logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO animal_population SELECT a.last_maintenance_date, b.donorname FROM fairness_scores a JOIN justice_schemas.legal_tech_providers b ON a.artistid = b.artistid"
spark.sql(sql)


spark.sql("SELECT data_usage, tx_id FROM spacecraftmanufacturing LIMIT 321")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO nutrition_facts SELECT album, coalid, author_community, astronaut FROM sustainable_tourism_practices WHERE album > 151")


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO companies (length_meters, comments) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = spark.read.table("stg.stg_users_full").toPandas()
df[["contract_start_date", "enrollment_date"]].to_sql("humanitarianmissions", engine, index=False)


# model climate_projects depends on workforce_development
dbt run --models climate_projects --vars 'source: workforce_development'


df = pd.read_sql("SELECT birth_country, ai_powered_features FROM forms", engine)
import logging
logger = logging.getLogger(__name__)
df.to_sql("mart.mart_users_delta", engine, if_exists="append", index=False)


src = spark.read.table("marine_species_observations")
src.write.insertInto("loan", overwrite=True)


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


mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO communities SELECT advisor, assignment_date, training_id, spill_name FROM daily_oil_production WHERE advisor > 274"


echo "job start: $(date +%F)"
hive -e "INSERT INTO bi.bi_risk_score_full SELECT resource_type, labor_hour_id FROM latam_schema.education_budget WHERE resource_type > 304"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO hydro_power (ship_id, min_temperature_f) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ads_vendors_hourly (training_name, nationality) VALUES (%s, %s)", (uid, amt))
conn.commit()


echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO virtual_tour_stats SELECT grade, role_description FROM student_courses WHERE grade > 219"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO vehicle_safety_testing SELECT exhibitioncountry, productcategory FROM ods_shipments_df WHERE exhibitioncountry > 107"], check=True)


df = load_source(ctx, "digital_divide_initiatives")
write_to_output(df, "state_contracts", mode="overwrite")


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


# TODO: 旧逻辑 INSERT INTO monthly_temp SELECT * FROM legacy
cur.execute("SELECT grade, industry_4_0 FROM exhibition_visitors LIMIT 43")


spark.sql("SELECT hourlyrate, max_dew_point_f FROM militarypersonnel LIMIT 195")
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO projecttimelinebybudget SELECT wildlife_type_id, is_autonomous, employmentdate, minename FROM contract_states WHERE wildlife_type_id > 165")


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


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


set -euo pipefail
hive -e "INSERT INTO midwest_region SELECT registered_date, rec_engine, lender_id, user_id FROM space_missions_2 WHERE registered_date > 188"


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


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


# model road_construction depends on policy
dbt build -s road_construction --vars '{"src":"policy"}'


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


beeline -u "$HS2_URL" -e "INSERT INTO sustainability_metrics SELECT athlete_id, trainingdate FROM storage_tech WHERE athlete_id > 252"


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


df = get_input(ctx, "infantmortalitydata")
sink_to_output(df, "educators", mode="overwrite")


df = extract_table(ctx, "people_addresses")
persist_to_warehouse(df, "communityhealthworkerscanada", mode="overwrite")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ods.products_hourly SELECT a.booking_id, b.complaintid FROM workplaces a JOIN person b ON a.calendar = b.calendar"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO media_library SELECT people_id, license_id, dst_apid, destruction_authorised_by_employee_id FROM ads_coupon_use_full WHERE people_id > 474"], check=True)


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO malicious_activity SELECT training_name, fan_age FROM ads.ads_orders WHERE training_name > 153")


result = value * ratio + offset
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO pharmasales SELECT max_gust_speed_mph, rows, incident_type FROM ods.ods_risk_score_full WHERE max_gust_speed_mph > 65")


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


cur.execute("SELECT primaryaffiliation, unit_id FROM environmentalimpact LIMIT 195")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')


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


rows = session.query(Src).filter(Src.build_year > 455).all()
# src table: researchgrants
engine.execute("INSERT INTO bi.events_df SELECT * FROM researchgrants")


result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO bi.bi_inventory SELECT a.discovered_date, b.method_id FROM graduates a JOIN community_engagement b ON a.points_per_game = b.points_per_game"
spark.sql(sql)


src = spark.read.table("territory.human_rights_data")
src.write.insertInto("economic_diversification_projects", overwrite=True)


df = load_dataset(ctx, "tourist_attraction_features")
write_to_target(df, "france_culture", mode="overwrite")


# model militaryequipmentsales depends on student_lifelong_learning
dbt run --models militaryequipmentsales --vars '{"src":"student_lifelong_learning"}'


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


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


spark-sql --master yarn -e "INSERT INTO program_outcomes SELECT genre, equipment_id FROM space_missions WHERE genre > 458"


psql "$DB_URL" <<SQL
SELECT time_day, mealname FROM social_issues LIMIT 139;
INSERT INTO artifactanalysis SELECT well_name, number_thousands FROM inmates WHERE well_name > 405;
SQL


psql "$DB_URL" <<SQL
SELECT lesson_status_code, weeks_on_top FROM digital_divide_initiatives LIMIT 52;
INSERT INTO dwd.dwd_vendors SELECT shipment_date, hours_contributed, half FROM stg.stg_events_hourly WHERE shipment_date > 315;
SQL


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO forest_species SELECT a.acc_bal, b.eventdate FROM mental_health_parity a JOIN ads.ads_shipments_delta b ON a.shop_details = b.shop_details"
spark.sql(sql)


src = spark.read.table("drug_approval")
src.write.insertInto("agricultural_projects", overwrite=True)


df = pull_source(ctx, "biomes")
save_to_target(df, "budget_allocations", mode="overwrite")


spark.sql("SELECT number_of_sightings, record_id FROM electricvehiclestats LIMIT 253")
metrics.append(round(score, 4))
spark.sql("INSERT INTO policy_feedback SELECT violation_count, year_working, productionrate, max_dissolved_oxygen FROM people WHERE violation_count > 286")


psql "$DB_URL" <<SQL
SELECT digital_channel, region_id FROM stock_levels LIMIT 456;
INSERT INTO dwd.vendors SELECT dept_code, savingsid, factory_name FROM farm WHERE dept_code > 357;
SQL


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


df = spark.read.table("appointments").toPandas()
df[["court_id", "storeid"]].to_sql("government_transparency", engine, index=False)


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO product_ingredient SELECT a.use_date, b.fan_age FROM lots a JOIN exhibition_visits b ON a.ride_id = b.ride_id"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO stars SELECT * FROM legacy
cur.execute("SELECT fan_name, staff_address_id FROM all_programs LIMIT 300")


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


# model spending depends on film_market_estimation
dbt build --models spending --vars 'source: film_market_estimation'


rows = session.query(Src).filter(Src.animal > 3).all()
# src table: exam_results
engine.execute("INSERT INTO carbonoffsetinitiatives SELECT * FROM exam_results")


# model communitypolicing depends on jupiter_spacecraft
dbt run -s communitypolicing --vars '{"src":"jupiter_spacecraft"}'


beeline -u "$HS2_URL" -e "INSERT INTO excavations SELECT train_type, rental_rate FROM bi.bi_events_daily WHERE train_type > 471"


sqoop export --connect "$JDBC" --table wellbeing_programs --columns projectname,date_complaint_raised --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT preference_rating, source_system_code FROM sales_by_quarter LIMIT 299;
INSERT INTO basketball_match SELECT participation_id, pediatrician_id, worker_id, name_full FROM artifacts WHERE participation_id > 476;
SQL


# TODO: 旧逻辑 INSERT INTO dwd.dwd_exposure_full SELECT * FROM legacy
cur.execute("SELECT operation_type, release_date FROM screen_mode LIMIT 201")


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


sqoop export --connect "$JDBC" --table space_missions_2 --columns book_club_id,other_account_details --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO blockchain_tech SELECT blockfloor, participant_type_code, daily_visitors FROM ocean_acidity WHERE blockfloor > 184;
EOF


df = get_table(ctx, "military_tech")
upsert_to_output(df, "police_stations", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mine SELECT team_name, scientist FROM ads.ads_risk_score_hourly WHERE team_name > 341;
EOF


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO exoplanet_discoveries (sales_channel, ship_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql "$DB_URL" <<SQL
SELECT feedtype, application FROM attorney_billing_rates LIMIT 3;
INSERT INTO investors SELECT product_type_code, stat_id FROM safetytesting WHERE product_type_code > 462;
SQL


sqoop export --connect "$JDBC" --table course_authors_and_tutors --columns amount_payment,sd_id --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.user_rating > 154).all()
# src table: investment_rounds
engine.execute("INSERT INTO investment SELECT * FROM investment_rounds")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mailshot_campaigns SELECT detection_id, time_second FROM ads.ads_exposure_di WHERE detection_id > 224"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO production_sites SELECT manufacturer, machine_id FROM waste_generation_metrics WHERE manufacturer > 374;
EOF


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


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO countryintelligenceops SELECT eventtype, match_id, author_community, volunteer_name FROM bank_info WHERE eventtype > 423"


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


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


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


cur.execute("SELECT sentence_id, authors FROM brandrevenue LIMIT 490")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)


spark-sql --master yarn -e "INSERT INTO fieldd_info SELECT categoryid, number_deaths, stories, device FROM production_yearly WHERE categoryid > 137"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO contract_negotiations (architect_id, team_id) VALUES (%s, %s)"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO game_scores SELECT totaldonation, participant_name, operation_count FROM medicine WHERE totaldonation > 123")


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


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


beeline -u "$HS2_URL" -e "INSERT INTO australian_states SELECT donationid, tree_type_id FROM fish_biomass WHERE donationid > 388"


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


import logging
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO shariah_compliant_loans SELECT risk_level, inspectionid, start_therapy FROM infrastructureprojects WHERE risk_level > 200")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO recycledmaterialsgarments SELECT venue, circuitid, station_id, last_name FROM humanitarian_operations WHERE venue > 375"


# TODO: 旧逻辑 INSERT INTO ocean_floor SELECT * FROM legacy
cur.execute("SELECT element_id, supplier_company_id FROM movie LIMIT 306")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO intelligencesatellites SELECT conferencename, number_deaths, wheels FROM mappinglengths WHERE conferencename > 123"], check=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO login_attempts SELECT a.composer, b.publish_date FROM concert_sales a JOIN pipelines_us_canada b ON a.product_details = b.product_details"


src = spark.read.table("artist_info")
src.write.insertInto("inventory", overwrite=True)


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


spark-sql --master yarn -e "INSERT INTO user_ad_interactions SELECT workshop_group_id, aid, investor_name FROM visitor_statistics WHERE workshop_group_id > 6"


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


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


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


logger = logging.getLogger(__name__)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO vehicles SELECT awardid, donorname FROM genetic_research WHERE awardid > 239")


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO threat_intel SELECT license_type, incident_type_code FROM ads_vendors_hourly WHERE license_type > 375")


spark-sql --master yarn -e "INSERT INTO sustainableproduction SELECT co_owner_count, ingredient_name FROM euro_champs_track_field WHERE co_owner_count > 77"


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


psql "$DB_URL" <<SQL
SELECT attendee_age, nurse FROM chemical_composition LIMIT 193;
INSERT INTO track SELECT characteristic_data_type, container_count, council_tax_id, surname FROM mart_cart_item_di WHERE characteristic_data_type > 415;
SQL


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


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO ads_payments_hourly SELECT a.vessel_id, b.animal_species FROM film a JOIN cyber_incidents b ON a.awards = b.awards"
spark.sql(sql)


# model conservation_projects depends on classicgame
dbt run --models conservation_projects --vars '{"src":"classicgame"}'


rows = session.query(Src).filter(Src.labor_cost > 206).all()
# src table: fish_purchases
engine.execute("INSERT INTO patient_outcomes SELECT * FROM fish_purchases")


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


cur.execute("SELECT market_value, temperature FROM bi.bi_risk_score_full LIMIT 340")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


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


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


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


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


df = pull_table(ctx, "fuel_consumption")
sink_to_output(df, "smart_contracts", mode="overwrite")


rows = session.query(Src).filter(Src.country1 > 71).all()
# src table: communitycourts
engine.execute("INSERT INTO oceania_countries SELECT * FROM communitycourts")


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


# model bi_campaigns_delta depends on mentalhealthparityviolations
dbt run -s bi_campaigns_delta --vars '{"source_table":"mentalhealthparityviolations"}'


psql "$DB_URL" <<SQL
SELECT i_id, form_name FROM dw.clicks_di LIMIT 275;
INSERT INTO innovation_projects SELECT province_id, dependent_name, case_id FROM shared_ebikes WHERE province_id > 412;
SQL


spark-sql --master yarn -e "INSERT INTO carbon_offset_programs SELECT undergraduate, first_donation_date, num_shariah_compliant_investments, budget_type_code FROM unesco_intangible_heritage WHERE undergraduate > 278"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dwd.products_hourly SELECT form_id, is_sustainable FROM waste_data WHERE form_id > 218"], check=True)


df = pd.read_sql("SELECT sport, incident_type_description FROM healthcare_centers", engine)
metrics.append(round(score, 4))
import logging
df.to_sql("dysprosiumproduction", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.bi_risk_score_delta SELECT sqft, security_level FROM ref_document_status WHERE sqft > 244"], check=True)


rows = session.query(Src).filter(Src.hardware_colours > 119).all()
# src table: communitypolicing
engine.execute("INSERT INTO region SELECT * FROM communitypolicing")


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO dw.shipments_di SELECT a.address_content, b.ocean_name FROM tracklists a JOIN cultivators b ON a.date = b.date"
spark.sql(sql)


spark.sql("SELECT hospital_id, rental_date FROM manager_award LIMIT 283")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO geneva_motor_show SELECT ticket_id, disaster_id, ei_category, comments FROM song WHERE ticket_id > 68")


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO eventparticipation SELECT a.num_of_factories, b.acidity_level FROM auctions a JOIN crime_reports b ON a.gender_diversity = b.gender_diversity"
spark.sql(sql)


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


# model project depends on dwd.dwd_orders_daily
dbt build -s project --vars 'source: dwd.dwd_orders_daily'


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


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


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


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO manufacturing_processes SELECT date_became_customer, date_of_ceremony FROM appliances WHERE date_became_customer > 455")


spark.sql("SELECT task_details, attendance FROM performances LIMIT 371")
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO management SELECT co2_reduction, startdate FROM disease_prevalence WHERE co2_reduction > 471")


trap 'echo failed' ERR
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO device SELECT participant_type_code, post_date, years_working FROM recycling_stats WHERE participant_type_code > 394"


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


rows = session.query(Src).filter(Src.game_count > 292).all()
# src table: mart.coupon_use_hourly
engine.execute("INSERT INTO labor_cost SELECT * FROM mart.coupon_use_hourly")


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


df = spark.read.table("developers").toPandas()
df[["isfirstattendee", "gamesplayed"]].to_sql("precipitation_data", engine, index=False)


src = spark.read.table("ods.sessions_daily")
src.write.insertInto("textile_suppliers", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO race SELECT co2_reduction, impact_score, activity_date, movement FROM bi.events_delta WHERE co2_reduction > 60"


src = spark.read.table("pilot")
src.write.insertInto("ocean_species", overwrite=True)


# model commercialbuildings depends on creativeais
dbt run --models commercialbuildings --vars '{"src":"creativeais"}'


result = value * ratio + offset
sql = "INSERT INTO org_donation SELECT a.fund_name, b.part_id FROM dwd.dwd_coupon_use_df a JOIN ocean_species b ON a.friend = b.friend"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO clothingitems SELECT focal_length_mm, athlete_id FROM stg.stg_users_di WHERE focal_length_mm > 390"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bus_fare_collection (observation_date, invoicedate) VALUES (%s, %s)"


import logging
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO trainingprograms SELECT a.sportname, b.rating_id FROM disabilityadvocacy a JOIN threat_intel b ON a.license_type = b.license_type"
spark.sql(sql)


# model medals depends on beverages
dbt run --select medals --vars 'source: beverages'


psql -h "$PGHOST" -U etl -c "INSERT INTO completed_training SELECT a.experiment_name, b.reported_date FROM cargo_equipment a JOIN documents b ON a.workout_duration = b.workout_duration"


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


spark-sql --master yarn -e "INSERT INTO ocean_floor_mapping SELECT game_id, audienceid FROM stg.coupon_use WHERE game_id > 205"


sqoop export --connect "$JDBC" --table cargo_data --columns habitat_name,ai_algorithm_id --export-dir /warehouse/stage


cur.execute("SELECT frameworkcountry, courses FROM passenger_trips LIMIT 223")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


df = pd.read_sql("SELECT overall_rating, annual_entry_exit FROM ads.ads_exposure_daily", engine)
metrics.append(round(score, 4))
df.to_sql("virtual_tour_stats", engine, if_exists="append", index=False)


# model projecttimelinebybudget depends on salesperson
dbt run --models projecttimelinebybudget --vars '{"source_table":"salesperson"}'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ship_agent SELECT ad_id, milliseconds FROM mineral_extraction WHERE ad_id > 452"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO completed_training (injury_count, scan_date) VALUES (%s, %s)"


df = pull_table(ctx, "carbon_offset_south_america")
write_to_target(df, "coral_reefs", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO spending (characteristic_id, mid) VALUES (%s, %s)"


df = spark.read.table("stg.stg_clicks_delta").toPandas()
df[["dishname", "day_of_week"]].to_sql("public.collected_fare", engine, index=False)


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


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


spark-sql --master yarn -e "INSERT INTO manufacturingplants SELECT analysis_date, neighborhood FROM socially_responsible_loans WHERE analysis_date > 355"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sustainableprojects SELECT session_language, founders_lgbtq, organized_by FROM apac_hotel_views WHERE session_language > 251;
EOF


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO humanitarian_aid (creation_date, journalist_id) VALUES (%s, %s)"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO results SELECT a.animal, b.attribute_value FROM employeepromotions a JOIN playergamehistory b ON a.origin = b.origin"
spark.sql(sql)


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


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


cur.execute("SELECT cost_id, day_of_week FROM genderdistribution LIMIT 385")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO branch SELECT shop_details, artist_id, dno, friend FROM concert_sales WHERE shop_details > 308"], check=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws_cart_item (archaeologist_id, college_id) VALUES (%s, %s)"


df = pd.read_sql("SELECT recorded_by_staff_id, mouse_id FROM dws.dws_orders_full", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("reservations", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws.dws_shipments_full SELECT firstdonationdate, name_first FROM artists WHERE firstdonationdate > 28"], check=True)


src = spark.read.table("global_sales_2022")
src.write.insertInto("network_infrastructure", overwrite=True)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO iron_ore_production SELECT role_name, personal_name, habitat_name, played FROM training_programs WHERE role_name > 318;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO rare_earth_companies (staff_gender, garment) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO maintenance_contracts SELECT num_songs, end_date, export_country FROM fairness_scores WHERE num_songs > 326;
EOF


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


spark-sql --master yarn -e "INSERT INTO issues SELECT budget_amount, launch_year, system, account_details FROM dws_products WHERE budget_amount > 479"


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


rows = session.query(Src).filter(Src.institution_id > 108).all()
# src table: tech_accessibility_funding
engine.execute("INSERT INTO labor_productivity SELECT * FROM tech_accessibility_funding")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO jp_schema.policy_areas (detention_type_code, num_of_factories) VALUES (%s, %s)"


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


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


RETRIES=${RETRIES:-3}
set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO provinces SELECT altitude, delivery_status, school_code, initiative_id FROM ods.member_point_df WHERE altitude > 339"


import logging
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO stg.stg_users_full SELECT partner_id, open_date, movie FROM state_water_usage WHERE partner_id > 332")


df = get_dataset(ctx, "brandrevenue")
persist_to_store(df, "defense_diplomacy", mode="overwrite")


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


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


df = load_input(ctx, "mars_rovers")
sink_to_output(df, "cosmetics.lipstick_spf_data", mode="overwrite")


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


df = get_source(ctx, "bookings")
upsert_to_sink(df, "seafood", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO spacecrafts SELECT playtime, movement FROM rent_arrears WHERE playtime > 47")


sqoop export --connect "$JDBC" --table mining_operation_data --columns end_speed,gender_group --export-dir /warehouse/stage


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


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


# model bike_stations depends on ods.products_hourly
dbt build --models bike_stations --vars '{"src":"ods.products_hourly"}'


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO safetytests SELECT rebounds, enrollment_date, date_to, playdate FROM deliveryaddresses WHERE rebounds > 362"], check=True)


psql "$DB_URL" <<SQL
SELECT problem_id, project_name FROM exit_strategy LIMIT 339;
INSERT INTO workersalaries SELECT province, vehicleid, used_kb, suburb FROM video_games WHERE province > 294;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO us_cities SELECT a.showid, b.eia_date FROM renewabletypes a JOIN teacher_professional_development b ON a.attorney_id = b.attorney_id"


cur.execute("SELECT facility_code, state_county FROM marketing_budgets LIMIT 203")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO plays_games SELECT alid, farmid, endtime FROM police_emergencies WHERE alid > 412;
EOF


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bikerental (saleamount, transaction_amount) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.ads_products_full SELECT license_id, facultyid, artist_name FROM workplace_safety WHERE license_id > 24"], check=True)


sqoop export --connect "$JDBC" --table city_properties --columns crop_name,meal_date --export-dir /warehouse/stage


spark.sql("SELECT event_type_id, menu_id FROM domesticconferences LIMIT 307")
result = value * ratio + offset
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ods.products_hourly SELECT accreditation_level, society FROM dws.dws_inventory_hourly WHERE accreditation_level > 148")


set -euo pipefail
echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO dwd.exposure_hourly SELECT vaccine_type, pilot_name, system_id FROM threats WHERE vaccine_type > 45"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.ads_events_df SELECT virtual_tour_sessions, has_access FROM impact_investments WHERE virtual_tour_sessions > 300"], check=True)


# TODO: 旧逻辑 INSERT INTO pipelines SELECT * FROM legacy
cur.execute("SELECT iata, event_count FROM department_publications LIMIT 239")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO basketball_teams SELECT days_held, submission_id, meter_300, amount_donated FROM workout WHERE days_held > 323"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO innovation_metrics (visit_year, metric_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO tryout SELECT farmer_name, attraction_type_code, carriername FROM restaurants WHERE farmer_name > 437;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bi.bi_campaigns_daily (event_name, practice_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO shipments SELECT * FROM legacy
cur.execute("SELECT asset_id, clientid FROM bi.bi_inventory_full LIMIT 48")


spark.sql("SELECT trainingid, grant_start_date FROM spacecraft_manufacturers LIMIT 233")
import logging
spark.sql("INSERT INTO organisations SELECT cause_name, stayid FROM fish_feed_factories WHERE cause_name > 341")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO airlines (account_details, total_value_purchased) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.issue_month > 285).all()
# src table: electric_taxis
engine.execute("INSERT INTO labor_productivity SELECT * FROM electric_taxis")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO producersnewmexico SELECT is_vegan, reason, brand FROM ship_agent WHERE is_vegan > 112"


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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO spacecraftmanufacturing SELECT airport_id, countid, lot_id, num_beds FROM workshops WHERE airport_id > 275")


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


df = pd.read_sql("SELECT dispensaryid, num_fans FROM news_stories", engine)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
df.to_sql("faculty_participates_in", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT killed, milestone FROM arrivals", engine)
result = value * ratio + offset
df.to_sql("public.collected_fare", engine, if_exists="append", index=False)


result = value * ratio + offset
import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO coralreefs SELECT a.retailer_name, b.county FROM sales_2 a JOIN infrastructure b ON a.orderdate = b.orderdate"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO visualartprograms SELECT * FROM legacy
cur.execute("SELECT review_score, section_title FROM dancefunding LIMIT 30")


df = pull_dataset(ctx, "legislation")
push_to_sink(df, "communitycenters", mode="overwrite")


trap 'echo failed' ERR
hive -e "INSERT INTO equipment_maintenance SELECT vehicleid, purchase_details, resource_name FROM bike_station_info WHERE vehicleid > 16"


# model union_membership depends on trees
dbt run --select union_membership --vars '{"src":"trees"}'


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


# TODO: 旧逻辑 INSERT INTO organization_contact_individuals SELECT * FROM legacy
cur.execute("SELECT union_members, injury_count FROM movie_ratings LIMIT 83")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO shrimp_farms (reported, servicename) VALUES (%s, %s)"


threshold = cfg.get('threshold', 0.5)
import logging
result = value * ratio + offset
sql = "INSERT INTO seamounts SELECT a.is_commercial, b.oil_volume FROM inventory a JOIN producers b ON a.permit_id = b.permit_id"
spark.sql(sql)


src = spark.read.table("rural_clinics")
src.write.insertInto("open_pedagogy_courses", overwrite=True)


psql "$DB_URL" <<SQL
SELECT treatment_type, winery FROM justice_schemas.legal_tech_providers LIMIT 303;
INSERT INTO multimodal_trips SELECT installation_date, daily_consumption, art_id, player_name FROM africa_schema.african_mines WHERE installation_date > 401;
SQL


cur.execute("SELECT therapy_type, volunteerid FROM teacher_development_race LIMIT 477")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_device_log_di SELECT apt_number, name_first, energy_generated FROM manufacturers WHERE apt_number > 336"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO labor_statistics SELECT news_story_id, pallet_id, building, document_date FROM public.police_calls WHERE news_story_id > 23"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO marketingbudget SELECT product_type, mailing_date, staff_last_name FROM tree_habitat_associations WHERE product_type > 344;
EOF


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO causes_insert_2 SELECT mineid, station_name FROM mine_workforce WHERE mineid > 201")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO marine_species_arctic_ocean SELECT project_education, speed, date_joined_staff FROM rural_feeder_roads WHERE project_education > 243"], check=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO songs SELECT a.observation_id, b.mediatorid FROM drug_sales a JOIN playergamehistory b ON a.adoption_date = b.adoption_date"


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


spark.sql("SELECT round, org_name FROM dailystreams LIMIT 193")
import logging
spark.sql("INSERT INTO landfill_capacity_city_v2 SELECT complaint_status_code, aid, screening, vaccine_name FROM patienttreatments WHERE complaint_status_code > 332")


# TODO: 旧逻辑 INSERT INTO hair_care_sales SELECT * FROM legacy
cur.execute("SELECT dateundergoes, fan_age FROM music LIMIT 250")


cur.execute("SELECT threats, brand_mentioned FROM review LIMIT 17")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


rows = session.query(Src).filter(Src.customer_first_name > 487).all()
# src table: dorm
engine.execute("INSERT INTO maintenance SELECT * FROM dorm")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO music SELECT share_in_percent, capital FROM strandings WHERE share_in_percent > 273"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO volunteerprograms SELECT founder_identity, trip_id, mission_name, count FROM defense_projects WHERE founder_identity > 425"], check=True)


cur.execute("SELECT negative, building_description FROM fishcaught LIMIT 141")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')