mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO wastewater_treatment_plants SELECT vehicle_model, galleryname FROM medical_professionals WHERE vehicle_model > 415"


sqoop export --connect "$JDBC" --table smartcitytech --columns sessionid,wellname --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO urban_transportation SELECT policy, policytype, diet, team_name FROM jupiter_missions WHERE policy > 58"


spark.sql("SELECT target_id, host_city FROM bi.device_log LIMIT 337")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO taxi_data SELECT effort_id, species_name FROM member_of WHERE effort_id > 444")


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO habitat_preservation SELECT a.artist_gender, b.cargo_weight FROM temperature_data a JOIN bi_shipments_daily b ON a.num_employees = b.num_employees"
spark.sql(sql)


# model donations depends on dws.events
dbt build --select donations --vars '{"src":"dws.events"}'


psql "$DB_URL" <<SQL
SELECT pets_allowed_yn, attribute_id FROM wildlife_sanctuaries LIMIT 301;
INSERT INTO item_inventory SELECT playerregion, policy_count, import_country FROM grant WHERE playerregion > 1;
SQL


metrics.append(round(score, 4))
spark.sql("INSERT INTO restaurant SELECT launch_agency, item FROM marketingbudget WHERE launch_agency > 224")


spark.sql("SELECT use_date, trade_name FROM mart_refunds LIMIT 455")
import logging
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO specieswatertemp SELECT sale_volume, chargeable_amount, treatment_date, investors FROM mart.mart_products_df WHERE sale_volume > 195")


df = spark.read.table("ocean_acidification").toPandas()
df[["time_of_day", "site_id"]].to_sql("economic_diversification", engine, index=False)


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


# TODO: 旧逻辑 INSERT INTO preferences SELECT * FROM legacy
cur.execute("SELECT last_workout_date, ai_powered_features FROM security_incidents LIMIT 88")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dwd.dwd_cart_item_di SELECT donationdate, team_id_br, company_name FROM arctic_weather WHERE donationdate > 331"


df = spark.read.table("dwd.users_daily")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("ods.ods_risk_score_full")


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


psql "$DB_URL" <<SQL
SELECT cargo, policyholderid FROM race LIMIT 14;
INSERT INTO civilcases SELECT follow_up_date, ingredient_id, is_autonomous FROM participation WHERE follow_up_date > 63;
SQL


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO instructor SELECT a.star_rating_description, b.funding_received FROM certificate a JOIN aus_wellbeing b ON a.founder_identifies_as_lgbtq = b.founder_identifies_as_lgbtq"
spark.sql(sql)


src = spark.read.table("site")
src.write.insertInto("light_rail_lines", overwrite=True)


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


mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO military_contracts SELECT inventoryid, employee, donor_program FROM baseball_teams WHERE inventoryid > 401"


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


spark-sql --master yarn -e "INSERT INTO precipitation_data SELECT visit_month, founding_year FROM licenses WHERE visit_month > 357"


spark-sql --master yarn -e "INSERT INTO tweets SELECT game_id, blockfloor, staff_details FROM dancefunding WHERE game_id > 176"


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO virtual_tour_offers (business_id, document_name) VALUES (%s, %s)"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO maintenance_engineers (creator, dock_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table environmental_impact_stats --columns tank,cargoid --export-dir /warehouse/stage


cur.execute("SELECT steps, green_building_id FROM production_rare_earth_elements LIMIT 413")
rows = cur.fetchall()
result = value * ratio + offset
import logging
threshold = cfg.get('threshold', 0.5)


spark-sql --master yarn -e "INSERT INTO playerscores SELECT artworkname, customer_first_name, airline FROM african_union_countries WHERE artworkname > 200"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sports_events SELECT tripid, recycler_id, fabricid FROM green_projects WHERE tripid > 140"


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO models_safety SELECT a.store_id, b.base_name FROM workerbuildings a JOIN dwd.dwd_inventory_hourly b ON a.item_type = b.item_type"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO spacecraftspeed (aid_name, daily_sales) VALUES (%s, %s)"


df = fetch_dataset(ctx, "playergamedata")
persist_to_output(df, "program_funding_2", mode="overwrite")


# model shipments_df depends on climate_data
dbt run --select shipments_df --vars '{"src":"climate_data"}'


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


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


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


psql "$DB_URL" <<SQL
SELECT data_usage, detection_date FROM farmers_india LIMIT 409;
INSERT INTO yoga SELECT exploited, deliveryid, next_maintenance FROM team_members WHERE exploited > 429;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO flight_emissions SELECT floor_exercise_points, extraction_date FROM pilot_record WHERE floor_exercise_points > 214;
EOF


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO professor SELECT clientid, participant_type_code, theme FROM vehiclemodels WHERE clientid > 422;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO creative_ai (labor_cost, trial_year) VALUES (%s, %s)"


beeline -u "$HS2_URL" -e "INSERT INTO student_program_mapping SELECT stu_num, visitor_country, acidity_level, suburb FROM drug_sales WHERE stu_num > 27"


cur.execute("SELECT product_size, game_genre FROM excavations LIMIT 49")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cargo_handling SELECT development_type, medicine_id FROM west_providers WHERE development_type > 434"


df = spark.read.table("product_review").toPandas()
df[["project_details", "artifact_name"]].to_sql("community.donors", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO pollution_initiatives SELECT inspection_date, booking_status_code, lname FROM model_data WHERE inspection_date > 428;
EOF


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


trap 'echo failed' ERR
hive -e "INSERT INTO dailystreams SELECT taskdate, green_building_certified, material_date, technique_id FROM book WHERE taskdate > 463"


spark-sql --master yarn -e "INSERT INTO concentrateprices SELECT production_rate, recycled, origin_city, vessel_name FROM yttrium_production WHERE production_rate > 15"


metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO swimmer SELECT airport_id, description FROM mart_refunds WHERE airport_id > 390")


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


df = pd.read_sql("SELECT sponsor_name, safety_record FROM camera_lens", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("platform_production", engine, if_exists="append", index=False)


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


# TODO: 旧逻辑 INSERT INTO safetyorgs SELECT * FROM legacy
cur.execute("SELECT city_population, genre_is FROM mental_health_professionals_2 LIMIT 492")


df = source_input(ctx, "travel_advisory")
save_to_sink(df, "satellites_in_orbit", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO fish_biomass SELECT community_size, handling_id, fine, gender FROM dw.dw_coupon_use_daily WHERE community_size > 99"


export TZ=Asia/Shanghai
hive -e "INSERT INTO stg.stg_risk_score SELECT memory_in_g, habitat, baseprice, silver FROM languages WHERE memory_in_g > 411"


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO threat_intelligence_budget SELECT a.case_outcome, b.video_id FROM laptimes a JOIN ads.ads_member_point_daily b ON a.stageposition = b.stageposition"
spark.sql(sql)


cur.execute("SELECT annual_carbon_offsets, clinic_name FROM discipline_enrollments LIMIT 340")
rows = cur.fetchall()
result = value * ratio + offset
import logging


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


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


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


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


cur.execute("SELECT exhibit_location, savings FROM disabilityadvocacy LIMIT 297")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO dws.payments_delta SELECT age_group_id, student_capacity FROM construction_union WHERE age_group_id > 25")


rows = session.query(Src).filter(Src.wage > 342).all()
# src table: esportsteamsafrica
engine.execute("INSERT INTO facility_production SELECT * FROM esportsteamsafrica")


sqoop export --connect "$JDBC" --table bi.bi_payments_full --columns num_of_staff,operating_system --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table route --columns machine_series,recipient_id --export-dir /warehouse/stage


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


cur.execute("SELECT dish, app_name FROM ai_safety_incidents LIMIT 112")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


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


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


src = spark.read.table("dwd.users_daily")
src.write.insertInto("race_ethnicity", overwrite=True)


src = spark.read.table("military_technology_projects")
src.write.insertInto("customer_size_diversity", overwrite=True)


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


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


rows = session.query(Src).filter(Src.zone_id > 24).all()
# src table: ads.users_full
engine.execute("INSERT INTO item SELECT * FROM ads.users_full")


df = spark.read.table("mart.vendors_full").toPandas()
df[["implementation_year", "hours_contributed"]].to_sql("gardens", engine, index=False)


# TODO: 旧逻辑 INSERT INTO construction_union SELECT * FROM legacy
cur.execute("SELECT building_short_name, pollution_id FROM offender_demographics LIMIT 39")


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


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


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


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


import logging
sql = "INSERT INTO goals SELECT a.program_name, b.clinic_name FROM menu_item a JOIN railway b ON a.fund_name = b.fund_name"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO healthcare SELECT * FROM legacy
cur.execute("SELECT co2_emission, store_name FROM mobile_plans LIMIT 123")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd.dwd_device_log_delta (claim_id, race) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO climatefinance SELECT capacity_mw, asset_name, invoice_details FROM property_community WHERE capacity_mw > 421;
EOF


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


spark-sql --master yarn -e "INSERT INTO industry_funding SELECT student_id, friend FROM chip_model WHERE student_id > 65"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.risk_score_df SELECT customer_country, channel FROM renewable_energy_projects WHERE customer_country > 78"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO album (fair_trade, fueldate) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model contract_transactions depends on mart_exposure_di
dbt run --models contract_transactions --vars 'source: mart_exposure_di'


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


psql "$DB_URL" <<SQL
SELECT floor_area_m2, ties FROM spacecraft_temperatures LIMIT 306;
INSERT INTO cybersecurity_strategies SELECT artworkname, home_team, medical_professional_id FROM customer_size_diversity WHERE artworkname > 379;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO roles SELECT a.trial_id, b.dock_count FROM music_streaming a JOIN temperaturehistory b ON a.asset_make = b.asset_make"


psql "$DB_URL" <<SQL
SELECT birth_date, weeks_on_top FROM ods_risk_score_delta LIMIT 258;
INSERT INTO dwd.exposure_hourly SELECT sample_date, judge_state FROM inclusive_housing WHERE sample_date > 19;
SQL


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


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


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO cybersecurityincidents SELECT a.name_last, b.stateid FROM attendees a JOIN menu_item b ON a.role_description = b.role_description"


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


df = pd.read_sql("SELECT * FROM bi.events_delta", conn)
df.to_sql("dws.dws_shipments_full", conn, if_exists="replace", index=False)


cur.execute("SELECT individual_last_name, actor_id FROM oceania_countries LIMIT 410")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
import logging


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


# model sanctuaryanimals depends on wins
dbt run -s sanctuaryanimals --vars '{"source_table":"wins"}'


cur.execute("SELECT waste_generation, outcome_id FROM militarycyberops LIMIT 157")
rows = cur.fetchall()
import logging
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


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


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


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


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


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO labor_cost (retailer_name, screen_mode) VALUES (%s, %s)"


cur.execute("SELECT arrival, home_games FROM criminalcases LIMIT 33")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO fish_farms SELECT organized_by, mental_health_rating FROM genetics_stats.research_projects WHERE organized_by > 436")


psql "$DB_URL" <<SQL
SELECT productid, productlaunchdate FROM nursing_homes LIMIT 346;
INSERT INTO chemical_production_5 SELECT quantitysold, assessment_date, membername FROM animals WHERE quantitysold > 374;
SQL


sqoop export --connect "$JDBC" --table evsales --columns customer_address,model_name --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT transaction_volume, itemid FROM ngo_funding LIMIT 24;
INSERT INTO donationsbycause SELECT coowner_name, departure_date, document_code FROM intelligence_personnel WHERE coowner_name > 431;
SQL


df = pd.read_sql("SELECT status_of_thing_code, currency FROM bi.bi_payments_delta", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("drugs", engine, if_exists="append", index=False)


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


sqoop export --connect "$JDBC" --table parking_fines --columns sales_amount,publish_date --export-dir /warehouse/stage


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


df = spark.read.table("ads.ads_users_hourly").toPandas()
df[["source_u_id", "cause"]].to_sql("marine_species_indian", engine, index=False)


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


cur.execute("SELECT bioprocess_id, organic FROM player_stats LIMIT 7")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stg.stg_products_delta (seal_species, home_city) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO ingredient_sourcing SELECT a.astronaut, b.average FROM ods_products_delta a JOIN team_members b ON a.schedule = b.schedule"


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


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


df = spark.read.table("wholesale_orders").toPandas()
df[["mining_operation", "pname"]].to_sql("tb_cases", engine, index=False)


# model flight_safety depends on diversity
dbt run -s flight_safety --vars 'source: diversity'


spark-sql --master yarn -e "INSERT INTO submarine_canyons SELECT first_year, tonnage FROM cargos WHERE first_year > 162"


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


echo "dry-run: INSERT INTO companies_extended SELECT 1"
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog


echo "dry-run: INSERT INTO city.community_policing SELECT 1"
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}


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


df = spark.read.table("campaigns_2023")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("list")


df = spark.read.table("climatefinance").toPandas()
df[["contract_start", "grantid"]].to_sql("open_pedagogy", engine, index=False)


sqoop export --connect "$JDBC" --table dw.dw_risk_score_full --columns name_last,founding_location --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO artifacts SELECT plantid, count_time, num_stops, date_payment_made FROM daily_industrial_water_usage WHERE plantid > 184"


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


# model exhibition_record depends on artsheritage
dbt run --select exhibition_record --vars '{"src":"artsheritage"}'


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


psql "$DB_URL" <<SQL
SELECT production_value, main_industry FROM has_amenity LIMIT 136;
INSERT INTO issues SELECT class_code, medicine_id FROM vaccinations WHERE class_code > 109;
SQL


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO bi.products_daily SELECT a.attack_count, b.inclusive FROM broadband_subscribers a JOIN ods.ods_payments_full b ON a.capacity = b.capacity"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO exhibition_visits SELECT cargo_weight, publication_date FROM stg.campaigns_df WHERE cargo_weight > 480"], check=True)


spark.sql("SELECT sex, union_name FROM rating LIMIT 98")
import logging
spark.sql("INSERT INTO artistsdemographics SELECT policy_description, lanes, post_date FROM customers_cards WHERE policy_description > 173")


rows = session.query(Src).filter(Src.emp_id > 360).all()
# src table: renewable_energy_projects
engine.execute("INSERT INTO department_stores SELECT * FROM renewable_energy_projects")


df = source_frame(ctx, "fossil_fuel_vehicles_japan")
upsert_to_output(df, "public.crime_types", mode="overwrite")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO busmaintenance (vendorname, coalquantity) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


cur.execute("SELECT build_date, chemical FROM station LIMIT 344")
rows = cur.fetchall()
import logging
logger = logging.getLogger(__name__)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.inventory_hourly (shipped_to, ship_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table patient_satisfaction --columns author_or_editor,call_id --export-dir /warehouse/stage


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


import logging
sql = "INSERT INTO permian_basin SELECT a.strain_name, b.supplier_phone FROM discipline_enrollments a JOIN emergency_responses b ON a.song_release_year = b.song_release_year"
spark.sql(sql)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO community_programs (warehouseid, refugee_id) VALUES (%s, %s)"


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


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO mart.mart_users_di SELECT chair_name, exit_type, property_price, communityid FROM communityengagementmetrics WHERE chair_name > 190"


df = pd.read_sql("SELECT caseid, tonnage FROM permian_basin", engine)
result = value * ratio + offset
df.to_sql("ads.ads_vendors_hourly", engine, if_exists="append", index=False)


df = read_input(ctx, "restaurant")
dump_to_store(df, "match_result", mode="overwrite")


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


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


rows = session.query(Src).filter(Src.degrees > 101).all()
# src table: all_documents
engine.execute("INSERT INTO tourist_destinations SELECT * FROM all_documents")


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


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


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


spark-sql --master yarn -e "INSERT INTO green_building_materials SELECT pd_id, contractor, donor_country FROM support_groups WHERE pd_id > 157"


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


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


rows = session.query(Src).filter(Src.total_budget_percent_budgeted > 417).all()
# src table: food_justice
engine.execute("INSERT INTO militaryequipmentsales SELECT * FROM food_justice")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO user_likes SELECT location_text, job, trip_id FROM country_renewable_energy WHERE location_text > 298;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO market SELECT a.supplierid, b.lawyer_name FROM soccer_teams a JOIN humanitarian_assistance b ON a.cruelty_free = b.cruelty_free"


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


rows = session.query(Src).filter(Src.clublocation > 439).all()
# src table: intelligence_agents
engine.execute("INSERT INTO caseattorneys SELECT * FROM intelligence_agents")


cur.execute("SELECT nickname, port_name FROM dwd.dwd_exposure_df LIMIT 111")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
import logging


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO address SELECT is_unionized, customer_number FROM police_officers_tx WHERE is_unionized > 201;
EOF


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


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
result = value * ratio + offset
sql = "INSERT INTO claims_processing_stages SELECT a.base_id, b.sculpture_name FROM trips a JOIN uniteddefense.equipmentsales b ON a.handling_id = b.handling_id"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO attorney_billing SELECT sustainability_initiative_id, matchdate, galleryid, citation_time FROM atlantic_ocean_fish WHERE sustainability_initiative_id > 117"], check=True)


spark.sql("SELECT retailer, faculty_id FROM brands LIMIT 337")
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO ref_locations SELECT country_of_origin, fabricid, aircraft_type, tech_id FROM editor WHERE country_of_origin > 132")


# TODO: 旧逻辑 INSERT INTO languages SELECT * FROM legacy
cur.execute("SELECT role_name, headquarters FROM military_bases LIMIT 31")


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


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO stg.risk_score_hourly SELECT created_date, sustainabilityrating FROM fabrics WHERE created_date > 470"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO e_scooter_trips (retailer, union_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


rows = session.query(Src).filter(Src.image_date > 427).all()
# src table: dws.dws_orders_full
engine.execute("INSERT INTO weapons SELECT * FROM dws.dws_orders_full")


export TZ=Asia/Shanghai
trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO emissions SELECT labor_practice, vehicletype FROM workout WHERE labor_practice > 45"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_users SELECT vehicle_id, destinationid FROM song WHERE vehicle_id > 352;
EOF


rows = session.query(Src).filter(Src.num_transactions > 134).all()
# src table: ods_member_point_full
engine.execute("INSERT INTO inmates SELECT * FROM ods_member_point_full")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO communitydevelopment (capacity_mw, mine_name) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT race, disaster_id FROM storage_tech LIMIT 257;
INSERT INTO architect SELECT regulation, claim_date, time_of_day, is_sustainable FROM bike_station_info WHERE regulation > 222;
SQL


spark.sql("SELECT language_id, line_name FROM satellite_missions_large LIMIT 418")
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO brand_info SELECT lastname, cargo_weight, forest_id FROM donationsbycause WHERE lastname > 199")


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


beeline -u "$HS2_URL" -e "INSERT INTO algorithmic_fairness SELECT community_id, astronaut_name, trench_name FROM bus_fares WHERE community_id > 203"


df = source_table(ctx, "public.collected_fare")
sink_to_warehouse(df, "party_forms", mode="overwrite")


rows = session.query(Src).filter(Src.cityname > 214).all()
# src table: employeedata
engine.execute("INSERT INTO conditions SELECT * FROM employeedata")


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


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


# model city depends on mart.shipments_delta
dbt build -s city --vars '{"source_table":"mart.shipments_delta"}'


df = extract_dataset(ctx, "smart_city_projects")
save_to_target(df, "green_projects", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO worker_scores SELECT fund_name, trip_date, line_1_number_building, num_of_component FROM bi.bi_sessions_daily WHERE fund_name > 10"], check=True)


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO topublictransportation SELECT genderid, booking_start_date, annual_carbon_offsets FROM instructor WHERE genderid > 118"


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mission SELECT line_name, team_id_br, operating_system, outcome_id FROM company_info WHERE line_name > 76"], check=True)


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


mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO menu_item SELECT emp_fname, last_maintenance FROM manufacturermaterials WHERE emp_fname > 306"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO dwd.dwd_campaigns SELECT round_type, building_address, team, productname FROM fish_purchases WHERE round_type > 182")


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


spark.sql("SELECT movie_id, parent_organization_id FROM ads.ads_exposure_di LIMIT 143")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO stg.stg_users_full SELECT no_of_customers, investor_id, statement_details, organizationid FROM virtual_tourism WHERE no_of_customers > 411")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO wholesale_orders (research_name, ll_hours) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO carbon_offset_south_america SELECT tripid, max_gust_speed_mph, exhibitioncountry FROM ads.ads_exposure_daily WHERE tripid > 257"], check=True)


mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO transportation SELECT gender_diversity, clean_jerk, staff_details FROM organisations WHERE gender_diversity > 484"


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


df = pd.read_sql("SELECT issue_id, serviceid FROM sustainableprojects", engine)
metrics.append(round(score, 4))
df.to_sql("deliveryaddresses", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO recovery_program (averagespeed, menucategory) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT aircraft, sale_quantity FROM supportservices LIMIT 95")
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO survey_data SELECT num_of_component, credit_score, fastestlapspeed, socially_responsible FROM landfillcapacitybycountry WHERE num_of_component > 185")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO canada_tech SELECT founders_lgbtq, carbon_offset_tons FROM fan_purchases WHERE founders_lgbtq > 69;
EOF


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


df = pull_frame(ctx, "incident_region")
export_to_target(df, "ticketspending", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO stores_2 SELECT minename, sustainabilityrating, forest_id FROM vessels_2 WHERE minename > 19"


psql -h "$PGHOST" -U etl -c "INSERT INTO underwater_trenches SELECT a.water_depth, b.event_type_id FROM urban_transportation a JOIN design_standards b ON a.num_students = b.num_students"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO traditional_arts (devices, tour_type) VALUES (%s, %s)"


cur.execute("SELECT treasurer_vote, donationid FROM exhibition_visitors LIMIT 148")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
result = value * ratio + offset
import logging


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO species_data (hours_served, playdate) VALUES (%s, %s)"


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


spark.sql("SELECT governor, mascot FROM us_cities LIMIT 184")
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO climate_adaptation_projects SELECT employeeid, contract_value, date_incident_end, tour_type FROM tb_reports WHERE employeeid > 305")


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO genetics.projects SELECT coach_name, hours FROM indigenouscommunities WHERE coach_name > 402")


cur.execute("SELECT community_id, complaint_date FROM vehicle_registrations LIMIT 433")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))


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


psql "$DB_URL" <<SQL
SELECT practice_id, disease FROM algorithmic_fairness_incidents_monthly LIMIT 405;
INSERT INTO sectors SELECT recruitername, developer_id FROM community_engagement WHERE recruitername > 352;
SQL


src = spark.read.table("price_data")
src.write.insertInto("animal_budget", overwrite=True)


spark.sql("SELECT programname, firm FROM public.trips_by_day_train LIMIT 96")
import logging
spark.sql("INSERT INTO airportdata SELECT grant_amount, report_date, received_date FROM match_result WHERE grant_amount > 370")


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


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


# TODO: 旧逻辑 INSERT INTO courses SELECT * FROM legacy
cur.execute("SELECT participatedinesports, reo_type FROM catalog_contents LIMIT 280")


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO hotel_reviews SELECT vehicletype, catalog_publisher FROM drug_sales WHERE vehicletype > 273"


spark-sql --master yarn -e "INSERT INTO cargos SELECT complete_date, plan_id FROM africa_projects WHERE complete_date > 494"


echo "job start: $(date +%F)"
trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO storage_projects SELECT vin, post_category FROM onlineengagement WHERE vin > 51"


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


df = get_dataset(ctx, "gameattendance")
dump_to_store(df, "wastewater_treatment_plants", mode="overwrite")


df = spark.read.table("candidates").toPandas()
df[["consider_rate", "drugname"]].to_sql("cinema", engine, index=False)


cur.execute("SELECT bookings, gender_diversity FROM eu_data_usage LIMIT 294")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


sqoop export --connect "$JDBC" --table shariah_compliant_loans --columns year_founded,innovation --export-dir /warehouse/stage


df = spark.read.table("field5")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


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


df = spark.read.table("higher_ed.publications").toPandas()
df[["target_name", "consultations"]].to_sql("store", engine, index=False)


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


src = spark.read.table("web_client_accelerator")
src.write.insertInto("mart.campaigns_di", overwrite=True)


rows = session.query(Src).filter(Src.method_id > 381).all()
# src table: technology_access
engine.execute("INSERT INTO stock SELECT * FROM technology_access")


df = pd.read_sql("SELECT project_id, storeid FROM landfill_capacity", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("incarcerated", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO culturalpractices SELECT carrierid, permits_issued FROM public_transportation_routes WHERE carrierid > 320"


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


spark-sql --master yarn -e "INSERT INTO supportprograms SELECT document_description, emissions, ironid FROM stg.risk_score_di WHERE document_description > 315"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO artistsales SELECT to_address, start, end_time, salesperson FROM soilmoisturedata WHERE to_address > 290;
EOF


# TODO: 旧逻辑 INSERT INTO spacemissions SELECT * FROM legacy
cur.execute("SELECT hotel_name, contractid FROM cuisine LIMIT 306")


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


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


import logging
sql = "INSERT INTO port_office SELECT a.item_sold, b.date_of_notes FROM aus_wellbeing a JOIN visits b ON a.participation_id = b.participation_id"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO browser SELECT wind_speed_mph, driller FROM model_fairness WHERE wind_speed_mph > 334;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO volunteer_hours SELECT brand, fda_approved FROM prepaid_mobile WHERE brand > 469"


rows = session.query(Src).filter(Src.src_apid > 11).all()
# src table: bi.bi_events_daily
engine.execute("INSERT INTO products_in_events SELECT * FROM bi.bi_events_daily")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO investments_esg (stageposition, is_recycled) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO branch SELECT a.id, b.film_id FROM artifactanalysis a JOIN tourismproviders b ON a.region = b.region"


spark.sql("SELECT trip_date, ota_id FROM singer_in_concert LIMIT 447")
import logging
spark.sql("INSERT INTO investor SELECT checkout, governor FROM fault_log_parts WHERE checkout > 335")


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO episodes (custid, savings) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO broadband_customers_global SELECT a.fault_short_name, b.fault_log_entry_datetime FROM exhibition a JOIN stg.stg_clicks_delta b ON a.restaurant = b.restaurant"


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


beeline -u "$HS2_URL" -e "INSERT INTO communityhealthworkerscanada SELECT date_formed, resource, bank_name FROM volunteer_hours WHERE date_formed > 462"


rows = session.query(Src).filter(Src.custid > 6).all()
# src table: healthcare_centers
engine.execute("INSERT INTO urbanagricrop SELECT * FROM healthcare_centers")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd_risk_score_hourly SELECT aid, investmentid, productionrate FROM dwd.coupon_use_full WHERE aid > 290;
EOF


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO vehicle_sales SELECT use_date, closuredate, incidentdate, farm_id FROM militaryoperations WHERE use_date > 175")


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


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


df = pull_input(ctx, "producersnewmexico")
write_to_output(df, "mart.mart_vendors", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO ods.ods_campaigns_delta SELECT a.contract_value, b.prof_num FROM ancient_artifacts a JOIN budgets b ON a.alid = b.alid"


set -euo pipefail
hive -e "INSERT INTO coal_reserves SELECT stat_type, market FROM plants WHERE stat_type > 188"


src = spark.read.table("solana_transactions")
src.write.insertInto("country_labor", overwrite=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO wholesale_orders SELECT end_date, num_owners, cuisine, serviceid FROM mart.mart_payments_df WHERE end_date > 459"


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO menu SELECT a.postal_code, b.project_education FROM bus_routes a JOIN vrplayers b ON a.energy_star_rating = b.energy_star_rating"


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO container_ships SELECT a.work_type, b.item_price FROM participation a JOIN maintenance_engineers b ON a.iata = b.iata"
spark.sql(sql)


df = load_dataset(ctx, "ods.ods_users_daily")
save_to_sink(df, "safety_violations", mode="overwrite")


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


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


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


df = spark.read.table("dws.dws_coupon_use_di").toPandas()
df[["ycard", "payment_type_code"]].to_sql("multimodalhubs", engine, index=False)


src = spark.read.table("stg.stg_inventory_full")
src.write.insertInto("operations", overwrite=True)


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


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


spark-sql --master yarn -e "INSERT INTO roller_coaster SELECT home_games, resolutiondate, policy_type_code FROM biosensor.patents WHERE home_games > 249"


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


sqoop export --connect "$JDBC" --table vesselfuel --columns policy_holder_id,injured --export-dir /warehouse/stage


# TODO: 旧逻辑 INSERT INTO storage_projects SELECT * FROM legacy
cur.execute("SELECT characteristic_id, phone FROM participation LIMIT 228")


src = spark.read.table("artwork")
src.write.insertInto("apac_hotel_views", overwrite=True)


cur.execute("SELECT name, damage_millions_usd FROM ecohousing LIMIT 237")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


cur.execute("SELECT minister, characteristic_data_type FROM employee LIMIT 78")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


psql -h "$PGHOST" -U etl -c "INSERT INTO peakhours SELECT a.testtype, b.max_age FROM mart.mart_refunds_di a JOIN rural_hospitals b ON a.production_qty = b.production_qty"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ads.sessions_hourly (port, quality) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


beeline -u "$HS2_URL" -e "INSERT INTO eventdates SELECT budget_type_description, contractor FROM marine_species WHERE budget_type_description > 124"


rows = session.query(Src).filter(Src.channel > 92).all()
# src table: healthbudget
engine.execute("INSERT INTO marine_mammals SELECT * FROM healthbudget")


src = spark.read.table("regular_order_products")
src.write.insertInto("reo_production", overwrite=True)


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


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


psql "$DB_URL" <<SQL
SELECT drill_count, name_first FROM voting_data LIMIT 175;
INSERT INTO haircaresales SELECT feature_details, engineer_id FROM has_allergy WHERE feature_details > 406;
SQL


cur.execute("SELECT interest_group, project_name FROM passenger_trips LIMIT 55")
rows = cur.fetchall()
result = value * ratio + offset
logger = logging.getLogger(__name__)
import logging


spark.sql("SELECT judge_id, away_team_score FROM wine LIMIT 155")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO dwd.coupon_use_full SELECT num_attendees, time_stamp, restaurant, oct FROM communication_scores WHERE num_attendees > 343")


beeline -u "$HS2_URL" -e "INSERT INTO publications SELECT email, funding_amount, material_type, emp_lname FROM has_allergy WHERE email > 316"


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


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO buildingpermits SELECT discovery_date, rating_id FROM healthcareaccess WHERE discovery_date > 233"


psql "$DB_URL" <<SQL
SELECT citation_time, year_built FROM stg.events_hourly LIMIT 281;
INSERT INTO dwd.inventory_df SELECT container_count, book_title, process_id FROM waterconservation WHERE container_count > 119;
SQL


beeline -u "$HS2_URL" -e "INSERT INTO creative_ai SELECT vrgameid, alert_id, document_type_code FROM country_labor WHERE vrgameid > 307"


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


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 * FROM drivers", conn)
df.to_sql("labor_cost", conn, if_exists="replace", index=False)


cur.execute("SELECT noise_level, request_id FROM cuisine LIMIT 256")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


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


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


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


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


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


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO tokyo_motor_show SELECT branch_id, itemid, secretary_vote FROM fruitimport WHERE branch_id > 228"


cur.execute("SELECT opening_hours, recycler_id FROM bi.bi_events_daily LIMIT 252")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dwd_payments_delta SELECT donationyear, acidity_level, discovered_date FROM solar_plants WHERE donationyear > 47"], check=True)


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO exhibition SELECT minename, local_authority, floors, call_time FROM school_districts WHERE minename > 59"


sqoop export --connect "$JDBC" --table precipitation_data --columns mappingid,petid --export-dir /warehouse/stage


spark.sql("SELECT days_held, inclusive FROM studies LIMIT 462")
metrics.append(round(score, 4))
spark.sql("INSERT INTO product_ingredient SELECT stars, count_date FROM fund_investments WHERE stars > 97")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO program_budget (model_id, diplomacy_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = read_table(ctx, "eco_diversification_investment")
dump_to_target(df, "brand_info", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO menu_engineering SELECT policy_name, register_year, service_type_description FROM africa_schema.african_mines WHERE policy_name > 36"


df = spark.read.table("dw.dw_events_di").toPandas()
df[["event_date", "bedtype"]].to_sql("defense_projects", engine, index=False)


cur.execute("SELECT trainingid, max_speed FROM museums LIMIT 224")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


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


# model regional_archaeologists depends on stg.device_log_df
dbt run --models regional_archaeologists --vars 'source: stg.device_log_df'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.risk_score SELECT zone_id, amount_paid, sex FROM mining_companies WHERE zone_id > 185;
EOF


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


cur.execute("SELECT temporary_acting, org FROM ads LIMIT 193")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO highways (order_item_id, attribute_id) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO african_union_countries (actor_name, sent_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.lastname > 359).all()
# src table: daily_industrial_water_usage
engine.execute("INSERT INTO mental_health_center SELECT * FROM daily_industrial_water_usage")


psql -h "$PGHOST" -U etl -c "INSERT INTO fault_log_parts SELECT a.shipment_year, b.transaction_product FROM show a JOIN miningwaterusage b ON a.line_1 = b.line_1"


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


psql "$DB_URL" <<SQL
SELECT major, component_name FROM supplychainemployees LIMIT 454;
INSERT INTO storage_projects SELECT contract_count, emergency_type, track_id FROM production WHERE contract_count > 59;
SQL


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


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


spark-sql --master yarn -e "INSERT INTO indigenous_food_systems SELECT soil_moisture, vehicle_name, patient FROM safetyorgs WHERE soil_moisture > 242"


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


rows = session.query(Src).filter(Src.region_id > 104).all()
# src table: platformg
engine.execute("INSERT INTO show SELECT * FROM platformg")


spark-sql --master yarn -e "INSERT INTO communityhealthworkers SELECT indigenous, vin, contractor_id FROM art_exhibit_attendance WHERE indigenous > 60"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO concert_events SELECT engagement_date, mission_name, made_in_usa, coach_id FROM diversion_programs WHERE engagement_date > 139;
EOF


# model products_di depends on shops
dbt run -s products_di --vars '{"source_table":"shops"}'


df = spark.read.table("caribbeansea").toPandas()
df[["shipping_mode", "fundingid"]].to_sql("ports", engine, index=False)


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


spark.sql("SELECT propertyid, artifactid FROM video_content LIMIT 425")
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO field_production SELECT cargo_weight, laborproductivity, transaction_amount FROM vr_tech WHERE cargo_weight > 399")


df = get_source(ctx, "haircaresales")
push_to_target(df, "travel_advisory", mode="overwrite")


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


# TODO: 旧逻辑 INSERT INTO waste SELECT * FROM legacy
cur.execute("SELECT campaign_id, product_category_description FROM materials_usage LIMIT 379")


# model efforts depends on staff_department_assignments
dbt run -s efforts --vars '{"source_table":"staff_department_assignments"}'


metrics.append(round(score, 4))
result = value * ratio + offset
sql = "INSERT INTO product_details SELECT a.detection_date, b.issued_date FROM carbon_sequestration a JOIN engineer_skills b ON a.permit_id = b.permit_id"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO erc20_transactions (advocate_id, rural) VALUES (%s, %s)"


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


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO inclusivehousing.affordablehousing SELECT shipment_id, machine_series FROM companies WHERE shipment_id > 368")


beeline -u "$HS2_URL" -e "INSERT INTO healthcare SELECT fiscal_year, document_type_name FROM catalog_structure WHERE fiscal_year > 339"


df = pd.read_sql("SELECT billingcountry, crs_code FROM news_stories", engine)
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("dws.device_log_df", engine, if_exists="append", index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO crypto_transactions SELECT entryid, cases_handled, manager_name, item_sold FROM regulatory_frameworks WHERE entryid > 221"


src = spark.read.table("co2price")
src.write.insertInto("nutritionfacts", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO researcher SELECT events, login_name, sales_details FROM facility WHERE events > 108;
EOF


spark-sql --master yarn -e "INSERT INTO bridges SELECT volunteer_name, thefttype, healthcareid FROM transportation WHERE volunteer_name > 225"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO research_grants SELECT menu_name, totaldonation, trip_distance FROM product_catalog WHERE menu_name > 147;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO grapes SELECT advocate_id, stationid FROM dwd.dwd_coupon_use_df WHERE advocate_id > 252;
EOF


psql "$DB_URL" <<SQL
SELECT year, class_president_vote FROM textile_sourcing LIMIT 132;
INSERT INTO stg.risk_score_hourly SELECT company_type_code, purchases, size_ha FROM autonomousvehicles WHERE company_type_code > 467;
SQL


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


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


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


df = read_source(ctx, "exhibition_record")
export_to_store(df, "ocean_depths", mode="overwrite")


df = pd.read_sql("SELECT releasedate, booking_start_date FROM exit", engine)
logger = logging.getLogger(__name__)
df.to_sql("mart.mart_member_point_hourly", engine, if_exists="append", index=False)


metrics.append(round(score, 4))
spark.sql("INSERT INTO trucks SELECT led_by, call_id, review_id FROM sustainable_urban_properties_2 WHERE led_by > 307")


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


sqoop export --connect "$JDBC" --table uniteddefense.equipmentsales --columns to_address,mean_visibility_miles --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO captain SELECT trench_name, established_date, budget, loan_amount FROM nasa_mars_program WHERE trench_name > 424"


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO unesco_intangible_heritage SELECT screening_id, culturalcompetency, facid, community_center_id FROM street_markets WHERE screening_id > 292;
EOF


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


psql -h "$PGHOST" -U etl -c "INSERT INTO erc20_transactions SELECT a.mission_id, b.sd_id FROM electric_taxis a JOIN recreation_centers b ON a.mental_health_resource_access = b.mental_health_resource_access"


# TODO: 旧逻辑 INSERT INTO routes SELECT * FROM legacy
cur.execute("SELECT document_date, mining_operation_id FROM org_donation LIMIT 234")


logger = logging.getLogger(__name__)
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO department_stores SELECT opening_hours, birthday FROM teams WHERE opening_hours > 124")


rows = session.query(Src).filter(Src.gdp > 105).all()
# src table: students_lifelong_learning
engine.execute("INSERT INTO bikerental SELECT * FROM students_lifelong_learning")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO states SELECT individual_id, horizontal_bar_points, healthequitymetricscore FROM solar_plants WHERE individual_id > 130;
EOF


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


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


echo "dry-run: INSERT INTO round SELECT 1"
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}


psql "$DB_URL" <<SQL
SELECT contributions, rehab_date FROM wellbeing_programs LIMIT 169;
INSERT INTO cargo_tracking SELECT ai_id, framework FROM atlantic_plate WHERE ai_id > 419;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO record SELECT event_type_id, technique_id FROM stations WHERE event_type_id > 114;
EOF


retries = int(os.environ.get('RETRIES', '3'))
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO nomination SELECT enrollment, daily_sales FROM arcticwildlifereserve WHERE enrollment > 450")


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


# model characteristics depends on causes
dbt run -s characteristics --vars 'source: causes'


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


# model zipcodes depends on ref_hotel_star_ratings
dbt run --models zipcodes --vars '{"src":"ref_hotel_star_ratings"}'


df = pull_source(ctx, "ods.shipments_df")
upsert_to_target(df, "arcticwildlifereserve", mode="overwrite")


df = spark.read.table("mailshot_campaigns").toPandas()
df[["funding_round_id", "debate_id"]].to_sql("rural_economy_2", engine, index=False)


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


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


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


rows = session.query(Src).filter(Src.completion_status > 482).all()
# src table: dws.dws_orders
engine.execute("INSERT INTO news_stories SELECT * FROM dws.dws_orders")


src = spark.read.table("disabilityadvocacy")
src.write.insertInto("mart.clicks", overwrite=True)


# TODO: 旧逻辑 INSERT INTO course_attendance SELECT * FROM legacy
cur.execute("SELECT contractor_name, contributiondate FROM doctors LIMIT 197")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart_events_full SELECT org_name, tv_show_id FROM news_reporting WHERE org_name > 136"], check=True)


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


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


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


df = pd.read_sql("SELECT style, virtual_tour_engagement_time FROM emissions", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("safety_incidents_india", engine, if_exists="append", index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO dwd.dwd_orders_daily SELECT a.artist_id, b.emp_hiredate FROM region a JOIN visualartprograms b ON a.allergytype = b.allergytype"


# model material depends on bi.bi_orders_delta
dbt run --models material --vars '{"source_table":"bi.bi_orders_delta"}'


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


df = spark.read.table("clinic_2022")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("item_prices")


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


sqoop export --connect "$JDBC" --table shariahfinance --columns starttime,away_team_score --export-dir /warehouse/stage


spark.sql("SELECT production_budget, agency_id FROM player_award LIMIT 305")
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO stg.stg_events_hourly SELECT tot_cred, game_genre, transactions, individual_name FROM park WHERE tot_cred > 454")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO market_trends (numhearings, subscribe_date) VALUES (%s, %s)"


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
import logging
spark.sql("INSERT INTO threatintelligence SELECT stu_lname, flightid, capacity_percentage, longitude FROM broadband_plans WHERE stu_lname > 306")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO city_properties (projectname, operation_count) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO clothingsales SELECT facility_name, is_unionized, college_location, ship_agent_id FROM bi.users_full WHERE facility_name > 282;
EOF


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


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


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


psql "$DB_URL" <<SQL
SELECT label_id, customer_id FROM safety_incident LIMIT 46;
INSERT INTO landfill_capacity_north_america SELECT product_id, name_last FROM attendance WHERE product_id > 344;
SQL


cur.execute("SELECT platformname, acc_regular_season FROM attorney_billing_rates LIMIT 212")
rows = cur.fetchall()
import logging


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


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO wastewater_facilities SELECT shipped_to, stat_type FROM excavations WHERE shipped_to > 122"


src = spark.read.table("on_call")
src.write.insertInto("oceania_countries", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO developers SELECT candidate_id, dependent_name, treatment_id FROM dws_coupon_use WHERE candidate_id > 467"


rows = session.query(Src).filter(Src.dept_id > 316).all()
# src table: online_travel_agency
engine.execute("INSERT INTO incidents_by_month SELECT * FROM online_travel_agency")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO disaster_response_donations SELECT a.environmental_impact, b.operationdate FROM noise_pollution a JOIN clinical_trials b ON a.date_id = b.date_id"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO underwater_cables SELECT a.other_details, b.plant_id FROM european_healthcare a JOIN salary b ON a.artifactid = b.artifactid"


spark.sql("SELECT maintenance_date, workeridentity FROM mart.mart_device_log LIMIT 271")
result = value * ratio + offset
spark.sql("INSERT INTO member_of SELECT mission, handling_id, loadingstart FROM shariah_compliant_loans WHERE mission > 415")


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


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO insurancetype SELECT fleet_id, awayteamid FROM music_streaming WHERE fleet_id > 429"


logger = logging.getLogger(__name__)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bi.bi_inventory_di SELECT pages_per_minute_color, capacity_percentage, community_name, attorney FROM field WHERE pages_per_minute_color > 492")


df = extract_source(ctx, "departments")
upsert_to_sink(df, "ai_safety_incidents", mode="overwrite")


rows = session.query(Src).filter(Src.number_thousands > 332).all()
# src table: stg.stg_inventory_hourly
engine.execute("INSERT INTO smart_contracts_table SELECT * FROM stg.stg_inventory_hourly")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO news_stories SELECT a.prof_num, b.dob FROM vessel_types a JOIN strandings b ON a.bus_number = b.bus_number"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO expenditure (ticket_id, subscriber_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO design_standards SELECT sessionid, inclusivehousing FROM digitalliteracytraining WHERE sessionid > 334")


df = spark.read.table("bi.users_full").toPandas()
df[["healthcareid", "reviews"]].to_sql("lots", engine, index=False)


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO disinformation_detection SELECT a.last_inspection_date, b.chair_name FROM shariah_compliant_finance a JOIN eventattendance b ON a.institution = b.institution"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO ads.ads_products_full SELECT budgeted, sustainabilityid FROM teacher_professional_development WHERE budgeted > 334"


df = pd.read_sql("SELECT volume, market FROM donationprograms", engine)
metrics.append(round(score, 4))
df.to_sql("dwd.exposure_hourly", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ap_budget SELECT invoice_date, initiative_name, donor_program FROM divisions WHERE invoice_date > 385;
EOF


sqoop export --connect "$JDBC" --table topublictransportation --columns gender_group,rehab_date --export-dir /warehouse/stage


df = spark.read.table("fleet").toPandas()
df[["userid", "claimamount"]].to_sql("dwd.dwd_inventory_hourly", engine, index=False)


df = spark.read.table("sustainabilityratings").toPandas()
df[["launched_year", "num_virtual_tours"]].to_sql("caribbeansea", engine, index=False)


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


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


df = pd.read_sql("SELECT * FROM dws.cart_item_full", conn)
df.to_sql("co2price", conn, if_exists="replace", index=False)


psql "$DB_URL" <<SQL
SELECT mental_health_resource_access, production FROM equipment_sales LIMIT 428;
INSERT INTO mental_health_professionals_2 SELECT university, fare_amount FROM plays_games WHERE university > 156;
SQL


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


df = spark.read.table("habitat").toPandas()
df[["wins", "maintenance_contract_id"]].to_sql("plants", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO timber_sales SELECT astronautid, cb_year FROM drug_approvals WHERE astronautid > 227"


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


sqoop export --connect "$JDBC" --table mexico_regions --columns eco_friendly,sustainable_practice --export-dir /warehouse/stage


# model sustainable_building depends on bi.bi_payments
dbt build -s sustainable_building --vars '{"src":"bi.bi_payments"}'


sqoop export --connect "$JDBC" --table tree_species --columns launch_agency,service_name --export-dir /warehouse/stage


cur.execute("SELECT mineral, cases_handled FROM causes_insert_2 LIMIT 98")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


rows = session.query(Src).filter(Src.galleryname > 257).all()
# src table: defenseprojects
engine.execute("INSERT INTO vehicle SELECT * FROM defenseprojects")


src = spark.read.table("submission")
src.write.insertInto("criticalincidents", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO asset_parts SELECT funding_source_type, store_phone, ingredient_id, street_address FROM dwd.dwd_events_delta WHERE funding_source_type > 88"


# TODO: 旧逻辑 INSERT INTO ocean_shipping.cargo SELECT * FROM legacy
cur.execute("SELECT artworkyear, hashtags FROM waste_generation_metrics LIMIT 199")


spark-sql --master yarn -e "INSERT INTO landfills SELECT routeid, registration_id FROM subway WHERE routeid > 209"


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


sqoop export --connect "$JDBC" --table tourism_activities --columns product_details,participant_id --export-dir /warehouse/stage


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO venture (claim_id, special_features) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO missions SELECT building_manager, total_donation_amount FROM development_hours WHERE building_manager > 275"], check=True)


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO emerging_markets.digital_assets SELECT a.launch_id, b.attorneyid FROM ods.ods_campaigns_df a JOIN labels b ON a.steps = b.steps"
spark.sql(sql)


sqoop export --connect "$JDBC" --table coral_reefs --columns community_center_id,production_volume --export-dir /warehouse/stage


df = spark.read.table("coffee_prices").toPandas()
df[["community_size", "subject_id"]].to_sql("electricvehiclestats", engine, index=False)


cur.execute("SELECT order_shipping_charges, report_id FROM sales_region LIMIT 204")
rows = cur.fetchall()
import logging


spark.sql("SELECT room, birth_place FROM regular_order_products LIMIT 30")
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO storage_projects SELECT artpiecename, filingdate, star_rating_description, sale_revenue FROM contract_timeline WHERE artpiecename > 81")


df = pd.read_sql("SELECT manufacturer_id, num_pallets FROM gamedesigndata", engine)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("user_workouts_march", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ingredientsvegancrueltyfree SELECT water_consumption, bioprocess_name, roomname FROM ads.ads_payments_hourly WHERE water_consumption > 267;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO college SELECT investor_id, lettergrade FROM uel_top10 WHERE investor_id > 437"


df = get_table(ctx, "wellbeing_program_participants")
dump_to_output(df, "country_renewable_energy", mode="overwrite")


# model daily_articles_by_category depends on wearable_metrics
dbt run --models daily_articles_by_category --vars '{"source_table":"wearable_metrics"}'


df = fetch_input(ctx, "travel_advisory")
persist_to_warehouse(df, "shark_biomass", mode="overwrite")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mart.mart_member_point_df (labor_id, established_date) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO light_rail_lines (stars, trip_duration) VALUES (%s, %s)"


df = spark.read.table("furniture").toPandas()
df[["donator_name", "enzyme_id"]].to_sql("participants_in_events", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO food_safety_inspections SELECT spf_level, certification, session_language, total_investment FROM patient_satisfaction WHERE spf_level > 316"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO trainers SELECT assessment_date, education_id FROM org_volunteer WHERE assessment_date > 304;
EOF


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


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


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


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


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


df = pd.read_sql("SELECT donor_country, drought_id FROM ods.ods_device_log_delta", engine)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
df.to_sql("contractorsales", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT recipient, treatment FROM climate_finance_organizations LIMIT 250;
INSERT INTO insurancetype SELECT preference_score, company_name, crs_description FROM aircraftsquadrons WHERE preference_score > 369;
SQL


# TODO: 旧逻辑 INSERT INTO bridges SELECT * FROM legacy
cur.execute("SELECT report_id, sales_count FROM vessel_positions LIMIT 7")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO electric_vehicle_stats SELECT capacity_percentage, catalog_id FROM green_certification WHERE capacity_percentage > 499;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO autoshow (initiativeid, prod_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO students_lifelong_learning SELECT requestid, anomaly FROM energy_efficiency_projects WHERE requestid > 77")


rows = session.query(Src).filter(Src.primary_conference > 49).all()
# src table: miningdepartment
engine.execute("INSERT INTO teams_mascots SELECT * FROM miningdepartment")


df = pd.read_sql("SELECT claim_header_id, ranking FROM therapy_session", engine)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
df.to_sql("chemical_production_5", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT shoe_brand, player_api_id FROM dwd_risk_score_hourly LIMIT 440;
INSERT INTO project_issues SELECT program_type, resource, oppose_rate FROM beverages WHERE program_type > 182;
SQL


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))


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


rows = session.query(Src).filter(Src.rest_id > 300).all()
# src table: open_pedagogy
engine.execute("INSERT INTO beauty_products SELECT * FROM open_pedagogy")


sqoop export --connect "$JDBC" --table conservation --columns running_time,planned_delivery_date --export-dir /warehouse/stage


cur.execute("SELECT charging_level, allergytype FROM event LIMIT 22")
rows = cur.fetchall()
metrics.append(round(score, 4))


mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO league_x SELECT mine_location, company_gender, co_owner_count FROM marketingbudget WHERE mine_location > 255"


df = pd.read_sql("SELECT gross_in_dollar, outcome_id FROM demographics", engine)
import logging
result = value * ratio + offset
df.to_sql("supportprograms", engine, if_exists="append", index=False)


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


# model review depends on customer_contact_channels
dbt build --select review --vars '{"source_table":"customer_contact_channels"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO orders SELECT a.violation_count, b.clean_date FROM buildings a JOIN trees b ON a.rental_date = b.rental_date"


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO bioprocess_engineering SELECT a.founders_lgbtq, b.artworkyear FROM open_pedagogy_courses a JOIN instructor b ON a.numpieces = b.numpieces"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO dwd.dwd_exposure_full SELECT * FROM legacy
cur.execute("SELECT cb_year, founder FROM royal_family LIMIT 465")


psql -h "$PGHOST" -U etl -c "INSERT INTO demographics SELECT a.don_id, b.researcher FROM infra_diversification a JOIN waste_production b ON a.servicename = b.servicename"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO procedures SELECT is_cruelty_free, grant_amount, worker_name, shipmenttype FROM lead_mines WHERE is_cruelty_free > 269"


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


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


spark.sql("SELECT customer_first_name, squadron FROM document_locations LIMIT 419")
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO tokyo_water_consumption SELECT unit_name, judge_state FROM vessel_incident_count WHERE unit_name > 193")


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


df = pd.read_sql("SELECT marketing_region_descriptrion, building_description FROM criticalincidents", engine)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
df.to_sql("musical", engine, if_exists="append", index=False)


result = value * ratio + offset
sql = "INSERT INTO assignedto SELECT a.grant_id, b.trend FROM dams a JOIN seamounts b ON a.research_id = b.research_id"
spark.sql(sql)


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


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO vendorfabrics SELECT addressid, detected_at, date_of_ceremony, incidenttype FROM staff_department_assignments WHERE addressid > 451"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO electric_taxis SELECT origin_city, year_founded, framework_id FROM roads WHERE origin_city > 263"], check=True)


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


result = value * ratio + offset
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 * FROM innovation_projects", conn)
df.to_sql("document_structures", conn, if_exists="replace", index=False)


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO agri_innov SELECT a.risk_level, b.investment_id FROM staff a JOIN hair_care_sales b ON a.date_incident_start = b.date_incident_start"
spark.sql(sql)


metrics.append(round(score, 4))
spark.sql("INSERT INTO chemical SELECT date_problem_reported, breed, club_id FROM customer WHERE date_problem_reported > 80")


df = pd.read_sql("SELECT daily_co2_emission, policy_number FROM policyanalysis", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("design_standards", engine, if_exists="append", index=False)


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


psql "$DB_URL" <<SQL
SELECT donation_date, threat_type FROM stg_payments_hourly LIMIT 321;
INSERT INTO mart.mart_events_di SELECT stocking_density, ironquantity, order_shipping_charges FROM fashion_trend_data WHERE stocking_density > 123;
SQL


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO carbon_offset_programs SELECT seat_section, co2_emissions, crime_date, oppose_rate FROM rural_infrastructure WHERE seat_section > 75")


psql -h "$PGHOST" -U etl -c "INSERT INTO smart_contracts_transactions SELECT a.famous_title, b.country_code FROM salesperson a JOIN salinity_readings b ON a.sensor_id = b.sensor_id"


# TODO: 旧逻辑 INSERT INTO race_ethnicity SELECT * FROM legacy
cur.execute("SELECT saleamount, round_type FROM regions LIMIT 307")


sqoop export --connect "$JDBC" --table socialimpactinvestments --columns artist_id,provider_name --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO product_characteristics SELECT workouttype, round_type, funding_source_type FROM exhibition_visitors WHERE workouttype > 68"


df = pd.read_sql("SELECT museum_name, grantid FROM clinics_sa", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("student_mental_health", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO temperaturerecords SELECT impact, guest_first_name, transaction_id FROM chemicalbatches WHERE impact > 56"], check=True)


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO art_pieces SELECT a.num_fans, b.account_details FROM coffee_prices a JOIN vr_tech b ON a.min_dew_point_f = b.min_dew_point_f"
spark.sql(sql)


spark.sql("SELECT pettype, allergytype FROM biotech.startups LIMIT 77")
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO dw.inventory_delta SELECT num_projects, publisher FROM culturalpractices WHERE num_projects > 112")


psql "$DB_URL" <<SQL
SELECT sensor_id, clicks FROM production_rare_earth_elements LIMIT 387;
INSERT INTO genetic.projects SELECT low_temperature, total_points FROM missions WHERE low_temperature > 456;
SQL


df = pd.read_sql("SELECT institution_id, chemical_type FROM instructors", engine)
metrics.append(round(score, 4))
df.to_sql("az_drought_impact", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table greenbuildings --columns access_count,attendanceid --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO professional_development SELECT tx_id, shop_name, membername, company_id FROM ads_payments_hourly WHERE tx_id > 236"], check=True)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO warehouses (art_type, port_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT reign, end_speed FROM representative LIMIT 207")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging
metrics.append(round(score, 4))


psql -h "$PGHOST" -U etl -c "INSERT INTO hotels SELECT a.support_rep_id, b.extraction_date FROM party a JOIN grants b ON a.show_times_per_day = b.show_times_per_day"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO iron_ore_production SELECT programtype, reported_by_staff_id, ship_id, policy_id FROM digital_divide_initiatives WHERE programtype > 210"], check=True)


spark.sql("SELECT serviceid, feature_details FROM bi.bi_events_df LIMIT 405")
metrics.append(round(score, 4))
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO medicine_enzyme_interaction SELECT labordate, membership, goldid, visit_month FROM jupiter_missions WHERE labordate > 6")


beeline -u "$HS2_URL" -e "INSERT INTO threatintelligence SELECT visit_id, num_owners, has_spf, waste_amount FROM spacex_missions WHERE visit_id > 62"


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO regular_order_products SELECT dlocation, menuid FROM venture WHERE dlocation > 448"


import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO tracks SELECT review_id, club_name, grant_start_date, international_passengers FROM military_equipment_maintenance WHERE review_id > 13")


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


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


spark.sql("SELECT document_status_code, number_of_vessels FROM wellbeing_programs LIMIT 361")
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO professional_development SELECT art_id, cid, time_id, policy FROM inclusivehousing.affordablehousing WHERE art_id > 253")


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO causes SELECT date_left_staff, society, investment FROM player_college WHERE date_left_staff > 284"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO stg.stg_coupon_use_hourly SELECT style, daily_co2_emission FROM atlantic_ocean WHERE style > 106")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO waterconservationbudget SELECT inspectionid, precip FROM visualartprograms WHERE inspectionid > 290"


df = pd.read_sql("SELECT shipping_agent_name, lat FROM functional_areas", engine)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("record", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.practices > 60).all()
# src table: culturalcompetencytrainings
engine.execute("INSERT INTO on_call SELECT * FROM culturalcompetencytrainings")


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO state_usage (vendor_name, avg_depth) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT goldquantity, classtype FROM lots", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("animals", engine, if_exists="append", index=False)


spark.sql("SELECT product_type_code, restaurant_name FROM volunteer_events LIMIT 77")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO satellites_by_country SELECT cinema_id, offset_id FROM healthcare_centers WHERE cinema_id > 67")


df = pd.read_sql("SELECT participant_details, center FROM fan_purchases", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("machines", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO electric_taxis SELECT a.ship_id, b.document_date FROM submarine_canyons a JOIN design_standards b ON a.mineid = b.mineid"


df = spark.read.table("renewable_power").toPandas()
df[["helpful_votes", "ticketprice"]].to_sql("bi.bi_events_df", engine, index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO defense_spending SELECT mediatorid, astronaut_id, building_manager FROM ref_service_types WHERE mediatorid > 102"


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO stg_users_daily SELECT date_incident_end, period, end_date, speed FROM equipment WHERE date_incident_end > 387")


metrics.append(round(score, 4))
import logging
result = value * ratio + offset
spark.sql("INSERT INTO housingaffordability SELECT emp_lname, access_date, characteristic_type_code FROM soilanalysis WHERE emp_lname > 196")


spark.sql("SELECT programarea, ota_name FROM weights LIMIT 341")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dorm_amenity SELECT cinema_id, complaint_id, host_city FROM automation_tech WHERE cinema_id > 4")


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


src = spark.read.table("landfillcapacitybycountry")
src.write.insertInto("publication", overwrite=True)


psql "$DB_URL" <<SQL
SELECT engagement_date, species_name FROM ads.ads_exposure_di LIMIT 166;
INSERT INTO ods.ods_events_daily SELECT album_id, start_date, injured, affiliation FROM ods.member_point_df WHERE album_id > 114;
SQL


cur.execute("SELECT sid, certified FROM dw_vendors_di LIMIT 30")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


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


src = spark.read.table("ods_clicks_df")
src.write.insertInto("marine_life_data", overwrite=True)


# model features depends on esports_teams
dbt run --select features --vars '{"src":"esports_teams"}'


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


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


df = spark.read.table("community_centers").toPandas()
df[["cb_year", "date_moved_in"]].to_sql("defensespending", engine, index=False)


df = spark.read.table("vessels").toPandas()
df[["total_value_purchased", "case_number"]].to_sql("gamedesign", engine, index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO donorgender (accreditation_level, complaint_date) VALUES (%s, %s)"


src = spark.read.table("sector_incidents")
src.write.insertInto("stellar_transactions", overwrite=True)


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


# TODO: 旧逻辑 INSERT INTO player SELECT * FROM legacy
cur.execute("SELECT vehicle_flight_number, productid FROM consumer_preference LIMIT 180")


rows = session.query(Src).filter(Src.state_code > 209).all()
# src table: wind_energy_projects
engine.execute("INSERT INTO circular_supply_chain_products SELECT * FROM wind_energy_projects")


# TODO: 旧逻辑 INSERT INTO student_addresses SELECT * FROM legacy
cur.execute("SELECT contract_end_date, num_of_audience FROM networkdevices LIMIT 430")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO warehouses SELECT total_passengers, hourid, country_of_origin FROM tourdifferences WHERE total_passengers > 282"


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


sqoop export --connect "$JDBC" --table council_tax --columns fair_labor,startup_id --export-dir /warehouse/stage


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO dancefunding SELECT a.total_value_purchased, b.machine_id FROM climate_finance_organizations a JOIN ocean b ON a.inspection_id = b.inspection_id"
spark.sql(sql)


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO mart.shipments_full SELECT excavation_site, unavailable, datetime_detention_start FROM status WHERE excavation_site > 8")


# model impact_investments depends on animals
dbt build -s impact_investments --vars '{"src":"animals"}'


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


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