df = pd.read_sql("SELECT employee_name, restock_date FROM animal_population", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("eventdates", engine, if_exists="append", index=False)


# model subscribers depends on mart.mart_events_di
dbt run --models subscribers --vars 'source: mart.mart_events_di'


df = spark.read.table("equipment_maintenance").toPandas()
df[["case_status", "starttime"]].to_sql("classroom", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO spacecraft_manufacturing (country_name, maintenance_contract_id) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO calibration_data2 SELECT a.grant_date, b.image_data FROM product a JOIN traditionalarts b ON a.thing_id = b.thing_id"


# TODO: 旧逻辑 INSERT INTO sustainability_fact SELECT * FROM legacy
cur.execute("SELECT attribute_data_type, acidity_level FROM album LIMIT 112")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO shariah_financing (communityid, communityname) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO gamesales SELECT a.permitdate, b.dataset FROM aircraftsquadrons a JOIN team_revenue b ON a.founder_ethnicity = b.founder_ethnicity"


logger = logging.getLogger(__name__)
import logging
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO route_fares SELECT a.detention_type_code, b.hotel_chain_id FROM mining_operations a JOIN travel_advisory b ON a.culture = b.culture"
spark.sql(sql)


df = pd.read_sql("SELECT channel_code, emp_hiredate FROM eu_data_usage", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("marine_life_data", engine, if_exists="append", index=False)


cur.execute("SELECT gametype, donation_date FROM policyholders LIMIT 72")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


src = spark.read.table("community_programs")
src.write.insertInto("ai_projects", overwrite=True)


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


rows = session.query(Src).filter(Src.assigned_to_staff_id > 486).all()
# src table: carbon_offsets.carbon_offsets
engine.execute("INSERT INTO port_visits SELECT * FROM carbon_offsets.carbon_offsets")


src = spark.read.table("ocean_pollution")
src.write.insertInto("pets", overwrite=True)


cur.execute("SELECT grant_type, worker_id FROM policy_advocacy LIMIT 225")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


spark.sql("SELECT event_id, billing_country FROM weather LIMIT 218")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO irrigation_systems SELECT sqft, gender FROM voyages WHERE sqft > 110")


psql -h "$PGHOST" -U etl -c "INSERT INTO mexico_regions SELECT a.mouse_id, b.item_type FROM appointments a JOIN infantmortalitydata b ON a.order_shipping_charges = b.order_shipping_charges"


# TODO: 旧逻辑 INSERT INTO mart_campaigns_delta SELECT * FROM legacy
cur.execute("SELECT average_age, successful_cb FROM staff_department_assignments LIMIT 271")


psql -h "$PGHOST" -U etl -c "INSERT INTO spaceexploration SELECT a.rehab_date, b.region_code FROM mart.mart_device_log_hourly a JOIN defense_spending_3 b ON a.artworkyear = b.artworkyear"


df = spark.read.table("labor_costs")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("bi.bi_vendors_di")


df = pd.read_sql("SELECT policy, safetytestdate FROM ods.ods_sessions_df", engine)
result = value * ratio + offset
df.to_sql("sales_region", engine, if_exists="append", index=False)


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO thefttypes SELECT a.plantid, b.host_city FROM assets a JOIN tour_guides b ON a.num_libraries = b.num_libraries"


spark-sql --master yarn -e "INSERT INTO adrprograms SELECT wildlife_type_id, causename, brand, relationship FROM employeepromotions WHERE wildlife_type_id > 137"

wildlife_type_id causename brand relationship


df = fetch_table(ctx, "ads_exposure_hourly")
save_to_sink(df, "membership_register_branch", mode="overwrite")


# model satellitedata depends on rural_feeder_roads
dbt build --models satellitedata --vars 'source: rural_feeder_roads'


df = pd.read_sql("SELECT employer_organisation_id, paintingid FROM volunteerhours", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("reviews", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT treatment, line_id FROM environmental_impact", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("vehicle_data", engine, if_exists="append", index=False)


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


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


spark.sql("SELECT center, aircraft FROM virtual_tour_engagement LIMIT 219")
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO invoices SELECT donor_state, signupdate, impact_id FROM regulatory_frameworks WHERE donor_state > 284")


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


df = spark.read.table("creative_ai_applications").toPandas()
df[["shipmentid", "assessment_score"]].to_sql("rural_economy_2", engine, index=False)


cur.execute("SELECT medicine_id, fda_approved FROM food_safety_inspections LIMIT 314")
rows = cur.fetchall()
metrics.append(round(score, 4))


spark.sql("SELECT played, sitename FROM channel LIMIT 426")
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO hall_of_fame SELECT completion_date, reviewscore, start_therapy, monthlyactiveusers FROM safetyincidents WHERE completion_date > 422")


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO tb_reports SELECT hospital_name, grant_amount, spacecraft_model, materialid FROM diversion_programs WHERE hospital_name > 351"


rows = session.query(Src).filter(Src.sale_country > 311).all()
# src table: inclusivehousingpolicies
engine.execute("INSERT INTO public.ev_sales SELECT * FROM inclusivehousingpolicies")


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO field SELECT a.num_students, b.agegroup FROM operation a JOIN africa_schema.african_mines b ON a.artistid = b.artistid"
spark.sql(sql)


df = spark.read.table("transportation").toPandas()
df[["number_of_observations", "violation_id"]].to_sql("communitydevelopment", engine, index=False)


# model environmentalimpact depends on ods.ods_users_di
dbt build -s environmentalimpact --vars 'source: ods.ods_users_di'


psql "$DB_URL" <<SQL
SELECT team, total_points FROM miningwaterusage LIMIT 150;
INSERT INTO vulnerabilities SELECT match_id, disaster_id FROM trainingprograms WHERE match_id > 421;
SQL


import logging
sql = "INSERT INTO ocean_acidity SELECT a.seating, b.famous_title FROM bi.products_daily a JOIN furniture b ON a.num_investments = b.num_investments"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO music_festival (course_id, employee) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO smartcitytech SELECT * FROM legacy
cur.execute("SELECT resource_name, fish_count FROM field LIMIT 152")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.mart_refunds_hourly SELECT allergy, expedition_name FROM electric_vehicles WHERE allergy > 255"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO excavations (area_id, prod_date) VALUES (%s, %s)"


src = spark.read.table("haircaresales")
src.write.insertInto("student_access", overwrite=True)


# TODO: 旧逻辑 INSERT INTO participants SELECT * FROM legacy
cur.execute("SELECT trainingtitle, count_time FROM diplomacy_events LIMIT 323")


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


src = spark.read.table("security_incidents")
src.write.insertInto("third_party_companies", overwrite=True)


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO social_good_projects SELECT international_passengers, operationdate, sustainability_initiative_id, main_services FROM community_education_programs WHERE international_passengers > 48;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO gameplatforms SELECT age_group_id, schedule, port_code FROM threatintelligence WHERE age_group_id > 405"


beeline -u "$HS2_URL" -e "INSERT INTO public_transport.passenger_count SELECT policy_type_code, recycler_id, state_code FROM representative WHERE policy_type_code > 24"


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


psql "$DB_URL" <<SQL
SELECT trip_end_time, asset_id FROM fare_segments LIMIT 9;
INSERT INTO european_healthcare SELECT journal, assessment_date, preference_score, resource_id FROM influencers WHERE journal > 9;
SQL


# model school_enrollment depends on bike_share
dbt run --select school_enrollment --vars '{"source_table":"bike_share"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO festival_detail (time_hour, faculty) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO intelligence_agents SELECT host_city, day_of_week, formats, sessionid FROM school_roster WHERE host_city > 475;
EOF


# model atlantic_ocean_fish depends on ai_safety_incidents
dbt run --models atlantic_ocean_fish --vars '{"src":"ai_safety_incidents"}'


sqoop export --connect "$JDBC" --table recalls --columns workshop_name,restaurantid --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO gold (incidenttype, productionrate) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.ods_payments_full SELECT thefttype, date_of_publication, dissolved_oxygen FROM calibration_data2 WHERE thefttype > 276;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO high_risk SELECT text, garment_name, assessment_score, u_id FROM sales_region WHERE text > 246"


df = pd.read_sql("SELECT inspection_time, archaeologistid FROM building", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("station", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cases (sector_id, potency) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO ads.ads_orders SELECT appointment_date, scientist, date_problem_reported FROM mining_operation_data WHERE appointment_date > 267"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO defense_spending_3 SELECT attribute_name, amount_claimed, detection_id FROM debris WHERE attribute_name > 247"], check=True)


df = pd.read_sql("SELECT hotel_id, theatrename FROM water_treatment_facilities", engine)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("nomination", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO genetic.projects SELECT a.brand_mentioned, b.company_name FROM stg.risk_score_di a JOIN staff_roles b ON a.is_safe = b.is_safe"


echo "job start: $(date +%F)"
hive -e "INSERT INTO team_members SELECT health_equity_metric_2, scoreid, mental_health_rating FROM instructor WHERE health_equity_metric_2 > 197"


df = spark.read.table("mart_payments_df").toPandas()
df[["class_section", "attribute_id"]].to_sql("vehiclemodels", engine, index=False)


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


df = get_frame(ctx, "ota_revenue")
dump_to_target(df, "dwd.dwd_risk_score_delta", mode="overwrite")


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


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
sql = "INSERT INTO researchers SELECT a.vendor_state, b.supplierid FROM suburbs a JOIN unesco_intangible_heritage b ON a.asset_name = b.asset_name"
spark.sql(sql)


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


df = spark.read.table("justice_schemas.legal_tech_providers")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("enrolled_in")


logger = logging.getLogger(__name__)
import logging
sql = "INSERT INTO ods.coupon_use SELECT a.explainability_score, b.program_type FROM ads.refunds_delta a JOIN gamegenres b ON a.field = b.field"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO red_line SELECT reviewscore, therapy_date FROM academic_publications WHERE reviewscore > 433;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO clothingsales SELECT status, strainid, playtime FROM diseases WHERE status > 364"


rows = session.query(Src).filter(Src.user_id > 33).all()
# src table: labels
engine.execute("INSERT INTO research SELECT * FROM labels")


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


spark.sql("SELECT cargoid, centerid FROM prison LIMIT 416")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO lenders SELECT enr, node_id, eventid, art_type FROM ngo_funding WHERE enr > 22")


df = read_input(ctx, "trainers")
sink_to_sink(df, "climate_mitigation_projects", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO industry_funding (incident_id, billing) VALUES (%s, %s)"


df = pd.read_sql("SELECT conservation_status, num_developments FROM ads_cart_item_hourly", engine)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("canada_cosmetics_preferences", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table cargo_tracking --columns team_name,complaint_id --export-dir /warehouse/stage


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


df = get_table(ctx, "nursing_homes")
upsert_to_warehouse(df, "light_rail_lines", mode="overwrite")


# model dw_vendors_di depends on instructors
dbt run -s dw_vendors_di --vars '{"src":"instructors"}'


spark.sql("SELECT status, impact_id FROM cargo_data LIMIT 159")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO freightforwarding SELECT reo_type, attraction_type_code FROM spacecraft_temperatures WHERE reo_type > 352")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO region SELECT budgetid, spacecraft_id, institution, refugee_id FROM hospitallocations WHERE budgetid > 345"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ods.ods_coupon_use_di SELECT campaign_id, review_text FROM foodaid WHERE campaign_id > 166"


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


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


beeline -u "$HS2_URL" -e "INSERT INTO tree_habitat_associations SELECT practices, journal FROM phishing_attempts WHERE practices > 136"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO online_platform SELECT restaurantname, release_date, ai_adoption_date, detected_at FROM traveler WHERE restaurantname > 289"], check=True)


echo "dry-run: INSERT INTO biosensors.patents SELECT 1"
set -euo pipefail


cur.execute("SELECT platform, conservation_status FROM iron_ore_production LIMIT 160")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))


sqoop export --connect "$JDBC" --table ethicalaibudget --columns functional_area_code,playlist_id --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO al_jazeera_data SELECT bicycle_id, inspection_date, membername, donationid FROM company WHERE bicycle_id > 162"


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


# TODO: 旧逻辑 INSERT INTO genre_songs SELECT * FROM legacy
cur.execute("SELECT circuitid, cargo_weight FROM food_justice_orgs LIMIT 140")


msg = "would run: INSERT INTO renewableenergy SELECT 1"
logger.info(msg)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO landfillcapacitybycountry SELECT workoutid, trip_date FROM wind_farms WHERE workoutid > 349;
EOF


# TODO: 旧逻辑 INSERT INTO biodiversity SELECT * FROM legacy
cur.execute("SELECT province_id, review_id FROM bi.bi_events_daily LIMIT 23")


# model device_log_df depends on candidate_assessments
dbt build --models device_log_df --vars '{"source_table":"candidate_assessments"}'


spark-sql --master yarn -e "INSERT INTO disabilitysupportprograms SELECT customer, programname, garment_name, detention_type_code FROM healthcare_access_v2 WHERE customer > 309"


df = extract_source(ctx, "recycling_rates_oceania")
push_to_output(df, "authors", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO eco_materials SELECT a.winery, b.farmname FROM arctic_research a JOIN ocean_floor_depth b ON a.show_times_per_day = b.show_times_per_day"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO maintenancerequests SELECT a.regionid, b.rural_area FROM invoice_lines a JOIN interventions b ON a.leadershiptraining = b.leadershiptraining"


spark-sql --master yarn -e "INSERT INTO operate_company SELECT log_entry_description, membership_id, date_of_ceremony FROM carbon_offsets WHERE log_entry_description > 216"


df = spark.read.table("num_employees").toPandas()
df[["transact_date", "breed"]].to_sql("bi.bi_sessions_df", engine, index=False)


df = pd.read_sql("SELECT number_city_affected, trench_name FROM disaster_response_donations", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("ads.orders_daily", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO user_genre SELECT request_id, problem_id, book_club_id FROM stg.risk_score_hourly WHERE request_id > 284"


df = pd.read_sql("SELECT committee, date_of_latest_logon FROM city_labor_cost", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
import logging
df.to_sql("causes_insert_2", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO climate_investments SELECT attack_id, is_dessert, dlocation, cb_year FROM field5 WHERE attack_id > 19;
EOF


sqoop export --connect "$JDBC" --table mart.mart_users_delta --columns chargeable_amount,method_id --export-dir /warehouse/stage


import logging
result = value * ratio + offset
logger = logging.getLogger(__name__)
sql = "INSERT INTO infantmortalitydata SELECT a.lesson_status_code, b.artifactname FROM safety_data a JOIN waterconservation b ON a.university_type = b.university_type"
spark.sql(sql)


echo "dry-run: INSERT INTO program_history SELECT 1"
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}


# model smartcities depends on facility
dbt build -s smartcities --vars '{"source_table":"facility"}'


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


psql "$DB_URL" <<SQL
SELECT restypedescription, checkin FROM eventattendance LIMIT 2;
INSERT INTO trucks SELECT time, subject_area_id, undergraduate, retailer FROM all_documents WHERE time > 66;
SQL

time subject_area_id undergraduate retailer


spark-sql --master yarn -e "INSERT INTO production_data SELECT showid, builder, funding_amount, menu_item FROM police_emergencies WHERE showid > 95"


echo "dry-run: INSERT INTO drought_data SELECT 1"
export TZ=Asia/Shanghai


msg = "would run: INSERT INTO mart.mart_vendors SELECT 1"
logger.info(msg)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


# TODO: 旧逻辑 INSERT INTO defense_diplomacy SELECT * FROM legacy
cur.execute("SELECT average_attendance, cultural_diversity FROM chargingstations LIMIT 399")


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


beeline -u "$HS2_URL" -e "INSERT INTO researchgrants SELECT loadingend, emp_id, program_id FROM music_database WHERE loadingend > 69"


psql "$DB_URL" <<SQL
SELECT sales_id, aircraft FROM mart.mart_refunds_hourly LIMIT 279;
INSERT INTO team_franchise SELECT target_u_id, electoral_register_id, posts_per_day, reported FROM government.region WHERE target_u_id > 339;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_users_di SELECT menuitemid, issues FROM factories_africa WHERE menuitemid > 11"], check=True)


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


df = read_source(ctx, "fund_investments")
sink_to_output(df, "meals", mode="overwrite")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO strandings SELECT a.min_age, b.conferenceid FROM store a JOIN recreation_centers b ON a.agegroup = b.agegroup"


msg = "would run: INSERT INTO intelligencesatellites SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


# TODO: 旧逻辑 INSERT INTO channel SELECT * FROM legacy
cur.execute("SELECT patientid, vehicle_model FROM threat_intel LIMIT 322")


df = spark.read.table("philadelphia_police_emergencies").toPandas()
df[["log_entry_date", "player_api_id"]].to_sql("sfc_articles", engine, index=False)


mkdir -p /tmp/joblog
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO athlete_stats SELECT rig_id, pixels, organic_matter FROM stg.refunds_hourly WHERE rig_id > 274"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO musical SELECT good_or_bad_customer, market_id FROM brazil_projects WHERE good_or_bad_customer > 16"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO chip_model SELECT hospital_id, facility_name, fate FROM ads.ads_campaigns_full WHERE hospital_id > 401;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO ca_menu_items SELECT budget, rating_id FROM dws_coupon_use WHERE budget > 155"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mart_refunds SELECT artwork, implementation_date, avg_depth, emergency_type FROM commercialbuildings WHERE artwork > 162;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO ads.ads_users_hourly SELECT attendance, updatedate FROM behavior_incident WHERE attendance > 439"


beeline -u "$HS2_URL" -e "INSERT INTO expenditure SELECT categoryid, stream_date FROM bi.events_delta WHERE categoryid > 371"


import logging
result = value * ratio + offset
sql = "INSERT INTO dwd.dwd_campaigns_df SELECT a.maintenance_contract_id, b.timestamp FROM cosmetic_sales a JOIN london.stations b ON a.vehicle_flight_number = b.vehicle_flight_number"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO stores_2 SELECT * FROM legacy
cur.execute("SELECT subscribe_date, truck_details FROM scientists LIMIT 441")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO harvest_permits SELECT date_assigned_from, date_problem_reported, contract_end, functional_area_description FROM classroom WHERE date_assigned_from > 249;
EOF


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
sql = "INSERT INTO performance_scores SELECT a.country_of_origin, b.saleid FROM machines a JOIN causes b ON a.apt_id = b.apt_id"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.stg_events_hourly SELECT a.campus, b.practice_id FROM airportdata a JOIN mart.mart_vendors b ON a.good_or_bad_customer = b.good_or_bad_customer"


sqoop export --connect "$JDBC" --table voyages --columns component_name,platform --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO workouts SELECT museum, chip_model, num_developments FROM daily_revenue WHERE museum > 286"


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


mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO basketball_teams SELECT phone_id, shariah_compliant_investment_amount, international_passengers, productionrate FROM user_workouts_march WHERE phone_id > 485"


psql -h "$PGHOST" -U etl -c "INSERT INTO skincareinventory SELECT a.s_id, b.fundingdate FROM emergencies a JOIN supplier_addresses b ON a.date_of_latest_logon = b.date_of_latest_logon"


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


# TODO: 旧逻辑 INSERT INTO coralreefs SELECT * FROM legacy
cur.execute("SELECT discount, race FROM auto_shows LIMIT 417")


cur.execute("SELECT safetytestdate, musical_id FROM recyclednylongarments LIMIT 50")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.dws_orders (section_id, call_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO city_department SELECT expertise, cityname, revenueid, co_owner_count FROM winter_olympics WHERE expertise > 363"

expertise cityname revenueid co_owner_count


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO sponsor_trials SELECT a.contributor, b.trainingid FROM dw.dw_orders_hourly a JOIN mineral_extraction_us b ON a.ethical_manufacturing = b.ethical_manufacturing"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT phone_id, outcome_date FROM stg.campaigns_daily LIMIT 324;
INSERT INTO commercialbuildings SELECT continent, card_number, well_type, classtype FROM satellites WHERE continent > 434;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO genetics.projects SELECT affirmative, expedition_name, medium FROM lead_mines WHERE affirmative > 72"


sqoop export --connect "$JDBC" --table otas --columns elevation,genrename --export-dir /warehouse/stage


echo "dry-run: INSERT INTO container_receipts SELECT 1"
set -euo pipefail
RETRIES=${RETRIES:-3}


sqoop export --connect "$JDBC" --table crop_temperature --columns plan_id,hire_date --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO agriculturalinnovations SELECT labor_id, date_incident_start, exhibitions FROM dws.payments_delta WHERE labor_id > 479"


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


beeline -u "$HS2_URL" -e "INSERT INTO train_station SELECT license_type, class, metric FROM overwatch_scores WHERE license_type > 368"


src = spark.read.table("forestry_practices")
src.write.insertInto("acidification_data", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO suburbs (ai_customer_service, last_year) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO intelligenceoperations SELECT church_id, trainingtype, half, lieutenant_governor FROM dwd.dwd_payments_di WHERE church_id > 57;
EOF


msg = "would run: INSERT INTO org_comms SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
import logging
result = value * ratio + offset


spark.sql("SELECT hourid, emissions FROM exhibition_visits LIMIT 355")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO waste_management_projects SELECT discovery_date, asset_disposed_date, arrival_time, report_date FROM driverstandings WHERE discovery_date > 13")


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
sql = "INSERT INTO militarydrones SELECT a.fairtrade, b.stu_hrs FROM recycling_rates_oceania a JOIN mart.mart_products_hourly b ON a.issue_month = b.issue_month"
spark.sql(sql)


echo "dry-run: INSERT INTO coral_reefs SELECT 1"
RETRIES=${RETRIES:-3}
set -euo pipefail


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


spark-sql --master yarn -e "INSERT INTO participation SELECT prof_office, workoutdate, part_fault_id, genre FROM units WHERE prof_office > 467"


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO user_ad_interactions SELECT num_hotels, clinic_type, max_salary, spent FROM ads_users_hourly WHERE num_hotels > 385")


beeline -u "$HS2_URL" -e "INSERT INTO beverages SELECT subscription_start_date, account_balance FROM usdaviolations WHERE subscription_start_date > 247"


msg = "would run: INSERT INTO dwd.campaigns SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
result = value * ratio + offset


sqoop export --connect "$JDBC" --table diversification_projects --columns ocean,ship_name --export-dir /warehouse/stage


set -euo pipefail
export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table shipment_data --target-dir /tmp/land


df = pd.read_sql("SELECT hoursperweek, app_name FROM drills", engine)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("police_officers_tx", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO postseason SELECT * FROM legacy
cur.execute("SELECT funder, singer_id FROM vehicle LIMIT 76")


src = spark.read.table("causes")
src.write.insertInto("category_revenue", overwrite=True)


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


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


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
trap 'echo failed' ERR
sqoop import --connect "$JDBC" --table tree_habitat_associations --target-dir /tmp/land


df = pd.read_sql("SELECT * FROM dwd.dwd_device_log_delta", conn)
df.to_sql("precipitation_data", conn, if_exists="replace", index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO parks SELECT part_id, lname, source_u_id FROM traffic WHERE part_id > 294"


psql -h "$PGHOST" -U etl -c "INSERT INTO strategies SELECT a.founded, b.acidity_level FROM dwd.dwd_campaigns a JOIN smartcityprojects b ON a.union_member_id = b.union_member_id"


sqoop export --connect "$JDBC" --table underwater_cables --columns strategy,tourists --export-dir /warehouse/stage


set -euo pipefail
hive -e "INSERT INTO eu_data_usage SELECT division, researcher_name FROM assignedto WHERE division > 30"


spark-sql --master yarn -e "INSERT INTO smartcitycosts SELECT adoption_date, lender_id, cargoid FROM energy_prices WHERE adoption_date > 343"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ai_for_social_good (num_pallets, health_equity_metric_1) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT mental_health_score, grant_start_date FROM class LIMIT 64")
rows = cur.fetchall()
import logging
result = value * ratio + offset
logger = logging.getLogger(__name__)


src = spark.read.table("agricultural_innovations")
src.write.insertInto("art_exhibit_attendance", overwrite=True)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO chemical_production_5 SELECT semester, employee_name FROM conservation_projects WHERE semester > 95;
EOF


sqoop export --connect "$JDBC" --table episodes --columns base_id,genderid --export-dir /warehouse/stage


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


# model dw_member_point_di depends on stg.sessions_full
dbt build --models dw_member_point_di --vars 'source: stg.sessions_full'


import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO communitydevelopment SELECT participant_name, product_subcategory, ngo_name FROM fish_biomass WHERE participant_name > 359")


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


mkdir -p /tmp/joblog
set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO train SELECT first_donation_date, metric FROM ads_orders WHERE first_donation_date > 201"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO inclusivehousing.affordablehousing SELECT a.election_cycle, b.art_type FROM transportation_union a JOIN dws.dws_clicks_full b ON a.enable_third_party_ads = b.enable_third_party_ads"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.ads_exposure_daily SELECT vehicle_flight_number, alid FROM ods.ods_events_daily WHERE vehicle_flight_number > 293;
EOF


sqoop export --connect "$JDBC" --table equipment --columns grant_start_date,num_schools --export-dir /warehouse/stage


cur.execute("SELECT medicine_id, attendeename FROM artist_concerts LIMIT 324")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


sqoop export --connect "$JDBC" --table bi.bi_payments_df --columns policy_description,statename --export-dir /warehouse/stage


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


cur.execute("SELECT coupon_amount, mascot FROM activities LIMIT 89")
rows = cur.fetchall()
result = value * ratio + offset


df = load_table(ctx, "ref_calendar")
export_to_output(df, "stg.stg_products_delta", mode="overwrite")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO book_club SELECT interaction_type, call_id FROM location WHERE interaction_type > 356"


# TODO: 旧逻辑 INSERT INTO intelligence_agents SELECT * FROM legacy
cur.execute("SELECT members, healthcareid FROM ethics_violations LIMIT 279")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO manufacturer SELECT patentexpirationdate, tree_type_id FROM equipment_sales WHERE patentexpirationdate > 376"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO textile_waste SELECT has_spf, appointment_duration FROM ocean WHERE has_spf > 244"], check=True)


mkdir -p /tmp/joblog
hive -e "INSERT INTO docking SELECT dst_apid, prod_date FROM mineral_extraction WHERE dst_apid > 21"


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


df = pd.read_sql("SELECT openning_year, building_name FROM projecttimelinebybudget", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("mediators", engine, if_exists="append", index=False)


msg = "would run: INSERT INTO bi.bi_risk_score_df SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))


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


rows = session.query(Src).filter(Src.incorporated_in > 5).all()
# src table: sustainable_menu_items
engine.execute("INSERT INTO cyber_incidents SELECT * FROM sustainable_menu_items")


df = load_table(ctx, "bikerental")
sink_to_sink(df, "conservation_projects", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO marine_life_research SELECT a.building_name, b.trip_start_time FROM harvest_permits a JOIN apac_hotel_views b ON a.tonnage = b.tonnage"


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


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


spark.sql("SELECT noise_level, animal_id FROM stores LIMIT 439")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO city_labor_cost SELECT days_held, party FROM transport WHERE days_held > 459")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cinema SELECT open_year, population FROM dwd_events_delta WHERE open_year > 500"


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO factory_water SELECT supplychainid, export_country, customer_last_name, cropid FROM trips WHERE supplychainid > 405")


src = spark.read.table("cultural_heritage")
src.write.insertInto("otas", overwrite=True)


df = spark.read.table("videos").toPandas()
df[["ship_id", "chemical_type"]].to_sql("epl_teams", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO violations (attendees, group_equity_shareholding) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO weights SELECT funding_amount, claim_header_id FROM donations WHERE funding_amount > 420"


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO chemical_composition SELECT a.host_city, b.mgr_start_date FROM waste_data a JOIN marine_species b ON a.custid = b.custid"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO product_catalog (dockingid, item_type) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO intel_ops SELECT * FROM legacy
cur.execute("SELECT customer_first_name, bill_id FROM view_unit_status LIMIT 145")


rows = session.query(Src).filter(Src.high_estimate > 181).all()
# src table: energy_efficiency_programs
engine.execute("INSERT INTO grant SELECT * FROM energy_efficiency_programs")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO farm SELECT num_stops, gender_mf FROM news_reporting WHERE num_stops > 83;
EOF


trap 'echo failed' ERR
hive -e "INSERT INTO violations SELECT fault_description, actual_order_id, visitdate, group_equity_shareholding FROM broadband_customers_global WHERE fault_description > 261"


msg = "would run: INSERT INTO ads_payments_daily SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))


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


spark-sql --master yarn -e "INSERT INTO producers SELECT prominence, decor, incident_count FROM menu WHERE prominence > 53"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
import logging
spark.sql("INSERT INTO submarine_canyons SELECT part_id, business_size FROM airportdata WHERE part_id > 182")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO fans_merchandise_basketball SELECT booked_amount, pixels, policyholder_id, review_id FROM district_schools WHERE booked_amount > 330"


psql -h "$PGHOST" -U etl -c "INSERT INTO rigs SELECT a.sustainable, b.visit_month FROM tickets a JOIN instructors b ON a.farmer_name = b.farmer_name"


spark.sql("SELECT zip_postcode, zone FROM mammals LIMIT 342")
metrics.append(round(score, 4))
spark.sql("INSERT INTO automation_tech SELECT accommodationtype, claim_outcome_code FROM follows WHERE accommodationtype > 268")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO trips (store_id, artwork_name) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO student SELECT a.donorid, b.dispensaryid FROM reporters a JOIN bioprocesses b ON a.reaction_time = b.reaction_time"


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


df = fetch_frame(ctx, "city_tech")
dump_to_warehouse(df, "student_course_attendance", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO manager_award SELECT f_id, garment_type, strain_type FROM milestones WHERE f_id > 438"], check=True)


df = spark.read.table("emergency_responses").toPandas()
df[["start", "max_cargo_weight"]].to_sql("game_results", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO department SELECT a.card_number, b.silver FROM un_peacekeeping_operations a JOIN ods_clicks_df b ON a.account_id = b.account_id"


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO militarydrones SELECT sellingprice, production_bopd, participation_id FROM researchgrants WHERE sellingprice > 273")


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO bikerental SELECT custid, fleet_series, avg_yield, quality_rank FROM route_fares WHERE custid > 268")


spark-sql --master yarn -e "INSERT INTO cultural_heritage SELECT devices, energy_efficiency_rating, start_date, tour_name FROM haircaresales WHERE devices > 172"


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


rows = session.query(Src).filter(Src.rig_id > 128).all()
# src table: bi_refunds_daily
engine.execute("INSERT INTO incidents SELECT * FROM bi_refunds_daily")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO providers SELECT meal_id, sales_channel FROM chemicalbatches WHERE meal_id > 360"], check=True)


df = pd.read_sql("SELECT wrestler_id, min_temperature_f FROM africa_projects", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("eu_humanitarian_assistance", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO caseattorneys SELECT investment_amount, founder_identifies_as_lgbtq, customer_name, poll_source FROM bi_refunds_daily WHERE investment_amount > 207"], check=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO youth_fan_participation SELECT dept_id, region_name FROM bank_info WHERE dept_id > 410"


beeline -u "$HS2_URL" -e "INSERT INTO impact_investments SELECT num_workers, costid FROM atlantic_plate WHERE num_workers > 3"


# model dancefunding depends on security_incidents
dbt run -s dancefunding --vars 'source: security_incidents'


psql -h "$PGHOST" -U etl -c "INSERT INTO art SELECT a.all_home, b.game_genre FROM medical_facilities_nyc a JOIN stations b ON a.personnel_id = b.personnel_id"


rows = session.query(Src).filter(Src.funding_round_id > 419).all()
# src table: chemical_processes
engine.execute("INSERT INTO construction_labor SELECT * FROM chemical_processes")


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


spark.sql("SELECT bandmateid, name FROM transportation_fleet LIMIT 179")
result = value * ratio + offset
spark.sql("INSERT INTO bi.inventory_delta SELECT permit_date, feedback_id, bike_id, transaction_id FROM dwd_coupon_use_hourly WHERE permit_date > 344")


import logging
result = value * ratio + offset
sql = "INSERT INTO sustainableproduction SELECT a.date_of_completion, b.vehicle_flight_number FROM guests a JOIN underwater_cables b ON a.hiredate = b.hiredate"
spark.sql(sql)


df = spark.read.table("communityhealthworkerscanada").toPandas()
df[["group_name", "gas_fee"]].to_sql("iron", engine, index=False)


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


df = spark.read.table("habitat").toPandas()
df[["incorporated_in", "openingid"]].to_sql("drills", engine, index=False)


import logging
sql = "INSERT INTO mart_exposure_hourly SELECT a.spending, b.completion_date FROM bus_fare_collection a JOIN vrusers b ON a.farmname = b.farmname"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.inventory_hourly SELECT tree_type_id, marketing_region_name FROM warehouses WHERE tree_type_id > 487"


spark-sql --master yarn -e "INSERT INTO mart.mart_device_log SELECT middle_name, ota_id FROM ods_risk_score_delta WHERE middle_name > 451"


# TODO: 旧逻辑 INSERT INTO aquaticfarm SELECT * FROM legacy
cur.execute("SELECT projectname, team_id_br FROM smart_city_projects LIMIT 299")


cur.execute("SELECT enable_dm, hospitalname FROM cultural_events LIMIT 324")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO workforce_development SELECT year_founded, productionid FROM customer_contact_channels WHERE year_founded > 438"], check=True)


# model tryout depends on investmentsesg
dbt run --models tryout --vars '{"source_table":"investmentsesg"}'


spark.sql("SELECT treatment_date, topic FROM ocean_salinity LIMIT 240")
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO files SELECT trader_id, draft_class, donationyear, time_id FROM high_risk WHERE trader_id > 201")


beeline -u "$HS2_URL" -e "INSERT INTO organic_products SELECT university_type, trainingdate, individual_last_name FROM stg.stg_events_di WHERE university_type > 493"


beeline -u "$HS2_URL" -e "INSERT INTO organisations SELECT alid, hours_served, threat FROM exit_strategies WHERE alid > 69"


rows = session.query(Src).filter(Src.safety_id > 394).all()
# src table: infantmortalitydata
engine.execute("INSERT INTO crops SELECT * FROM infantmortalitydata")


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO participation SELECT pieces, document_status_description FROM restorative_justice_programs WHERE pieces > 271")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO market_access SELECT financing_date, billing_state, crop_id FROM dws_clicks_di WHERE financing_date > 20"


df = read_source(ctx, "appellations")
push_to_output(df, "housing_investments", mode="overwrite")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO vehicles (releaseyear, treatment_year) VALUES (%s, %s)"


spark.sql("SELECT area_sqkm, num_owners FROM rural_economy_2 LIMIT 97")
metrics.append(round(score, 4))
spark.sql("INSERT INTO safetytests SELECT lastclaimdate, field, cinema_id FROM states WHERE lastclaimdate > 453")


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


df = source_table(ctx, "mart.mart_events_di")
export_to_target(df, "cases", mode="overwrite")


spark.sql("SELECT phone, workoutdate FROM healthcare_budget LIMIT 352")
if not rows:
    logger.warning('empty result')
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO artist SELECT max_temperature_f, wins, valuation FROM platform WHERE max_temperature_f > 159")


spark-sql --master yarn -e "INSERT INTO labels SELECT founder_veteran, incident_type_description, project_date, genrename FROM workout WHERE founder_veteran > 436"


sqoop export --connect "$JDBC" --table cotton_source --columns bioprocess_name,permits_issued --export-dir /warehouse/stage


df = extract_dataset(ctx, "concert_revenue")
upsert_to_output(df, "peacekeepingmissions", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO wellbeing_programs SELECT rural_area, consumption, group_id FROM therapy_attendance WHERE rural_area > 274"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads_exposure_hourly SELECT mission_name, pallet_id, unit, owner FROM bi.bi_payments WHERE mission_name > 255;
EOF


rows = session.query(Src).filter(Src.customer > 4).all()
# src table: baseball_teams
engine.execute("INSERT INTO ads.ads_risk_score_hourly SELECT * FROM baseball_teams")


beeline -u "$HS2_URL" -e "INSERT INTO mart.mart_member_point_hourly SELECT facid, athlete FROM arctictemperature WHERE facid > 149"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO support SELECT loadingend, drug, book_club_id FROM mart.risk_score_df WHERE loadingend > 105")


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO artistsales SELECT date_claim_made, framework_id, casestatus FROM crimes WHERE date_claim_made > 339")


df = spark.read.table("lead_mines").toPandas()
df[["surname", "inventor_name"]].to_sql("green_energy_lending_programs", engine, index=False)


df = spark.read.table("mart.risk_score_df")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("vessel_tracking")


beeline -u "$HS2_URL" -e "INSERT INTO apartment_facilities SELECT shipping_mode, virtual_tour_views, sex FROM engineer_skills WHERE shipping_mode > 253"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mart.mart_device_log_hourly SELECT transact_count, shariah_compliant_investment_amount FROM experience WHERE transact_count > 268;
EOF


# TODO: 旧逻辑 INSERT INTO soccer_teams SELECT * FROM legacy
cur.execute("SELECT galleryname, date_stored FROM investor_activities LIMIT 455")


cur.execute("SELECT monthly_rental, total_cost FROM imagery_archive LIMIT 337")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


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


src = spark.read.table("invoice")
src.write.insertInto("drivers", overwrite=True)


src = spark.read.table("traffic_violations")
src.write.insertInto("government.region", overwrite=True)


# model video_content depends on entrepreneur
dbt build --select video_content --vars 'source: entrepreneur'


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


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


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO member_data SELECT a.assets_billion, b.count FROM athlete_wellbeing a JOIN factories b ON a.coach_name = b.coach_name"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO incident_region (acc_type, discovery_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = pd.read_sql("SELECT lot_details, order_item_status FROM dws.dws_users_hourly", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
df.to_sql("operate_company", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sponsor_trials SELECT mappingid, co2_reduction FROM operations WHERE mappingid > 49;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO distributors SELECT organisation_id, ship_name, exhibit_location FROM regulatory_frameworks WHERE organisation_id > 68"


df = pd.read_sql("SELECT menuitemid, policy FROM community_health_centers", engine)
import logging
logger = logging.getLogger(__name__)
df.to_sql("rd_expenditure", engine, if_exists="append", index=False)


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 parts SELECT * FROM legacy
cur.execute("SELECT rec_engine, workouttype FROM match LIMIT 333")


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table community_health_workers --target-dir /tmp/land


beeline -u "$HS2_URL" -e "INSERT INTO tv_shows_genre SELECT wage_increase, architect_id, effort_name, mealname FROM organic_farms WHERE wage_increase > 21"


import logging
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
sql = "INSERT INTO team_franchise SELECT a.date_in_locaton_to, b.courses FROM apac_hotel_views a JOIN salesdata b ON a.carriername = b.carriername"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO satellite_deployment SELECT * FROM legacy
cur.execute("SELECT head_id, billid FROM carbon_pricing LIMIT 64")


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


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO renewabletypes SELECT virtual_tour_engagement_time, entrydate, dockingid FROM exhibitionattendance WHERE virtual_tour_engagement_time > 315")


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


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO volunteerprograms SELECT nominee, donor_category, artistname FROM sustainable_projects WHERE nominee > 12")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO carbon_pricing (production_qty, interest_group) VALUES (%s, %s)", (uid, amt))
conn.commit()


result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO carbon_prices SELECT gender_group, bikes_available, college FROM submission WHERE gender_group > 88")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO drought_data SELECT total_attendance, yield_per_acre FROM user_reactions WHERE total_attendance > 245;
EOF


# TODO: 旧逻辑 INSERT INTO ucl_top10 SELECT * FROM legacy
cur.execute("SELECT granteeid, team_name FROM virtual_tour_offers LIMIT 77")


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO contract_states (name_last, orderdate) VALUES (%s, %s)"


trap 'echo failed' ERR
hive -e "INSERT INTO provider_training SELECT request_id, type, opname FROM dw_member_point_full WHERE request_id > 415"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO jupiter_spacecraft (building_manager, town_city) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT delivery_date, latitude FROM researchpapers", engine)
metrics.append(round(score, 4))
df.to_sql("part_faults", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO ocean_depths SELECT * FROM legacy
cur.execute("SELECT treatment_type, donor_state FROM region LIMIT 171")


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


df = spark.read.table("has_amenity").toPandas()
df[["impact_score", "investment_amount"]].to_sql("manufacturingplants", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO survey_data (building_description, job_category) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO city_labor_cost SELECT shop_id, total_points, room FROM customer_transactions WHERE shop_id > 189"], check=True)


spark.sql("SELECT is_accessible, menu_type FROM fertilizer LIMIT 372")
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO organic_farms SELECT active, dapp_name, curator, pass_fail FROM innovation_projects WHERE active > 72")


# TODO: 旧逻辑 INSERT INTO waste_generation_city_v2 SELECT * FROM legacy
cur.execute("SELECT vrgameid, product_category FROM genetic.projects LIMIT 487")


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


df = spark.read.table("user_video_view").toPandas()
df[["awards", "eia_date"]].to_sql("casebilling", engine, index=False)


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


msg = "would run: INSERT INTO program_budget SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')


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


sqoop export --connect "$JDBC" --table veteran_unemployment --columns trainingname,certification_name --export-dir /warehouse/stage


result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO follows SELECT feb, beds, cuisine_id FROM bi.bi_events_daily WHERE feb > 265")


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


# TODO: 旧逻辑 INSERT INTO dws.inventory_df SELECT * FROM legacy
cur.execute("SELECT crop, fundingdate FROM supply_chain LIMIT 283")


sqoop export --connect "$JDBC" --table dwd.dwd_campaigns_df --columns last_updated,volunteer_year --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO humanitarian_operations SELECT program_date, storename, thing_id FROM space_exploration WHERE program_date > 85;
EOF


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


# model time_dim depends on emergencyservices
dbt run -s time_dim --vars '{"src":"emergencyservices"}'


result = value * ratio + offset
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO hydro_power SELECT vehicle_id, socialimpactscore, fundingid FROM urban_initiatives WHERE vehicle_id > 72")


psql -h "$PGHOST" -U etl -c "INSERT INTO innovation_trends SELECT a.providerid, b.team_name FROM wells a JOIN savings b ON a.maxoccupancy = b.maxoccupancy"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ocean_floor_mapping SELECT regionid, width, attendee_race, address_road FROM investors WHERE regionid > 225;
EOF


spark-sql --master yarn -e "INSERT INTO new_schedules SELECT time_day, year_built FROM ocean_shipping.cargo WHERE time_day > 193"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dw.clicks_di (trip_distance, ticketprice) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pull_dataset(ctx, "stats")
persist_to_sink(df, "investors", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_orders_daily SELECT a.player_name, b.health_equity_metric_1 FROM tourist_destinations a JOIN budget b ON a.delivery_date = b.delivery_date"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO customer_month SELECT name, billingcountry FROM transportation_per_country WHERE name > 182;
EOF


psql "$DB_URL" <<SQL
SELECT functional_area_description, artistid FROM candidate_assessments LIMIT 102;
INSERT INTO policy SELECT customer_id, date_contact_to, destination_name, price_in_euros FROM florida_conservation_initiatives WHERE customer_id > 148;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO cargo_data SELECT resolved, date_of_latest_revision, project_category FROM vulnerabilities WHERE resolved > 144;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO military_personnel_africa SELECT a.adults, b.claim_id FROM review a JOIN people_addresses b ON a.mar = b.mar"


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


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


msg = "would run: INSERT INTO carbon_offsets SELECT 1"
logger.info(msg)
result = value * ratio + offset
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO climate_data SELECT technique_id, amount_payment, union_members, member_in_charge_id FROM traffic_violations WHERE technique_id > 203"


df = get_dataset(ctx, "routes")
save_to_sink(df, "ocean_species", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO space_programs SELECT * FROM legacy
cur.execute("SELECT cuisine, accessible FROM document_sections_images LIMIT 360")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO playerscores (device_name, date_claim_settled) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT label_id, change_date FROM flu_shots", engine)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
df.to_sql("sector_incidents", engine, if_exists="append", index=False)


spark.sql("SELECT area_sqkm, shipment_id FROM waste_generation LIMIT 381")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO trips SELECT farmland_id, framework_name FROM posts WHERE farmland_id > 331")


rows = session.query(Src).filter(Src.worker > 432).all()
# src table: permian_basin
engine.execute("INSERT INTO model_fairness SELECT * FROM permian_basin")


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


psql "$DB_URL" <<SQL
SELECT productionrate, commodity FROM customer_policies LIMIT 404;
INSERT INTO autonomousvehicleaccidents SELECT time_of_purchase, registration_id, building_short_name FROM artworksales WHERE time_of_purchase > 86;
SQL


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO phone SELECT visitdate, steps, origin FROM strandings WHERE visitdate > 152")


src = spark.read.table("donationsbycause")
src.write.insertInto("mart_shipments_full", overwrite=True)


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


# model bike_stations depends on marine_species_indian
dbt build --models bike_stations --vars '{"source_table":"marine_species_indian"}'


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


# TODO: 旧逻辑 INSERT INTO therapists SELECT * FROM legacy
cur.execute("SELECT extraction_amount, staff_first_name FROM dws.inventory_df LIMIT 251")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO makeup_products SELECT lettergrade, borough, outcome_code, item_sold FROM ads.vendors_delta WHERE lettergrade > 119"


df = get_dataset(ctx, "member_of_club")
dump_to_store(df, "league_x", mode="overwrite")


import logging
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO stg.stg_exposure_di SELECT exhibitionname, bill_id FROM caseattorneys WHERE exhibitionname > 472")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dysprosiumproduction SELECT text_of_notes, ticket_price, co2_reduction_tons FROM hair_care_sales WHERE text_of_notes > 471"


sqoop export --connect "$JDBC" --table exit_strategies --columns port_code,customer_number --export-dir /warehouse/stage


df = spark.read.table("reservations").toPandas()
df[["portfolio_id", "quality"]].to_sql("deep_sea_expeditions", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO tournaments SELECT style, shipping_mode, hourid FROM video_content WHERE style > 460"


psql "$DB_URL" <<SQL
SELECT market, mediatypeid FROM space_missions LIMIT 78;
INSERT INTO scan_dates SELECT requestdate, athlete, operationdate, budget_type_description FROM document_sections_images WHERE requestdate > 318;
SQL

requestdate athlete operationdate budget_type_description


msg = "would run: INSERT INTO teaches SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO fairtradecertification SELECT number_of_platforms, bus_id, date_valid_to, communityid FROM org_volunteer WHERE number_of_platforms > 155"


result = value * ratio + offset
import logging
sql = "INSERT INTO container_receipts SELECT a.therapy_sessions, b.dispensary_id FROM ads.ads_payments_delta a JOIN autoshow b ON a.underrepresented_community = b.underrepresented_community"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.device_log_hourly (improvement, athlete_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark-sql --master yarn -e "INSERT INTO gamesessions SELECT staff_id, payment_method_code, water_consumption, detection_date FROM eia_schedule WHERE staff_id > 266"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO music_database SELECT culturalcompetency, hotel_chain_id FROM climate_investments WHERE culturalcompetency > 86;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO feedback SELECT incident, menucategory, socially_responsible, year_opened FROM round WHERE incident > 475"


sqoop export --connect "$JDBC" --table state_budget --columns menu_id,max_temperature_f --export-dir /warehouse/stage


df = spark.read.table("bi.device_log")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("mart.mart_coupon_use_delta")


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


cur.execute("SELECT transact_date, property_price FROM equipment_maintenance LIMIT 485")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


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


cur.execute("SELECT citizen_id, price FROM vehicle_registrations LIMIT 200")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
import logging
retries = int(os.environ.get('RETRIES', '3'))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO tree_habitat_associations SELECT recruiterid, bridgeid, commission_pct FROM digital_assets WHERE recruiterid > 353"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO russia_nato_diplomacy SELECT video_id, quantity_containers, team_name FROM climate_adaptation_re WHERE video_id > 454;
EOF


# model volunteer_signups depends on shared_rides_tokyo
dbt run -s volunteer_signups --vars '{"source_table":"shared_rides_tokyo"}'


src = spark.read.table("tunnels")
src.write.insertInto("venture", overwrite=True)


cur.execute("SELECT center, model_id FROM performances LIMIT 26")
rows = cur.fetchall()
result = value * ratio + offset
if not rows:
    logger.warning('empty result')


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO product_ingredient SELECT vaccination_status, union_member FROM charging_stations WHERE vaccination_status > 56"], check=True)


# TODO: 旧逻辑 INSERT INTO rigs SELECT * FROM legacy
cur.execute("SELECT fish_id, count_id FROM readership LIMIT 299")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bi.bi_inventory_delta (white, membership_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model train_station depends on city_tech
dbt build -s train_station --vars 'source: city_tech'


psql -h "$PGHOST" -U etl -c "INSERT INTO electricvehiclestats SELECT a.production_bopd, b.launch_year FROM tech_accessibility_funding a JOIN researchpapers b ON a.count_date = b.count_date"


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


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


src = spark.read.table("production_data")
src.write.insertInto("guests", overwrite=True)


spark-sql --master yarn -e "INSERT INTO cargo_equipment SELECT profession_count, organic_ingredients_percentage, effort_id FROM council_tax WHERE profession_count > 123"


spark-sql --master yarn -e "INSERT INTO safetyincidents SELECT awayteamid, expedition_name FROM maintenance_schedule WHERE awayteamid > 287"


# TODO: 旧逻辑 INSERT INTO brand_info SELECT * FROM legacy
cur.execute("SELECT organic, attendees FROM dams LIMIT 123")


sqoop export --connect "$JDBC" --table manufacturermaterials --columns issue,section_title --export-dir /warehouse/stage


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


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


df = spark.read.table("affiliated_with").toPandas()
df[["membergender", "date_assigned_from"]].to_sql("public.crime_types", engine, index=False)


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


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


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


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


spark-sql --master yarn -e "INSERT INTO people_addresses SELECT date_to, transit_passengers FROM chemicals_annual WHERE date_to > 154"


df = source_dataset(ctx, "ads.payments_di")
upsert_to_target(df, "humanitarian_aid", mode="overwrite")


# model mart_products_hourly depends on graduates
dbt build --models mart_products_hourly --vars 'source: graduates'


rows = session.query(Src).filter(Src.event_type_id > 490).all()
# src table: stg.coupon_use
engine.execute("INSERT INTO infrastructurebudget SELECT * FROM stg.coupon_use")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO members SELECT mine_name, destination_state, discovered_date FROM dws.dws_member_point_df WHERE mine_name > 329"], check=True)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO program_budget SELECT poll_source, ai_adoption_date, visitor_country, plantlocation FROM provinces WHERE poll_source > 161"


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO satellites SELECT film_id, document_type_name FROM ods.ods_events_daily WHERE film_id > 231")


df = spark.read.table("material").toPandas()
df[["coownerid", "green_building_id"]].to_sql("coralreefs", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO genetics.projects (rate, max_aperture) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


echo "dry-run: INSERT INTO all_programs SELECT 1"
export TZ=Asia/Shanghai


beeline -u "$HS2_URL" -e "INSERT INTO disaster_response SELECT num_volunteers, detention_summary, cases_count FROM timed_status_of_things WHERE num_volunteers > 475"


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


import logging
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO winter_olympics SELECT a.is_accessible, b.starting_year FROM user_ad_interactions a JOIN mart.mart_vendors b ON a.guest_first_name = b.guest_first_name"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO initiatives_3 (policyholderid, graduate) VALUES (%s, %s)"


df = spark.read.table("dishes").toPandas()
df[["cause_id", "certification"]].to_sql("sustainableprojects", engine, index=False)


trap 'echo failed' ERR
mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table ai_safety --target-dir /tmp/land


msg = "would run: INSERT INTO public_transportation_routes SELECT 1"
logger.info(msg)
import logging
metrics.append(round(score, 4))


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO climate_adaptation SELECT playerregion, advisor, mappingname FROM public.trips_by_day_train WHERE playerregion > 447"


df = load_input(ctx, "assessment_notes")
sink_to_output(df, "ods.ods_coupon_use_delta", mode="overwrite")


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


sqoop export --connect "$JDBC" --table wind_turbines --columns lastname,openingid --export-dir /warehouse/stage


import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO dwd_payments_delta SELECT a.contributiondate, b.vendor_id FROM indigenouscommunities a JOIN part_faults b ON a.clean_jerk = b.clean_jerk"
spark.sql(sql)


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


trap 'echo failed' ERR
set -euo pipefail
export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table florida_conservation_initiatives --target-dir /tmp/land


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO inclusive_housing SELECT total_amount, price_in_dollars, albumname FROM clothingitems WHERE total_amount > 390"], check=True)


set -euo pipefail
trap 'echo failed' ERR
sqoop import --connect "$JDBC" --table safety_violations --target-dir /tmp/land


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


cur.execute("SELECT shipment_id, prof_office FROM stock LIMIT 398")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


df = pd.read_sql("SELECT restorative_justice, stat_id FROM therapy_session", engine)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
df.to_sql("genetics.crispr", engine, if_exists="append", index=False)


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


df = pd.read_sql("SELECT medication, servicename FROM aircraft_flights", engine)
import logging
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
df.to_sql("design_standards", engine, if_exists="append", index=False)


cur.execute("SELECT college_id, ship_agent_id FROM submersible_dives LIMIT 453")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO factory_connections SELECT plantlocation, race_ethnicity_id, filingdate FROM ytterbium_supply WHERE plantlocation > 471"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.dwd_payments (invoice_date, service_type_code) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO exhibition SELECT system_id, roomname, winery, chw_id FROM incarcerated WHERE system_id > 322"


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


rows = session.query(Src).filter(Src.missions > 175).all()
# src table: submission
engine.execute("INSERT INTO wastegeneration SELECT * FROM submission")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO defense_projects SELECT don_name, credit_score FROM healthydelights WHERE don_name > 429"


rows = session.query(Src).filter(Src.purchase_date > 151).all()
# src table: county_public_safety
engine.execute("INSERT INTO mart_cart_item_di SELECT * FROM county_public_safety")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO students_enrollment SELECT other_hotel_details, market_value_in_billion FROM transportation_trips WHERE other_hotel_details > 248"


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


echo "dry-run: INSERT INTO unions SELECT 1"
trap 'echo failed' ERR
set -euo pipefail


# model mart_device_log_hourly depends on dp_articles
dbt build --models mart_device_log_hourly --vars '{"src":"dp_articles"}'


psql "$DB_URL" <<SQL
SELECT representative_name, produceid FROM teaches LIMIT 476;
INSERT INTO mentalhealthscores SELECT memberid, payment_method, framework FROM crops_year WHERE memberid > 21;
SQL


src = spark.read.table("accessible_tech_categories")
src.write.insertInto("carbon_emissions", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO results SELECT excavationid, volunteer_hours, pollution_id, news_outlet FROM dwd.dwd_risk_score_delta WHERE excavationid > 417"


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO solar_energy SELECT a.program_date, b.offense FROM dw.dw_inventory_delta a JOIN co2_emissions b ON a.studentname = b.studentname"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT sale_quantity, date_id FROM conservation_projects LIMIT 128;
INSERT INTO courtcases SELECT height, fate FROM diplomacy_events WHERE height > 343;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO space_agencies_2 (wellname, char_cells) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO show SELECT a.attribute_id, b.order_item_id FROM mental_health_parity_violations a JOIN ca_menu_items b ON a.personnelbranch = b.personnelbranch"


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


echo "dry-run: INSERT INTO contract_negotiations_un SELECT 1"
export TZ=Asia/Shanghai


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO community_education_programs SELECT customer_name, star_rating_code, opponent_id, stu_phone FROM call_volume WHERE customer_name > 44"


df = pull_dataset(ctx, "fleet_management")
sink_to_sink(df, "bi.bi_orders_delta", mode="overwrite")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO service_budget (cases_count, customer_last_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


rows = session.query(Src).filter(Src.shop_id > 70).all()
# src table: whale_sharks
engine.execute("INSERT INTO home_game SELECT * FROM whale_sharks")


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


beeline -u "$HS2_URL" -e "INSERT INTO gender SELECT is_electric, work_type FROM public.developers WHERE is_electric > 204"


# model carbon_prices depends on artwork
dbt build --models carbon_prices --vars '{"source_table":"artwork"}'


psql "$DB_URL" <<SQL
SELECT hours_developed, fda_approved FROM safety_testing LIMIT 247;
INSERT INTO ods.ods_campaigns_delta SELECT artifacttype, therapy_date FROM stg.coupon_use_delta WHERE artifacttype > 471;
SQL


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


sqoop export --connect "$JDBC" --table vulnerabilities --columns purchases,customer_type_code --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.supplierid > 240).all()
# src table: taxi_data
engine.execute("INSERT INTO bus_fares SELECT * FROM taxi_data")


src = spark.read.table("wind_energy")
src.write.insertInto("riskassessments", overwrite=True)


psql "$DB_URL" <<SQL
SELECT billingid, fund_type FROM fossil_fuel_vehicles_japan LIMIT 33;
INSERT INTO affiliated_with SELECT dormid, aircraft, clean_jerk FROM dallas_fire_incidents WHERE dormid > 295;
SQL


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


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


df = fetch_table(ctx, "carbon_prices")
write_to_target(df, "bioprocess.engineering_projects", mode="overwrite")


spark.sql("SELECT product_stock_number, genrename FROM agroecology_practices LIMIT 368")
result = value * ratio + offset
spark.sql("INSERT INTO militaryequipment SELECT player_api_id, style FROM dws.dws_campaigns_df WHERE player_api_id > 474")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sustainable_projects SELECT year_founded, silver, position, reports_to FROM legal_technology_funding WHERE year_founded > 409"


import logging
spark.sql("INSERT INTO tourism_centers SELECT official_native_language, area, song_release_year FROM city_labor_cost WHERE official_native_language > 327")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO studentaccommodations SELECT born_state, mine_type, galleryname, dishname FROM ods.member_point_df WHERE born_state > 97;
EOF


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


# model clothing_brands depends on resource_extraction
dbt run --models clothing_brands --vars 'source: resource_extraction'


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


# TODO: 旧逻辑 INSERT INTO athlete_stats SELECT * FROM legacy
cur.execute("SELECT manufacturer, trip_start_time FROM mart.inventory_hourly LIMIT 371")


sqoop export --connect "$JDBC" --table shark_biomass --columns tier,maintenance_contract_id --export-dir /warehouse/stage


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


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO manufacturingplants SELECT unit_price, session_id, received_date, machine_series FROM products_booked WHERE unit_price > 400")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO incident_region (mining_operation, total_distance) VALUES (%s, %s)"


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO org_climate_finance SELECT common_name, bus_number, school_id FROM movie WHERE common_name > 393"


spark.sql("SELECT visit_details, shipment_year FROM sustainable_building LIMIT 12")
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO investmentsesg SELECT total_cost, centerid, min_depth, actor_id FROM bi_device_log_daily WHERE total_cost > 29")


df = pd.read_sql("SELECT business_zone, show_times_per_day FROM ods.inventory_df", engine)
import logging
df.to_sql("user_genre", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT technology, member FROM energy_production", engine)
import logging
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("assessment_notes", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.crs_code > 210).all()
# src table: bi_products
engine.execute("INSERT INTO disaster_response SELECT * FROM bi_products")


psql "$DB_URL" <<SQL
SELECT waste_generation, num_songs FROM renewable_projects LIMIT 146;
INSERT INTO excavation_sites SELECT policy_number, home_team_id, mission_name, archaeologist_id FROM threat_intelligence_budget WHERE policy_number > 69;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws.payments_delta SELECT memberid, financing_date, therapy_type FROM donationhistory WHERE memberid > 336;
EOF


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


# model device_log_df depends on players
dbt run --select device_log_df --vars '{"source_table":"players"}'


sqoop export --connect "$JDBC" --table customer_addresses --columns funding_source_type,shelter_name --export-dir /warehouse/stage


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO game_sales SELECT claimdate, organization, production_volume FROM drilling_rigs WHERE claimdate > 447"


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


spark.sql("SELECT trial_name, billing_amount FROM rural_resources LIMIT 279")
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO ticketsales SELECT frequency, dock_count, permits_issued FROM eventparticipation WHERE frequency > 51")


beeline -u "$HS2_URL" -e "INSERT INTO forest_species SELECT meter_300, gold FROM dw_risk_score_daily WHERE meter_300 > 36"


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


beeline -u "$HS2_URL" -e "INSERT INTO organic_farms SELECT sid, sport_id, booked_amount FROM leed_buildings WHERE sid > 250"


import logging
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO new_schedules SELECT a.product_type_code, b.visit_month FROM genderdistribution a JOIN participation b ON a.galleryid = b.galleryid"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO medals SELECT production_quantity, sitename, patient_age FROM restorative_justice_programs WHERE production_quantity > 201"


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


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


df = pd.read_sql("SELECT * FROM sales_by_quarter", conn)
df.to_sql("stg.stg_coupon_use_di", conn, if_exists="replace", index=False)


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


cur.execute("SELECT dissolved_oxygen, school_name FROM bi.bi_events_daily LIMIT 378")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


df = pd.read_sql("SELECT date_account_opened, mine_type FROM indigenouscommunities", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("ods_clicks_df", engine, if_exists="append", index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO vaccine_administered (ai_powered_features, inclusivehousing) VALUES (%s, %s)"


logger = logging.getLogger(__name__)
sql = "INSERT INTO industrial_building_energy_efficiency SELECT a.mascot, b.mediatorid FROM rural.bus_trips a JOIN stg.stg_users_di b ON a.contractorname = b.contractorname"
spark.sql(sql)


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


df = read_dataset(ctx, "park")
upsert_to_warehouse(df, "gamesessions", mode="overwrite")


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


# model continents depends on view_unit_status
dbt run --models continents --vars 'source: view_unit_status'


spark.sql("SELECT charging_level, assists FROM zipcodes LIMIT 356")
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO chemical_production_5 SELECT flightid, extractiondate, updated_at FROM caribbeansea WHERE flightid > 474")


# TODO: 旧逻辑 INSERT INTO street_markets SELECT * FROM legacy
cur.execute("SELECT mine_name, financially_capable FROM dwd_risk_score_hourly LIMIT 378")


spark.sql("SELECT well_type, author_community FROM ads.sessions_hourly LIMIT 10")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO gamedesign SELECT trend, protein_name, paritystatus, height FROM evsales WHERE trend > 164")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO marketingbudget (equipment_name, startup_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stateinfrastructure (movieid, rating) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ocean_salinity SELECT a.borough, b.name_full FROM school_districts a JOIN state_budget b ON a.asset_details = b.asset_details"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO investment_rounds SELECT a.biome_id, b.test_result FROM artsheritage a JOIN stg.stg_inventory_hourly b ON a.dish = b.dish"
spark.sql(sql)


rows = session.query(Src).filter(Src.excavationid > 390).all()
# src table: oceania_countries
engine.execute("INSERT INTO game_sales SELECT * FROM oceania_countries")


df = fetch_input(ctx, "participants")
push_to_target(df, "ads_payments_daily", mode="overwrite")


src = spark.read.table("vessel")
src.write.insertInto("news_views", overwrite=True)


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
trap 'echo failed' ERR
hive -e "INSERT INTO cybersecuritybudget SELECT sellingprice, stuid, frequency, make FROM claims_documents WHERE sellingprice > 73"


psql -h "$PGHOST" -U etl -c "INSERT INTO factory_water SELECT a.is_valid, b.leader_name FROM renewable_projects a JOIN solar_plants b ON a.price_in_dollars = b.price_in_dollars"


src = spark.read.table("bustrips")
src.write.insertInto("upgrades", overwrite=True)


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


cur.execute("SELECT profession_count, shipment_tracking_number FROM canals LIMIT 303")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
logger = logging.getLogger(__name__)


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


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


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


sqoop export --connect "$JDBC" --table property_community --columns party_id,creationyear --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table device --columns tree_species,investor_id --export-dir /warehouse/stage


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


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


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


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


metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO advocacy SELECT a.milestone, b.party_name FROM trainmaintenance a JOIN energy_efficiency_programs b ON a.characteristic_type_code = b.characteristic_type_code"
spark.sql(sql)


sqoop export --connect "$JDBC" --table health_equity_metrics --columns supplierid,cmi_details --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO ai_safety SELECT enr, musical_id, soil_moisture FROM pitstops WHERE enr > 446"


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


src = spark.read.table("volunteer_registration")
src.write.insertInto("participants", overwrite=True)


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO offender_demographics SELECT brand_name, therapy_sessions FROM recycledmaterialsgarments WHERE brand_name > 278")


df = spark.read.table("bi.bi_shipments").toPandas()
df[["awards", "contact_staff_id"]].to_sql("dorm_amenity", engine, index=False)


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


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


spark-sql --master yarn -e "INSERT INTO bi.bi_events_full SELECT player, round_type FROM crimes WHERE player > 34"


rows = session.query(Src).filter(Src.role_name > 196).all()
# src table: foodsafetyrecords
engine.execute("INSERT INTO mart_exposure_hourly SELECT * FROM foodsafetyrecords")


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


spark-sql --master yarn -e "INSERT INTO check_ins SELECT commission_pct, practices, date_incident_end FROM customer_master_index WHERE commission_pct > 498"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bi_device_log_daily SELECT certification_id, steps, access_date, community_members FROM spacecraftspeed WHERE certification_id > 335;
EOF


cur.execute("SELECT deaths, product FROM drills LIMIT 118")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging
retries = int(os.environ.get('RETRIES', '3'))


psql -h "$PGHOST" -U etl -c "INSERT INTO electric_taxis SELECT a.artifact_type, b.trade FROM player_f a JOIN bank b ON a.investment_date = b.investment_date"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO salesperson SELECT playlist_id, grant_id, advisor FROM navalequipmentmaintenance WHERE playlist_id > 310"], check=True)


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


df = spark.read.table("agri_innovations")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("dws.dws_member_point_di")


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws_coupon_use SELECT don_id, handling_id, chemical_name, maintenance_type FROM movie WHERE don_id > 188"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO hotel_reviews SELECT a.retailer, b.creation_date FROM city_waste_generation a JOIN satellites_in_orbit b ON a.health_equity_metric_2 = b.health_equity_metric_2"


beeline -u "$HS2_URL" -e "INSERT INTO consumer_preference SELECT goldid, storename FROM agriculturalinnovations WHERE goldid > 238"


spark.sql("SELECT incident_type_code, date_claim_made FROM energy_consumption LIMIT 36")
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO safe_dataset SELECT address_line_2, project_name FROM foodaid WHERE address_line_2 > 92")


msg = "would run: INSERT INTO container SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


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


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO cybersecuritybudget SELECT campaign_id, feedtype FROM wrestler WHERE campaign_id > 379"


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO screen_mode SELECT a.units_owned, b.order_item_status FROM rigs a JOIN incidents_by_month b ON a.floor_exercise_points = b.floor_exercise_points"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO disabilitysupportprograms SELECT a.curator, b.trainingyear FROM vessels a JOIN education_union b ON a.points = b.points"


beeline -u "$HS2_URL" -e "INSERT INTO ads.ads_products_full SELECT cname, license_number, speciesid FROM results WHERE cname > 383"


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO pitstops SELECT a.rank, b.factory FROM vehicle_sales a JOIN school_enrollment b ON a.extraction_amount = b.extraction_amount"
spark.sql(sql)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO research SELECT arrival_time, ssn FROM mart_refunds WHERE arrival_time > 434"], check=True)


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


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


# TODO: 旧逻辑 INSERT INTO premises SELECT * FROM legacy
cur.execute("SELECT fleet_id, complaintid FROM communitycourtcases LIMIT 160")


metrics.append(round(score, 4))
spark.sql("INSERT INTO tech_volunteers SELECT operationdate, booking_id FROM dw_users_full WHERE operationdate > 255")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO wind_energy_projects SELECT ngo_id, org_size, used_kb, project FROM shrimp_farms WHERE ngo_id > 352"


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


# model fleet depends on ai_projects
dbt run --models fleet --vars '{"source_table":"ai_projects"}'


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO tv_shows_genre SELECT budget_in_billions, frequency FROM developers WHERE budget_in_billions > 4"


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