mysql -h db01 -uetl -p"$PW" -e "INSERT INTO agriculturalinvestments (visitid, property_price) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table artist_demographics --columns check_in_id,chargeable_amount --export-dir /warehouse/stage


src = spark.read.table("donations2022")
src.write.insertInto("ocean_salinity", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO restorative_justice_sentences SELECT date_of_publication, recipient_id FROM broadband_providers WHERE date_of_publication > 350;
EOF


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))


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO factory_water SELECT meal_name, founder, offense, review_text FROM casesbyyear WHERE meal_name > 492"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO startup_founders SELECT num_shariah_compliant_investments, base_id FROM phone WHERE num_shariah_compliant_investments > 320"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO extraction_methods SELECT device_id, apid FROM safe_dataset WHERE device_id > 165"


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


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO mart.inventory_hourly SELECT ssn, shariah_compliant_investment_amount, founding_location FROM professor WHERE ssn > 202"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart_events_full SELECT commission_pct, socially_responsible FROM circular_economy_initiatives WHERE commission_pct > 440"], check=True)


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


df = source_input(ctx, "ai_papers")
save_to_target(df, "dwd.inventory_df", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO defense_personnel (activity_type, asset_make) VALUES (%s, %s)"


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


rows = session.query(Src).filter(Src.host_city > 161).all()
# src table: teaches
engine.execute("INSERT INTO fish_feed_factories SELECT * FROM teaches")


sqoop export --connect "$JDBC" --table game_scores --columns orderdate,zone_name --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO player_award SELECT dob, customer_type_code, injury_count FROM tourist_destinations WHERE dob > 152"], check=True)


df = extract_dataset(ctx, "convictions")
save_to_sink(df, "singer", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO daily_articles_by_category SELECT a.bikes_available, b.claim_outcome_code FROM bus_fares a JOIN video_content b ON a.mission_date = b.mission_date"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO socialimpactinvestments SELECT category_name, chargeable_amount, regional_population, rural_area FROM people WHERE category_name > 399")


export TZ=Asia/Shanghai
hive -e "INSERT INTO space_debris SELECT partner_id, booking_status_code FROM social_good_projects WHERE partner_id > 378"


df = pull_input(ctx, "pollution_control_initiatives")
write_to_store(df, "socially_responsible_lending", mode="overwrite")


df = read_dataset(ctx, "galleries")
save_to_output(df, "cultivators", mode="overwrite")


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


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


sqoop export --connect "$JDBC" --table exoplanet_discoveries --columns route_short_name,detention_summary --export-dir /warehouse/stage


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO editor (energy_id, don_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table average --columns donation_amount,building_address --export-dir /warehouse/stage


df = pd.read_sql("SELECT application_date, stream_id FROM maintenancerequests", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("dws.shipments_daily", engine, if_exists="append", index=False)


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


cur.execute("SELECT claim_type, capital FROM gamegenres LIMIT 8")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


df = pd.read_sql("SELECT domestic_passengers, grant_date FROM ads.ads_products_hourly", engine)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("dw.dw_risk_score_full", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO demographics (completion_date, address_line_1) VALUES (%s, %s)"


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


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO gamestats SELECT a.stockid, b.consumption FROM ancient_cultures a JOIN salary b ON a.crime_id = b.crime_id"
spark.sql(sql)


echo "job start: $(date +%F)"
hive -e "INSERT INTO ai_ethics SELECT emp_jobcode, label, floor_exercise_points, co2_reduction_tons FROM architect WHERE emp_jobcode > 167"


psql -h "$PGHOST" -U etl -c "INSERT INTO screen_mode SELECT a.actor_id, b.card_number FROM bi.bi_sessions_df a JOIN stores_2 b ON a.orderid = b.orderid"


psql -h "$PGHOST" -U etl -c "INSERT INTO stg_orders_hourly SELECT a.class_section, b.contract_id FROM ship a JOIN eventattendance b ON a.director = b.director"


beeline -u "$HS2_URL" -e "INSERT INTO artwork SELECT total_attendance, form_name FROM member WHERE total_attendance > 49"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO animal_population_status SELECT hourid, metric_id, client, cuisine_name FROM tree_habitat_associations WHERE hourid > 265"], check=True)


# model disaster_response depends on forms
dbt run --models disaster_response --vars '{"src":"forms"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO oceania_countries (annual_entry_exit, store_email_address) VALUES (%s, %s)"


mkdir -p /tmp/joblog
hive -e "INSERT INTO space_debris SELECT status_code, unit_price FROM ai_ethics_policies WHERE status_code > 364"


src = spark.read.table("emergency_calls")
src.write.insertInto("machine_emissions", overwrite=True)


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


cur.execute("SELECT donorname, granteeid FROM ads.refunds LIMIT 420")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


src = spark.read.table("pollutionincidents")
src.write.insertInto("investor", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.mart_payments_df (date_of_birth, passenger_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO mart_payments_df SELECT driver_id, issue_date, group_equity_shareholding, do_value FROM org_climate_finance WHERE driver_id > 53"


import logging
result = value * ratio + offset
logger = logging.getLogger(__name__)
sql = "INSERT INTO resource_extraction SELECT a.market_value_billion, b.serve_id FROM hotel_reviews a JOIN campaigns b ON a.student_name = b.student_name"
spark.sql(sql)


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


spark.sql("SELECT sale_value, dept_code FROM regional_archaeologists LIMIT 385")
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO developers SELECT fueldate, brand_name FROM third_party_companies WHERE fueldate > 459")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO staff_roles (pname, follow_up_date) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO fair_trade_brands SELECT albumid, year_deforested, year_opened, secretary_vote FROM playersessions WHERE albumid > 37"


df = spark.read.table("fleet_management").toPandas()
df[["num_workers", "patentexpirationdate"]].to_sql("vehicle_sales", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO geological_survey SELECT show_name, prod_id, paritystatus FROM user_interests WHERE show_name > 298;
EOF


spark-sql --master yarn -e "INSERT INTO dws.exposure SELECT ticket_price, menuname, society, funder FROM ais WHERE ticket_price > 347"


# TODO: 旧逻辑 INSERT INTO chemical_production_5 SELECT * FROM legacy
cur.execute("SELECT tot_cred, ticketprice FROM environmental_impact_stats LIMIT 424")


sqoop export --connect "$JDBC" --table sustainableproduction --columns stu_fname,vegetable --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.archaeologist_name > 144).all()
# src table: virtual_tour_offers
engine.execute("INSERT INTO soilmoisturedata SELECT * FROM virtual_tour_offers")


trap 'echo failed' ERR
set -euo pipefail
export TZ=Asia/Shanghai
hive -e "INSERT INTO maintenance_engineers SELECT document_date, ship_id, call_date, budget_million FROM ingredient WHERE document_date > 305"


psql "$DB_URL" <<SQL
SELECT organisation_type, involved_in_lifelong_learning FROM patient LIMIT 61;
INSERT INTO astronauts SELECT cvid, count_time, gameid FROM wind_projects WHERE cvid > 406;
SQL


result = value * ratio + offset
import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO dws.cart_item_full SELECT a.running_time, b.seasons FROM arctic_marine_species a JOIN atlantic_plate b ON a.therapy_session = b.therapy_session"
spark.sql(sql)


df = spark.read.table("student_tests_taken").toPandas()
df[["members", "enroll_grade"]].to_sql("forest_species", engine, index=False)


rows = session.query(Src).filter(Src.rec_engine > 475).all()
# src table: mart_exposure_hourly
engine.execute("INSERT INTO energy_production SELECT * FROM mart_exposure_hourly")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO energy_production SELECT investment_amount, amount, shop_name FROM classrooms WHERE investment_amount > 218"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO staff_department_assignments SELECT a.seasons, b.customer_address_id FROM stg.stg_users_daily a JOIN view_product_availability b ON a.claimid = b.claimid"


psql -h "$PGHOST" -U etl -c "INSERT INTO civilcases SELECT a.meter_300, b.trend FROM party_host a JOIN judges b ON a.document_status_code = b.document_status_code"


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO battery_projects SELECT a.centername, b.draft_pick_number FROM studies a JOIN dws.dws_users_hourly b ON a.sale_date = b.sale_date"
spark.sql(sql)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO local_impact_japan SELECT date_to, company, genrename, job_category FROM sites WHERE date_to > 309"], check=True)


# TODO: 旧逻辑 INSERT INTO crime_stats SELECT * FROM legacy
cur.execute("SELECT causeid, served_subscribers FROM bookings LIMIT 284")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ethicalaibudget SELECT decoration_theme, first_name, building_id FROM attendance WHERE decoration_theme > 381"], check=True)


psql "$DB_URL" <<SQL
SELECT has_disability, port_code FROM healthcare_facilities LIMIT 393;
INSERT INTO phishing_targets SELECT vehicle_details, competition FROM infrastructureprojects WHERE vehicle_details > 144;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO stg.stg_coupon_use_hourly SELECT emp_jobcode, plan_type, royal_family_details, u_id FROM organic_cosmetics WHERE emp_jobcode > 322"


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


spark.sql("SELECT quarter, issue FROM dws.dws_inventory_di LIMIT 385")
result = value * ratio + offset
spark.sql("INSERT INTO volunteerhours SELECT delivery_date, max_temperature_f, volunteer_date, building_manager FROM wine WHERE delivery_date > 73")


beeline -u "$HS2_URL" -e "INSERT INTO price_data SELECT producerid, time_of_day FROM indigenous_food_systems WHERE producerid > 371"


# model mart_refunds_hourly depends on tech_volunteers
dbt run -s mart_refunds_hourly --vars '{"src":"tech_volunteers"}'


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


sqoop export --connect "$JDBC" --table org_comms --columns update_date,statement_details --export-dir /warehouse/stage


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


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


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


psql "$DB_URL" <<SQL
SELECT attendeeid, org_size FROM veterans LIMIT 90;
INSERT INTO dailystreams SELECT dock_status, company_name FROM community_members WHERE dock_status > 422;
SQL


df = get_source(ctx, "biosensors.projects")
persist_to_target(df, "item_inventory", mode="overwrite")


src = spark.read.table("nutrition_facts")
src.write.insertInto("ticket_sales", overwrite=True)


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


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


# model loan depends on hotel_business_partnerships
dbt run -s loan --vars 'source: hotel_business_partnerships'


spark.sql("SELECT orderid, operationdate FROM stg.stg_risk_score LIMIT 170")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO documents_to_be_destroyed SELECT employee_address_id, total_donation_amount, eventtype FROM candidate_assessments WHERE employee_address_id > 363")


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


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
sql = "INSERT INTO intelligence_agency SELECT a.shariah_compliant_investment_amount, b.community_name FROM field_rainfall a JOIN movies b ON a.filingdate = b.filingdate"
spark.sql(sql)


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


src = spark.read.table("tencel_sources")
src.write.insertInto("goals", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO safetyincidents SELECT vehicle_flight_number, decision, vendorid FROM ref_hotel_star_ratings WHERE vehicle_flight_number > 312"], check=True)


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


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


spark.sql("SELECT served_subscribers, inventoryid FROM underwater_trenches LIMIT 418")
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO gamegenres SELECT waste_amount, community_type, screen_mode, incidentdate FROM paris_real_estate WHERE waste_amount > 119")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO driverstandings (planned_delivery_date, water_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT retweets, material FROM donationhistory LIMIT 142")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
import logging


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO vessel_incident_count (subject_id, next_maintenance) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("mart.mart_payments_delta").toPandas()
df[["half", "consumption"]].to_sql("birds", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO infantmortalitydata (patient_age, tournament_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


psql -h "$PGHOST" -U etl -c "INSERT INTO marketing_budgets SELECT a.content_type, b.count_time FROM game_results a JOIN game_scores b ON a.provider = b.provider"


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


spark-sql --master yarn -e "INSERT INTO emerging_markets.digital_assets SELECT region_code, field_id FROM gameplatforms WHERE region_code > 367"


df = spark.read.table("infra_diversification").toPandas()
df[["venue", "is_public"]].to_sql("student_mental_health", engine, index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO healthbudget SELECT num_courses, production_volume FROM sustainability_metrics WHERE num_courses > 243"


beeline -u "$HS2_URL" -e "INSERT INTO technician SELECT squadron, contract_count, conservation_status FROM mart.mart_coupon_use_delta WHERE squadron > 16"


spark.sql("SELECT emp_jobcode, occupation FROM provinces LIMIT 459")
metrics.append(round(score, 4))
spark.sql("INSERT INTO faculty SELECT sustainable_practice, latitude, wrestler_id, consumption FROM pharmasales WHERE sustainable_practice > 481")


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


spark.sql("SELECT role_name, workoutdate FROM economic_diversification_argentina LIMIT 201")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO hotel_chains SELECT hireid, partid, attribute_id FROM cuisine WHERE hireid > 364")


sqoop export --connect "$JDBC" --table payments --columns song_year,savings --export-dir /warehouse/stage


cur.execute("SELECT impactid, start FROM view_unit_status LIMIT 68")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


df = pd.read_sql("SELECT publicationid, dish FROM auto_show", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("landfill_capacity_north_america", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table stg.stg_exposure_daily --columns experiment_name,source_system_code --export-dir /warehouse/stage


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


import logging
result = value * ratio + offset
sql = "INSERT INTO policyadvocacyevents SELECT a.building_manager, b.transact_date FROM shrimp_farms a JOIN makeup_sales b ON a.organization_details = b.organization_details"
spark.sql(sql)


echo "dry-run: INSERT INTO haircaresales SELECT 1"
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog


logger = logging.getLogger(__name__)
sql = "INSERT INTO permian_basin SELECT a.delivery_time, b.coach_name FROM platform_production a JOIN participation b ON a.posted_at = b.posted_at"
spark.sql(sql)


rows = session.query(Src).filter(Src.grant_id > 48).all()
# src table: province.human_rights_data
engine.execute("INSERT INTO thefts SELECT * FROM province.human_rights_data")


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


spark.sql("SELECT period, recipient FROM routes LIMIT 4")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO record SELECT unit_name, permit_date, meal_name, investorgender FROM excavation_sites WHERE unit_name > 1")


df = spark.read.table("stg.stg_risk_score").toPandas()
df[["workshop_name", "home_team_id"]].to_sql("electricvehicles", engine, index=False)


df = pd.read_sql("SELECT zone_id, observation_date FROM fabricinventory", engine)
threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')
df.to_sql("guests", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO artsales (date_in_locaton_to, tripid) VALUES (%s, %s)"


df = pd.read_sql("SELECT cropname, emission_date FROM project", engine)
metrics.append(round(score, 4))
import logging
df.to_sql("chemical_production_3", engine, if_exists="append", index=False)


src = spark.read.table("bi.bi_events_daily")
src.write.insertInto("store", overwrite=True)


spark.sql("SELECT amount_outstanding, to_address FROM individual LIMIT 387")
import logging
spark.sql("INSERT INTO animal_budget SELECT order_status_code, temporary_acting FROM contract_transactions WHERE order_status_code > 23")


rows = session.query(Src).filter(Src.contractor_name > 187).all()
# src table: diversity
engine.execute("INSERT INTO volume SELECT * FROM diversity")


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


df = spark.read.table("donations_insert_2")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO genderdistribution SELECT schedule_id, price, neighborhoodid, address_line_2 FROM campaigns WHERE schedule_id > 142"


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


cur.execute("SELECT country, machine FROM fare_collection LIMIT 410")
rows = cur.fetchall()
import logging


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO chemical_production_3 SELECT affirmative, creationyear FROM trip WHERE affirmative > 323;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO underwater_cables (mine_type, task_details) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO music_festival SELECT a.composer, b.funding_id FROM traditionalarts a JOIN hotel_business_partnerships b ON a.tree_id = b.tree_id"


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


# TODO: 旧逻辑 INSERT INTO carbon_footprint SELECT * FROM legacy
cur.execute("SELECT orderdate, researcher_id FROM refugee_support LIMIT 110")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO hosting_city SELECT white, end_date, field_name, savings FROM renewables.renewable_projects WHERE white > 167;
EOF


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO product_reviews SELECT a.competition_type, b.number_of_matches FROM problem_log a JOIN influencers b ON a.signupdate = b.signupdate"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT customer_code, brandid FROM marine_life_sightings LIMIT 73;
INSERT INTO fairtradecertifications SELECT accreditation_type, field_name, claim_status_name FROM bi.bi_events_df WHERE accreditation_type > 108;
SQL


logger = logging.getLogger(__name__)
sql = "INSERT INTO sites SELECT a.camera_lens_id, b.appointmentid FROM ads.risk_score a JOIN courtcases b ON a.received_date = b.received_date"
spark.sql(sql)


df = pd.read_sql("SELECT catalog_id, host FROM streams", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("market", engine, if_exists="append", index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO carbon_offsets SELECT a.delivery_time, b.points_per_game FROM injury_accident a JOIN highways b ON a.price = b.price"


# TODO: 旧逻辑 INSERT INTO broadband_subscribers SELECT * FROM legacy
cur.execute("SELECT mappingname, official_native_language FROM bi.bi_orders_delta LIMIT 385")


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO space_exploration (trainingyear, ngo_name) VALUES (%s, %s)"


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO musical SELECT routeid, staff_id, institution FROM satellites_by_country WHERE routeid > 196"


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO irrigation_systems SELECT maintenance_id, anomaly, main_industry, department_name FROM dwd_payments_delta WHERE maintenance_id > 273"


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


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


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


echo "dry-run: INSERT INTO mart_events_full SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


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


psql -h "$PGHOST" -U etl -c "INSERT INTO vesselfuel SELECT a.algorithm_name, b.number_of_hosts FROM inmates a JOIN purchases b ON a.news_story_id = b.news_story_id"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO ticket_sales SELECT clubdesc, region_id, advocate_name FROM open_data_initiatives WHERE clubdesc > 56"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO excavation SELECT a.culture, b.ihsaa_football_class FROM dws.dws_risk_score_df a JOIN threats b ON a.worker_name = b.worker_name"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_events_di SELECT operation, donor_country FROM ads.sessions_hourly WHERE operation > 7;
EOF


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


echo "dry-run: INSERT INTO mart.mart_payments_df SELECT 1"
trap 'echo failed' ERR


sqoop export --connect "$JDBC" --table sustainable_tourism_practices --columns active_to_date,plant --export-dir /warehouse/stage


import logging
spark.sql("INSERT INTO ca_menu_items SELECT length_meters, environmental_impact, school_id FROM philadelphia_police_emergencies WHERE length_meters > 3")


# TODO: 旧逻辑 INSERT INTO recovery_program SELECT * FROM legacy
cur.execute("SELECT competition, postalcode FROM mart.mart_device_log LIMIT 231")


df = spark.read.table("labour_productivity")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("dwd.dwd_orders_daily")


src = spark.read.table("market")
src.write.insertInto("experience", overwrite=True)


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO militarydrones SELECT area_name, donationid FROM opioid_overdoses WHERE area_name > 125")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO artifacts SELECT last_maintenance, delegate, rainfall FROM ai_systems WHERE last_maintenance > 154"


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


sqoop export --connect "$JDBC" --table online_platform --columns period,grape --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table intelligence_personnel --columns sitename,description --export-dir /warehouse/stage


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO stg.device_log_df SELECT fleet_id, num_owners FROM mining_operations WHERE fleet_id > 231"


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


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


metrics.append(round(score, 4))
sql = "INSERT INTO vessel_types SELECT a.round_date, b.state_county FROM safe_dataset a JOIN dailystreams b ON a.working_horses = b.working_horses"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO artist_concerts SELECT virtual_tour_engagement_time, style FROM stg.stg_campaigns_hourly WHERE virtual_tour_engagement_time > 433;
EOF


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


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


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


df = get_source(ctx, "operation")
upsert_to_target(df, "climate_finance_asia", mode="overwrite")


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


beeline -u "$HS2_URL" -e "INSERT INTO staff_department_assignments SELECT claim_number, distributorid FROM fraud_detections WHERE claim_number > 307"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.bi_payments_delta SELECT gender_mf, dish, gender_group FROM safety_incident WHERE gender_mf > 438"], check=True)


cur.execute("SELECT goals, initiativename FROM section LIMIT 93")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


spark-sql --master yarn -e "INSERT INTO labor_practices SELECT num_of_factories, staff_last_name FROM canals WHERE num_of_factories > 115"


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


spark-sql --master yarn -e "INSERT INTO buildings SELECT daily_sales, part_id FROM experience WHERE daily_sales > 469"


df = spark.read.table("dwd.dwd_orders_daily").toPandas()
df[["songid", "departure_date"]].to_sql("sponsor_trials", engine, index=False)


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


sqoop export --connect "$JDBC" --table crops_table --columns followers,species_id --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.away_team > 453).all()
# src table: volunteer_registration
engine.execute("INSERT INTO ecohousing SELECT * FROM volunteer_registration")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO faculty SELECT fish_count, brand_name FROM program_budget WHERE fish_count > 67;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO seafood SELECT commanding_officer, membership_amount, era, denomination FROM enzyme WHERE commanding_officer > 308"


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


beeline -u "$HS2_URL" -e "INSERT INTO coal_reserves SELECT business_name, characteristic_type_code, issue_month, fuelid FROM fault_log_parts WHERE business_name > 353"


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO nomination SELECT market_rate, compatible_since_year, acidification_level, mid FROM research_grants WHERE market_rate > 303"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO community_development.transactions SELECT art_id, customer_event_id, share_count, order_shipping_charges FROM video_games WHERE art_id > 246"


psql "$DB_URL" <<SQL
SELECT restypename, court_appearances FROM circulation_history LIMIT 136;
INSERT INTO videos SELECT development_name, undergraduate, amount_paid FROM mart.mart_risk_score_hourly WHERE development_name > 18;
SQL


spark-sql --master yarn -e "INSERT INTO culturalevents SELECT num_attendees, green_building_id, min_salary FROM refugees WHERE num_attendees > 103"


beeline -u "$HS2_URL" -e "INSERT INTO advisor SELECT organizationid, produceid, directed_by, roomtype FROM flight_emissions WHERE organizationid > 370"

organizationid produceid directed_by roomtype


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO galleries SELECT energy_id, membergender, cases_count FROM military_personnel_africa WHERE energy_id > 406"], check=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO milestones SELECT secretary_vote, asset_acquired_date, capacity, research_name FROM gymnast WHERE secretary_vote > 157"


spark.sql("SELECT garment_type, sustainability_certified FROM gamedesign LIMIT 19")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO topublictransportation SELECT route, claim_id, thing_id FROM user_genre WHERE route > 226")


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


df = pd.read_sql("SELECT sex, threat FROM dw_orders_df", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("farmers", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO provider_training SELECT sales_id, workforce_development, domestic_passengers, platformid FROM safety_data WHERE sales_id > 218"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO immunization (stream_id, amount_funded) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws_clicks_di SELECT age_group, rate, pediatrician_id FROM concentrateprices WHERE age_group > 296"], check=True)


sqoop export --connect "$JDBC" --table studentaccommodations --columns organization_id,founder_ethnicity --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO renewable_projects (fair_trade, supplier_country) VALUES (%s, %s)"


result = value * ratio + offset
import logging
spark.sql("INSERT INTO party SELECT driver_id, stationid, to_address FROM skincaresales WHERE driver_id > 431")


beeline -u "$HS2_URL" -e "INSERT INTO patient SELECT membership_card, round FROM document_sections_images WHERE membership_card > 325"


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


rows = session.query(Src).filter(Src.opened_date > 363).all()
# src table: policy_feedback
engine.execute("INSERT INTO education_union SELECT * FROM policy_feedback")


msg = "would run: INSERT INTO co2_sequestration SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO defense_contracts SELECT developer_id, class_section, game_genre FROM tickets WHERE developer_id > 26"


spark.sql("SELECT exhibition_id, donator_name FROM fraud_detections LIMIT 176")
logger = logging.getLogger(__name__)
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO highest_scores SELECT bathroom_count, albumid FROM habitat WHERE bathroom_count > 202")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mine (gamepreference, program) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO packages SELECT a.hoursspent, b.part_name FROM australian_states a JOIN lessons b ON a.brandid = b.brandid"


src = spark.read.table("carbon_offset_programs")
src.write.insertInto("providers", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO album SELECT monthly_rental, reported FROM beverages WHERE monthly_rental > 269;
EOF


sqoop export --connect "$JDBC" --table researchpapers --columns region_name,export_country --export-dir /warehouse/stage


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


# model recyclers depends on traffic_accidents
dbt run --select recyclers --vars '{"source_table":"traffic_accidents"}'


df = read_frame(ctx, "donor")
push_to_target(df, "conservation_initiatives", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO biosensor.patents SELECT src_apid, membership FROM waterconservation WHERE src_apid > 453"


psql -h "$PGHOST" -U etl -c "INSERT INTO socially_responsible_lending SELECT a.contact_staff_id, b.first_donation_date FROM province.human_rights_data a JOIN food_items b ON a.seating = b.seating"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO publications SELECT gross_worldwide, hours FROM team WHERE gross_worldwide > 400;
EOF


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


spark.sql("SELECT document_id, dish_id FROM mart.campaigns_di LIMIT 294")
result = value * ratio + offset
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO cloud_issues SELECT cases_handled, age_group_id, post_id FROM gymnast WHERE cases_handled > 333")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_campaigns_hourly SELECT pilot, group_equity_shareholding FROM supportservices WHERE pilot > 500"], check=True)


spark.sql("SELECT water_depth, building_phone FROM endowment LIMIT 437")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO stg.stg_exposure_di SELECT contract_start_date, firstdonationdate, energy_generated, news_outlet FROM exhibition_visits WHERE contract_start_date > 411")


sqoop export --connect "$JDBC" --table ocean_acidification --columns languageid,ship_date --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_coupon_use_di SELECT effective_date, catalog_level_number, event_attendance, call_id FROM labor_hours WHERE effective_date > 272;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO circular_supply_chain_products (quantityproduced, building_id) VALUES (%s, %s)"


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


df = spark.read.table("innovation_metrics").toPandas()
df[["zipcode", "country1"]].to_sql("biotech.startups", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO disabilitysupportprograms (value, course_description) VALUES (%s, %s)"


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


df = load_source(ctx, "climate_finance_organizations")
sink_to_target(df, "spacecraft_manufacturers", mode="overwrite")


sqoop export --connect "$JDBC" --table first_notification_of_loss --columns calendar_date,laborproductivity --export-dir /warehouse/stage


src = spark.read.table("instructor")
src.write.insertInto("us_cities", overwrite=True)


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO chemicalproducts SELECT document_type_code, rating_in_percent, item_id FROM trade_history WHERE document_type_code > 260"], check=True)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sponsor_trials SELECT snatch, degrees FROM station_company WHERE snatch > 322;
EOF


psql "$DB_URL" <<SQL
SELECT claim_amount, journalist_id FROM publicchargingstations LIMIT 341;
INSERT INTO countries SELECT year_working, race_ethnicity_id, train_id FROM county_public_safety WHERE year_working > 74;
SQL


rows = session.query(Src).filter(Src.course_name > 221).all()
# src table: roads
engine.execute("INSERT INTO culturalevents SELECT * FROM roads")


df = spark.read.table("mart.mart_payments_delta").toPandas()
df[["party_phone", "content_type"]].to_sql("billstatus", engine, index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO financialwellbeing SELECT a.made_in_usa, b.investors FROM platformstats a JOIN dw.dw_users_di b ON a.artist_name = b.artist_name"


echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO safetytestingcounts SELECT hospitalid, date_payment_made, review_text FROM bi.bi_events_full WHERE hospitalid > 485"


spark-sql --master yarn -e "INSERT INTO vehicle_registrations SELECT sustainability_initiative_id, brandname, protein_name, carbon_footprint FROM transportation_per_country WHERE sustainability_initiative_id > 431"


result = value * ratio + offset
spark.sql("INSERT INTO waterconservation SELECT statement_id, num_rooms FROM wedding WHERE statement_id > 438")


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


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


# TODO: 旧逻辑 INSERT INTO catalogs SELECT * FROM legacy
cur.execute("SELECT gold, review_rating FROM bike_share LIMIT 451")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO daily_transaction_volume SELECT injury, hiv, ship_date, vesselname FROM dwd.dwd_users_hourly WHERE injury > 230"], check=True)


sqoop export --connect "$JDBC" --table hotel_business_partnerships --columns certification_id,system --export-dir /warehouse/stage


import logging
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))


# model labour_productivity depends on pets
dbt run --select labour_productivity --vars '{"src":"pets"}'


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO program_history SELECT astronaut_name, competition_type FROM ods.member_point_df WHERE astronaut_name > 442"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO regional_archaeologists SELECT start_date, main_industry FROM state_info WHERE start_date > 382;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO ads.ads_shipments_delta SELECT aid_name, asset_name, founded_year, offender_name FROM heritagesites WHERE aid_name > 177"


sqoop export --connect "$JDBC" --table voting_data --columns vessel,student_capacity --export-dir /warehouse/stage


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


metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO district_schools SELECT a.gamesplayed, b.haslegalprecedent FROM collective_bargaining a JOIN electronics_factories b ON a.org_id = b.org_id"
spark.sql(sql)


df = fetch_source(ctx, "co_ownership_program")
save_to_sink(df, "stg.stg_inventory_hourly", mode="overwrite")


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


psql "$DB_URL" <<SQL
SELECT customer_address, restaurant_name FROM news_views LIMIT 265;
INSERT INTO machine_emissions SELECT prominence, health_equity_metric_2, stu_gpa FROM laptimes WHERE prominence > 323;
SQL


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


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO climate_finance_re SELECT rig_id, winery, launch_date FROM watertreatmentplants WHERE rig_id > 256"


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


df = pd.read_sql("SELECT ai_id, prereq_id FROM drug_sales", engine)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("ocean_acidification", engine, if_exists="append", index=False)


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


echo "dry-run: INSERT INTO water_conservation_brazil SELECT 1"
set -euo pipefail
trap 'echo failed' ERR
mkdir -p /tmp/joblog


cur.execute("SELECT program_category, ngo_name FROM innovation_trends LIMIT 166")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO province.human_rights_data SELECT cultivatorname, org_size, testtypeid FROM precipitation_data WHERE cultivatorname > 78")


src = spark.read.table("fair_trade_suppliers")
src.write.insertInto("individual", overwrite=True)


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO programoutcomes SELECT a.shipmenttype, b.gross_worldwide FROM life_expectancy a JOIN sustainabilityratings b ON a.has_aloe_vera = b.has_aloe_vera"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO sustainabilityratings SELECT song_year, count_time, workers FROM overwatch_scores WHERE song_year > 302"


df = spark.read.table("user_stats").toPandas()
df[["duration", "preference_score"]].to_sql("sustainable_tourism_practices", engine, index=False)


psql "$DB_URL" <<SQL
SELECT network, attorney_id FROM intelligenceoperations LIMIT 271;
INSERT INTO dws.dws_events_df SELECT mentalhealthscore, season FROM industrial_building_energy_efficiency WHERE mentalhealthscore > 452;
SQL


rows = session.query(Src).filter(Src.provider_parity_score > 349).all()
# src table: recreation_centers
engine.execute("INSERT INTO gamedata SELECT * FROM recreation_centers")


beeline -u "$HS2_URL" -e "INSERT INTO fossil_fuel_vehicles_japan SELECT pages_per_minute_color, is_organic, wind_speed_mph, practicename FROM sustainable_urban_properties_2 WHERE pages_per_minute_color > 96"


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


sqoop export --connect "$JDBC" --table mobile_usage --columns video_id,matchdate --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO project_timelines SELECT patient_age, shop_name, total_horses, astronautid FROM yttrium_production WHERE patient_age > 118"


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


beeline -u "$HS2_URL" -e "INSERT INTO driver SELECT complaint_id, startyear, stu_dob FROM ref_calendar WHERE complaint_id > 377"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO student_addresses (booking_status_code, merchandise_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO projecttimelinebybudget SELECT a.assessmentname, b.retail_price FROM militaryequipmentsales a JOIN drug_approval b ON a.date_in_locaton_to = b.date_in_locaton_to"
spark.sql(sql)


echo "job start: $(date +%F)"
hive -e "INSERT INTO basketball_teams SELECT reported, product_quantity FROM medicine WHERE reported > 179"


psql -h "$PGHOST" -U etl -c "INSERT INTO solana_transactions SELECT a.principal_activities, b.player_name FROM creative_ai a JOIN classroom b ON a.trial_success_rate = b.trial_success_rate"


df = pd.read_sql("SELECT file_size, wheels FROM arcticocean", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("problem_log", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO galleryc SELECT customer_id, loadingend, grantamount, number_of_vessels FROM safety_violations WHERE customer_id > 345"


psql "$DB_URL" <<SQL
SELECT word_count, fastestlapspeed FROM public.trips_by_day_train LIMIT 375;
INSERT INTO recycledmaterialsgarments SELECT builder, day_of_week, played FROM equipment_sales WHERE builder > 479;
SQL


src = spark.read.table("event_attendance")
src.write.insertInto("military_tech", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO vessel_registry SELECT a.cropname, b.report_date FROM user_interests a JOIN textile_suppliers b ON a.delivery_id = b.delivery_id"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO incidents SELECT cvid, daily_visitors FROM residents_services WHERE cvid > 161"


df = spark.read.table("disasters").toPandas()
df[["injury_date", "stadium_id"]].to_sql("chip_model", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO aquaticfarm SELECT wage, vessel_id FROM store_product WHERE wage > 141;
EOF


rows = session.query(Src).filter(Src.royal_family_id > 249).all()
# src table: industry_funding
engine.execute("INSERT INTO dwd.dwd_orders_di SELECT * FROM industry_funding")


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO readership SELECT a.galleryid, b.well_name FROM weather a JOIN first_notification_of_loss b ON a.building_address = b.building_address"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO biosensors.patents (coach_name, statement_id) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO southchinasea.wells SELECT * FROM legacy
cur.execute("SELECT matchdate, membergender FROM mart_shipments_full LIMIT 71")


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


df = read_input(ctx, "hockey_players")
sink_to_target(df, "ads.users_full", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.inventory_delta SELECT art_movement, cb_year, evaluationid FROM educators WHERE art_movement > 226"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ai_projects SELECT lesson_time, aid_name, trackid, workout_name FROM vrplayers WHERE lesson_time > 234"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO fields SELECT business_name, investment_name, dnumber FROM labor_statistics WHERE business_name > 114"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO units SELECT a.vaccinations, b.headquarters FROM biosensors.projects a JOIN stg.refunds b ON a.capacity_percentage = b.capacity_percentage"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ship (main_industry, wastetype) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bi.device_log_hourly (event_id, operation_name) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO performance_scores SELECT specialty, money_requested, violation_id, artist_id FROM dw.dw_events_di WHERE specialty > 474"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO public.crime_types SELECT health_equity_metric_3, attack_country, recipient, taskdate FROM militarypersonnel WHERE health_equity_metric_3 > 309"], check=True)


df = spark.read.table("crime_reports").toPandas()
df[["condition", "visit_date"]].to_sql("billstatus", engine, index=False)


spark.sql("SELECT party_email, effort FROM ods.ods_payments_full LIMIT 333")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO weights SELECT equipment_name, mine_name FROM healthcare_facilities WHERE equipment_name > 192")


metrics.append(round(score, 4))
spark.sql("INSERT INTO training SELECT initiative_type, playtime, accessible, trade_name FROM electric_buses WHERE initiative_type > 347")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO sales_2 (order_quantity, offer_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO marinespeciesobservations SELECT characteristic_data_type, budget_allocated, total_value_purchased FROM faculty WHERE characteristic_data_type > 99"


spark-sql --master yarn -e "INSERT INTO biosensors.projects SELECT stop, plant, lipstick_id, squadron FROM ocean_acidification WHERE stop > 397"


set -euo pipefail
hive -e "INSERT INTO mart.mart_risk_score_hourly SELECT openning_year, invoicedate FROM safety_incidents WHERE openning_year > 311"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.coupon_use_delta SELECT a.productiondate, b.founding_location FROM mobile_plans a JOIN ods.clicks_delta b ON a.score = b.score"


psql -h "$PGHOST" -U etl -c "INSERT INTO whale_sharks SELECT a.character, b.export_country FROM rural_projects a JOIN movies b ON a.supply_volume = b.supply_volume"


df = pd.read_sql("SELECT employee_id, num_solo_exhibitions FROM soccer_teams", engine)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
df.to_sql("stg.coupon_use_delta", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO electric_vehicle_stats SELECT * FROM legacy
cur.execute("SELECT heritage_site, fault_log_entry_id FROM art_exhibit_attendance LIMIT 495")


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM trends_2022"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO defenseprojects (organizationname, incorporated_in) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT project_details, date_claim_settled FROM flights LIMIT 271;
INSERT INTO completed_training SELECT injury_count, opening_hours FROM mars_spacecraft WHERE injury_count > 60;
SQL


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO auctions SELECT a.strainid, b.sid FROM labor_costs a JOIN gamegenres b ON a.community_size = b.community_size"
spark.sql(sql)


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


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


df = pd.read_sql("SELECT roomname, person_id FROM submarine_canyons", engine)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("vessels_2", engine, if_exists="append", index=False)


df = spark.read.table("gamedesigndata").toPandas()
df[["num_of_staff", "frequency"]].to_sql("impact_investments", engine, index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO device (injury_date, location_name) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table associatedheritages --columns treatment_type,document_type_description --export-dir /warehouse/stage


df = pd.read_sql("SELECT number_city_affected, flag FROM displaced_people", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
import logging
df.to_sql("taj_mahal_visitors", engine, if_exists="append", index=False)


# model communitycourtcases depends on wholesale_orders
dbt run --select communitycourtcases --vars '{"src":"wholesale_orders"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO org_comms SELECT raceid, routeid, warehouse_name, number_of_platforms FROM features WHERE raceid > 453"


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


df = spark.read.table("stay").toPandas()
df[["is_hybrid", "serviceid"]].to_sql("disaster_mitigation", engine, index=False)


src = spark.read.table("player_coach")
src.write.insertInto("claims_documents", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO product_categories SELECT hospitalid, participated_in_open_pedagogy, stream_id, vaccine_type FROM architect WHERE hospitalid > 432"], check=True)


metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO communitycourts SELECT a.chair_name, b.hub_id FROM humanitarian_assistance a JOIN total_consumption b ON a.gname = b.gname"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO mart.shipments_delta SELECT * FROM legacy
cur.execute("SELECT ai_adoption, functional_area_description FROM route LIMIT 2")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO pharmasales SELECT coal_reserve_remaining, schedule_date, sample_date FROM mental_health_professionals_2 WHERE coal_reserve_remaining > 137"


spark.sql("SELECT crispr_id, attraction_type_description FROM inspections LIMIT 476")
result = value * ratio + offset
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO agriculturalinvestments SELECT menu_name, genderid FROM ads WHERE menu_name > 402")


df = source_frame(ctx, "mines")
push_to_sink(df, "intelligence_personnel", mode="overwrite")


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


cur.execute("SELECT aircraft_id, ticket_subject FROM customer_master_index LIMIT 218")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO apartments (service_name, catalog_level_number) VALUES (%s, %s)"


df = pd.read_sql("SELECT profession_count, grantid FROM vehicle_data", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("busmaintenance", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO drilling_rigs SELECT * FROM legacy
cur.execute("SELECT creationyear, experiment_name FROM buildings LIMIT 243")


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


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


df = spark.read.table("public_schools").toPandas()
df[["family_name", "customer_email_address"]].to_sql("totalenergyproduction", engine, index=False)


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


psql "$DB_URL" <<SQL
SELECT payment_method_code, events FROM donations LIMIT 262;
INSERT INTO galleryc SELECT personnelid, property_id, employee_address_id, shippingmethod FROM discount_coupons WHERE personnelid > 163;
SQL


cur.execute("SELECT matchid, enrollment FROM constructorstandings LIMIT 329")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


df = spark.read.table("patients")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("dwd.inventory_df")


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


sqoop export --connect "$JDBC" --table defense_contracts --columns continent_id,transactions --export-dir /warehouse/stage


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


spark-sql --master yarn -e "INSERT INTO review SELECT offer_id, asessment_outcome_code, approach, snatch FROM beverages WHERE offer_id > 132"


spark-sql --master yarn -e "INSERT INTO whale_sightings SELECT loadingstart, club_id, enable_third_party_ads FROM documents WHERE loadingstart > 97"


rows = session.query(Src).filter(Src.waste_type > 9).all()
# src table: refugee_support
engine.execute("INSERT INTO dispensaries SELECT * FROM refugee_support")


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO research_grants SELECT neighborhoodname, launch_date, product_description, company_name FROM disabilityadvocacy WHERE neighborhoodname > 253"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
logger = logging.getLogger(__name__)
sql = "INSERT INTO city_tech SELECT a.strategy, b.detention_type_code FROM spacex_missions a JOIN disaster_response b ON a.market_id = b.market_id"
spark.sql(sql)


df = pd.read_sql("SELECT soil_moisture, num_cases FROM unions", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
df.to_sql("smart_grids", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO police_stations SELECT a.middle_name, b.exit_strategy FROM product_review a JOIN biomes b ON a.has_parabens = b.has_parabens"


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO streams SELECT sellingprice, purchaseid FROM historicalcontexts WHERE sellingprice > 342"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO workshop SELECT training_name, disaster_type, last_maintenance FROM ads_payments_hourly WHERE training_name > 460;
EOF


spark-sql --master yarn -e "INSERT INTO ads.ads_products_hourly SELECT discount, chemical_name FROM support_programs WHERE discount > 387"


rows = session.query(Src).filter(Src.donationamount > 136).all()
# src table: artifactanalysis
engine.execute("INSERT INTO spacecraftmanufacturing SELECT * FROM artifactanalysis")


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


cur.execute("SELECT events, votes FROM investments LIMIT 260")
rows = cur.fetchall()
metrics.append(round(score, 4))
import logging


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO climate_projects SELECT attendance_id, ll_id, approach, prof_office FROM fabric WHERE attendance_id > 176"], check=True)


df = spark.read.table("financial_capability").toPandas()
df[["browser_id", "manager_id"]].to_sql("region", engine, index=False)


df = spark.read.table("dwd.dwd_events_delta")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("inmates")


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO fans_merchandise_basketball SELECT task, grant_name FROM vehicle_maintenance WHERE task > 277"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO investment_accounts SELECT bandmateid, browser_id, experiment_name FROM shared_scooters WHERE bandmateid > 89"


src = spark.read.table("makeup_products")
src.write.insertInto("elements_price", overwrite=True)


src = spark.read.table("bias_categories")
src.write.insertInto("biosensors.readings", overwrite=True)


# TODO: 旧逻辑 INSERT INTO haircare_sales SELECT * FROM legacy
cur.execute("SELECT phone_id, ai_algorithm_id FROM bank_info LIMIT 184")


sqoop export --connect "$JDBC" --table safety_incidents_india --columns acc_percent,amenity_name --export-dir /warehouse/stage


presto --server presto01:8080 --catalog hive --execute "INSERT INTO al_jazeera_data SELECT sessiondate, condition_id, event_count FROM astronaut_missions WHERE sessiondate > 457"


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


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


sqoop export --connect "$JDBC" --table stg.sessions_full --columns num_transactions,booking_date --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO iot_sensors SELECT subscription_start_date, last_name FROM gamedesign WHERE subscription_start_date > 12"], check=True)


rows = session.query(Src).filter(Src.dept_store_id > 13).all()
# src table: waterconservationbudget
engine.execute("INSERT INTO initiatives_3 SELECT * FROM waterconservationbudget")


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


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO landfill_capacity SELECT a.alid, b.ratingdate FROM equipment a JOIN conditions b ON a.menu_id = b.menu_id"


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


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


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


cur.execute("SELECT cityname, count_date FROM model_data LIMIT 441")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
import logging


df = source_table(ctx, "all_programs")
sink_to_store(df, "agricultural_projects", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO trainmaintenance (fan_id, s_id) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO news_stories SELECT date_opened, observation_id, agegroup FROM pharmasales WHERE date_opened > 94;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cities SELECT rating_in_percent, follows_ethical_practices, strategy_name FROM e_scooter_trips WHERE rating_in_percent > 76"], check=True)


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))


psql "$DB_URL" <<SQL
SELECT fund_id, quantity_sold FROM police_emergencies LIMIT 166;
INSERT INTO concerts SELECT elevation, pollutant_type, updated_at FROM ods.ods_member_point_df WHERE elevation > 33;
SQL


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


beeline -u "$HS2_URL" -e "INSERT INTO fashion_trend_data SELECT ai_id, school_code, dapp_name, movie FROM ads_sessions_di WHERE ai_id > 266"


cur.execute("SELECT heritage_site, applicant FROM indian_ocean_wells LIMIT 355")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


spark-sql --master yarn -e "INSERT INTO reporters SELECT start_date, well_name, amount_outstanding FROM player_attributes WHERE start_date > 334"


# model price_data depends on ods.ods_device_log_delta
dbt build -s price_data --vars '{"src":"ods.ods_device_log_delta"}'


# model midwest_materials depends on ocean_salinity
dbt run --models midwest_materials --vars '{"source_table":"ocean_salinity"}'


spark.sql("SELECT journal, fertilizer_id FROM noise_pollution LIMIT 156")
metrics.append(round(score, 4))
spark.sql("INSERT INTO ads.ads_payments_delta SELECT showid, gas_production_2020, attraction_name, founder_gender FROM bi.bi_risk_score_full WHERE showid > 42")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws.dws_clicks_full SELECT max_age, era FROM visual_arts WHERE max_age > 42"], check=True)


psql "$DB_URL" <<SQL
SELECT therapy_type, habitat_name FROM carbon_offsets LIMIT 161;
INSERT INTO stg.stg_exposure_daily SELECT union_id, trend, totalamount FROM creativeais WHERE union_id > 184;
SQL


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO satellite_deployment SELECT a.store_name, b.part_id FROM stg.device_log_df a JOIN stg.stg_risk_score_df b ON a.campaign = b.campaign"
spark.sql(sql)


df = spark.read.table("city_waste_generation").toPandas()
df[["date_became_customer", "employee_name"]].to_sql("concerts", engine, index=False)


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


# model hall_of_fame depends on colorado_river_basin
dbt build -s hall_of_fame --vars '{"source_table":"colorado_river_basin"}'


if not rows:
    logger.warning('empty result')
import logging
sql = "INSERT INTO mart.mart_users SELECT a.program_expenses, b.routename FROM tourism a JOIN conditions b ON a.join_year = b.join_year"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT stu_dob, claimtype FROM humanitarianmissions LIMIT 404;
INSERT INTO pollution_initiatives SELECT openingid, sale_id, dapp_name FROM artpieces WHERE openingid > 499;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO eventattendance SELECT a.artpiecename, b.governor FROM purchases a JOIN shelters b ON a.resident_id = b.resident_id"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO smart_cities (route_short_name, governor) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.ads_device_log_di SELECT a.issues, b.number_cities FROM county_public_safety a JOIN vessel_safety b ON a.hosts = b.hosts"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO food_safety_inspections (num_of_audience, industry_4_0) VALUES (%s, %s)", (uid, amt))
conn.commit()


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO community_members SELECT review_id, zone, practice FROM opioid_overdoses WHERE review_id > 479")


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


msg = "would run: INSERT INTO project SELECT 1"
logger.info(msg)
import logging
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')


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


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


# model mentalhealthprovider depends on bridgeconstruction
dbt run -s mentalhealthprovider --vars '{"src":"bridgeconstruction"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO train (first_donation_date, gradepoint) VALUES (%s, %s)"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO lead_mines SELECT passenger_id, attendeeid FROM mart_vendors_full WHERE passenger_id > 181"


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


spark-sql --master yarn -e "INSERT INTO platformi SELECT invested, animal_type FROM makeup_products WHERE invested > 500"


spark-sql --master yarn -e "INSERT INTO artifact_analysis SELECT dish_name, vehicle_flight_number, professional_development FROM mart_refunds WHERE dish_name > 81"


psql "$DB_URL" <<SQL
SELECT hoursperweek, sector FROM uel_top10 LIMIT 433;
INSERT INTO culturalcompetencytraining SELECT visit_details, game_name, email, transact_date FROM electricvehiclestats WHERE visit_details > 484;
SQL


src = spark.read.table("dw.dw_campaigns_di")
src.write.insertInto("financial_capability_id", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO laborstatistics SELECT dataset, ei_category FROM exam_results WHERE dataset > 312"


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


df = spark.read.table("militarypatents").toPandas()
df[["owner_id", "representative_name"]].to_sql("urban_initiatives", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO seasonalvegetables SELECT area_type, operation_count, emp_dob FROM docking WHERE area_type > 81;
EOF


psql "$DB_URL" <<SQL
SELECT rating, trader_id FROM paris_train LIMIT 95;
INSERT INTO bi.events_delta SELECT method_name, attribute_name, runtime FROM organization WHERE method_name > 169;
SQL


# TODO: 旧逻辑 INSERT INTO mart.clicks SELECT * FROM legacy
cur.execute("SELECT comment_count, financial_wellbeing_score FROM water_treatment_facilities LIMIT 369")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO co2price (catalog_name, green_building_certified) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model trafficviolations depends on professionals
dbt build --models trafficviolations --vars 'source: professionals'


beeline -u "$HS2_URL" -e "INSERT INTO plots SELECT area, local_authority, district FROM conservation_projects WHERE area > 110"


spark.sql("SELECT total_beds, round_number FROM bus_fare_collection LIMIT 15")
threshold = cfg.get('threshold', 0.5)
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO workplaces SELECT line_1, local, year FROM college WHERE line_1 > 9")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cyber_incidents SELECT asset_details, date_of_notes, instid FROM engineer_visits WHERE asset_details > 260"


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


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


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


src = spark.read.table("worker_union")
src.write.insertInto("prepaid_mobile", overwrite=True)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO reporters SELECT location, material_id FROM chemical WHERE location > 389;
EOF


# model experiments depends on visual_arts
dbt run -s experiments --vars 'source: visual_arts'


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


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


df = pd.read_sql("SELECT exhibit_location, image_data FROM plots", engine)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
df.to_sql("military_spending", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO food_safety_inspections SELECT project_category, organization_id FROM carbon_emissions WHERE project_category > 9"], check=True)


cur.execute("SELECT therapy_sessions, professional_development FROM farms LIMIT 77")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


df = spark.read.table("bi.bi_member_point").toPandas()
df[["community_id", "acc_bal"]].to_sql("document_locations", engine, index=False)


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


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


psql "$DB_URL" <<SQL
SELECT capacity, departmentid FROM accessible_tech_categories LIMIT 353;
INSERT INTO fish_farms SELECT host_id, impact_id, co2_emission, position FROM fields_production WHERE host_id > 162;
SQL


rows = session.query(Src).filter(Src.recruitername > 170).all()
# src table: ods_vendors_daily
engine.execute("INSERT INTO ods.sessions SELECT * FROM ods_vendors_daily")


cur.execute("SELECT call_count, spacecraft_name FROM coal LIMIT 206")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
import logging


# TODO: 旧逻辑 INSERT INTO article_views SELECT * FROM legacy
cur.execute("SELECT plant, festival_id FROM urban_initiatives LIMIT 403")


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


src = spark.read.table("textileworkers")
src.write.insertInto("drug_sales", overwrite=True)


# model has_amenity depends on trip
dbt build --models has_amenity --vars 'source: trip'


spark-sql --master yarn -e "INSERT INTO contract_transactions SELECT contract_start, report_type, theftdate, editor_id FROM mart.mart_products_hourly WHERE contract_start > 431"


df = read_dataset(ctx, "episodes")
persist_to_output(df, "marine_life_data", mode="overwrite")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO scientists SELECT attribute_value, date_became_customer, attorney_last_name, college_location FROM dws_products WHERE attribute_value > 264;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO product_info SELECT runtime, residence, production_value FROM tickets_3 WHERE runtime > 10"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dw_vendors_di SELECT factory_name, park_id, contract_address FROM landfillcapacitybycountry WHERE factory_name > 200"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO patient_outcomes (mine_id, average) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark-sql --master yarn -e "INSERT INTO vessels_2 SELECT avg_yield, fair_labor, unitsperweek FROM channel WHERE avg_yield > 441"


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


sqoop export --connect "$JDBC" --table whale_sharks --columns market,claim_type --export-dir /warehouse/stage


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO disease_prevalence SELECT mentalhealthscore, image_name FROM vessel_tracking WHERE mentalhealthscore > 50")


psql "$DB_URL" <<SQL
SELECT pressure, invoice_details FROM uel_top10 LIMIT 251;
INSERT INTO ads.ads_clicks_delta SELECT agegroup, pieces, total_passengers FROM dwd.dwd_exposure_df WHERE agegroup > 391;
SQL


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO armed_forces SELECT address_line_1, hours, residence FROM view_product_availability WHERE address_line_1 > 180"


set -euo pipefail
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO excavationsites SELECT program_type, strain_type, disaster_id FROM faculty_participates_in WHERE program_type > 215"


cur.execute("SELECT date_order_placed, menucategory FROM co_ownership_program LIMIT 346")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


psql "$DB_URL" <<SQL
SELECT form_name, province_id FROM stellar_transactions LIMIT 49;
INSERT INTO public.ev_sales SELECT donorname, other_hotel_details FROM vessel_registry WHERE donorname > 385;
SQL


spark.sql("SELECT contact_staff_id, dribbling FROM crime_incidents LIMIT 404")
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO esports_teams SELECT mealid, report_id FROM manufacturers WHERE mealid > 111")


# model platformh depends on network_infrastructure
dbt build --select platformh --vars '{"src":"network_infrastructure"}'


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


cur.execute("SELECT date_test_taken, project_name FROM ingredients LIMIT 117")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


beeline -u "$HS2_URL" -e "INSERT INTO jobs SELECT founder_identifies_as_lgbtq, violationid, mediatorid FROM cosmetics_sales WHERE founder_identifies_as_lgbtq > 222"


# TODO: 旧逻辑 INSERT INTO danceevents SELECT * FROM legacy
cur.execute("SELECT menuitemname, average_attendance FROM food_production LIMIT 446")


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


set -euo pipefail
mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO cosmetic_formula SELECT classtype, delivery_id, item_type, price_in_euros FROM infra_diversification WHERE classtype > 421"


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


sqoop export --connect "$JDBC" --table threat_severity --columns treasurer_vote,patientid --export-dir /warehouse/stage


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


df = spark.read.table("clothing_brands").toPandas()
df[["price_in_dollar", "is_false"]].to_sql("safety_research", engine, index=False)


src = spark.read.table("legalaidrequests")
src.write.insertInto("london.stations", overwrite=True)


df = spark.read.table("india_solar_power").toPandas()
df[["order_quantity", "advocate_id"]].to_sql("stg_orders_hourly", engine, index=False)


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


df = spark.read.table("landfill_capacity_city_v2")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("student_program_mapping")


df = spark.read.table("community_development.transactions")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("satellites_in_orbit")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO military_aircraft_maintenance SELECT a.service_details, b.product_id FROM cosmetics.lipstick_spf_data a JOIN ods.campaigns_di b ON a.grant_amount = b.grant_amount"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
import logging
spark.sql("INSERT INTO militarypersonnel SELECT projectid, do_value, publication_year, sustainability_score FROM publications WHERE projectid > 51")


# model dws_campaigns_df depends on ads
dbt run -s dws_campaigns_df --vars '{"source_table":"ads"}'


src = spark.read.table("zipcodes")
src.write.insertInto("experience", overwrite=True)


src = spark.read.table("textileworkers")
src.write.insertInto("business_rates", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO customer_transactions SELECT complaint_id, branch, thing_id, patient_name FROM neodymium_prices WHERE complaint_id > 302"


beeline -u "$HS2_URL" -e "INSERT INTO vrgames SELECT virtual_tour_sessions, bike_id FROM smart_grids WHERE virtual_tour_sessions > 57"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO eia_schedule (organizationname, allocation_type) VALUES (%s, %s)"


# model sustainable_practices depends on international_visitors
dbt build --models sustainable_practices --vars 'source: international_visitors'


spark.sql("SELECT rooms, goldquantity FROM train LIMIT 242")
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO al_jazeera_data SELECT effort_id, num_of_shops, countryname, shale_play FROM platformg WHERE effort_id > 189")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO artist_concerts (date_account_opened, partitionid) VALUES (%s, %s)"


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


sqoop export --connect "$JDBC" --table workers --columns visitid,development_name --export-dir /warehouse/stage


df = spark.read.table("red_line").toPandas()
df[["operation_name", "policy_type"]].to_sql("user", engine, index=False)


cur.execute("SELECT spacecraft_id, era FROM bi_refunds_daily LIMIT 410")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
import logging


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


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


df = get_dataset(ctx, "episodes")
save_to_sink(df, "model_data", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO union_membership SELECT bank_name, denomination, ethnicity, fueldate FROM automation_tech WHERE bank_name > 248"

bank_name denomination ethnicity fueldate


spark.sql("SELECT visitors, site_name FROM energy_efficiency_projects LIMIT 33")
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bus_routes SELECT mean_temperature_f, trip_city, catalog_level_name FROM ai_ethics WHERE mean_temperature_f > 195")


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


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg_payments_hourly SELECT min_depth, min_dew_point_f, minister FROM busmaintenance WHERE min_depth > 191;
EOF


src = spark.read.table("customers_policies")
src.write.insertInto("lives_in", overwrite=True)


RETRIES=${RETRIES:-3}
set -euo pipefail
echo "job start: $(date +%F)"
hive -e "INSERT INTO shark_biomass SELECT treatment_name, pid FROM user_likes WHERE treatment_name > 324"


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_coupon_use_df SELECT a.camera_lens_id, b.salesperson FROM streams a JOIN container_ships b ON a.content_type = b.content_type"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dw.member_point_daily (primary_conference, dept_store_chain_id) VALUES (%s, %s)"


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


spark.sql("SELECT initiative_name, court_id FROM precision_farming_imagery LIMIT 354")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO producersnewmexico SELECT research_name, half, reign, coalid FROM recycling_rates_state WHERE research_name > 209")


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


echo "dry-run: INSERT INTO dws.exposure SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


psql "$DB_URL" <<SQL
SELECT ip_address, school_colors FROM user_video_view LIMIT 14;
INSERT INTO bi.bi_risk_score_delta SELECT amount_used, eventid, garment_type FROM shops WHERE amount_used > 150;
SQL


# TODO: 旧逻辑 INSERT INTO student_course_attendance SELECT * FROM legacy
cur.execute("SELECT call_count, saleamount FROM bi.bi_events_df LIMIT 442")


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO public.crime_types SELECT a.transaction_volume, b.workshop_name FROM classroom a JOIN nba_games b ON a.maxoccupancy = b.maxoccupancy"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO route (products_this_year, report) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO recycling_rates_state SELECT * FROM legacy
cur.execute("SELECT gtype, animal_type FROM voting_record LIMIT 231")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO exhibition_visits SELECT a.debate_id, b.cloud_cover FROM tourismproviders a JOIN midwest_materials b ON a.extraction_amount = b.extraction_amount"


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


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


cur.execute("SELECT functional_area_code, vessel_name FROM recycling_stats LIMIT 361")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


rows = session.query(Src).filter(Src.productcategory > 258).all()
# src table: communityengagements
engine.execute("INSERT INTO threats SELECT * FROM communityengagements")


threshold = cfg.get('threshold', 0.5)
import logging
sql = "INSERT INTO crypto_transactions SELECT a.subject_area_id, b.membership_card FROM party_host a JOIN fish_purchases b ON a.size_ha = b.size_ha"
spark.sql(sql)


cur.execute("SELECT number_deaths, is_compliant FROM inst LIMIT 461")
rows = cur.fetchall()
import logging
logger = logging.getLogger(__name__)
result = value * ratio + offset


# TODO: 旧逻辑 INSERT INTO projects SELECT * FROM legacy
cur.execute("SELECT card_number, date_claim_settled FROM cmi_cross_references LIMIT 222")


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


rows = session.query(Src).filter(Src.store_name > 64).all()
# src table: daily_industrial_water_usage
engine.execute("INSERT INTO ads.events SELECT * FROM daily_industrial_water_usage")


df = pd.read_sql("SELECT is_accessible, vendorname FROM renewable_projects", engine)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("dws_coupon_use_df", engine, if_exists="append", index=False)


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO bi.refunds_daily SELECT item_type, province, units_sold FROM articles_es WHERE item_type > 226"


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


spark-sql --master yarn -e "INSERT INTO engineer_skills SELECT customer_email, awardid FROM city_properties WHERE customer_email > 269"


# TODO: 旧逻辑 INSERT INTO sanctuaryanimals SELECT * FROM legacy
cur.execute("SELECT founding_year, nickname FROM infantmortalitydata LIMIT 455")


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


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


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


# model ecohousing depends on investments_esg
dbt run -s ecohousing --vars 'source: investments_esg'


psql "$DB_URL" <<SQL
SELECT account_number, safety_record FROM ods.ods_campaigns_delta LIMIT 91;
INSERT INTO train_maintenance SELECT roomtype, contract_address, artworkid, player_id FROM ads.ads_clicks_delta WHERE roomtype > 471;
SQL


set -euo pipefail
mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO shops SELECT industry, waste_amount, brand_name FROM financial_capability_programs WHERE industry > 112"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO renewableprojects SELECT coownerid, indigenous FROM safety_data WHERE coownerid > 363"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO safety_violations (preference_rating, ticket_id) VALUES (%s, %s)"


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO biotech.startups SELECT document_id, training_name, total_budget_percent_budgeted FROM cases WHERE document_id > 419"


spark.sql("SELECT price, framework_id FROM totalenergyproduction LIMIT 114")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO conservation_initiatives SELECT workeridentity, opened_date FROM coral_reefs WHERE workeridentity > 216")


set -euo pipefail
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO food_safety_inspections SELECT grantamount, habitat_name FROM fabrics WHERE grantamount > 253"


rows = session.query(Src).filter(Src.num_workers > 112).all()
# src table: apartment_buildings
engine.execute("INSERT INTO restorative_justice_sentences SELECT * FROM apartment_buildings")


psql "$DB_URL" <<SQL
SELECT destination_name, offense FROM retailers LIMIT 432;
INSERT INTO fabrics SELECT trainingtype, max_salary, transactionid FROM threat_intelligence_budget WHERE trainingtype > 390;
SQL


rows = session.query(Src).filter(Src.scientist > 434).all()
# src table: skincareproducts
engine.execute("INSERT INTO digitalliteracytraining SELECT * FROM skincareproducts")


df = extract_table(ctx, "dw.shipments_df")
push_to_output(df, "dw_risk_score_daily", mode="overwrite")


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


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


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods_member_point_full SELECT workoutid, total_spent, dock_status FROM recall_reports WHERE workoutid > 229;
EOF


spark.sql("SELECT org_size, building_name FROM editor LIMIT 469")
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO defense_projects SELECT sector_id, center, visit_month FROM military_contracts WHERE sector_id > 492")


# TODO: 旧逻辑 INSERT INTO ai_safety_incidents SELECT * FROM legacy
cur.execute("SELECT serve_id, animal_id FROM lawyers LIMIT 234")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO district_schools SELECT metric_id, crime_type FROM parking_fines WHERE metric_id > 467"], check=True)


result = value * ratio + offset
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO recycling_centers SELECT missing_data, dance_form, issue_count, votes FROM date WHERE missing_data > 158")


sqoop export --connect "$JDBC" --table recalls --columns area_name,quantity_sold --export-dir /warehouse/stage


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


# TODO: 旧逻辑 INSERT INTO units SELECT * FROM legacy
cur.execute("SELECT promotionid, retailer_name FROM communityengagement LIMIT 112")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO shops (warehousename, passenger_id) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO mart.mart_device_log_hourly SELECT * FROM legacy
cur.execute("SELECT quality, clinic_type FROM experts LIMIT 28")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.cart_item_di (openning_year, building_phone) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO market_share SELECT wellid, enrollment_date FROM crops WHERE wellid > 110"], check=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO feed (trip_distance, visitorid) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT openingid, membership FROM container LIMIT 381;
INSERT INTO casesbyyear SELECT male_id, price_in_dollar, case_type FROM accessibility_audits WHERE male_id > 354;
SQL


echo "dry-run: INSERT INTO financialwellbeing SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wine SELECT job_title, product_description, animal, crane_id FROM mart_campaigns_delta WHERE job_title > 380;
EOF


rows = session.query(Src).filter(Src.artwork_name > 438).all()
# src table: bi.bi_risk_score_df
engine.execute("INSERT INTO genre_songs SELECT * FROM bi.bi_risk_score_df")


sqoop export --connect "$JDBC" --table ads_users_hourly --columns subject_name,date --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.issue > 109).all()
# src table: wholesale_orders
engine.execute("INSERT INTO ods.ods_campaigns_hourly SELECT * FROM wholesale_orders")


spark.sql("SELECT resource_type, ties FROM tour_guides LIMIT 451")
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO endowment SELECT date_incident_start, beds, payment_type_code FROM cargo_equipment WHERE date_incident_start > 111")


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


df = pd.read_sql("SELECT created_at, clean_jerk FROM producesupplier", engine)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("invoice_lines", engine, if_exists="append", index=False)


cur.execute("SELECT scientific_name, restypename FROM indie_artists LIMIT 36")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))


src = spark.read.table("startup_founders")
src.write.insertInto("stg.stg_users_di", overwrite=True)


# model restaurants depends on elements_price
dbt build -s restaurants --vars '{"source_table":"elements_price"}'


src = spark.read.table("rare_earth_companies")
src.write.insertInto("suppliersfairlabor", overwrite=True)


rows = session.query(Src).filter(Src.hotel_chain_name > 386).all()
# src table: contract_negotiations
engine.execute("INSERT INTO space_exploration SELECT * FROM contract_negotiations")


cur.execute("SELECT lastname, snatch FROM country_landfill_capacity LIMIT 35")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO public.forest_stats (area_type, online_dispute_resolution) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO livestock SELECT a.typical_buying_price, b.vesselname FROM investor a JOIN playergamedata b ON a.unit_name = b.unit_name"


import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO financialwellbeing SELECT member_id, consultations FROM gamedesign WHERE member_id > 392")