins SELECT status_code, users_engaged, call_time FROM veteran_unemployment WHERE status_code > 471"


logger = logging.getLogger(__name__)
import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO epl_teams SELECT a.musical_id, b.products_last_year FROM dispensaries a JOIN video_games b ON a.home_team = b.home_team"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO food_safety_inspections SELECT algorithmic_fairness_score, billing_amount FROM contract_negotiations_un WHERE algorithmic_fairness_score > 254"


df = spark.read.table("veteran_employment")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


# TODO: 旧逻辑 INSERT INTO building_stats SELECT * FROM legacy
cur.execute("SELECT strain_type, session_language FROM unions LIMIT 245")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO drought_impact (destroyed_by_employee_id, strain) VALUES (%s, %s)"


cur.execute("SELECT content_id, contributions FROM sustainablebrands LIMIT 450")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


rows = session.query(Src).filter(Src.threat > 268).all()
# src table: tourism
engine.execute("INSERT INTO defense_spending SELECT * FROM tourism")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO providers (excavation_site, all_home) VALUES (%s, %s)", (uid, amt))
conn.commit()


msg = "would run: INSERT INTO ocean_pollution SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
import logging


msg = "would run: INSERT INTO new_schedules SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


beeline -u "$HS2_URL" -e "INSERT INTO smartcontracts SELECT satellite_id, habitat, equipment_id FROM ai_systems WHERE satellite_id > 283"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ytterbiumproduction SELECT residence, friend, claim_id, seat_section FROM volunteerhours WHERE residence > 221"


msg = "would run: INSERT INTO engineer_skills SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


src = spark.read.table("safe_dataset")
src.write.insertInto("brandrevenue", overwrite=True)


# model dws_orders_full depends on militarycyberops
dbt build --select dws_orders_full --vars '{"source_table":"militarycyberops"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.mart_risk_score_hourly (room_number, facid) VALUES (%s, %s)", (uid, amt))
conn.commit()


import logging
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO artist_demographics SELECT union_member_id, stageposition, hotel_chain_name, runtime FROM mining_operations WHERE union_member_id > 289")


df = pd.read_sql("SELECT * FROM production_rare_earth_elements", conn)
df.to_sql("intelligenceoperations", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO inst SELECT * FROM legacy
cur.execute("SELECT area_size, nurse FROM vehicle_data LIMIT 267")


rows = session.query(Src).filter(Src.population > 451).all()
# src table: plants
engine.execute("INSERT INTO international_visitors SELECT * FROM plants")


df = spark.read.table("customer_master_index")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("phone_market")


beeline -u "$HS2_URL" -e "INSERT INTO model_fairness SELECT frameworkcountry, stu_dob, membership_amount FROM artpieces WHERE frameworkcountry > 186"


beeline -u "$HS2_URL" -e "INSERT INTO platformh SELECT incident_category, emp_jobcode FROM program_history WHERE incident_category > 147"


echo "job start: $(date +%F)"
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO strategies SELECT violation_count, half FROM train_maintenance WHERE violation_count > 302"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO disabilitysupportprograms SELECT unit_of_measure, player_id FROM vehicle_registrations WHERE unit_of_measure > 222;
EOF


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO stg.stg_device_log_daily SELECT developer, shipping_agent_code, last_workout_date, customer_status_code FROM professional_development WHERE developer > 450")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM movies"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO water_conservation SELECT popularity, fleet_id, elevation, implemented_date FROM disaster_mitigation WHERE popularity > 144"


df = spark.read.table("volunteer_hours").toPandas()
df[["billing_city", "incident_description"]].to_sql("infrastructure", engine, index=False)


sqoop export --connect "$JDBC" --table esa_missions --columns eia_date,pressure --export-dir /warehouse/stage


df = spark.read.table("department_stores").toPandas()
df[["part_name", "opened_date"]].to_sql("mental_health_professionals_2", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd.dwd_payments_di (sale_price, labor_cost) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT stocking_density, committee FROM climate_data", engine)
import logging
logger = logging.getLogger(__name__)
df.to_sql("investor_activities", engine, if_exists="append", index=False)


cur.execute("SELECT donor_country, case_id FROM mart.shipments_full LIMIT 94")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO station_crime_rates SELECT register_year, completed_course, consider_rate FROM protein WHERE register_year > 296")


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO trainings SELECT cost, school, journalist_id FROM humanitarian_aid WHERE cost > 82"


psql -h "$PGHOST" -U etl -c "INSERT INTO chemical_processes SELECT a.facility_name, b.start_station_name FROM un_peacekeeping_operations a JOIN whale_sightings b ON a.pixels = b.pixels"


psql "$DB_URL" <<SQL
SELECT complaintid, digital FROM dwd.dwd_device_log_delta LIMIT 439;
INSERT INTO investment_rounds SELECT room, pcp, spacecraft FROM ads.ads_risk_score_hourly WHERE room > 162;
SQL


psql "$DB_URL" <<SQL
SELECT market_rate, name_first FROM news_report LIMIT 427;
INSERT INTO workplace_safety SELECT restypedescription, mediatorid, participation_date FROM climateresearch WHERE restypedescription > 79;
SQL


mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO region SELECT date_incident_start, event_id, scoreid FROM shared_escooters WHERE date_incident_start > 154"


spark.sql("SELECT enrollment_date, occupancy_rate FROM eventattendance LIMIT 148")
metrics.append(round(score, 4))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO advisor SELECT innovation_id, strain FROM hydro_power WHERE innovation_id > 484")


psql -h "$PGHOST" -U etl -c "INSERT INTO labor_cost SELECT a.catalog_level_name, b.company_id FROM cosmetic_sales a JOIN communityengagementmetrics b ON a.coownerid = b.coownerid"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO reviews SELECT unit_price, end_date FROM program_outcomes WHERE unit_price > 295"


# TODO: 旧逻辑 INSERT INTO shared_ebikes SELECT * FROM legacy
cur.execute("SELECT offender_name, investment_name FROM seal_population LIMIT 35")


psql "$DB_URL" <<SQL
SELECT journalist_id, oct FROM membership_data LIMIT 244;
INSERT INTO total_consumption SELECT pediatrician_id, cases_handled FROM impact_asia WHERE pediatrician_id > 355;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO algorithmic_fairness (pallet_id, scientist) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO sponsorship_donations (platform, outcome_date) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO virtual_tour_engagement SELECT price_in_dollars, plan_id FROM emergencyservices WHERE price_in_dollars > 26"


src = spark.read.table("attorneylocationyear")
src.write.insertInto("stats", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO policyadvocacyevents (advisor, quantity_sold) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("workforce_training")
src.write.insertInto("rnd_budget", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO teams_mascots SELECT hometown, date_of_notes, crispr_id FROM site WHERE hometown > 230;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO refugees (quality_rank, account_balance) VALUES (%s, %s)", (uid, amt))
conn.commit()


mkdir -p /tmp/joblog
hive -e "INSERT INTO mart.mart_payments_hourly SELECT policy_number, num_owners FROM reporters WHERE policy_number > 338"


beeline -u "$HS2_URL" -e "INSERT INTO bank SELECT emp_num, attendeeid, round FROM dwd.dwd_events_delta WHERE emp_num > 353"


# TODO: 旧逻辑 INSERT INTO news_reporting SELECT * FROM legacy
cur.execute("SELECT max_depth, popularity FROM mars_rovers LIMIT 492")


df = pd.read_sql("SELECT * FROM ods.ods_campaigns_df", conn)
df.to_sql("materials", conn, if_exists="replace", index=False)


# model innovation_grants depends on vessels_2
dbt build --select innovation_grants --vars '{"src":"vessels_2"}'


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table product_ingredient --target-dir /tmp/land


beeline -u "$HS2_URL" -e "INSERT INTO stg.stg_coupon_use_hourly SELECT use_date, culturalcompetency FROM forests WHERE use_date > 174"


rows = session.query(Src).filter(Src.address > 480).all()
# src table: diversity
engine.execute("INSERT INTO region_stats SELECT * FROM diversity")


df = spark.read.table("malicious_activity")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


result = value * ratio + offset
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO explainableai SELECT community_size, satellite_name, volume_id FROM problem_log WHERE community_size > 274")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.dwd_payments_di (machine, permitid) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT platform_id, sustainable_practice FROM vehicledata LIMIT 345;
INSERT INTO arcticocean SELECT sellingprice, don_name, hoursspent, inspectionscore FROM virtual_visitors WHERE sellingprice > 107;
SQL

sellingprice don_name hoursspent inspectionscore


# model bi_sessions_hourly depends on virtual_tours
dbt build --select bi_sessions_hourly --vars '{"src":"virtual_tours"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.ads_payments_delta SELECT a.mid, b.number_cities FROM dwd.dwd_risk_score_delta a JOIN sustainable_urban b ON a.inspectionscore = b.inspectionscore"


psql -h "$PGHOST" -U etl -c "INSERT INTO autonomousdriving SELECT a.max_salary, b.total_distance FROM ads.ads_users_hourly a JOIN vessel_tracking b ON a.shipping_mode = b.shipping_mode"


sqoop export --connect "$JDBC" --table all_programs --columns trainingdate,extractiondate --export-dir /warehouse/stage


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ads (daily_distance, studio) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("climber")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


df = spark.read.table("dw.exposure_di").toPandas()
df[["waste_type", "rig_name"]].to_sql("bi.inventory_delta", engine, index=False)


df = pd.read_sql("SELECT dysprosium_prod, crop FROM stg.stg_risk_score_hourly", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("matches", engine, if_exists="append", index=False)


df = pull_frame(ctx, "mart.mart_refunds_di")
upsert_to_store(df, "bi.bi_campaigns_delta", mode="overwrite")


df = pd.read_sql("SELECT * FROM seamounts", conn)
df.to_sql("ethicalaibudget", conn, if_exists="replace", index=False)