spark-sql --master yarn -e "INSERT INTO dwd_payments_delta SELECT number_of_vessels, sensor_id, working_horses FROM item WHERE number_of_vessels > 125"


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


df = pd.read_sql("SELECT start_station_name, rental_rate FROM miningdepartment", engine)
metrics.append(round(score, 4))
df.to_sql("esportsteamsafrica", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO daily_revenue SELECT speed, contract_end_date, student_details, log_entry_date FROM video_content WHERE speed > 416;
EOF


df = get_input(ctx, "publication")
write_to_output(df, "dwd.dwd_cart_item_di", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO humanitarian_operations SELECT elimination_move, transaction_date FROM excavation_sites WHERE elimination_move > 194"


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO southeast_providers SELECT apt_number, acidification_level, cultural_diversity FROM machinery WHERE apt_number > 438")


spark-sql --master yarn -e "INSERT INTO player_sessions SELECT shipment_date, unionid FROM indie_artists WHERE shipment_date > 451"


# TODO: 旧逻辑 INSERT INTO accounts SELECT * FROM legacy
cur.execute("SELECT stockid, method_name FROM characteristics LIMIT 371")


df = extract_input(ctx, "fabrics")
push_to_output(df, "habitat", mode="overwrite")


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO mentalhealthprofessional SELECT sustainability_rating, department_id, product_category, exoplanet FROM atlantic_ocean WHERE sustainability_rating > 117")


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


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


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


sqoop export --connect "$JDBC" --table medicine_enzyme_interaction --columns farmer_id,vin --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table carbon_offsets.carbon_offsets --columns draft_details,catalog_level_name --export-dir /warehouse/stage


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO diversity_metrics SELECT season_number, undergraduate, museum_name, away_team_score FROM thefts WHERE season_number > 109"


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


psql "$DB_URL" <<SQL
SELECT programoutcomeid, fuelconsumed FROM productsafety LIMIT 376;
INSERT INTO unions SELECT party_name, dlocation, problem_log_id FROM ads_coupon_use_full WHERE party_name > 396;
SQL


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


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


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


cur.execute("SELECT addressid, resource_id FROM stations LIMIT 61")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
result = value * ratio + offset
import logging


df = spark.read.table("stores_2").toPandas()
df[["garment_id", "crop_name"]].to_sql("militarydrones", engine, index=False)


psql "$DB_URL" <<SQL
SELECT last_updated, sqft FROM call_volume LIMIT 243;
INSERT INTO ads_exposure_hourly SELECT dorm_name, storename FROM ads.ads_inventory_df WHERE dorm_name > 393;
SQL


rows = session.query(Src).filter(Src.health_equity_metric_3 > 314).all()
# src table: restaurant_revenue
engine.execute("INSERT INTO medicine SELECT * FROM restaurant_revenue")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO competition SELECT silver, sport, contract_count FROM ads.ads_member_point_daily WHERE silver > 197"


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


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


rows = session.query(Src).filter(Src.member_in_charge_id > 294).all()
# src table: habitats
engine.execute("INSERT INTO dorm SELECT * FROM habitats")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO levees (farmland_id, prepnurse) VALUES (%s, %s)"


beeline -u "$HS2_URL" -e "INSERT INTO show SELECT time_year, sustainability_id, lettergrade FROM dwd.dwd_payments WHERE time_year > 384"


psql -h "$PGHOST" -U etl -c "INSERT INTO local_impact_japan SELECT a.prereq_id, b.fertilizer_id FROM manufacturing_processes a JOIN fossil_fuel_vehicles_japan b ON a.dphone = b.dphone"


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


beeline -u "$HS2_URL" -e "INSERT INTO infrastructureprojects SELECT video_id, sodium, pname FROM sanctuaryanimals WHERE video_id > 398"


df = spark.read.table("rural_resources").toPandas()
df[["service_id", "q1_2022_views"]].to_sql("sustainableprojects", engine, index=False)


df = spark.read.table("prereq").toPandas()
df[["entrydate", "species_id"]].to_sql("rural_areas", engine, index=False)


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO film_actor SELECT explainability_score, ad_type, healthequitymetricscore, train_type FROM station_emergencies WHERE explainability_score > 329"


df = spark.read.table("wildlife").toPandas()
df[["restaurantname", "area_ha"]].to_sql("defense_project_timelines", engine, index=False)


psql "$DB_URL" <<SQL
SELECT participated_in_open_pedagogy, game_id FROM brand_info LIMIT 138;
INSERT INTO part_faults SELECT operating_system, transact_count, product_subcategory, gdp FROM bi.events_df WHERE operating_system > 269;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO climate_investments (mappingname, sensor_reading) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT schedule, calendar_date FROM historicalcontexts LIMIT 370")
import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO streams SELECT fare_amount, ingredient FROM support WHERE fare_amount > 407")


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


cur.execute("SELECT num_of_stock, fabricid FROM bi_refunds_daily LIMIT 5")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO spacemissions (killed, customer_details) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT fabrictype, payment_method FROM mart.mart_users", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("mine", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT emp_jobcode, client_id FROM activity LIMIT 496;
INSERT INTO catalog_contents_additional_attributes SELECT maintenance_contract_id, fuelid, train_type, all_home FROM vehicle_prices WHERE maintenance_contract_id > 426;
SQL


# model tourism_activities depends on rnd_budget
dbt build --select tourism_activities --vars 'source: rnd_budget'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO trends_2022 (is_compliant, investment) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


# TODO: 旧逻辑 INSERT INTO sustainable_fabrics SELECT * FROM legacy
cur.execute("SELECT vesselname, event_count FROM algorithmic_fairness LIMIT 480")


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


df = spark.read.table("peacekeeping_units").toPandas()
df[["state_province", "stu_gpa"]].to_sql("exit", engine, index=False)


df = load_dataset(ctx, "restorative_justice_sentences")
upsert_to_warehouse(df, "stg.stg_products_delta", mode="overwrite")


metrics.append(round(score, 4))
spark.sql("INSERT INTO subway SELECT rank, contractor FROM railway WHERE rank > 265")


set -euo pipefail
echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO green_certification SELECT played, membership_id FROM dws.cart_item_full WHERE played > 86"


psql "$DB_URL" <<SQL
SELECT vehicleid, address_id FROM asia_events LIMIT 261;
INSERT INTO party_events SELECT plan_id, resolution, pollutant_type, green_building_id FROM vessel WHERE plan_id > 384;
SQL


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO salary SELECT next_entry_id, tripdatetime, date_of_ceremony FROM product_characteristics WHERE next_entry_id > 431;
EOF


spark-sql --master yarn -e "INSERT INTO mexico_regions SELECT founder_race, truck_details FROM projects WHERE founder_race > 204"


cur.execute("SELECT membership_type, velocity FROM companies_extended LIMIT 26")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


# model transaction depends on green_building_projects
dbt build --models transaction --vars '{"source_table":"green_building_projects"}'


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


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


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


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


# model safe_dataset depends on open_pedagogy_enrollment
dbt build --models safe_dataset --vars 'source: open_pedagogy_enrollment'


import logging
result = value * ratio + offset
sql = "INSERT INTO language SELECT a.attraction_type_description, b.resident_id FROM factory_connections a JOIN stg.stg_events_hourly b ON a.fish_population = b.fish_population"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO environmental_impact_stats SELECT student, depth, asset_disposed_date FROM functional_areas WHERE student > 346"


df = read_source(ctx, "dwd.dwd_products")
push_to_store(df, "disabilitysupportprograms", mode="overwrite")


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


# TODO: 旧逻辑 INSERT INTO diseases SELECT * FROM legacy
cur.execute("SELECT document_code, typeid FROM sites LIMIT 60")


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_events_di SELECT a.speed, b.valuation FROM bi.products_daily a JOIN roller_coaster b ON a.observation_id = b.observation_id"


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO geological_survey SELECT license_plate, safety_record, local, show_name FROM recycledmaterialsgarments WHERE license_plate > 368"


psql -h "$PGHOST" -U etl -c "INSERT INTO sustainability_fact SELECT a.pricepergram, b.assistingnurse FROM chemical_production_3 a JOIN mart.mart_payments_df b ON a.tour_id = b.tour_id"


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


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO seamounts SELECT algorithm, sustainability_id, price_in_euros, unit FROM inclusion_efforts WHERE algorithm > 457")


sqoop export --connect "$JDBC" --table employee_demographics --columns condition_id,therapy_date --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO seafoodsouthafricakenya SELECT artist_name, researcher, hours_played, launch_id FROM weather WHERE artist_name > 472"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO employees SELECT show_name, ratingdate FROM dailyapplestreams WHERE show_name > 472"], check=True)


spark-sql --master yarn -e "INSERT INTO dysprosium_mines SELECT hourlyrate, recipient_id, floors, tree_species FROM member_details WHERE hourlyrate > 350"


psql "$DB_URL" <<SQL
SELECT policy_holder_id, chemicalid FROM latam_schema.education_budget LIMIT 257;
INSERT INTO energy_efficiency_projects SELECT target_id, fund_name FROM defense_projects WHERE target_id > 357;
SQL


# TODO: 旧逻辑 INSERT INTO vehicle_sales SELECT * FROM legacy
cur.execute("SELECT voter_id, content_type FROM labour_productivity LIMIT 141")


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


spark.sql("SELECT offender_name, attendee_race FROM region_stats LIMIT 447")
metrics.append(round(score, 4))
spark.sql("INSERT INTO sustainable_urban_properties_2 SELECT invoice_date, component_name, attraction_name, volunteer_year FROM employeepromotions WHERE invoice_date > 113")


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


cur.execute("SELECT min_age, meal_name FROM ods.vendors_di LIMIT 253")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO pets SELECT openingid, directed_by, mentalhealthscore FROM event_attendance WHERE openingid > 370"


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


df = load_frame(ctx, "platform")
push_to_sink(df, "healthequitymetrics", mode="overwrite")


result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO exhibition_record SELECT well_depth, organisation_id, agency_id FROM asia_events WHERE well_depth > 296")


df = pd.read_sql("SELECT * FROM genetics_stats.research_projects", conn)
df.to_sql("habitat", conn, if_exists="replace", index=False)


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


set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO charging_stations SELECT resolution, date_of_latest_revision, location FROM florida_conservation_initiatives WHERE resolution > 269"


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


cur.execute("SELECT weight, healthcareid FROM sustainable_menu_items LIMIT 472")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO disease_prevalence (coupon_id, reported) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO affordablehousing SELECT user_account, system_name, email_address FROM dailystreams WHERE user_account > 478"


# TODO: 旧逻辑 INSERT INTO carbon_prices SELECT * FROM legacy
cur.execute("SELECT vehicle_flight_number, make FROM oil_production LIMIT 195")


sqoop export --connect "$JDBC" --table streams --columns player_id,cargoid --export-dir /warehouse/stage


spark.sql("SELECT university_type, vehicle_model FROM france_culture LIMIT 77")
metrics.append(round(score, 4))
spark.sql("INSERT INTO securityincidents SELECT centerid, contract_start_date, quantity FROM trenches WHERE centerid > 113")


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


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


sqoop export --connect "$JDBC" --table carbon_emissions --columns archaeologist_id,team_id_loser --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT agency_id, violation_type FROM artcollection LIMIT 239;
INSERT INTO daily_industrial_water_usage SELECT donationid, phone_number, sensor_type, playlist_id FROM renewable_energy_projects WHERE donationid > 19;
SQL


# TODO: 旧逻辑 INSERT INTO exhibition_visits SELECT * FROM legacy
cur.execute("SELECT home_team_score, score FROM vrgames LIMIT 205")


cur.execute("SELECT actual_order_id, special_features FROM co2emissions LIMIT 81")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mountain SELECT patient_age, build_date, is_ev FROM oceania_countries WHERE patient_age > 126"


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO students SELECT supplier_id, amount_paid, biz_date FROM defense_diplomacy WHERE supplier_id > 221")


# model dorm_amenity depends on seafood
dbt build -s dorm_amenity --vars '{"source_table":"seafood"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO port_visits (fund_name, tasktype) VALUES (%s, %s)"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO cosmetics SELECT last_checkup_date, market_value, form_type_code FROM mart_refunds_delta WHERE last_checkup_date > 134")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO gradeconversion SELECT eliminated_by, number_of_platforms, supply_volume FROM trip WHERE eliminated_by > 490"], check=True)


logger = logging.getLogger(__name__)
sql = "INSERT INTO member_attendance SELECT a.vice_president_vote, b.sponsor_name FROM innovation_projects a JOIN donationsbycause b ON a.sales_in_billion = b.sales_in_billion"
spark.sql(sql)


df = source_dataset(ctx, "excavation_sites")
persist_to_store(df, "jobs", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO therapy SELECT song, trackid, host FROM asteroids WHERE song > 222"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO intel_ops SELECT accelerator_id, satelliteid, resolved, decision FROM militaryinnovations WHERE accelerator_id > 90"

accelerator_id satelliteid resolved decision


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


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))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads_vendors_hourly SELECT ingredient, trial_name, purchase_details, publisher FROM rural_infrastructure WHERE ingredient > 392"], check=True)


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


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


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO public.crime_types SELECT mean_sea_level_pressure_inches, shelter_name, permit_date, digital_asset FROM service_budget WHERE mean_sea_level_pressure_inches > 285"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO maintenance_engineers SELECT building, film_id, inspection_time FROM carbon_prices_3 WHERE building > 159;
EOF


psql "$DB_URL" <<SQL
SELECT founders, studentname FROM shop LIMIT 88;
INSERT INTO research SELECT deliveryid, meal_name, founder_count FROM measurements WHERE deliveryid > 244;
SQL


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


threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO sectors SELECT a.contract_start, b.contract_amount FROM article_views a JOIN dwd.dwd_vendors b ON a.cust_name = b.cust_name"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO attorney_billing_rates (document_structure_code, cruelty_free) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model recyclingrates depends on shipment
dbt build -s recyclingrates --vars '{"src":"shipment"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO threat_severity (visit_date, local) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("train").toPandas()
df[["city_town", "volunteer_hours"]].to_sql("playergamedata", engine, index=False)


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO erc20_transactions SELECT fish_id, working_horses FROM facility WHERE fish_id > 220"


import logging
result = value * ratio + offset
sql = "INSERT INTO ocean_acidification_antarctic SELECT a.statement_id, b.sustainability_certified FROM startup_founders a JOIN ocean_health_monitor b ON a.agreementid = b.agreementid"
spark.sql(sql)


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


cur.execute("SELECT railway_id, asset_make FROM vaccine_administered LIMIT 360")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO enzyme SELECT room_count, year_opened FROM dwd.dwd_exposure_df WHERE room_count > 137"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO urbanagricrop SELECT enrollment_date, marketing_region_descriptrion, savingsid, exhibitioncountry FROM cerium_production WHERE enrollment_date > 132;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO visitor_statistics SELECT primary_conference, trackid, document_type_name, sustainability_certified FROM user_likes WHERE primary_conference > 199;
EOF


src = spark.read.table("flu_cases")
src.write.insertInto("body_builder", overwrite=True)


cur.execute("SELECT ethnicity, financial_capability_score FROM docking LIMIT 453")
rows = cur.fetchall()
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO wastedata SELECT a.sighting_id, b.hours_contributed FROM employment a JOIN diversification_projects b ON a.advocate_id = b.advocate_id"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO document_functional_areas (game, incidentid) VALUES (%s, %s)"


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


psql "$DB_URL" <<SQL
SELECT quantityproduced, assistingnurse FROM cultural_competency_training LIMIT 126;
INSERT INTO urban_agriculture_initiatives SELECT date_incident_start, sales_transaction_id, church_id, paper_id FROM transport WHERE date_incident_start > 460;
SQL


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


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


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


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


rows = session.query(Src).filter(Src.player_name > 467).all()
# src table: stars
engine.execute("INSERT INTO thefttypes SELECT * FROM stars")


mkdir -p /tmp/joblog
hive -e "INSERT INTO department_publications SELECT countryid, round_amount FROM device_usage WHERE countryid > 315"


spark-sql --master yarn -e "INSERT INTO bridge SELECT mgr_start_date, station_name FROM satisfaction WHERE mgr_start_date > 60"


beeline -u "$HS2_URL" -e "INSERT INTO marine_species SELECT dysprosium_prod, faculty, mining_operation FROM vesselfuel WHERE dysprosium_prod > 36"


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


beeline -u "$HS2_URL" -e "INSERT INTO funding_records SELECT position, saleamount, container_count FROM claims_processing_stages WHERE position > 124"


# model ca_menu_items depends on labor_unions
dbt build --models ca_menu_items --vars '{"src":"labor_unions"}'


# model bridges depends on restaurants
dbt run --select bridges --vars '{"src":"restaurants"}'


psql "$DB_URL" <<SQL
SELECT business_name, purchase_id FROM farmer_details LIMIT 214;
INSERT INTO cybersecurityincidents SELECT flightid, dispensaryid FROM financial_transactions WHERE flightid > 498;
SQL


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


echo "dry-run: INSERT INTO dws.dws_coupon_use_full SELECT 1"
mkdir -p /tmp/joblog


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


# TODO: 旧逻辑 INSERT INTO shipments SELECT * FROM legacy
cur.execute("SELECT port, produceid FROM bi.inventory_daily LIMIT 304")


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


# model stg_clicks_delta depends on ocean
dbt build --select stg_clicks_delta --vars '{"source_table":"ocean"}'


df = spark.read.table("dws_events_df").toPandas()
df[["policyholder_id", "ai_powered_features"]].to_sql("models_safety", engine, index=False)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.refunds SELECT open_year, routename FROM engineer_skills WHERE open_year > 427"], check=True)


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


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


psql "$DB_URL" <<SQL
SELECT author_id, swimmer_id FROM tencel_sources LIMIT 19;
INSERT INTO india_ingredient_sourcing SELECT sitename, visitor_count, app_name FROM ticketspending WHERE sitename > 471;
SQL


rows = session.query(Src).filter(Src.region > 142).all()
# src table: tvshows
engine.execute("INSERT INTO smart_contracts_table SELECT * FROM tvshows")


psql -h "$PGHOST" -U etl -c "INSERT INTO plots SELECT a.shoe_brand, b.anomaly FROM associatedheritages a JOIN wastewater_plants b ON a.project_id = b.project_id"


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


# TODO: 旧逻辑 INSERT INTO playergamedata SELECT * FROM legacy
cur.execute("SELECT sales_channel, passenger_id FROM arctic_research LIMIT 230")


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


cur.execute("SELECT host_city_id, author_community FROM circuits LIMIT 183")
rows = cur.fetchall()
result = value * ratio + offset
if not rows:
    logger.warning('empty result')


spark-sql --master yarn -e "INSERT INTO ref_service_types SELECT affiliation, professional_development_programs FROM order_items WHERE affiliation > 325"


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO casebilling SELECT media_type_id, garment_type, coach_name FROM smartcityprojects WHERE media_type_id > 383"


beeline -u "$HS2_URL" -e "INSERT INTO bi.bi_payments SELECT guest_last_name, lawyer_name, tank, museum_name FROM communitycourtcases WHERE guest_last_name > 427"


src = spark.read.table("decentralized_apps")
src.write.insertInto("benefits_overpayments", overwrite=True)


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


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


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO job_change SELECT home_city, mission, artist FROM org_climate_finance WHERE home_city > 299")


cur.execute("SELECT assessment_date, customer_phone FROM product_ingredient LIMIT 245")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


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


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


spark-sql --master yarn -e "INSERT INTO product_sales SELECT time_day, participant_details, cause, nutrient_level FROM country_waste_generation WHERE time_day > 147"


spark-sql --master yarn -e "INSERT INTO indie_artists SELECT access_count, stockid, artwork_id FROM exhibitions WHERE access_count > 445"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO recycling_rates_state (attraction_name, sector) VALUES (%s, %s)"


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


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


spark.sql("SELECT hours_played, lettergrade FROM members LIMIT 368")
import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO libraries SELECT stu_hrs, architect_id FROM genetics.projects WHERE stu_hrs > 149")


rows = session.query(Src).filter(Src.fueldate > 145).all()
# src table: trainings
engine.execute("INSERT INTO miningdepartment SELECT * FROM trainings")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO volunteer_hours SELECT date_of_transaction, cruelty_free, booking_start_date, units_owned FROM member_details WHERE date_of_transaction > 232"], check=True)


rows = session.query(Src).filter(Src.outcome_code > 120).all()
# src table: consumer
engine.execute("INSERT INTO refugee_support SELECT * FROM consumer")


psql -h "$PGHOST" -U etl -c "INSERT INTO weights SELECT a.museumname, b.preference_score FROM song a JOIN material_production b ON a.trade_name = b.trade_name"


rows = session.query(Src).filter(Src.facid > 5).all()
# src table: investment_accounts
engine.execute("INSERT INTO stg.cart_item_full SELECT * FROM investment_accounts")


spark-sql --master yarn -e "INSERT INTO audience_demographics SELECT therapeutic_area, outcome, representative_id FROM human_resources WHERE therapeutic_area > 264"


psql "$DB_URL" <<SQL
SELECT award, hometeamid FROM smart_contracts LIMIT 235;
INSERT INTO organisations SELECT address_line_1, opponent_id, hispanic, volunteer_name FROM stg.stg_campaigns WHERE address_line_1 > 299;
SQL


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


msg = "would run: INSERT INTO co2price SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO emergency_calls SELECT round_date, emp_num, openingid, group_name FROM customers_policies WHERE round_date > 170"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO claims_documents SELECT founded_year, stayid FROM galleries WHERE founded_year > 243"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO school_bus SELECT regional_population, instructor_id FROM india_solar_power WHERE regional_population > 309"], check=True)


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


df = pull_dataset(ctx, "song")
write_to_sink(df, "cultural_competency", mode="overwrite")


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


psql "$DB_URL" <<SQL
SELECT transactions, course_completion FROM investments LIMIT 377;
INSERT INTO course_attendance SELECT is_ev, theatrename, username FROM sustainable_sourcing WHERE is_ev > 472;
SQL


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


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


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


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


retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
import logging
spark.sql("INSERT INTO rd_expenditure SELECT app_id, trip_distance FROM contractnegotiations WHERE app_id > 124")


psql "$DB_URL" <<SQL
SELECT daily_visitors, address FROM danceevents LIMIT 57;
INSERT INTO sourcing SELECT professional_development_programs, account_balance FROM claims_documents WHERE professional_development_programs > 238;
SQL


rows = session.query(Src).filter(Src.cropid > 163).all()
# src table: genderdistribution
engine.execute("INSERT INTO dw_users_full SELECT * FROM genderdistribution")


set -euo pipefail
hive -e "INSERT INTO textileworkers SELECT virtual_tour_views, investorgender, assets FROM spacecraft WHERE virtual_tour_views > 450"


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


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


# model shariah_compliant_products depends on militaryequipmentsales
dbt run -s shariah_compliant_products --vars 'source: militaryequipmentsales'


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


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO streams SELECT workouttype, daily_distance, invoice_id, potency FROM nasa_mars_program WHERE workouttype > 484")


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


df = extract_frame(ctx, "circular_supply_chain_products")
save_to_target(df, "trainers", mode="overwrite")


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


cur.execute("SELECT shipping_agent_name, enrollment_date FROM site LIMIT 425")
rows = cur.fetchall()
result = value * ratio + offset
import logging


df = spark.read.table("visitor_exhibition").toPandas()
df[["intervention_type", "line_id"]].to_sql("order_items", engine, index=False)


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


df = pd.read_sql("SELECT averagespeed, people_id FROM australia_offset_programs", engine)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
import logging
df.to_sql("cases", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.risk_score_hourly SELECT inspection_id, number_of_platforms, settlement_amount FROM music_events WHERE inspection_id > 435"], check=True)


metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO laptimes SELECT accelerator_id, equipment_id FROM associatedheritages WHERE accelerator_id > 254")


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


sqoop export --connect "$JDBC" --table underwater_cables --columns review_score,building_type --export-dir /warehouse/stage


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO organicproducts (reason, date_of_notes) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT squadron, num_of_staff FROM watertreatmentplants LIMIT 179")
metrics.append(round(score, 4))
spark.sql("INSERT INTO voting_data SELECT stop, astronaut_name, meter_300 FROM farms WHERE stop > 267")


if not rows:
    logger.warning('empty result')
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO battery_storage SELECT aid, license_type FROM threat_intelligence WHERE aid > 84")


rows = session.query(Src).filter(Src.publication_year > 162).all()
# src table: ads.ads_exposure_daily
engine.execute("INSERT INTO financialwellbeing SELECT * FROM ads.ads_exposure_daily")


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


spark-sql --master yarn -e "INSERT INTO submersible_dives SELECT hometeam, mouse_id FROM department_store_chain WHERE hometeam > 139"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO waste_types SELECT mean_humidity, stu_phone, mission_date, project_category FROM dw_vendors_di WHERE mean_humidity > 374"


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


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO military_personnel SELECT a.specialty, b.eventid FROM safety_testing a JOIN therapists b ON a.avg_usage = b.avg_usage"
spark.sql(sql)


# model organisations depends on artists_valuation
dbt build --models organisations --vars 'source: artists_valuation'


spark-sql --master yarn -e "INSERT INTO venture SELECT virtual_tour_views, line_name, working_year_starts, arrival_time FROM drought_data WHERE virtual_tour_views > 76"


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


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


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO ca_menu_items SELECT a.wifi, b.premise_details FROM tv_shows a JOIN calibration_data2 b ON a.framework = b.framework"
spark.sql(sql)


df = pull_input(ctx, "volunteer_registration")
upsert_to_warehouse(df, "mart.mart_products_df", mode="overwrite")


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


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


trap 'echo failed' ERR
hive -e "INSERT INTO artsandcrafts SELECT community_size, goal_id, nation FROM people_addresses WHERE community_size > 286"


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


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


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO euroavev SELECT chemical_type, highscore, mean_temperature_f, ticket_subject FROM train_maintenance WHERE chemical_type > 346")


beeline -u "$HS2_URL" -e "INSERT INTO student_program_mapping SELECT preference_rating, donationamount, apt_type_code, start FROM water_usage WHERE preference_rating > 383"


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


spark.sql("SELECT method_name, fan_age FROM smart_city_projects LIMIT 136")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO labor_cost SELECT total_shipped, assessment_score FROM participants WHERE total_shipped > 204")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO retailers SELECT outcome_type, jul, clublocation, publish_date FROM department_publications WHERE outcome_type > 23"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO atlantic_plate (founder_gender, rig_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO sustainable_materials SELECT founded, emp_id, transit_passengers, num_songs FROM sectors WHERE founded > 379"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO language SELECT contributorname, courses, last_service FROM platformi WHERE contributorname > 299;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO space_debris SELECT a.issue_date, b.date_of_ceremony FROM ods_shipments_df a JOIN platformstats b ON a.production_cost = b.production_cost"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO regional_railways SELECT fare, hometeam, data_usage, month FROM class WHERE fare > 123"], check=True)


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO airportdata SELECT a.crs_description, b.worker FROM contract_timeline a JOIN waste_production b ON a.awardid = b.awardid"
spark.sql(sql)


df = pd.read_sql("SELECT therapist_id, healthequitymetricscore FROM ads_coupon_use_full", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("inclusivehousingpolicies", engine, if_exists="append", index=False)


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


rows = session.query(Src).filter(Src.home_team_points > 64).all()
# src table: audience_demographics
engine.execute("INSERT INTO artistsdemographics SELECT * FROM audience_demographics")


spark.sql("SELECT billing, water_temp FROM trust LIMIT 265")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO electric_vehicle_stats SELECT lat, user_name, is_operational FROM fabricdata WHERE lat > 94")


df = spark.read.table("space_agencies_2")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


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


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


df = pull_dataset(ctx, "smartcityprojects")
sink_to_target(df, "regional_railways", mode="overwrite")


df = read_dataset(ctx, "workforcediversity")
dump_to_store(df, "bi.bi_payments", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws.exposure_df SELECT hours_developed, heritage_site_id, friend FROM bi.users_full WHERE hours_developed > 210;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO manufacturermaterials SELECT college_location, researcher_name FROM submersible_dives WHERE college_location > 145"


spark.sql("SELECT defendant_id, dept_name FROM invoices LIMIT 167")
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ytterbiumproduction SELECT log_entry_description, purchaseid FROM ref_product_categories WHERE log_entry_description > 123")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO basketball_teams SELECT province_id, employmentdate, unitsperweek FROM fairtradecertifications WHERE province_id > 336"], check=True)


trap 'echo failed' ERR
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
sqoop import --connect "$JDBC" --table ods.shipments_df --target-dir /tmp/land


spark-sql --master yarn -e "INSERT INTO building_permits SELECT court_id, rural_area FROM chemical_processes WHERE court_id > 164"


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO union_members SELECT trainingname, effort, tree_id, industry_4_0 FROM volunteer_events WHERE trainingname > 176"


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


sqoop export --connect "$JDBC" --table public_schools --columns stadium_id,fund_type --export-dir /warehouse/stage


spark.sql("SELECT union_members, is_sustainable FROM safety_records LIMIT 47")
metrics.append(round(score, 4))
spark.sql("INSERT INTO bi.bi_exposure_hourly SELECT amount_used, mealname, vulnerability, org_name FROM renewableenergy WHERE amount_used > 349")


df = spark.read.table("veterans").toPandas()
df[["permit_date", "device"]].to_sql("southchinasea.wells", engine, index=False)


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bank_info SELECT operationid, review_date, donor_state, coownerid FROM fabricdata WHERE operationid > 164")


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


df = source_input(ctx, "block")
sink_to_store(df, "stg.risk_score_hourly", mode="overwrite")


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


psql "$DB_URL" <<SQL
SELECT decor, assigned_to_staff_id FROM visualartprograms LIMIT 243;
INSERT INTO viewership SELECT signupdate, payment_type_code FROM platformh WHERE signupdate > 4;
SQL


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


df = pd.read_sql("SELECT visitors, workouttype FROM tech_workers_union", engine)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("broadband_revenue", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO brand_info SELECT worker_name, chip_model, fleet_name FROM branch WHERE worker_name > 184"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO renewable_energy_projects SELECT eco_friendly, meter_200 FROM traditionalarts WHERE eco_friendly > 129;
EOF


spark-sql --master yarn -e "INSERT INTO navalvessels SELECT court_id, participant_name, rig_id, farmname FROM manufacturer WHERE court_id > 7"


# model government_transparency depends on bank
dbt build --models government_transparency --vars '{"source_table":"bank"}'


spark.sql("SELECT household_size, total_donation_amount FROM recycling_rates_state LIMIT 223")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO wedding SELECT bridgeid, metric, money_requested, shop_id FROM drought_impact WHERE bridgeid > 217")


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO menu SELECT end_date, threat_type FROM caribbean_tourists WHERE end_date > 303"


df = pd.read_sql("SELECT ranking, disability_type FROM ref_incident_type", engine)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("county_public_safety", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO dw.dw_sessions_full SELECT a.trial_name, b.festival_id FROM dws.dws_risk_score_daily a JOIN service_budget b ON a.propertyid = b.propertyid"


df = extract_source(ctx, "medicine_enzyme_interaction")
export_to_warehouse(df, "policyanalysis", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.payments_di SELECT pname, donorname, closure_authorised_by_staff_id, mine_location FROM section WHERE pname > 129;
EOF


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO drug_approvals SELECT working_year_starts, field, center_id FROM safetyorgs WHERE working_year_starts > 259"], check=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO commercialbuildings (individual_name, contractorname) VALUES (%s, %s)"


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


df = spark.read.table("thefts").toPandas()
df[["access_count", "co2_offset_amount"]].to_sql("user_profiles", engine, index=False)


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


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


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


rows = session.query(Src).filter(Src.num_cases > 133).all()
# src table: bi.bi_payments_full
engine.execute("INSERT INTO participants SELECT * FROM bi.bi_payments_full")


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


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


sqoop export --connect "$JDBC" --table bioprocess_engineering --columns rebounds,mean_visibility_miles --export-dir /warehouse/stage


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


spark.sql("SELECT filingdate, facultyid FROM recyclingrates LIMIT 117")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO waste_management_projects SELECT factory_name, grant_name FROM circular_economy_companies WHERE factory_name > 480")


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


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


beeline -u "$HS2_URL" -e "INSERT INTO climate_finance_organizations SELECT num_hotels, potency, investor_details FROM suburbs WHERE num_hotels > 382"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mobile_plans (bill_id, energy_consumption) VALUES (%s, %s)"


cur.execute("SELECT founders_lgbtq, book_id FROM donations LIMIT 97")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


psql "$DB_URL" <<SQL
SELECT strain, ship_name FROM onlineengagement LIMIT 415;
INSERT INTO high_risk SELECT vehicleid, production_quantity FROM submarine_canyons WHERE vehicleid > 18;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ingredient (file_size, date) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table customer_transactions --columns vehicle_name,business_id --export-dir /warehouse/stage


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


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


# model skincareproducts depends on winter_olympics
dbt build --select skincareproducts --vars '{"src":"winter_olympics"}'


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO office_locations SELECT trial_status, ram_mib, cityname, trend_id FROM factories WHERE trial_status > 34"], check=True)


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


sqoop export --connect "$JDBC" --table industrial_customers --columns professionalid,staff_details --export-dir /warehouse/stage


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


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO bi.bi_campaigns_daily SELECT a.operationid, b.attendance FROM art a JOIN stg.stg_shipments_hourly b ON a.enable_location_tracking = b.enable_location_tracking"
spark.sql(sql)


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


rows = session.query(Src).filter(Src.guest_id > 57).all()
# src table: projecttimelinebybudget
engine.execute("INSERT INTO browser SELECT * FROM projecttimelinebybudget")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO heritage_sites_3 (skill_description, participant_type_code) VALUES (%s, %s)"


src = spark.read.table("economic_diversification_argentina")
src.write.insertInto("ods_risk_score_delta", overwrite=True)


df = source_input(ctx, "student_program_mapping")
upsert_to_sink(df, "skills", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO drills SELECT * FROM legacy
cur.execute("SELECT lawyer_name, artwork_id FROM communitydevelopment LIMIT 249")


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO phone_market SELECT composer, produceid, building_description FROM salary WHERE composer > 337"


psql -h "$PGHOST" -U etl -c "INSERT INTO canals SELECT a.player_api_id, b.school_id FROM customer a JOIN parking_fines b ON a.loan_id = b.loan_id"


spark.sql("SELECT algorithm_name, round_type FROM programs LIMIT 280")
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO indigenous_food_systems SELECT orderid, fairness_score FROM ods.campaigns_di WHERE orderid > 35")


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


psql "$DB_URL" <<SQL
SELECT year_deforested, major FROM district_schools LIMIT 371;
INSERT INTO humanitarian_aid SELECT accreditation_level, incident_category FROM rural_development.agriculture_projects WHERE accreditation_level > 376;
SQL


sqoop export --connect "$JDBC" --table licenses --columns diagnosis,farmland_id --export-dir /warehouse/stage


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


psql -h "$PGHOST" -U etl -c "INSERT INTO producesupplier SELECT a.build_year, b.trainingdate FROM brandrevenue a JOIN bi.refunds_daily b ON a.festival_name = b.festival_name"


sqoop export --connect "$JDBC" --table dwd.dwd_products --columns deaths,business_id --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bioprocess.engineering_projects (vendor_state, platform_name) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO crime_reports SELECT a.inclusivehousing, b.shipment_id FROM city_properties a JOIN research_grants b ON a.customerid = b.customerid"


rows = session.query(Src).filter(Src.permit_id > 32).all()
# src table: ticket_sales
engine.execute("INSERT INTO passenger_trips SELECT * FROM ticket_sales")


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


# TODO: 旧逻辑 INSERT INTO stg.campaigns_df SELECT * FROM legacy
cur.execute("SELECT clublocation, number_thousands FROM overwatch_scores LIMIT 305")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO regular_order_products SELECT partnership_id, energy_efficiency_savings, job_title, lesson_id FROM dw.dw_coupon_use_daily WHERE partnership_id > 329;
EOF


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO territory.human_rights_data (complaint_date, archaeologistid) VALUES (%s, %s)"


src = spark.read.table("state_usage")
src.write.insertInto("material_production", overwrite=True)


# TODO: 旧逻辑 INSERT INTO renewable_power SELECT * FROM legacy
cur.execute("SELECT nominee, operation_name FROM fossil_fuel_vehicles LIMIT 146")


beeline -u "$HS2_URL" -e "INSERT INTO donation SELECT operationid, products_this_year FROM food_justice WHERE operationid > 485"


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


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


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


spark-sql --master yarn -e "INSERT INTO wells SELECT subject_id, award, threat FROM shariah_compliant_loans WHERE subject_id > 224"


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


df = pd.read_sql("SELECT wrestler_id, budget_in_billions FROM hospitallocations", engine)
import logging
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("manufacturermaterials", engine, if_exists="append", index=False)


df = load_table(ctx, "city.community_policing")
push_to_output(df, "art_exhibit_attendance", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO device_accessibility SELECT * FROM legacy
cur.execute("SELECT built_year, cuisine_id FROM urban_transportation LIMIT 383")


if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO flights SELECT wage, eventname, price_in_dollars FROM ads.ads_member_point_daily WHERE wage > 350")


df = extract_table(ctx, "bi.bi_orders_hourly")
dump_to_sink(df, "fields_production", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO farmers_india SELECT contract_start_date, inspectionid, galleryname, workoutdate FROM green_building_materials WHERE contract_start_date > 478"

contract_start_date inspectionid galleryname workoutdate


import logging
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))


df = pd.read_sql("SELECT grade, partitionid FROM precision_farming_imagery", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("boston_emergency_response", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO marine_life_research SELECT trade, component_type, event_id FROM wastewater_treatment_plants WHERE trade > 140"


sqoop export --connect "$JDBC" --table dws_cart_item --columns rural_area,facultyid --export-dir /warehouse/stage


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO extraction_methods (patient_age, order_quantity) VALUES (%s, %s)"


trap 'echo failed' ERR
echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO stg.stg_users SELECT datetime_detention_start, attendanceid FROM public_schools WHERE datetime_detention_start > 166"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO web_client_accelerator SELECT forest_type, founders FROM haircare_sales WHERE forest_type > 21"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO savings SELECT contract_address, extraction_state, author_or_editor, country_name FROM ads.ads_exposure_di WHERE contract_address > 458"


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


beeline -u "$HS2_URL" -e "INSERT INTO threats SELECT vessel, uk_vat_number FROM stg.stg_campaigns WHERE vessel > 451"


df = spark.read.table("workshops").toPandas()
df[["transaction_value", "maintenanceid"]].to_sql("solar_farms", engine, index=False)


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


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


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


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


psql "$DB_URL" <<SQL
SELECT unionname, characteristic_type_code FROM landfillcapacitybycountry LIMIT 11;
INSERT INTO residents_services SELECT app_id, route_name, secretary_vote FROM ai_safety_incidents WHERE app_id > 33;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.member_point_df SELECT attendeeid, batting_average, playdate FROM player_sessions WHERE attendeeid > 328"], check=True)


src = spark.read.table("runs")
src.write.insertInto("military_expenditure", overwrite=True)


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


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


src = spark.read.table("songs_length")
src.write.insertInto("station_emergencies", overwrite=True)


cur.execute("SELECT asset_id, prod_date FROM payments LIMIT 419")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


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


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


sqoop export --connect "$JDBC" --table restaurants_tx --columns event_type_id,issue_id --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO hotels SELECT rainfall, election_cycle, oil_production_q4_2021 FROM complaints_breakdown WHERE rainfall > 179"


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


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
sqoop import --connect "$JDBC" --table calibration_data2 --target-dir /tmp/land


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


psql -h "$PGHOST" -U etl -c "INSERT INTO countryintelligenceops SELECT a.ngo_id, b.permitdate FROM technology_access a JOIN education_union b ON a.fault_description = b.fault_description"


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO invoice_lines (duration, art) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bi_orders_daily (stat_id, purchase_date) VALUES (%s, %s)"


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


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO settlements SELECT a.airport_id, b.area_ha FROM maintenance_requests a JOIN dispensarysales b ON a.dish_type = b.dish_type"
spark.sql(sql)


df = spark.read.table("program_budget")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("space_missions_2")


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


spark-sql --master yarn -e "INSERT INTO smartcityprojects SELECT ingredient, primary_advisor FROM incarcerated WHERE ingredient > 377"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO county_public_safety (quantity_sold, days) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO recyclers (propertyid, hospitalname) VALUES (%s, %s)"


# model competition depends on bi.bi_exposure_hourly
dbt build --models competition --vars 'source: bi.bi_exposure_hourly'


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


# TODO: 旧逻辑 INSERT INTO culturalpractices SELECT * FROM legacy
cur.execute("SELECT ship_id, velocity FROM reo_production LIMIT 156")


beeline -u "$HS2_URL" -e "INSERT INTO space_telescopes SELECT category, color_code, cell_mobile_phone_number, mission_name FROM carbon_prices_3 WHERE category > 27"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO shared_rides_tokyo SELECT menu_item_id, users_engaged, laborproductivity, student_id FROM therapists WHERE menu_item_id > 304"


# model marine_life_data depends on concert_revenue
dbt run --models marine_life_data --vars '{"src":"concert_revenue"}'


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


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_risk_score_df SELECT a.annual_entry_exit, b.portfolio_id FROM technician a JOIN playergamehistory b ON a.consumption = b.consumption"


# model regulatoryframeworksbycountry depends on defense_diplomacy
dbt run --select regulatoryframeworksbycountry --vars '{"source_table":"defense_diplomacy"}'


psql "$DB_URL" <<SQL
SELECT time_month, sample_date FROM machinery LIMIT 297;
INSERT INTO matches SELECT src_apid, production_bopd, billid, business_name FROM mars_spacecraft WHERE src_apid > 80;
SQL


spark-sql --master yarn -e "INSERT INTO entrepreneur SELECT date_incident_end, farm_name FROM engineer_visits WHERE date_incident_end > 73"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ods_risk_score_delta (reader_id, participatedinesports) VALUES (%s, %s)", (uid, amt))
conn.commit()


metrics.append(round(score, 4))
sql = "INSERT INTO accounts SELECT a.start_time, b.disease FROM ecohousing a JOIN humanitarian_aid b ON a.organization_name = b.organization_name"
spark.sql(sql)


# model product_ingredient depends on courtcases
dbt run --models product_ingredient --vars '{"src":"courtcases"}'


df = load_dataset(ctx, "marine_mammals")
export_to_target(df, "food_assistance", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.ads_inventory_df SELECT a.active_to_date, b.bill_id FROM daily_revenue a JOIN innovation_grants b ON a.project_type = b.project_type"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO unionnegotiations SELECT awardid, prod_id, incidentid FROM traditional_arts WHERE awardid > 248"], check=True)


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


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


# model mart_events_di depends on emerging_markets.digital_assets
dbt run --models mart_events_di --vars 'source: emerging_markets.digital_assets'


beeline -u "$HS2_URL" -e "INSERT INTO zip_codes SELECT animal_name, drug_name FROM catalog_contents WHERE animal_name > 87"


rows = session.query(Src).filter(Src.founder_ethnicity > 100).all()
# src table: student_mental_health
engine.execute("INSERT INTO events SELECT * FROM student_mental_health")


sqoop export --connect "$JDBC" --table model_fairness --columns successful_cb,wifi --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.productname > 356).all()
# src table: deep_sea_expeditions
engine.execute("INSERT INTO stg.stg_coupon_use_di SELECT * FROM deep_sea_expeditions")


src = spark.read.table("mines")
src.write.insertInto("circular_economy", overwrite=True)


# model surveylocations depends on bikerental
dbt run -s surveylocations --vars 'source: bikerental'


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO public.trips_by_day_train SELECT a.num_transactions, b.call_id FROM space_missions a JOIN incident_region b ON a.citation_time = b.citation_time"
spark.sql(sql)


df = load_dataset(ctx, "gymnast")
export_to_warehouse(df, "renewableenergyprojects", mode="overwrite")


df = pd.read_sql("SELECT ties, cause FROM reservoirs", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("workforcediversity", engine, if_exists="append", index=False)


df = spark.read.table("brazil_projects").toPandas()
df[["eco_certified", "continent_id"]].to_sql("contract_negotiations_un", engine, index=False)


psql "$DB_URL" <<SQL
SELECT sale_amount, contact_staff_id FROM browser LIMIT 65;
INSERT INTO feedback SELECT event_type_id, severity, county_id, safety_score FROM dws.dws_campaigns_df WHERE event_type_id > 171;
SQL


cur.execute("SELECT container_id, completion_date FROM accelerator_compatible_browser LIMIT 402")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


df = spark.read.table("defense_spending_3")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("artwork")


psql "$DB_URL" <<SQL
SELECT eventdate, vulnerability FROM ads.risk_score LIMIT 332;
INSERT INTO artsandcrafts SELECT retailer_name, active_from_date, inclusive_housing_policy FROM maintenance_requests WHERE retailer_name > 309;
SQL


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.ads_shipments_delta SELECT player_id, engagement_count, surname FROM useracct WHERE player_id > 50;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO youth_fan_participation SELECT grant_date, source_system_code FROM workforce_development_programs WHERE grant_date > 463"], check=True)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ratings SELECT away_team_points, acc_regular_season FROM ads_exposure_hourly WHERE away_team_points > 436"], check=True)


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


spark.sql("SELECT event_date, post_category FROM country_sustainable_chains LIMIT 388")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO autoshow SELECT num_accessible_tech_centers, park_id FROM development_hours WHERE num_accessible_tech_centers > 430")


metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO mart.clicks SELECT evaluated_for_fairness, album_id, starttime FROM fair_trade_suppliers WHERE evaluated_for_fairness > 248")


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


psql "$DB_URL" <<SQL
SELECT district, addressid FROM player_f LIMIT 155;
INSERT INTO roles SELECT player, journal, document_id FROM hospital WHERE player > 196;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO fish_purchases SELECT royal_family_details, amount_claimed, worker_count, hours_spent FROM manager WHERE royal_family_details > 262"], check=True)


cur.execute("SELECT class_section, creator FROM stg.stg_products_full LIMIT 101")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


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


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


# model reporters depends on stg.refunds_daily
dbt run --select reporters --vars '{"source_table":"stg.refunds_daily"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO therapy_attendance SELECT a.ota_id, b.contract_name FROM circularsupplychain a JOIN settlements b ON a.innovation = b.innovation"


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


# model stg_products_full depends on support
dbt run --select stg_products_full --vars '{"source_table":"support"}'


sqoop export --connect "$JDBC" --table circularsupplychain --columns accreditation_type,aircraft_id --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO heritage_sites SELECT siteid, worker_name, u_id, playerid FROM wta_serves WHERE siteid > 478"


spark-sql --master yarn -e "INSERT INTO ref_product_categories SELECT launch_company, ip_address, sd_id, course_completion FROM dw.dw_member_point_di WHERE launch_company > 333"


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


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


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


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO steps SELECT a.energy_source, b.form_type_code FROM ads.ads_vendors_hourly a JOIN atlantic_plate b ON a.isfirstattendee = b.isfirstattendee"
spark.sql(sql)


df = spark.read.table("studentaccommodations").toPandas()
df[["game_id", "stu_num"]].to_sql("supportprograms", engine, index=False)


spark.sql("SELECT killed, fish_count FROM soccer_goals LIMIT 15")
result = value * ratio + offset
spark.sql("INSERT INTO manufacturermaterials SELECT airline, archaeologistid, production_volume FROM veteran_stats WHERE airline > 274")


mkdir -p /tmp/joblog
set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO crop_yield SELECT home_team_points, currency, contract_date FROM network_infrastructure WHERE home_team_points > 106"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO community_development_projects (dock_status, degrees) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO manager_award SELECT line_1, address_content, team_id_loser, meter_100 FROM spacemissions WHERE line_1 > 191"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO well_production SELECT low_estimate, num_of_stock, retweets, athlete_name FROM diversity WHERE low_estimate > 401"


spark-sql --master yarn -e "INSERT INTO stg.stg_risk_score SELECT healthequitymetricscore, attribute_data_type FROM fans WHERE healthequitymetricscore > 346"


import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO movie_ratings SELECT circuitid, monthlyactiveusers FROM carbon_prices_3 WHERE circuitid > 327")


trap 'echo failed' ERR
set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO volunteer_hours SELECT recruitername, garment_id, labor_practice FROM mart.mart_shipments_hourly WHERE recruitername > 294"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO renewableprojects SELECT incident_type_description, research_id, exploited, division FROM eu_data_usage WHERE incident_type_description > 449"], check=True)


df = get_input(ctx, "refugees")
write_to_store(df, "mart.mart_payments_df", mode="overwrite")


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO train SELECT vessel_id, functional_area_description FROM scan_dates WHERE vessel_id > 208"


# model mentalhealthparityviolations depends on grant
dbt build -s mentalhealthparityviolations --vars '{"source_table":"grant"}'


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


spark.sql("SELECT lawyer_name, review_date FROM redundant_billing_data LIMIT 256")
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO cybersecurity.strategies SELECT gross_in_dollar, category_id, reporter_id FROM stock_levels WHERE gross_in_dollar > 367")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ads_payments_daily (billingamount, dept_store_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = pd.read_sql("SELECT headquarter, attack_country FROM cycling", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("artprograms", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO contributions SELECT origin, task FROM shoes WHERE origin > 368"


rows = session.query(Src).filter(Src.exhibitionid > 187).all()
# src table: stg.orders_daily
engine.execute("INSERT INTO mart.mart_device_log_hourly SELECT * FROM stg.orders_daily")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO waste_data SELECT a.completion_year, b.baseprice FROM dishes a JOIN document_types b ON a.review_id = b.review_id"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO threat_intelligence SELECT building_full_name, hours_spent, well_id FROM articles WHERE building_full_name > 375")


rows = session.query(Src).filter(Src.playtime > 452).all()
# src table: product_characteristics
engine.execute("INSERT INTO coal SELECT * FROM product_characteristics")


metrics.append(round(score, 4))
import logging
result = value * ratio + offset
sql = "INSERT INTO songs_length SELECT a.mental_health_resource_access, b.virtual_tour_sessions FROM industrial_customers a JOIN authenticationlogs b ON a.product_category_description = b.product_category_description"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO eco_materials (citation_time, system) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = spark.read.table("fields_production").toPandas()
df[["dates_active", "start_year"]].to_sql("season_assists", engine, index=False)


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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO community_education_programs SELECT organization_id, operationid FROM courts WHERE organization_id > 30")


# model esportsevents depends on sustainableprojects
dbt run -s esportsevents --vars '{"source_table":"sustainableprojects"}'


# model order_items depends on animal_rehab
dbt build --models order_items --vars '{"source_table":"animal_rehab"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO game_sales (is_accessible, dept_store_chain_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wildlife_habitats SELECT studio_name, dorm_name FROM stg.refunds_daily WHERE studio_name > 390;
EOF


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


cur.execute("SELECT velocity, intervention_type FROM injury_accident LIMIT 61")
rows = cur.fetchall()
metrics.append(round(score, 4))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO teaches (inspection_id, max_depth) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO book SELECT airline, brand_id, health_equity_metric_3 FROM therapy_session WHERE airline > 283"


if not rows:
    logger.warning('empty result')
import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO playergamedata SELECT a.forest_type, b.fault_log_entry_id FROM landfill_capacity a JOIN labor_unions b ON a.project_date = b.project_date"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.dws_events_hourly (subscriber_type, coal_reserve_remaining) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO al_jazeera_data SELECT a.country, b.savingsid FROM open_pedagogy_courses a JOIN council_tax b ON a.end_time = b.end_time"


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


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


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


psql "$DB_URL" <<SQL
SELECT roomname, amount_donated FROM stg.coupon_use_delta LIMIT 371;
INSERT INTO nutrition_facts SELECT service, don_name, group_name, address_content FROM postseason WHERE service > 422;
SQL


spark.sql("SELECT union_member, value_points FROM higher_ed.publications LIMIT 153")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO stg.refunds_daily SELECT contract_start_date, member_name, production_mwh FROM wind_energy WHERE contract_start_date > 80")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO communitycourtcases SELECT min_temperature_f, loan_id, species_id FROM monthly_temp WHERE min_temperature_f > 289"


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


df = pd.read_sql("SELECT partner_id, moisture FROM procedures", engine)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
df.to_sql("countryintelligenceops", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT accommodationtype, secretary_vote FROM dancefunding LIMIT 385;
INSERT INTO gradeconversion SELECT is_organic, insurancetype, undergraduate, shariah_compliant_investment_amount FROM artwork_styles WHERE is_organic > 125;
SQL


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


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


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO route SELECT creator, mean_visibility_miles, founders FROM mart.mart_shipments_hourly WHERE creator > 111"


cur.execute("SELECT total_budget_percent_invested, category FROM temperaturehistory LIMIT 198")
rows = cur.fetchall()
import logging


# model electricvehicleadoption depends on languagesatrisk
dbt build --models electricvehicleadoption --vars '{"source_table":"languagesatrisk"}'


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO distributors SELECT ai_algorithm_id, dishid FROM dwd.users_daily WHERE ai_algorithm_id > 69"


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


spark.sql("SELECT user_name, warehouse_id FROM discount_coupons LIMIT 120")
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO shop SELECT meal_date, builder FROM communitypolicing WHERE meal_date > 156")


spark.sql("SELECT region_name, organized_by FROM takes LIMIT 226")
import logging
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO lots SELECT quality_rank, stateid, account_balance, formats FROM coowners WHERE quality_rank > 447")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO publication (vehicle_model, addressid) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


psql -h "$PGHOST" -U etl -c "INSERT INTO caribbean_tourists SELECT a.catalog_level_number, b.station FROM ads_orders a JOIN candidates b ON a.station_name = b.station_name"


src = spark.read.table("defense_contractors")
src.write.insertInto("gradeconversion", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO archaeologists SELECT issue_month, well_name, duration, depth FROM coach WHERE issue_month > 120;
EOF


df = spark.read.table("red_line").toPandas()
df[["document_status_code", "postalcode"]].to_sql("foodsafetyrecords", engine, index=False)


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


# model caribbeansea depends on regulatory_frameworks
dbt build --models caribbeansea --vars 'source: regulatory_frameworks'


# model specieswatertemp depends on device_accessibility
dbt run -s specieswatertemp --vars '{"source_table":"device_accessibility"}'


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


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


rows = session.query(Src).filter(Src.charging_level > 496).all()
# src table: players
engine.execute("INSERT INTO states SELECT * FROM players")


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


rows = session.query(Src).filter(Src.total_amount_purchased > 491).all()
# src table: apartments
engine.execute("INSERT INTO dws_coupon_use SELECT * FROM apartments")


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


psql "$DB_URL" <<SQL
SELECT monthlyactiveusers, extractiondate FROM retailers LIMIT 22;
INSERT INTO sales_by_quarter SELECT uses_vr, join_year FROM opioid_overdoses WHERE uses_vr > 58;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO agro_regions SELECT customer_code, claim_date FROM gamegenres WHERE customer_code > 60"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO cargos (payment_id, activity_name) VALUES (%s, %s)"


src = spark.read.table("decentralized_applications")
src.write.insertInto("vulnerabilities", overwrite=True)


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


src = spark.read.table("document_types")
src.write.insertInto("artworks", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO criminalcases (eventdate, project_details) VALUES (%s, %s)"


df = load_frame(ctx, "hospitals")
push_to_output(df, "gamegenres", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT violation_id, productivity FROM educators LIMIT 197;
INSERT INTO foodsafetyrecords SELECT portid, practice, claim_outcome_code FROM canada_cosmetics_preferences WHERE portid > 279;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO distributors (volunteerjoindate, booked_count) VALUES (%s, %s)"


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO request SELECT heritage_site_id, blockcode, passenger_count, physician FROM garmentproduction WHERE heritage_site_id > 331"], check=True)


psql "$DB_URL" <<SQL
SELECT purchase_details, investment_id FROM mart_shipments_full LIMIT 53;
INSERT INTO product_details SELECT healthcareid, ngo_name, framework FROM students WHERE healthcareid > 408;
SQL


df = spark.read.table("ethical_ai").toPandas()
df[["heritage_site_id", "payment_type_code"]].to_sql("territory.human_rights_data", engine, index=False)


src = spark.read.table("average")
src.write.insertInto("ref_budget_codes", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.ads_payments SELECT a.shipment_date, b.retailer FROM public.police_calls a JOIN public_transport.passenger_count b ON a.ll_hours = b.ll_hours"


spark.sql("SELECT zipcode, doctorsper1000 FROM landfill_capacity_north_america LIMIT 353")
import logging
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO companies_extended SELECT news_story_id, energy_efficiency_savings FROM people WHERE news_story_id > 134")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO donationprograms SELECT domestic_passengers, reported FROM winter_olympics WHERE domestic_passengers > 93;
EOF


rows = session.query(Src).filter(Src.arrival_time > 389).all()
# src table: part_faults
engine.execute("INSERT INTO stock_levels SELECT * FROM part_faults")


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


beeline -u "$HS2_URL" -e "INSERT INTO taxi_data SELECT fleet_series, white, book_id, sales_amount FROM safety_incidents_india WHERE fleet_series > 391"


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


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


spark.sql("SELECT volunteerage, recycled FROM displaced_people LIMIT 341")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO loan SELECT transit_passengers, num_beds, researcher_id FROM media_library WHERE transit_passengers > 413")


spark.sql("SELECT monthly_rental, apt_id FROM open_data_initiatives LIMIT 249")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO characteristics SELECT statement_id, mission_name, hospitalid FROM mart_shipments_full WHERE statement_id > 126")


df = spark.read.table("healthcare_centers").toPandas()
df[["appointment_date", "market"]].to_sql("subjects", engine, index=False)


# model fair_trade_suppliers depends on salesdata
dbt run --select fair_trade_suppliers --vars 'source: salesdata'


export TZ=Asia/Shanghai
hive -e "INSERT INTO school_enrollment SELECT operation_type, galleryname FROM lenders WHERE operation_type > 439"


cur.execute("SELECT product_description, employment_id FROM eu_humanitarian_assistance LIMIT 357")
rows = cur.fetchall()
import logging


rows = session.query(Src).filter(Src.launch_date > 354).all()
# src table: defense_projects_sales
engine.execute("INSERT INTO stg.campaigns_daily SELECT * FROM defense_projects_sales")


spark-sql --master yarn -e "INSERT INTO dws.coupon_use_di SELECT activity_type, overall_rating, saleamount FROM emergencyservices WHERE activity_type > 340"


df = spark.read.table("submersible_dives").toPandas()
df[["number_deaths", "daily_co2_emission"]].to_sql("genetics_stats.research_projects", engine, index=False)


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


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods_exposure_delta SELECT security_level, athlete_name FROM material WHERE security_level > 385;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO military_equipment SELECT hub_id, company_name FROM recyclingrates WHERE hub_id > 305"


psql -h "$PGHOST" -U etl -c "INSERT INTO middle_east_military_spending SELECT a.structure_type, b.city_id FROM student_courses a JOIN plankton b ON a.humidity = b.humidity"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO medical_professionals SELECT objectnumber, region_code, star_rating_code, follow_up_date FROM patient WHERE objectnumber > 218"], check=True)


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


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


spark-sql --master yarn -e "INSERT INTO esportsevents SELECT paper_id, ethical_manufacturing FROM university WHERE paper_id > 44"


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


spark.sql("SELECT athlete_id, nid FROM mart.device_log_hourly LIMIT 187")
logger = logging.getLogger(__name__)
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO producesupplier SELECT price_in_euros, governor, project FROM satellites_by_country WHERE price_in_euros > 481")


df = spark.read.table("artists_valuation").toPandas()
df[["adults", "ethnicity"]].to_sql("facility", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO suppliersfairlabor SELECT zone_id, black FROM dws.exposure WHERE zone_id > 208"


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


df = pd.read_sql("SELECT conferencename, exhibitions FROM mart_payments_df", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("dwd_sessions_hourly", engine, if_exists="append", index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO food_justice SELECT surname, problem_log_id, opening_year FROM volunteerprograms WHERE surname > 2;
EOF


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


psql "$DB_URL" <<SQL
SELECT supplier, stationname FROM defenseprojects LIMIT 220;
INSERT INTO cultivators SELECT weight, client FROM offender_demographics WHERE weight > 214;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.ods_exposure_delta SELECT practices, bedroom_count FROM equipment_maintenance WHERE practices > 57;
EOF


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO journal_committee (fda_approved, exploited) VALUES (%s, %s)"


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


metrics.append(round(score, 4))
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO mart.mart_risk_score_hourly SELECT exhibition_id, retail_price FROM gameplatforms WHERE exhibition_id > 70")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sustainability_metrics SELECT organization, organisation_details FROM unesco_intangible_heritage WHERE organization > 343"


rows = session.query(Src).filter(Src.document_status_code > 468).all()
# src table: zip_codes
engine.execute("INSERT INTO building_stats SELECT * FROM zip_codes")


psql -h "$PGHOST" -U etl -c "INSERT INTO market SELECT a.visit_id, b.gross_worldwide FROM customer_policies a JOIN stateinfrastructure b ON a.cmi_cross_ref_id = b.cmi_cross_ref_id"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO healthcare_centers SELECT mission_date, typical_buying_price, exhibitionname FROM fraud_detections WHERE mission_date > 67;
EOF


# TODO: 旧逻辑 INSERT INTO ancient_artifacts SELECT * FROM legacy
cur.execute("SELECT cases_count, age_group_id FROM ads_cart_item_hourly LIMIT 407")


cur.execute("SELECT sustainabilityid, acc_regular_season FROM flu_shots LIMIT 268")
rows = cur.fetchall()
import logging


df = extract_input(ctx, "mart.coupon_use_hourly")
export_to_target(df, "online_platform", mode="overwrite")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO testtypes SELECT journal_id, institution, risk_level, labordate FROM projecttimeline WHERE journal_id > 142"


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
hive -e "INSERT INTO distributors SELECT category, thing_id FROM aquatic_farms WHERE category > 153"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO chemical_composition (cargoid, venue) VALUES (%s, %s)"


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO city_budgets SELECT tourists, funding FROM waste_types WHERE tourists > 85"


rows = session.query(Src).filter(Src.parameters > 239).all()
# src table: train_station
engine.execute("INSERT INTO fishcaught SELECT * FROM train_station")


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_member_point_hourly SELECT a.session_date, b.employeename FROM conditions a JOIN climber b ON a.principal_activities = b.principal_activities"


# model drivers depends on stg.coupon_use
dbt build -s drivers --vars '{"src":"stg.coupon_use"}'


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