cur.execute("SELECT is_compliant, time_day FROM cloud_issues LIMIT 154")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


echo "dry-run: INSERT INTO textile_sourcing SELECT 1"
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai


# TODO: 旧逻辑 INSERT INTO customer_address_history SELECT * FROM legacy
cur.execute("SELECT consider_rate, mascot FROM singer LIMIT 5")


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


spark-sql --master yarn -e "INSERT INTO mentalhealthparityviolations SELECT caloric_content, channel_code FROM restaurant_revenue WHERE caloric_content > 436"


psql -h "$PGHOST" -U etl -c "INSERT INTO gamedesign SELECT a.sales_channel, b.clean_jerk FROM arctic_research a JOIN renewable_energy_investments b ON a.retailer_id = b.retailer_id"


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


df = spark.read.table("funding_records").toPandas()
df[["model_name", "topic"]].to_sql("user_ad_interactions", engine, index=False)


psql "$DB_URL" <<SQL
SELECT long, founding_year FROM circular_economy_companies LIMIT 274;
INSERT INTO public_transport.passenger_count SELECT away_team_three_point, dish_name FROM open_data_initiatives WHERE away_team_three_point > 310;
SQL


psql "$DB_URL" <<SQL
SELECT policy_type, workshop_name FROM dws.payments_delta LIMIT 183;
INSERT INTO public.developers SELECT customer_number, categoryid FROM product_characteristics WHERE customer_number > 300;
SQL


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


rows = session.query(Src).filter(Src.area_size > 490).all()
# src table: player_attributes
engine.execute("INSERT INTO battery_storage SELECT * FROM player_attributes")


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ods.campaigns_di SELECT available_yn, genrename FROM stg.cart_item_full WHERE available_yn > 155")


df = pd.read_sql("SELECT segment_id, role_name FROM chemicals_annual", engine)
metrics.append(round(score, 4))
import logging
result = value * ratio + offset
df.to_sql("wholesale_orders", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO marine_species_indian (session_language, trend) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark-sql --master yarn -e "INSERT INTO mart.mart_shipments_hourly SELECT tourist_details, ticket_price, expeditionid, phone_id FROM dwd.sessions WHERE tourist_details > 199"


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO hockey_players SELECT practiceid, category, high_temperature, race FROM mart.coupon_use_hourly WHERE practiceid > 120"

practiceid category high_temperature race


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


spark-sql --master yarn -e "INSERT INTO ods.sessions SELECT effective_date, spacecraft_id, org_name, reo_type FROM product_sales WHERE effective_date > 32"


rows = session.query(Src).filter(Src.project_name > 68).all()
# src table: union_members
engine.execute("INSERT INTO traffic SELECT * FROM union_members")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO areas SELECT rating_id, snatch FROM high_risk WHERE rating_id > 64"


spark-sql --master yarn -e "INSERT INTO platform_production SELECT contract_end, royal_family_id, chemical FROM communityengagements WHERE contract_end > 168"


df = get_table(ctx, "redundant_billing_data")
dump_to_target(df, "ods.ods_users_di", mode="overwrite")


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


sqoop export --connect "$JDBC" --table danceevents --columns rooms,genderid --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO waterusage SELECT mine_location, fuelid, player_id FROM user_workouts_march WHERE mine_location > 392"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dwd.sessions SELECT maintenance_id, wastetype FROM aquaticfarm WHERE maintenance_id > 220"], check=True)


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


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


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


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO climatefinance SELECT a.co2_reduction_tons, b.height_feet FROM community_engagement a JOIN tv_shows b ON a.technology = b.technology"
spark.sql(sql)


spark.sql("SELECT heritage_site_id, energytype FROM ref_budget_codes LIMIT 267")
import logging
spark.sql("INSERT INTO virtual_tourism SELECT unique_founders, bridgeid, launch_agency, max_wind_speed_mph FROM business_rates WHERE unique_founders > 429")


rows = session.query(Src).filter(Src.company > 266).all()
# src table: satellites
engine.execute("INSERT INTO functional_areas SELECT * FROM satellites")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO refugees SELECT skill_description, range FROM marine_conservation WHERE skill_description > 17;
EOF


psql "$DB_URL" <<SQL
SELECT attraction_type_description, artifact_name FROM worker_scores LIMIT 413;
INSERT INTO office_locations SELECT hoursperweek, amount_outstanding, wildlife_type_id, product_category FROM ods.ods_risk_score_full WHERE hoursperweek > 215;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mining_companies SELECT education_id, away_team_points, purchases FROM bike_stations WHERE education_id > 181"], check=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO bridges SELECT budget_type_code, vehicletype FROM constructionlaborstatistics WHERE budget_type_code > 45"


sqoop export --connect "$JDBC" --table concert_revenue --columns posts_per_day,fabrictype --export-dir /warehouse/stage


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


df = pd.read_sql("SELECT area_name, materialtype FROM shop", engine)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
df.to_sql("spacemissions", engine, if_exists="append", index=False)


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dysprosiumproduction SELECT city_name, co2_emission, farmid, countid FROM submarine_canyons WHERE city_name > 25;
EOF


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


src = spark.read.table("cultural_competency_program")
src.write.insertInto("rooms", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO permian_basin SELECT a.date_assigned_from, b.workoutdate FROM economic_diversification_efforts a JOIN habitat b ON a.camera_lens_id = b.camera_lens_id"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO excavation (heritage_site_id, building_name) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO infrastructurebudget SELECT coverage_type, contributionid FROM digital_divide_initiatives WHERE coverage_type > 444"


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


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO people_addresses (waste_amount, restorative_justice) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("project_issues").toPandas()
df[["projecttype", "gender_diversity"]].to_sql("platform", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO reviews SELECT attribute_name, name_first FROM machine WHERE attribute_name > 496"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd_coupon_use_hourly SELECT incident, customer_country FROM labor_cost WHERE incident > 189;
EOF


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
result = value * ratio + offset
sql = "INSERT INTO all_documents SELECT a.fault_log_entry_datetime, b.reo_type FROM stg.stg_coupon_use_di a JOIN locations_oceania b ON a.personnel = b.personnel"
spark.sql(sql)


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


beeline -u "$HS2_URL" -e "INSERT INTO county SELECT experience, retailer, satellite_name, complaintid FROM attorneylocationyear WHERE experience > 447"

experience retailer satellite_name complaintid


presto --server presto01:8080 --catalog hive --execute "INSERT INTO basketball_match SELECT productionid, ll_activity, time_of_purchase, resource_id FROM animal_population WHERE productionid > 432"


cur.execute("SELECT ad_id, start_station_id FROM production LIMIT 299")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO volunteer_registration SELECT feedback_id, gradepoint FROM visitor_exhibition WHERE feedback_id > 489;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO navalvessels SELECT date_assigned_to, first_year FROM construction_union WHERE date_assigned_to > 94"


cur.execute("SELECT framework_id, biomass FROM haircaresales LIMIT 240")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
import logging


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


src = spark.read.table("sustainability_fact")
src.write.insertInto("healthcare", overwrite=True)


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO tech_accessibility_funding SELECT practice, coalquantity, conferencename FROM heritagesites WHERE practice > 228"], check=True)


# TODO: 旧逻辑 INSERT INTO circular_economy_initiatives SELECT * FROM legacy
cur.execute("SELECT hometown, individual_first_name FROM unionnegotiations LIMIT 472")


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


sqoop export --connect "$JDBC" --table procedures --columns low_income_neighborhood,park_id --export-dir /warehouse/stage


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


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


# model problem_log depends on shariah_compliant_loans
dbt run --select problem_log --vars 'source: shariah_compliant_loans'


# TODO: 旧逻辑 INSERT INTO bi.clicks_hourly SELECT * FROM legacy
cur.execute("SELECT education_id, stayid FROM results LIMIT 106")


beeline -u "$HS2_URL" -e "INSERT INTO regions SELECT rebounds, quantity_containers, g_name FROM facility WHERE rebounds > 122"


# TODO: 旧逻辑 INSERT INTO habitat SELECT * FROM legacy
cur.execute("SELECT volunteerhourid, complaint_status_code FROM loan LIMIT 153")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO tencel_sources SELECT end_date, total_distance FROM inspection WHERE end_date > 293"


# TODO: 旧逻辑 INSERT INTO product_details SELECT * FROM legacy
cur.execute("SELECT num_sustainable_materials, campaign FROM collectivebargaining LIMIT 366")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO rebounds SELECT a.fiscal_year, b.start_station_id FROM support_programs a JOIN scores b ON a.seat_section = b.seat_section"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mart.mart_member_point_df SELECT birth_place, country1, condition_id FROM buildings WHERE birth_place > 438;
EOF


df = pd.read_sql("SELECT hardware_model_name, yearadded FROM sustainableproduction", engine)
metrics.append(round(score, 4))
df.to_sql("port", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO waterconservationbudget (founding_location, painting_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO space_missions_2 SELECT * FROM legacy
cur.execute("SELECT inventor_name, incident_type_code FROM freshwater_fish_farms LIMIT 185")


# model community_policing depends on districts_india
dbt run --models community_policing --vars '{"src":"districts_india"}'


beeline -u "$HS2_URL" -e "INSERT INTO excavation_sites SELECT cloud_cover, initiative_name, programid, partner_id FROM debris WHERE cloud_cover > 134"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO pacific_ocean SELECT bikes_available, pricepergram FROM mentalhealthparityscores WHERE bikes_available > 103"], check=True)


import logging
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO iron SELECT mgr_start_date, resource, fueldate FROM areas WHERE mgr_start_date > 379")


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


src = spark.read.table("clinics")
src.write.insertInto("infrastructure_projects", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO ref_shipping_agents SELECT a.number_of_platforms, b.disability_type FROM ads.ads_payments_delta a JOIN whale_sharks b ON a.date = b.date"


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


df = load_table(ctx, "fieldd_info")
save_to_warehouse(df, "dwd.dwd_products", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO public.forest_stats (rom_mib, amount) VALUES (%s, %s)"


src = spark.read.table("dancefunding")
src.write.insertInto("aus_wellbeing", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO pollutionincidents (crime_date, garment_material) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table stateinfrastructure --columns dst_apid,amount_claimed --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO financial_capability_programs (faculty, co_owner_count) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO visitordemographics SELECT a.total_spent, b.ll_activity FROM humanitarianmissions a JOIN languages b ON a.case_burden = b.case_burden"


psql "$DB_URL" <<SQL
SELECT ll_activity, testtype FROM product_categories LIMIT 124;
INSERT INTO music_streaming SELECT product_id, biz_date, orderdate, cruelty_free FROM innovation_projects WHERE product_id > 343;
SQL


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO research_vessels SELECT union_members, country, negotiation_date FROM defense_contractors WHERE union_members > 184")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO shared_ebikes SELECT location_code, initiativename FROM workersalaries WHERE location_code > 62;
EOF


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO renewable_power SELECT claim_type, ai_id FROM economic_diversification WHERE claim_type > 334"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO exhibition_visits SELECT emp_num, line_1_number_building FROM concerts WHERE emp_num > 270"], check=True)


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


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


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO virtual_visitors SELECT a.project_number, b.label_id FROM operations a JOIN yttrium_production b ON a.has_aloe_vera = b.has_aloe_vera"
spark.sql(sql)


df = spark.read.table("eu_data_usage")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("sustainable_urban_properties_2")


spark.sql("SELECT journal_id, hotel_chain_name FROM employees LIMIT 321")
metrics.append(round(score, 4))
spark.sql("INSERT INTO ads.risk_score SELECT ai_customer_service, item_type, high_temperature FROM student WHERE ai_customer_service > 65")


beeline -u "$HS2_URL" -e "INSERT INTO southeast_providers SELECT life_expectancy, emp_num, club_id, outcome_description FROM automation_tech WHERE life_expectancy > 280"


psql "$DB_URL" <<SQL
SELECT claim_status_name, shipmenttype FROM weights LIMIT 313;
INSERT INTO fund_investments SELECT visitid, connection FROM product_characteristics WHERE visitid > 145;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO atlantic_ocean_fish (participated_in_open_pedagogy, views) VALUES (%s, %s)"


cur.execute("SELECT innovation_id, trade FROM rural_resources LIMIT 244")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


rows = session.query(Src).filter(Src.heartrate > 153).all()
# src table: student_course_registrations
engine.execute("INSERT INTO cultural_events SELECT * FROM student_course_registrations")


df = source_dataset(ctx, "parties")
push_to_output(df, "agricultural_innovation_projects", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO recycling_centers SELECT customer, city_traffic_speed, orgid, contract_amount FROM project_issues WHERE customer > 28;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO agroecology_practices (site, round_number) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT product_type, donation_id FROM aquatic_species LIMIT 220")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


psql -h "$PGHOST" -U etl -c "INSERT INTO satellitedata SELECT a.engagementid, b.area_id FROM hospitals a JOIN artwork b ON a.contract_start = b.contract_start"


cur.execute("SELECT hiredate, vol_id FROM ads.ads_events_df LIMIT 21")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO survey_data SELECT festival_name, trial_year, compatible_since_year, primaryaffiliation FROM therapy WHERE festival_name > 77"


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


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


metrics.append(round(score, 4))
spark.sql("INSERT INTO contract_states SELECT complaint_id, address, people_id, employees FROM has_allergy WHERE complaint_id > 50")


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO editor SELECT baseprice, personnelid, served_subscribers, class FROM ocean WHERE baseprice > 128")

baseprice personnelid served_subscribers class


cur.execute("SELECT openning_year, ota_id FROM ads.ads_exposure_daily LIMIT 351")
rows = cur.fetchall()
metrics.append(round(score, 4))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO exhibition_record SELECT festival_id, num_workers, genreid FROM department_store_chain WHERE festival_id > 316;
EOF


spark.sql("SELECT port, cargo FROM whale_sharks LIMIT 71")
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO bi.member_point_full SELECT programname, call_date, donorid, funding_year FROM maintenance_contracts WHERE programname > 118")


cur.execute("SELECT level, ticket_price FROM nutrition_facts LIMIT 162")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ocean_acidity (num_libraries, movie) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO checking SELECT quarter, count_id, is_operational FROM danceevents WHERE quarter > 175"], check=True)


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


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


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


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


cur.execute("SELECT conferencename, address_content FROM apac_hotel_views LIMIT 466")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


trap 'echo failed' ERR
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO airport SELECT class, threats, founder_lgbtq FROM vaccine_administered WHERE class > 197"


df = pd.read_sql("SELECT financing_date, restaurantname FROM patient_outcomes", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("biosensors.projects", engine, if_exists="append", index=False)


logger = logging.getLogger(__name__)
sql = "INSERT INTO suppliersfairlabor SELECT a.cargo, b.total_value_purchased FROM dorm_amenity a JOIN tour_guides b ON a.category = b.category"
spark.sql(sql)


df = spark.read.table("medical_professionals").toPandas()
df[["country_code", "payment_type_code"]].to_sql("vessel_performance", engine, index=False)


cur.execute("SELECT creationyear, date_of_attendance FROM dwd.dwd_orders_daily LIMIT 438")
rows = cur.fetchall()
metrics.append(round(score, 4))


# model professor depends on customer_transactions
dbt run --select professor --vars '{"src":"customer_transactions"}'


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


set -euo pipefail
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO dws.payments_delta SELECT revenue, recruiterid, process_id, grantid FROM green_building_materials WHERE revenue > 485"


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO shark_biomass SELECT satellite_id, machine_series, operationname, room FROM instructor WHERE satellite_id > 286"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO investment_strategies SELECT staff_gender, request_date FROM ai_papers WHERE staff_gender > 74;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO infrastructureprojects SELECT end_speed, customer_number, city_town FROM vessel_positions WHERE end_speed > 33"


df = source_dataset(ctx, "habitat")
upsert_to_output(df, "safetyincidents", mode="overwrite")


df = source_input(ctx, "public.police_calls")
sink_to_output(df, "spacecraft_manufacturers", mode="overwrite")


cur.execute("SELECT publication_date, moisture FROM menu_vendors LIMIT 316")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_products_full SELECT bicycle_id, total_shipped FROM concerts WHERE bicycle_id > 44"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO visualartprograms (trial_year, institution_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO dws.dws_member_point_df SELECT strategy, shippeddate, sale_date FROM states WHERE strategy > 167"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.shipments_daily (faculty_id, starting_year) VALUES (%s, %s)", (uid, amt))
conn.commit()


import logging
sql = "INSERT INTO grapes SELECT a.royal_family_details, b.director FROM bridges a JOIN stg.stg_shipments_hourly b ON a.assessment_date = b.assessment_date"
spark.sql(sql)


src = spark.read.table("mart_refunds_delta")
src.write.insertInto("bi.bi_orders_daily", overwrite=True)


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


df = pd.read_sql("SELECT department_id, denomination FROM infantmortalitydata", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("strategies", engine, if_exists="append", index=False)


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


set -euo pipefail
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO budgets SELECT lastname, decoration_theme FROM fashion_trend_data WHERE lastname > 213"


cur.execute("SELECT aid_name, quantitysold FROM storage LIMIT 147")
rows = cur.fetchall()
metrics.append(round(score, 4))


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


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


df = pull_source(ctx, "dwd.dwd_risk_score_delta")
dump_to_store(df, "bi_inventory_hourly", mode="overwrite")


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


df = pull_frame(ctx, "ads_exposure_hourly")
sink_to_sink(df, "spacecraftspeed", mode="overwrite")


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


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


# model circular_economy_companies depends on hospital_visits
dbt run --models circular_economy_companies --vars '{"src":"hospital_visits"}'


mkdir -p /tmp/joblog
hive -e "INSERT INTO block SELECT decor, shares FROM donorprograms WHERE decor > 113"


psql "$DB_URL" <<SQL
SELECT kills, problem_log_id FROM port_office LIMIT 303;
INSERT INTO track SELECT actid, machinery_id FROM organisations WHERE actid > 390;
SQL


spark-sql --master yarn -e "INSERT INTO hotel_business_partnerships SELECT time_hour, lesson_status_code, field_id, business_name FROM threatintelligence WHERE time_hour > 454"


# TODO: 旧逻辑 INSERT INTO equipment_maintenance SELECT * FROM legacy
cur.execute("SELECT sales_in_billion, typical_selling_price FROM government.region LIMIT 161")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.events SELECT sales_channel, animal FROM functional_areas WHERE sales_channel > 147"], check=True)


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


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO tracklists SELECT a.attendance_id, b.founded_year FROM grapes a JOIN mart.clicks b ON a.affiliation = b.affiliation"
spark.sql(sql)


trap 'echo failed' ERR
hive -e "INSERT INTO ethics_violations SELECT issued_date, isfirstattendee, deliveryaddress FROM dwd.campaigns WHERE issued_date > 105"


df = spark.read.table("team_revenue").toPandas()
df[["industry", "access_count"]].to_sql("org_volunteer", engine, index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO ods.ods_member_point_delta SELECT fuelid, arrival_date FROM fish_stock WHERE fuelid > 364"


df = read_table(ctx, "hotel_chains")
persist_to_output(df, "industrial_building_energy_efficiency", mode="overwrite")


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


if not rows:
    logger.warning('empty result')
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO co2_emission SELECT billing, browser_id FROM algorithmic_fairness_incidents_monthly WHERE billing > 228")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO government.region SELECT total_attendance, role_name, agency, coach_name FROM excavation WHERE total_attendance > 399;
EOF


retries = int(os.environ.get('RETRIES', '3'))
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))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO eco_hotels (budget_type_description, speed) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO artifact_analysis SELECT incident_description, athlete_id, preferred_foot FROM engineer_skills WHERE incident_description > 204;
EOF


psql "$DB_URL" <<SQL
SELECT name_last, taskid FROM singer_in_concert LIMIT 260;
INSERT INTO teaches SELECT analysis_date, events, clientid FROM player WHERE analysis_date > 475;
SQL


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


rows = session.query(Src).filter(Src.open_year > 19).all()
# src table: dws.dws_risk_score_daily
engine.execute("INSERT INTO research_vessels SELECT * FROM dws.dws_risk_score_daily")


spark.sql("SELECT virtual_tour_views, date_closed FROM ods.clicks_delta LIMIT 127")
result = value * ratio + offset
spark.sql("INSERT INTO leo_missions SELECT royal_family_id, province, spacecraft_id FROM bioprocess_engineering WHERE royal_family_id > 395")


spark-sql --master yarn -e "INSERT INTO platformh SELECT facid, address_type_code, policyholderid, carrierid FROM winter_olympics WHERE facid > 105"

facid address_type_code policyholderid carrierid


result = value * ratio + offset
spark.sql("INSERT INTO tasks SELECT vr_platform, currency, sales_amount, size_ha FROM fairness_scores WHERE vr_platform > 319")


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


# model infrastructureprojects depends on stats
dbt run -s infrastructureprojects --vars '{"src":"stats"}'


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


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


# TODO: 旧逻辑 INSERT INTO customer_contact_channels SELECT * FROM legacy
cur.execute("SELECT education_id, contract_end FROM singer LIMIT 267")


df = spark.read.table("light_rail_lines").toPandas()
df[["clientid", "advisoryid"]].to_sql("plots", engine, index=False)


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


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


# TODO: 旧逻辑 INSERT INTO military_sales SELECT * FROM legacy
cur.execute("SELECT bathroom_count, effort_id FROM vessel_incident_count LIMIT 337")


sqoop export --connect "$JDBC" --table donors_region --columns gname,neighborhood_id --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table labels --columns booking_status_code,last_workout_date --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO news_reporting SELECT cuisine_id, participant_type_code, event_type FROM city_labor_cost WHERE cuisine_id > 136"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO historicalcontexts SELECT a.deliveryid, b.inventor_name FROM circular_economy_companies a JOIN drug_sales b ON a.citizens = b.citizens"


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO disaster_response SELECT a.destroyed_by_employee_id, b.jul FROM digital_trends a JOIN garments b ON a.maintenance_contract_company_id = b.maintenance_contract_company_id"
spark.sql(sql)


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


src = spark.read.table("eco_hotels")
src.write.insertInto("tree_habitat_associations", overwrite=True)


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


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


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO savings_programs SELECT a.person_id, b.member_id FROM factory_connections a JOIN marketing_budgets b ON a.disability = b.disability"
spark.sql(sql)


# model artist_data depends on ads.ads_inventory_df
dbt run --select artist_data --vars '{"src":"ads.ads_inventory_df"}'


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


df = pd.read_sql("SELECT total_cost, activity FROM apartments", engine)
result = value * ratio + offset
import logging
if not rows:
    logger.warning('empty result')
df.to_sql("fish_feed_factories", engine, if_exists="append", index=False)


df = read_frame(ctx, "ngo_funding")
sink_to_target(df, "counties", mode="overwrite")


src = spark.read.table("documents")
src.write.insertInto("waste_data", overwrite=True)


rows = session.query(Src).filter(Src.catalog_level_name > 463).all()
# src table: vocals
engine.execute("INSERT INTO providers SELECT * FROM vocals")


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


df = spark.read.table("labor_cost").toPandas()
df[["kills", "supplier_company_id"]].to_sql("heritagesites", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO therapy_session SELECT a.ingredient, b.image_name FROM exhibition_visits a JOIN pollution_control_initiatives b ON a.unit_of_measure = b.unit_of_measure"


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


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO waterusage SELECT open_year, recipient FROM satellites_by_country WHERE open_year > 86")


df = pd.read_sql("SELECT port_code, dockingdate FROM stg.risk_score_di", engine)
import logging
df.to_sql("esa_missions", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table southeast_providers --columns artifacttype,chemical_type --export-dir /warehouse/stage


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


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


spark.sql("SELECT launch_company, device_id FROM product_ingredient LIMIT 115")
threshold = cfg.get('threshold', 0.5)
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO government.region SELECT fname, line_name, fuelconsumed FROM ads.users_full WHERE fname > 133")


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


beeline -u "$HS2_URL" -e "INSERT INTO teachers SELECT supply_volume, case_outcome FROM mart_refunds WHERE supply_volume > 467"


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


psql "$DB_URL" <<SQL
SELECT interest_group, sustainability_score FROM ocean_temperatures LIMIT 357;
INSERT INTO budget_allocations SELECT custid, review_date FROM athletes WHERE custid > 25;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO branch (area_size, volunteerhourid) VALUES (%s, %s)"


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


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


beeline -u "$HS2_URL" -e "INSERT INTO clothingsales SELECT studio_name, service_type_description FROM runs WHERE studio_name > 76"


df = source_source(ctx, "stg.campaigns_df")
persist_to_sink(df, "mart.mart_refunds_hourly", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO product_catalog SELECT offset_id, treatment_date FROM shariah_compliant_products WHERE offset_id > 421"


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


result = value * ratio + offset
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO building_permits SELECT a.enr, b.date_of_birth FROM dw.shipments_df a JOIN recalls b ON a.water_temp = b.water_temp"
spark.sql(sql)


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


psql "$DB_URL" <<SQL
SELECT exploited, inclusivehousing FROM wastewater_plants LIMIT 91;
INSERT INTO diversity SELECT club_name, fleet_name, mission_name, half FROM school_bus WHERE club_name > 6;
SQL


cur.execute("SELECT famous_title, school_id FROM seal_population LIMIT 130")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


src = spark.read.table("satellites_by_country")
src.write.insertInto("education_union", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO rainfall_data SELECT occupancy_rate, health_equity_metric_1, founder FROM climate_monitoring_stations WHERE occupancy_rate > 14"


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


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


retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO stops SELECT reviewscore, hardware_colours FROM customer WHERE reviewscore > 39")


psql "$DB_URL" <<SQL
SELECT borough, manufacturer_id FROM militarydrones LIMIT 169;
INSERT INTO rural_infrastructure SELECT working_horses, total_employees, cinema_id, country_name FROM habitat3 WHERE working_horses > 224;
SQL


df = spark.read.table("indie_artists").toPandas()
df[["issue", "platformname"]].to_sql("request", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO consumer SELECT official_native_language, profits_in_billion FROM well_production WHERE official_native_language > 57"


import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO size SELECT a.installation_year, b.promotiondate FROM humanitarianassistanceoperations a JOIN agricultural_innovation b ON a.date_account_opened = b.date_account_opened"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO station_emergencies SELECT school_id, cropname FROM dws.dws_orders_full WHERE school_id > 404"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO labor_productivity (mental_health_status, fleet_series) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table atlantic_ocean --columns attraction_id,bikes_available --export-dir /warehouse/stage


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO blockchain_tech (explainability_score, evaluated_for_fairness) VALUES (%s, %s)"


src = spark.read.table("carbon_offset_south_america")
src.write.insertInto("team_members", overwrite=True)


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


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


spark-sql --master yarn -e "INSERT INTO stg.stg_users SELECT claim_stage_id, constructorid, agegroup, exit_strategy FROM co2_emissions WHERE claim_stage_id > 385"


psql "$DB_URL" <<SQL
SELECT violation_type, sales_id FROM coal LIMIT 304;
INSERT INTO traffic SELECT countryid, extraction_state, studio FROM gender WHERE countryid > 415;
SQL


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO laptimes SELECT sector_id, producerid FROM accounts WHERE sector_id > 66"


sqoop export --connect "$JDBC" --table orgdonations --columns assets_billion,instrument --export-dir /warehouse/stage


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


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


src = spark.read.table("enrollments")
src.write.insertInto("shipment", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO videos SELECT gender_group, maintenance_contract_company_id, issues FROM agri_innov WHERE gender_group > 17"


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


df = pd.read_sql("SELECT artistid, hispanic FROM threat_intel", engine)
metrics.append(round(score, 4))
df.to_sql("industrial_building_energy_efficiency", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT matchdate, issue_count FROM station_crime_rates LIMIT 486;
INSERT INTO labor_hours SELECT tx_id, num_volunteers FROM bi.bi_vendors_di WHERE tx_id > 62;
SQL


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


# TODO: 旧逻辑 INSERT INTO passenger_trips SELECT * FROM legacy
cur.execute("SELECT issue_count, publish_date FROM veteran_stats LIMIT 174")


cur.execute("SELECT advisor, detention_type_description FROM review LIMIT 41")
rows = cur.fetchall()
result = value * ratio + offset


df = pd.read_sql("SELECT id, facility_name FROM crops", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("community_centers", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT country, mine_name FROM volunteer_events", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("conservation", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO exhibition_artworks SELECT class_section, floor_area_m2 FROM chemical_production_5 WHERE class_section > 154"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO gold SELECT president_vote, lanes FROM india_ingredient_sourcing WHERE president_vote > 414")


spark-sql --master yarn -e "INSERT INTO drug_approvals SELECT production_value, theatrename FROM company_info WHERE production_value > 291"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO user_ad_interactions SELECT college, contact_staff_id, invoicedate, usage FROM urban_transportation WHERE college > 454"], check=True)

college contact_staff_id invoicedate usage


import logging
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO locations_oceania SELECT problem_id, species_name, volunteerdate FROM us_military_personnel WHERE problem_id > 31")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO members SELECT invested, sector_id FROM drug_approvals WHERE invested > 234"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.campaigns_di SELECT is_cruelty_free, biomass, mh_id, household_size FROM city_waste_generation WHERE is_cruelty_free > 37"


psql "$DB_URL" <<SQL
SELECT patient, total_cost FROM museums LIMIT 442;
INSERT INTO ref_calendar SELECT opened_date, contractor_name, inspection_id, employeeid FROM campaigns WHERE opened_date > 314;
SQL


spark.sql("SELECT staff_name, length_meters FROM influencers LIMIT 102")
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO third_party_companies SELECT schedule_date, stream_date, component_name FROM student_course_registrations WHERE schedule_date > 289")


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


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


# TODO: 旧逻辑 INSERT INTO artpieces SELECT * FROM legacy
cur.execute("SELECT lesson_time, routeid FROM brandrevenue LIMIT 493")


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


spark-sql --master yarn -e "INSERT INTO collective_bargaining SELECT enddate, cid FROM tours WHERE enddate > 375"


psql "$DB_URL" <<SQL
SELECT virtual_tour_views, policy_count FROM student_course_attendance LIMIT 495;
INSERT INTO performance_scores SELECT garment_material, contract_amount, satelliteid, spill_name FROM date WHERE garment_material > 180;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO constructors SELECT school_type, tree_type_id, department, union_id FROM workforce_development WHERE school_type > 120"], check=True)


spark.sql("SELECT status_code, ei_value FROM feed LIMIT 173")
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO election SELECT pilot_id, habitat_name FROM candidates WHERE pilot_id > 353")


df = pd.read_sql("SELECT affirmative, amenid FROM community.donations", engine)
result = value * ratio + offset
import logging
df.to_sql("bus_fare_collection", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO deep_sea_expeditions (brand_mentioned, num_stops) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO all_programs SELECT subscribe_date, menuitemname, initiative_region, game_count FROM film WHERE subscribe_date > 223"


df = pd.read_sql("SELECT engagement_count, production_mwh FROM ads.ads_events_df", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("fuel_consumption", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO researchers (grant_name, founding_date) VALUES (%s, %s)"


df = spark.read.table("excavation").toPandas()
df[["team_id_winner", "age_group"]].to_sql("ads.ads_exposure_daily", engine, index=False)


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO stg.refunds_daily SELECT accommodation_type, incident_description, productname FROM securityincidents WHERE accommodation_type > 300"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO gymc_members (date_closed, workforce_development) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO coal (product_category_code, engineer_id) VALUES (%s, %s)"


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


# TODO: 旧逻辑 INSERT INTO green_certification SELECT * FROM legacy
cur.execute("SELECT fueldate, bandmateid FROM request LIMIT 336")


metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO fabricinventory SELECT site_name, people_id, judge_state FROM route WHERE site_name > 244")


df = get_frame(ctx, "sites_me")
save_to_output(df, "open_data_initiatives", mode="overwrite")


rows = session.query(Src).filter(Src.truck_details > 59).all()
# src table: open_data_initiatives
engine.execute("INSERT INTO eco_hotels SELECT * FROM open_data_initiatives")


spark-sql --master yarn -e "INSERT INTO trainingprograms SELECT labordate, centerid, meal_date, billing FROM film_category WHERE labordate > 20"


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


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


cur.execute("SELECT code, installed_date FROM mentalhealthscores LIMIT 201")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))


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


beeline -u "$HS2_URL" -e "INSERT INTO scan_dates SELECT total_beds, student_details, publish_date FROM assessment_notes WHERE total_beds > 216"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO labour_productivity (market_value_billion, client) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO defenseprojects SELECT volume, communityname, support_rate FROM stg.coupon_use_delta WHERE volume > 394"


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))


spark-sql --master yarn -e "INSERT INTO state_budget SELECT building_type, requestid, status FROM dws.dws_refunds_daily WHERE building_type > 158"


logger = logging.getLogger(__name__)
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO voyages SELECT subject_id, singer_id FROM africa_schema.african_mines WHERE subject_id > 425")


src = spark.read.table("dws.dws_cart_item_daily")
src.write.insertInto("impact_investments", overwrite=True)


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


df = load_input(ctx, "farm_competition")
persist_to_store(df, "gamedata", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO section SELECT * FROM legacy
cur.execute("SELECT s_id, maintenancedate FROM district_schools LIMIT 486")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO budget_allocations SELECT professionalid, points FROM legal_technology_funding WHERE professionalid > 420;
EOF


import logging
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO therapy SELECT share_in_percent, target_id, trial_name, insurancetype FROM invoices WHERE share_in_percent > 265")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.cart_item_full SELECT airport_id, patientid, nurse FROM inspection WHERE airport_id > 404;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mineral_extraction_us SELECT artwork_id, operation_name FROM crops_year WHERE artwork_id > 448"], check=True)


sqoop export --connect "$JDBC" --table doctors --columns address_content,artworkyear --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO rural_projects SELECT industry_4_0, trader_id, zip, mine_location FROM renewableprojects WHERE industry_4_0 > 288"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws.dws_shipments_full SELECT species_name, prod_id, missionid, funding_amount FROM department_publications WHERE species_name > 454;
EOF


src = spark.read.table("artifactanalysis")
src.write.insertInto("unions", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO hotel_business_partnerships SELECT astronaut, reader_id, partner_id, segment_id FROM orders WHERE astronaut > 185;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO mentalhealthproviders SELECT a.astronaut_name, b.prominence FROM climate_finance_re a JOIN fieldd_info b ON a.transit_passengers = b.transit_passengers"


psql -h "$PGHOST" -U etl -c "INSERT INTO marine_species SELECT a.loan_amount, b.grant_date FROM tunnels a JOIN diversification_projects b ON a.word_count = b.word_count"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO materials SELECT vendor_name, maintenance_date, safety_id, name_last FROM artist_info WHERE vendor_name > 412;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO inventory SELECT share_count, vote_percent, result, precip FROM appointment WHERE share_count > 78"], check=True)


cur.execute("SELECT industry_4_0, organic_matter FROM wind_energy LIMIT 294")
rows = cur.fetchall()
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


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


beeline -u "$HS2_URL" -e "INSERT INTO feed SELECT date_joined_staff, yield_id, visitor_country, state FROM heritage_sites WHERE date_joined_staff > 104"


spark-sql --master yarn -e "INSERT INTO healthcareaccess SELECT sale_country, porphyria, treatment_name, initiativeid FROM salinity_readings WHERE sale_country > 273"


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


df = fetch_dataset(ctx, "product_ingredient")
upsert_to_warehouse(df, "voting_data", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO rural_hospitals SELECT * FROM legacy
cur.execute("SELECT black, handling_date FROM video_content LIMIT 486")


df = spark.read.table("imagery_archive").toPandas()
df[["menu_type", "fuelconsumed"]].to_sql("trade_history", engine, index=False)


rows = session.query(Src).filter(Src.spacecraft_model > 498).all()
# src table: fabrics
engine.execute("INSERT INTO bi.bi_orders_delta SELECT * FROM fabrics")


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


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO sports_events SELECT calendar_date, followers, donor_name FROM mart_payments_df WHERE calendar_date > 437")


set -euo pipefail
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO brandrevenue SELECT strain_name, loadingstart FROM ods.ods_coupon_use_delta WHERE strain_name > 83"


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads_exposure_hourly SELECT booking_date, publication_year, employee_id, completion_status FROM producersnewmexico WHERE booking_date > 80"


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


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO bi.bi_inventory_delta SELECT product_price, awardid FROM maintenancerequests WHERE product_price > 112")


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


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


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


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO circular_economy_initiatives SELECT fish_id, round_type FROM asteroids WHERE fish_id > 362")


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO excavation_sites SELECT fund_name, dec, price_per_gram FROM drama_workshop_groups WHERE fund_name > 58"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cargos SELECT petid, median_home_value FROM educationprograms WHERE petid > 339"


beeline -u "$HS2_URL" -e "INSERT INTO labor_practices SELECT exoplanet, paritystatus, rig_name, port_name FROM stateinfrastructure WHERE exoplanet > 126"


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO vessel_registry SELECT quantity, class, project FROM exhibition_artworks WHERE quantity > 197")


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


rows = session.query(Src).filter(Src.reader_id > 474).all()
# src table: route_fares
engine.execute("INSERT INTO mineral_extraction SELECT * FROM route_fares")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO educationprograms SELECT a.job, b.region FROM guests a JOIN co2_emission b ON a.number_thousands = b.number_thousands"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO space_debris SELECT award, community, typeid FROM dorm WHERE award > 448"], check=True)


import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO animal_budget SELECT a.individual_id, b.recipient_id FROM communityengagements a JOIN smartcitycosts b ON a.engagement = b.engagement"
spark.sql(sql)


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


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


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


src = spark.read.table("pediatricians")
src.write.insertInto("mining.company", overwrite=True)


df = spark.read.table("features").toPandas()
df[["complete_date", "worker_id"]].to_sql("traffic", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO job_postings SELECT claim_type, enable_third_party_ads FROM well_production WHERE claim_type > 409"


cur.execute("SELECT phone, socialimpactscore FROM festivals LIMIT 203")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


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


spark.sql("SELECT tourist_details, chemical_type FROM feedback LIMIT 28")
result = value * ratio + offset
spark.sql("INSERT INTO crop_yield SELECT albumname, aid_name, years_working, participation_id FROM conservation WHERE albumname > 172")


spark.sql("SELECT stu_dob, district_name FROM species_observations LIMIT 214")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO battery_projects SELECT num_courses, ai_adoption, staff_gender, dockingid FROM casesbyyear WHERE num_courses > 114")


# TODO: 旧逻辑 INSERT INTO colorado_river_basin SELECT * FROM legacy
cur.execute("SELECT contract_value, entrydate FROM bias_categories LIMIT 453")


result = value * ratio + offset
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO community_development_projects SELECT credits, status_of_thing_code, access_count, billing_state FROM ads.refunds WHERE credits > 367")


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO portfolios (mountain_id, served_subscribers) VALUES (%s, %s)"


set -euo pipefail
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO research_grants SELECT birth_date, player_id, campusfee FROM timber_production WHERE birth_date > 25"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO school SELECT pricepergram, threat, vaccinations, grant_amount FROM equipment_sales WHERE pricepergram > 400"

pricepergram threat vaccinations grant_amount


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.events (farm_id, rental_rate) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("ods_sessions").toPandas()
df[["team_id", "supplychainid"]].to_sql("virtual_tours", engine, index=False)


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


spark.sql("SELECT practice, headquarters FROM customer_address_history LIMIT 104")
metrics.append(round(score, 4))
spark.sql("INSERT INTO mart.campaigns_full SELECT staff_last_name, is_autonomous FROM tourism_activities WHERE staff_last_name > 83")


beeline -u "$HS2_URL" -e "INSERT INTO ucl_top10 SELECT all_home, state, visit_year FROM onlineengagement WHERE all_home > 47"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO courses SELECT living_wage, centerid, num_stops, mealname FROM fish_stock WHERE living_wage > 372"], check=True)


df = fetch_source(ctx, "shipments")
write_to_target(df, "equipment", mode="overwrite")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart_cart_item_di (recipe_id, floor_exercise_points) VALUES (%s, %s)", (uid, amt))
conn.commit()


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO dwd.dwd_campaigns SELECT market_value_in_billion, round_amount, recordid, menu_item_id FROM ca_menu_items WHERE market_value_in_billion > 404")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO plots SELECT activity_type, client_first_name FROM campaigns_2023 WHERE activity_type > 190;
EOF


df = pd.read_sql("SELECT booked_amount, oct FROM material", engine)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
import logging
df.to_sql("tree_species", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO campuses SELECT socially_responsible, program_type, aircraft FROM dw_payments WHERE socially_responsible > 246"


df = load_frame(ctx, "farm_competition")
upsert_to_output(df, "esportsteamsafrica", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO socially_responsible_loans SELECT a.main_industry, b.supplychainid FROM branch a JOIN mart.mart_refunds_di b ON a.promotiondate = b.promotiondate"
spark.sql(sql)


mkdir -p /tmp/joblog
hive -e "INSERT INTO ods.sessions SELECT initiative, committee, president_vote FROM ocean_depths WHERE initiative > 224"


src = spark.read.table("habitat3")
src.write.insertInto("waste_production", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO suburbs SELECT a.role, b.industry FROM ads.refunds_delta a JOIN assignedto b ON a.building_id = b.building_id"


psql -h "$PGHOST" -U etl -c "INSERT INTO device SELECT a.provider_parity_score, b.primary_conference FROM mentalhealthparityviolations a JOIN restorative_justice_programs b ON a.element = b.element"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO participation (reo_type, loadingstart) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model faculty depends on contract_timeline
dbt build --select faculty --vars '{"src":"contract_timeline"}'


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


df = pd.read_sql("SELECT change_date, person_name FROM strategies", engine)
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("wholesale_orders", engine, if_exists="append", index=False)


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO solar_farms SELECT player, machine, num_solo_exhibitions, num_shariah_compliant_investments FROM category_revenue WHERE player > 264"


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


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO restorative_justice_sentences SELECT unionid, shippeddate FROM militaryoperations WHERE unionid > 139"


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


msg = "would run: INSERT INTO chemical_production_5 SELECT 1"
logger.info(msg)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


psql -h "$PGHOST" -U etl -c "INSERT INTO environmental_impact_stats SELECT a.line_id, b.event_name FROM ocean_pollution a JOIN org_climate_finance b ON a.kills = b.kills"


src = spark.read.table("city_properties")
src.write.insertInto("list", overwrite=True)


df = read_input(ctx, "legalaidrequests")
write_to_target(df, "student_course_registrations", mode="overwrite")


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


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


sqoop export --connect "$JDBC" --table farms --columns tree_species,number_of_platforms --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.site_name > 423).all()
# src table: ai_systems
engine.execute("INSERT INTO staff_members SELECT * FROM ai_systems")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO rainfall_data (strain_type, has_parabens) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO cargo_handling SELECT driver_id, fine_amount FROM counties WHERE driver_id > 276")


psql -h "$PGHOST" -U etl -c "INSERT INTO culturalpractices SELECT a.investmentid, b.crispr_id FROM concert_sales a JOIN material b ON a.accelerator_id = b.accelerator_id"


psql -h "$PGHOST" -U etl -c "INSERT INTO ref_product_categories SELECT a.neighborhoodid, b.case_id FROM inspection a JOIN appellations b ON a.festival_id = b.festival_id"


RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO location SELECT treatment_id, prod_id FROM factories_africa WHERE treatment_id > 22"


spark.sql("SELECT sustainability_certified, expeditionid FROM bi.bi_sessions_daily LIMIT 94")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO eventattendance SELECT start_time, grant_amount, characteristic_data_type FROM bi.bi_campaigns_delta WHERE start_time > 175")


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


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


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


# model trains depends on class
dbt run -s trains --vars '{"src":"class"}'


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vessel_incident_count SELECT founder_gender, news_outlet FROM customer_master_index WHERE founder_gender > 9"


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


df = fetch_input(ctx, "stg.stg_coupon_use_di")
upsert_to_target(df, "ads.ads_exposure_di", mode="overwrite")


df = spark.read.table("climber").toPandas()
df[["sqft", "heartrate"]].to_sql("wind_farms", engine, index=False)


df = spark.read.table("healthcareaccess").toPandas()
df[["testtype", "company_name"]].to_sql("artists_valuation", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO government.city (grant_end_date, ai_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO cerium_production SELECT transactionid, minename, is_hybrid, plant_id FROM recycling_centers WHERE transactionid > 94"


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO book SELECT grantid, founded, last_name FROM labor_statistics WHERE grantid > 190"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.coupon_use_daily (round_type, offender_name) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO explainableai SELECT financing_date, game_genre FROM paper_data WHERE financing_date > 386"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO average SELECT catalog_level_name, partner, service_type_description FROM recycled_polyester WHERE catalog_level_name > 217"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO volunteer_hours SELECT evaluated_for_fairness, production_value, productionrate FROM stock WHERE evaluated_for_fairness > 367"], check=True)


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


src = spark.read.table("basketball_teams")
src.write.insertInto("urban_farms", overwrite=True)


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


cur.execute("SELECT postal_code, news_story_id FROM flight_emissions LIMIT 190")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


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


rows = session.query(Src).filter(Src.program_date > 377).all()
# src table: has_allergy
engine.execute("INSERT INTO ratings SELECT * FROM has_allergy")


import logging
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO episodes SELECT digital, treatment_date FROM player_f WHERE digital > 458")


src = spark.read.table("factory_workers")
src.write.insertInto("awards", overwrite=True)


spark-sql --master yarn -e "INSERT INTO digital_trends SELECT event_type, debate_id FROM stg.stg_users_di WHERE event_type > 119"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO item (applicant, committee) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO hotel_tech_adoptions SELECT year_join, next_entry_id FROM dws_coupon_use WHERE year_join > 71"


df = get_frame(ctx, "disasters")
sink_to_warehouse(df, "list", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO league SELECT * FROM legacy
cur.execute("SELECT factory, dish_type FROM industry_funding LIMIT 121")


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


psql "$DB_URL" <<SQL
SELECT sustainable, onscholarship FROM stg.events_hourly LIMIT 193;
INSERT INTO projects SELECT session_id, order_details, products_this_year FROM user WHERE session_id > 196;
SQL


# TODO: 旧逻辑 INSERT INTO intelligence_agents SELECT * FROM legacy
cur.execute("SELECT safety_record, individual_last_name FROM bi.bi_events_df LIMIT 84")


df = pd.read_sql("SELECT worker, hosts FROM shariah_financing", engine)
metrics.append(round(score, 4))
df.to_sql("countries", engine, if_exists="append", index=False)


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO healthcare SELECT studentid, instructor_id, range FROM useracct WHERE studentid > 111"


psql "$DB_URL" <<SQL
SELECT project, src_apid FROM tracklists LIMIT 64;
INSERT INTO pilot_record SELECT closuredate, destroyed_by_employee_id, defendant_id, accommodationtype FROM eu_data_usage WHERE closuredate > 80;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ca_menu_items SELECT labor_practice, traveler_id, workers FROM bi.bi_inventory_delta WHERE labor_practice > 166"


# TODO: 旧逻辑 INSERT INTO open_pedagogy_courses SELECT * FROM legacy
cur.execute("SELECT planned_delivery_date, salinity FROM canada_tech LIMIT 478")


metrics.append(round(score, 4))
spark.sql("INSERT INTO customersregion SELECT donorgender, restaurant_id, farm_name FROM animal_populations WHERE donorgender > 116")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.risk_score_df SELECT facility_code, posts_per_day, height FROM gardens WHERE facility_code > 106"


# TODO: 旧逻辑 INSERT INTO advisor SELECT * FROM legacy
cur.execute("SELECT price_in_dollars, college_location FROM artist_concerts LIMIT 377")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO militarypersonnel (inspectionscore, development_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO landfill_capacity_north_america SELECT max_dissolved_oxygen, avg_usage, city_id FROM london.stations WHERE max_dissolved_oxygen > 420"


beeline -u "$HS2_URL" -e "INSERT INTO rural_infrastructure SELECT contributiondate, request_date, home_team_id, personnel_id FROM community_engagement WHERE contributiondate > 122"


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO water_consumption SELECT a.material_name, b.court_appearances FROM agroecology_practices a JOIN gene b ON a.hoursspent = b.hoursspent"
spark.sql(sql)


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


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))


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO playergamedata (project_id, subject) VALUES (%s, %s)"


echo "dry-run: INSERT INTO vessel_tracking SELECT 1"
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
mkdir -p /tmp/joblog


df = spark.read.table("sustainable_practices_2").toPandas()
df[["technology", "contributor"]].to_sql("mart_orders_di", engine, index=False)


df = pd.read_sql("SELECT isfirstattendee, meter_200 FROM sustainable_practices_2", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("news_stories", engine, if_exists="append", index=False)


import logging
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO stg.member_point_df SELECT a.operationname, b.player_name FROM constructionlaborstatistics a JOIN diplomacy_events b ON a.amount_settled = b.amount_settled"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO phishing_targets SELECT premises_type, pilot_id, patentexpirationdate, cb_year FROM dw.inventory_delta WHERE premises_type > 129"


psql -h "$PGHOST" -U etl -c "INSERT INTO dp_articles SELECT a.nation, b.factory_id FROM ref_budget_codes a JOIN club b ON a.total_amount = b.total_amount"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO item_prices SELECT lieutenant_governor, productiondate FROM vehicledata WHERE lieutenant_governor > 23;
EOF


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


spark.sql("SELECT budget_allocation, person_name FROM wildlife LIMIT 340")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO green_building_projects SELECT steps, rooms FROM classicgame WHERE steps > 218")


cur.execute("SELECT agency_id, ship_id FROM disaster_response_donations LIMIT 282")
rows = cur.fetchall()
import logging


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO defense_projects (views, access_date) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO drug_sales SELECT floor_area_m2, amount_settled, calories FROM documents WHERE floor_area_m2 > 448;
EOF


sqoop export --connect "$JDBC" --table school --columns worker,fault_log_entry_datetime --export-dir /warehouse/stage


result = value * ratio + offset
import logging
sql = "INSERT INTO nomination SELECT a.product_type, b.enable_dm FROM co2emissions a JOIN yearly_production b ON a.student_name = b.student_name"
spark.sql(sql)


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
sql = "INSERT INTO attorneylocationyear SELECT a.healthequitymetricscore, b.customer_number FROM customers a JOIN customer b ON a.cmi_cross_ref_id = b.cmi_cross_ref_id"
spark.sql(sql)


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


sqoop export --connect "$JDBC" --table atlantic_plate --columns donorid,ship_agent_id --export-dir /warehouse/stage


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


# model dws_coupon_use_hourly depends on workshops
dbt run --select dws_coupon_use_hourly --vars '{"source_table":"workshops"}'


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


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


beeline -u "$HS2_URL" -e "INSERT INTO satisfaction SELECT fuelconsumed, plant, competition_type, last_name FROM ap_budget WHERE fuelconsumed > 66"


beeline -u "$HS2_URL" -e "INSERT INTO dishes SELECT interest_group, origin_city, postal_code, treatment_type FROM trains WHERE interest_group > 84"


beeline -u "$HS2_URL" -e "INSERT INTO fund_investments SELECT species_id, dockingdate, max_depth FROM uniteddefense.equipmentsales WHERE species_id > 245"


psql -h "$PGHOST" -U etl -c "INSERT INTO indian_ocean_wells SELECT a.book_club_id, b.steps FROM film_actor a JOIN dates b ON a.class_section = b.class_section"


spark.sql("SELECT activity_date, meal_date FROM dw.users_hourly LIMIT 96")
metrics.append(round(score, 4))
import logging
result = value * ratio + offset
spark.sql("INSERT INTO sustainable_urban_properties_2 SELECT location_text, attorney_last_name, shippingmethod, potency FROM bi.member_point_full WHERE location_text > 305")


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


psql "$DB_URL" <<SQL
SELECT lot_details, number_deaths FROM iron_ore_production LIMIT 345;
INSERT INTO researchgrants SELECT framework_id, draft_class, financial_wellbeing_score FROM menu_engineering WHERE framework_id > 484;
SQL


df = pd.read_sql("SELECT ll_hours, maintenanceid FROM timber_sales", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("dws.dws_member_point_df", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO microfinance_clients SELECT inspection_id, quarter, source_u_id FROM waste_production WHERE inspection_id > 190"


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


# TODO: 旧逻辑 INSERT INTO subjects SELECT * FROM legacy
cur.execute("SELECT is_commercial, characteristic_name FROM mart.mart_products_hourly LIMIT 324")


df = spark.read.table("recyclingratessouthamerica").toPandas()
df[["comptroller", "animal_type"]].to_sql("iron", engine, index=False)


rows = session.query(Src).filter(Src.teamname > 62).all()
# src table: visits_restaurant
engine.execute("INSERT INTO exit_strategy SELECT * FROM visits_restaurant")


spark.sql("SELECT promotionid, num_hotels FROM human_resources LIMIT 375")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ods.ods_coupon_use_di SELECT accident_date, checkout, diagnosis, yield_id FROM assets_frameworks WHERE accident_date > 154")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO cerium_production SELECT velocity, flightid, ssn FROM dws.coupon_use_di WHERE velocity > 153;
EOF


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO green_buildings SELECT payment_date, merchandise_id, quantitysold FROM food_safety_inspections WHERE payment_date > 133")


sqoop export --connect "$JDBC" --table manufacturermaterials --columns review_date,media_type_id --export-dir /warehouse/stage


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO aid_missions SELECT a.recipient, b.artwork_id FROM street_markets a JOIN port_office b ON a.portname = b.portname"
spark.sql(sql)


cur.execute("SELECT num_stops, consumer_id FROM militarycyberops LIMIT 247")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


src = spark.read.table("ai_safety_incidents")
src.write.insertInto("ods.ods_users_daily", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO claims_documents (market, sales_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model bridges depends on landfill_capacity
dbt run --select bridges --vars 'source: landfill_capacity'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO market_trends SELECT purchase_date, installation_date, donationamount FROM accounts WHERE purchase_date > 50;
EOF


threshold = cfg.get('threshold', 0.5)
import logging
sql = "INSERT INTO defense_contracts SELECT a.isfirstattendee, b.consumer_id FROM event_attendance a JOIN team b ON a.archaeologist_name = b.archaeologist_name"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO equipment (garment_type, review_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO vessels_2 (schedule_id, program_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT training_id, labor_hour_id FROM digital_assets LIMIT 416")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


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


spark.sql("SELECT fault_short_name, underrepresented_community FROM player_college LIMIT 92")
metrics.append(round(score, 4))
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO league SELECT community_members, stories, hotel_chain_name FROM food_production WHERE community_members > 79")


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


cur.execute("SELECT spacecraftid, campaign FROM org_donation LIMIT 132")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')


beeline -u "$HS2_URL" -e "INSERT INTO auctions SELECT fertilizer_id, date_order_placed FROM navalvessels WHERE fertilizer_id > 394"


# model region depends on ods.member_point_df
dbt run --select region --vars '{"source_table":"ods.member_point_df"}'


df = pd.read_sql("SELECT meter_100, cost FROM researchgrants", engine)
metrics.append(round(score, 4))
df.to_sql("drought_data", engine, if_exists="append", index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dw.dw_member_point_di SELECT initiative, loan_amount, driverid, cause_id FROM laborstatistics WHERE initiative > 155;
EOF


df = read_table(ctx, "ads.ads_cart_item_hourly")
persist_to_sink(df, "bioprocesses", mode="overwrite")


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


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


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO stg.stg_exposure_di SELECT vaccine_name, timestamp FROM store_district WHERE vaccine_name > 127")


df = read_source(ctx, "platformh")
upsert_to_warehouse(df, "co2_emissions", mode="overwrite")


sqoop export --connect "$JDBC" --table player_stats --columns preference_score,ssn --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO habitat3 SELECT a.equipment_id, b.annual_entry_exit FROM soil_moisture a JOIN org_volunteer b ON a.building_address = b.building_address"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO enzyme SELECT long, rank, fieldid FROM attendee_demographics WHERE long > 94;
EOF


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO organization SELECT professional_development, labordate, part_name FROM royal_family WHERE professional_development > 464"


src = spark.read.table("bi_device_log_daily")
src.write.insertInto("genre_songs", overwrite=True)


# TODO: 旧逻辑 INSERT INTO stg.stg_shipments_hourly SELECT * FROM legacy
cur.execute("SELECT customer, extraction_amount FROM missions LIMIT 12")


rows = session.query(Src).filter(Src.flno > 420).all()
# src table: ods.shipments_df
engine.execute("INSERT INTO dws.dws_events_hourly SELECT * FROM ods.shipments_df")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO participates_in (maxoccupancy, budget_in_billions) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO rooms SELECT post_category, services, period FROM product_details WHERE post_category > 500"


src = spark.read.table("esports_teams")
src.write.insertInto("crop_yield", overwrite=True)


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


cur.execute("SELECT relationship, plant_name FROM phone LIMIT 259")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO contract_timeline (brand_id, fabric_id) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.entrydate > 277).all()
# src table: ocean_acidity
engine.execute("INSERT INTO economic_diversification_efforts SELECT * FROM ocean_acidity")


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


mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO procedures SELECT partner, physician, animal_type, day_of_week FROM mining_companies WHERE partner > 267"


sqoop export --connect "$JDBC" --table concert_revenue --columns course_name,offender_name --export-dir /warehouse/stage


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table ods.campaigns_di --target-dir /tmp/land


spark-sql --master yarn -e "INSERT INTO member SELECT year_built, union_members, building_address, categoryid FROM biotech_startups WHERE year_built > 467"


spark.sql("SELECT advisory_id, taxi_model FROM cuisine LIMIT 247")
import logging
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO songs SELECT projectid, initiative_id FROM product_details WHERE projectid > 348")


# TODO: 旧逻辑 INSERT INTO bridge SELECT * FROM legacy
cur.execute("SELECT extraction_state, disease FROM commercialbuildings LIMIT 133")


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


import logging
spark.sql("INSERT INTO races SELECT mineral, section_id FROM school_roster WHERE mineral > 325")


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 inclusive_housing SELECT 1"
trap 'echo failed' ERR
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai


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


echo "job start: $(date +%F)"
set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO construction_union SELECT fare_date, community_size FROM trucks WHERE fare_date > 138"


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


rows = session.query(Src).filter(Src.amount_due > 497).all()
# src table: community_leaders
engine.execute("INSERT INTO renewable_energy_investments SELECT * FROM community_leaders")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cargo_handling (quantity_containers, ngo_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT campaign_name, assistingnurse FROM shipments LIMIT 58")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO routes SELECT profession_count, savingsid FROM vessel_registry WHERE profession_count > 177")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO pacific_ocean SELECT don_id, astronaut_name, truck_details, thing_id FROM ancient_artifacts WHERE don_id > 236"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO grapes SELECT involved_in_lifelong_learning, foreign, chip_model, amount_donated FROM arctic_research WHERE involved_in_lifelong_learning > 56"], check=True)


rows = session.query(Src).filter(Src.sustainablepractices > 411).all()
# src table: human_resources
engine.execute("INSERT INTO police_stations SELECT * FROM human_resources")


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


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


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


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


spark.sql("SELECT clubid, attorney_id FROM vessel_tracking LIMIT 267")
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO healthcare_centers SELECT water_type, enable_dm, order_status_code FROM film_category WHERE water_type > 321")


rows = session.query(Src).filter(Src.is_commercial > 95).all()
# src table: ods.inventory_df
engine.execute("INSERT INTO farmers SELECT * FROM ods.inventory_df")


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO military_technology_projects SELECT transactionid, media_literacy_score, venue FROM fairness_scores WHERE transactionid > 323"


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO dwd.dwd_member_point_di SELECT a.num_tools, b.org_size FROM investment_accounts a JOIN all_star b ON a.assessment_score = b.assessment_score"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO community_education_programs (access_date, energy_star_rating) VALUES (%s, %s)"


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


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


result = value * ratio + offset
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO container_ships SELECT a.winning_pilot, b.hoursspent FROM rigs a JOIN ytterbium_supply b ON a.gender_diversity = b.gender_diversity"
spark.sql(sql)


cur.execute("SELECT launch_agency, healthcareid FROM cybersecurity_strategies LIMIT 77")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO manufacturer SELECT chip_model, vendor FROM document_sections_images WHERE chip_model > 237")


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


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


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


set -euo pipefail
hive -e "INSERT INTO emerging_markets.digital_assets SELECT requestdate, customer_status_code FROM flu_cases WHERE requestdate > 60"


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO healthcare_budget SELECT a.organizationname, b.precedent_id FROM courts a JOIN dws.dws_risk_score_daily b ON a.count_id = b.count_id"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.dwd_risk_score_delta (staff_id, family_name) VALUES (%s, %s)"


spark.sql("SELECT thefttypeid, vr_platform FROM evsales LIMIT 255")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO artifact_analysis SELECT yearadded, content_type FROM gold WHERE yearadded > 400")


rows = session.query(Src).filter(Src.unavailable > 30).all()
# src table: spacecraftspeed
engine.execute("INSERT INTO submission SELECT * FROM spacecraftspeed")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO construction_labor SELECT fairtrade, document_id, white FROM australia_offset_programs WHERE fairtrade > 282;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO seal_population SELECT dependent_name, roomtype FROM weather WHERE dependent_name > 191"


df = spark.read.table("food_safety_inspections").toPandas()
df[["inspectionscore", "onscholarship"]].to_sql("regional_railways", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO musicsales (local_authority, participation_id) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO team_revenue SELECT number_of_sightings, dish_name, exit_type, catalog_name FROM militaryequipmentsales WHERE number_of_sightings > 295"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO therapists SELECT totalprice, subject_id, form_id, element_id FROM disaster_zones WHERE totalprice > 36"], check=True)


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


df = spark.read.table("station_company")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("ods.campaigns_di")


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


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO device SELECT dockingdate, uses_vr, founder_lgbtq, open_year FROM tourism_activities WHERE dockingdate > 15"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mart.mart_users (cost, incident_count) VALUES (%s, %s)"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO emissions SELECT a.played, b.mining_operation_id FROM dwd.products_hourly a JOIN underwater_trenches b ON a.artpiecename = b.artpiecename"


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO vehicle_data SELECT workerid, complaint_status_code, impact_id FROM athlete_wellbeing WHERE workerid > 108")


df = spark.read.table("legal_aid_providers").toPandas()
df[["shipmentid", "start_therapy"]].to_sql("section", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO iron (neighborhoodid, elevation) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table train_maintenance --columns floor_area_m2,artpiecename --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO rent_arrears (production_rate, used_kb) VALUES (%s, %s)"


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


psql "$DB_URL" <<SQL
SELECT shipped_to, practiceid FROM paper_data LIMIT 34;
INSERT INTO menu_vendors SELECT grade, shelter_id FROM articles_es WHERE grade > 343;
SQL


df = pd.read_sql("SELECT dishid, dish_type FROM mart.mart_campaigns_daily", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
df.to_sql("waste_generation_metrics", engine, if_exists="append", index=False)


metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO public_transport.passenger_count SELECT warehouse_state, yield_per_acre, refugee_name, customer_address FROM reservoirs WHERE warehouse_state > 113")


# model west_providers depends on dwd_payments_delta
dbt build -s west_providers --vars 'source: dwd_payments_delta'


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


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


export TZ=Asia/Shanghai
set -euo pipefail
RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table global_sales_2022 --target-dir /tmp/land