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


psql -h "$PGHOST" -U etl -c "INSERT INTO open_pedagogy_enrollment SELECT a.participant_details, b.diagnosis FROM ocean_acidity a JOIN journal_committee b ON a.institution = b.institution"


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


beeline -u "$HS2_URL" -e "INSERT INTO inclusivehousing.affordablehousing SELECT facilityid, skill_id, transaction_category FROM nursing_homes WHERE facilityid > 195"


# model member_point_daily depends on iron_ore_production
dbt run -s member_point_daily --vars 'source: iron_ore_production'


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


src = spark.read.table("peacekeeping_units")
src.write.insertInto("performingartsprograms", overwrite=True)


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


spark-sql --master yarn -e "INSERT INTO auto_show SELECT fda_approved, chargeable_amount, draft_pick_number FROM fairness_scores WHERE fda_approved > 199"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO wastewater_treatment (ai_powered_features, disease) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO movie SELECT a.therapy_session, b.price_range FROM mart.mart_sessions_di a JOIN digital_divide_initiatives b ON a.amount_of_refund = b.amount_of_refund"


result = value * ratio + offset
import logging
spark.sql("INSERT INTO communitypolicing SELECT active_from_date, denomination FROM spending WHERE active_from_date > 106")


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


df = spark.read.table("online_platform").toPandas()
df[["trip_distance", "centername"]].to_sql("museums", engine, index=False)


df = pd.read_sql("SELECT saleid, date_in_location_from FROM member_details", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("equipment_sales", engine, if_exists="append", index=False)


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO astronaut_medical_3 SELECT a.protected, b.hiredate FROM leo_missions a JOIN fairness_scores b ON a.date_order_placed = b.date_order_placed"
spark.sql(sql)


sqoop export --connect "$JDBC" --table militarypatents --columns disaster_id,manufacturerid --export-dir /warehouse/stage


# TODO: 旧逻辑 INSERT INTO school_details SELECT * FROM legacy
cur.execute("SELECT reason, latitude FROM user_reactions LIMIT 172")


# model irrigation_systems depends on building
dbt build --select irrigation_systems --vars 'source: building'


df = source_table(ctx, "bioprocess.engineering_projects")
push_to_target(df, "london.stations", mode="overwrite")


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO nasa_mars_program (approval_date, judge_id) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO accessibility_audits SELECT a.hometeamid, b.review_text FROM oceanography a JOIN research_grants b ON a.labor_cost = b.labor_cost"


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO aircraftsquadrons SELECT implementation_date, fish_population, hotel_name, facility_id FROM carbonoffsetinitiatives WHERE implementation_date > 437"


src = spark.read.table("plants")
src.write.insertInto("wind_energy_projects", overwrite=True)


df = pd.read_sql("SELECT supplierid, donortype FROM bioprocess_engineering", engine)
logger = logging.getLogger(__name__)
import logging
df.to_sql("canada_cosmetics_preferences", engine, if_exists="append", index=False)


df = pull_source(ctx, "royal_family")
write_to_output(df, "public.police_calls", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO attendee_demographics (contract_end, clean_jerk) VALUES (%s, %s)"


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


beeline -u "$HS2_URL" -e "INSERT INTO blockchain_tech SELECT valuation, is_commercial, donortype FROM organic_farms WHERE valuation > 60"


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO home_game SELECT position, creationyear FROM funding_records WHERE position > 312")


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO marine_life_research SELECT company_type_code, served_subscribers, property_id FROM singer_in_concert WHERE company_type_code > 246"


# model clinical_trials depends on carbon_footprint
dbt build -s clinical_trials --vars '{"source_table":"carbon_footprint"}'


src = spark.read.table("asia_events")
src.write.insertInto("member_data", overwrite=True)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO environmental_impact_stats SELECT course_completion, main_industry, startup_id, restaurant_name FROM sustainable_materials WHERE course_completion > 231;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO chemical_production_3 SELECT a.visitor_count, b.branch FROM urban_transportation a JOIN restaurant_type b ON a.strain_id = b.strain_id"


df = spark.read.table("vendorfabrics").toPandas()
df[["participation_date", "max_depth"]].to_sql("pilot", engine, index=False)


spark-sql --master yarn -e "INSERT INTO bike_stations SELECT vaccinations, founders_lgbtq, team_id_br, restaurant FROM human_resources WHERE vaccinations > 342"


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


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


psql "$DB_URL" <<SQL
SELECT contactid, trend FROM mine_workforce LIMIT 106;
INSERT INTO multimodal_trips SELECT booking_date, advisor FROM assets WHERE booking_date > 466;
SQL


spark.sql("SELECT fish_id, lettergrade FROM ads.ads_exposure_daily LIMIT 37")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO pacific_ocean SELECT implementation_year, biomass, part_id FROM teacher_development_race WHERE implementation_year > 55")


src = spark.read.table("organic_cosmetics")
src.write.insertInto("mining_operation_data", overwrite=True)


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


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO dw.dw_inventory_delta SELECT a.outcome_code, b.ingredient FROM socialimpactinvestments a JOIN manufacturing_processes b ON a.paintingid = b.paintingid"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO employee (party, registration_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dailystreams SELECT playdate, permit_id FROM sustainable_fabrics WHERE playdate > 21"


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


sqoop export --connect "$JDBC" --table language --columns artist_id,date_incident_end --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT method_name, site FROM adrprograms LIMIT 27;
INSERT INTO organic_farms SELECT languageid, emp_id FROM garmentproduction WHERE languageid > 236;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO digital_assets SELECT artworkname, budget_allocation, left_office, target_u_id FROM claims WHERE artworkname > 20"], check=True)


psql "$DB_URL" <<SQL
SELECT fault_log_entry_id, initiative_id FROM aircraft LIMIT 385;
INSERT INTO euroavev SELECT sex, caloric_content, delegate, stu_num FROM bi.bi_payments_delta WHERE sex > 41;
SQL


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


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


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO sitem SELECT policy_number, coownerid, unit_price, employee FROM crops_year WHERE policy_number > 335"


psql -h "$PGHOST" -U etl -c "INSERT INTO aircraft SELECT a.class_code, b.contributorname FROM stg.stg_campaigns_hourly a JOIN haircare_cruelty b ON a.production = b.production"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bioprocess.engineering_projects (meter_200, market_rate) VALUES (%s, %s)"


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


df = pull_frame(ctx, "manufacturing_processes")
dump_to_target(df, "union_membership", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
import logging
result = value * ratio + offset
spark.sql("INSERT INTO music_streaming SELECT last_checkup_date, sales_transaction_id, date_valid_from, technique_id FROM orgdonations WHERE last_checkup_date > 9")


psql "$DB_URL" <<SQL
SELECT production_cost, followers FROM asia_events LIMIT 115;
INSERT INTO dapps SELECT brand, issue_id, cell_mobile_phone_number FROM country_waste_generation WHERE brand > 125;
SQL


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


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


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


sqoop export --connect "$JDBC" --table public_transportation_routes --columns device_name,outcome_code --export-dir /warehouse/stage


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO healthcare_access_v2 SELECT a.game_count, b.payment_date FROM daily_transaction_volume a JOIN ref_colors b ON a.num_workers = b.num_workers"
spark.sql(sql)


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


cur.execute("SELECT founder_count, veteran_unemployment_rate FROM org_volunteer LIMIT 318")
rows = cur.fetchall()
import logging


presto --server presto01:8080 --catalog hive --execute "INSERT INTO imagery_archive SELECT artist_gender, purchase_transaction_id, fabricid FROM bi.bi_vendors_di WHERE artist_gender > 363"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO country_labor SELECT shipment_year, ingredient_name, crop, serving_size FROM prescribes WHERE shipment_year > 68"


df = load_table(ctx, "menuitems")
write_to_store(df, "indigenouscommunities", mode="overwrite")


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


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


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


spark.sql("SELECT thefttype, client FROM community_policing LIMIT 169")
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO labor_statistics SELECT budget_allocated, installation_year, enroll_grade, feedtype FROM tokyo_water_consumption WHERE budget_allocated > 432")


df = get_table(ctx, "fraud_detections")
save_to_output(df, "vrusers", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO coral_reefs SELECT neighborhoodname, catalog_entry_id, projectid FROM shariah_compliant_finance WHERE neighborhoodname > 30"


df = spark.read.table("taj_mahal_visitors").toPandas()
df[["high_temperature", "building_name"]].to_sql("team", engine, index=False)


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


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


spark-sql --master yarn -e "INSERT INTO salinity_readings SELECT last_workout_date, capacity_mw, team_id_winner, community_size FROM chemical_processes WHERE last_workout_date > 226"


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


set -euo pipefail
hive -e "INSERT INTO biosensors.patents SELECT reported, campusfee, interaction_type, acc_regular_season FROM news_report WHERE reported > 252"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO chemical_production_3 SELECT a.tree_species, b.budget_amount FROM school a JOIN user b ON a.pricepergram = b.pricepergram"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO market_trends SELECT virtual_tour_views, neighborhood_id, copy_number FROM initiatives WHERE virtual_tour_views > 249"


beeline -u "$HS2_URL" -e "INSERT INTO engineer_skills SELECT drought_id, avg_yield FROM safety_records WHERE drought_id > 297"


sqoop export --connect "$JDBC" --table container_receipts --columns transaction_product,movie --export-dir /warehouse/stage


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


beeline -u "$HS2_URL" -e "INSERT INTO tour_guides SELECT disaster_id, incidentdate, astronautid FROM product_characteristics WHERE disaster_id > 45"


rows = session.query(Src).filter(Src.port_code > 132).all()
# src table: visitor_statistics
engine.execute("INSERT INTO ads.ads_risk_score_hourly SELECT * FROM visitor_statistics")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods_member_point_full SELECT iata, vrdevice FROM fare_segments WHERE iata > 298;
EOF


df = get_frame(ctx, "stars")
dump_to_sink(df, "pilot_record", mode="overwrite")


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


sqoop export --connect "$JDBC" --table mart.mart_campaigns_daily --columns fish_population,fine_amount --export-dir /warehouse/stage


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


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


rows = session.query(Src).filter(Src.mission_count > 295).all()
# src table: visitor_exhibition
engine.execute("INSERT INTO countryintelligenceops SELECT * FROM visitor_exhibition")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO shops SELECT film_id, donation_date, clicks FROM department WHERE film_id > 138"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO skincare_sales SELECT fda_approved, average_age FROM traveler WHERE fda_approved > 5"


# model video_content depends on climate_monitoring_stations
dbt build --select video_content --vars '{"source_table":"climate_monitoring_stations"}'


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


result = value * ratio + offset
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO cultural_competency_training SELECT interaction_type, saleid, equipment_id, adults FROM mentalhealthprovider WHERE interaction_type > 66")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO marinespeciesobservations SELECT train_number, outcome_description, sensor_id, min_dew_point_f FROM artpieces WHERE train_number > 2;
EOF


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


psql -h "$PGHOST" -U etl -c "INSERT INTO bustrips SELECT a.size, b.dish_type FROM organisations a JOIN energy_consumption b ON a.incident_region = b.incident_region"


sqoop export --connect "$JDBC" --table excavationsites --columns faculty_id,customer_id --export-dir /warehouse/stage


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO onlineengagement SELECT contributionid, stop, review_id FROM dws_coupon_use_df WHERE contributionid > 482"


psql "$DB_URL" <<SQL
SELECT units_owned, conferenceid FROM product_info LIMIT 407;
INSERT INTO sales_by_quarter SELECT skill_id, resname, manufacturername FROM public_works_projects WHERE skill_id > 432;
SQL


df = spark.read.table("exhibitionsartworks").toPandas()
df[["home_team_three_point", "startup_id"]].to_sql("disaster_response", engine, index=False)


cur.execute("SELECT left_office, pets_allowed_yn FROM agricultural_innovation_projects LIMIT 71")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
import logging


import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO iron_ore_production SELECT last_workout_date, typical_buying_price FROM chemical_processes WHERE last_workout_date > 464")


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO mental_health_parity SELECT building_address, unsure_rate, tier, star_rating_code FROM labor_costs WHERE building_address > 347"


beeline -u "$HS2_URL" -e "INSERT INTO researchgrants SELECT invested, festival_name, individual_name FROM stg.member_point_df WHERE invested > 205"


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


cur.execute("SELECT rid, manager_name FROM trade_history LIMIT 187")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO sfc_articles (allergy, oil_volume) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO communityengagements SELECT date_valid_to, assessment_date, amenity_name FROM advisor WHERE date_valid_to > 82"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mart.campaigns_full (profits_in_billion, refugee_name) VALUES (%s, %s)"


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


cur.execute("SELECT asset_model, temp FROM donation LIMIT 355")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


spark-sql --master yarn -e "INSERT INTO us_military_personnel SELECT partid, head_id FROM autonomousdriving WHERE partid > 124"


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


beeline -u "$HS2_URL" -e "INSERT INTO ods_exposure_delta SELECT route_name, amount_paid, project_category, detention_type_code FROM dwd.dwd_campaigns_df WHERE route_name > 358"


# TODO: 旧逻辑 INSERT INTO developers SELECT * FROM legacy
cur.execute("SELECT share_in_percent, carrierid FROM music_streaming LIMIT 34")


df = spark.read.table("underwater_cables").toPandas()
df[["team_id_loser", "sale_price"]].to_sql("competition", engine, index=False)


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO customer_size_diversity SELECT a.address_content, b.forename FROM autoshows a JOIN urbanagricrop b ON a.violation_id = b.violation_id"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO user_video_view SELECT inspectionid, workshop_group_id, city_traffic_speed, award FROM funding_rounds WHERE inspectionid > 161"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO travel_advisory (water_type, contractorid) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO ods.ods_risk_score_df SELECT a.profession, b.origin_city FROM financial_transactions a JOIN chemical_processes b ON a.commodity = b.commodity"


set -euo pipefail
hive -e "INSERT INTO ai_safety_incidents SELECT participated_in_open_pedagogy, dishid FROM exit_strategy WHERE participated_in_open_pedagogy > 20"


import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO mealtypes SELECT a.maintenance_contract_id, b.mhw_id FROM tencel_sources a JOIN performances b ON a.tourist_id = b.tourist_id"
spark.sql(sql)


src = spark.read.table("record")
src.write.insertInto("indigenous_communities", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO attendance SELECT attendanceid, damage_millions_usd, club_name, postal_code FROM tournaments WHERE attendanceid > 141;
EOF


df = pd.read_sql("SELECT sustainability_certified, participated_in_open_pedagogy FROM bus_routes", engine)
logger = logging.getLogger(__name__)
df.to_sql("organization_contact_individuals", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO airport_aircraft (posted_at, clicks) VALUES (%s, %s)"


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


df = extract_table(ctx, "seasonalvegetables")
push_to_warehouse(df, "defense_diplomacy", mode="overwrite")


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO legal_aid_providers SELECT a.centername, b.algorithm_name FROM genderdistribution a JOIN city_department b ON a.experience = b.experience"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO round (framework_id, organic) VALUES (%s, %s)"


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


sqoop export --connect "$JDBC" --table healthbudget --columns scooter_id,protein_name --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO performingartsprograms SELECT installation_year, store_name FROM support_groups WHERE installation_year > 112;
EOF


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


msg = "would run: INSERT INTO sustainable_urban_properties_2 SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
import logging
result = value * ratio + offset


presto --server presto01:8080 --catalog hive --execute "INSERT INTO biomes SELECT share_in_percent, outcome_type, nominee, donor FROM communication_scores WHERE share_in_percent > 107"


# TODO: 旧逻辑 INSERT INTO contract_negotiations SELECT * FROM legacy
cur.execute("SELECT promotionid, energy_efficiency_kwh_m2_year FROM threat_intelligence LIMIT 472")


df = pd.read_sql("SELECT tank, major FROM workout_sessions", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
result = value * ratio + offset
df.to_sql("tb_cases", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO tunnels (num_investments, advisoryid) VALUES (%s, %s)"


src = spark.read.table("customer_addresses")
src.write.insertInto("tickets", overwrite=True)


spark.sql("SELECT permitid, lesson_status_code FROM agroecology_practices LIMIT 291")
metrics.append(round(score, 4))
spark.sql("INSERT INTO salary SELECT passenger_id, customer_address FROM useracct WHERE passenger_id > 375")


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


beeline -u "$HS2_URL" -e "INSERT INTO genre SELECT profession, resource FROM bus_routes WHERE profession > 390"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO agri_innov (cropname, school_code) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO genetics.experiments SELECT zip_code, emp_num, wrestler_id, ad_id FROM mart.mart_campaigns_daily WHERE zip_code > 161"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO election SELECT a.tree_id, b.exit_strategy FROM operate_company a JOIN labor_practices b ON a.days_held = b.days_held"


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO canada_cosmetics_preferences SELECT a.sale_id, b.use_date FROM member_details a JOIN players b ON a.statement_details = b.statement_details"


spark-sql --master yarn -e "INSERT INTO landfill_capacity SELECT school_id, truck_details FROM youth_fan_participation WHERE school_id > 230"


# TODO: 旧逻辑 INSERT INTO club SELECT * FROM legacy
cur.execute("SELECT stu_hrs, grantid FROM fair_trade_brands LIMIT 326")


rows = session.query(Src).filter(Src.sales_transaction_id > 97).all()
# src table: farms
engine.execute("INSERT INTO driver SELECT * FROM farms")


psql -h "$PGHOST" -U etl -c "INSERT INTO vrgames SELECT a.directed_by, b.game_genre FROM space_agencies_2 a JOIN appliances b ON a.causeid = b.causeid"


# TODO: 旧逻辑 INSERT INTO deep_sea_species SELECT * FROM legacy
cur.execute("SELECT opponent_id, part_id FROM mining.company LIMIT 472")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO permit SELECT offender_name, capital FROM production_costs WHERE offender_name > 423"


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


cur.execute("SELECT centername, hearingdate FROM fault_log LIMIT 84")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


df = pd.read_sql("SELECT premise_id, unionid FROM expenses", engine)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("environmentalimpact", engine, if_exists="append", index=False)


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


spark.sql("SELECT timestamp, promotiondate FROM low_value_contracts LIMIT 346")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO southchinasea.wells SELECT fault_status, dissolved_oxygen, royal_family_id, ironid FROM tokyo_water_consumption WHERE fault_status > 210")


psql "$DB_URL" <<SQL
SELECT policy_id, is_hybrid FROM startup_founders LIMIT 252;
INSERT INTO supportservices SELECT show_times_per_day, treatment_date, successful_cb FROM fieldd_info WHERE show_times_per_day > 26;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws_events_di SELECT do_value, assists FROM policy_feedback WHERE do_value > 40;
EOF


spark.sql("SELECT support_rate, ratingdate FROM dws.dws_orders LIMIT 312")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO network_infrastructure SELECT yearadded, fieldid FROM bus_fare_collection WHERE yearadded > 83")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO measurements SELECT actor_id, ship_date FROM fossil_fuel_vehicles WHERE actor_id > 92"


df = pd.read_sql("SELECT tree_species, pettype FROM sites_me", engine)
logger = logging.getLogger(__name__)
df.to_sql("member_of", engine, if_exists="append", index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO defenseprojects SELECT bathroom_count, chemicalid, emission_date FROM soilmoisturedata WHERE bathroom_count > 354"


# model mentalhealthprofessional depends on arcticocean
dbt build --models mentalhealthprofessional --vars '{"src":"arcticocean"}'


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO communityhealthworkerscanada SELECT profession, transaction_date, spill_name FROM creative_ai WHERE profession > 205"], check=True)


spark-sql --master yarn -e "INSERT INTO bi.bi_orders_hourly SELECT mh_id, amount_of_refund, workerid, category_name FROM state_usage WHERE mh_id > 434"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO epl_teams (restypename, menuitemid) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.ads_clicks_delta SELECT wrestler_id, activity, amount FROM energy_efficiency_programs WHERE wrestler_id > 239"], check=True)


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


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


mkdir -p /tmp/joblog
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO collectivebargaining SELECT bill_id, culturalcompetency FROM electric_buses WHERE bill_id > 454"


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO public.collected_fare SELECT a.treasurer_vote, b.community_id FROM militarypatents a JOIN organization_contact_individuals b ON a.no_of_customers = b.no_of_customers"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO product_characteristics (fate, tournament_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model ads depends on military_sales
dbt run --models ads --vars '{"src":"military_sales"}'


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


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


cur.execute("SELECT excavation_site_id, organic_ingredients_percentage FROM permit LIMIT 8")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


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


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


# model bi_inventory_di depends on agencies
dbt run --models bi_inventory_di --vars '{"src":"agencies"}'


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


df = spark.read.table("wastewater_plants").toPandas()
df[["total_employees", "diagnosis"]].to_sql("vehicle", engine, index=False)


src = spark.read.table("production_costs")
src.write.insertInto("parties", overwrite=True)


cur.execute("SELECT album, policy_type FROM view_product_availability LIMIT 328")
rows = cur.fetchall()
import logging


spark.sql("SELECT port, years_operating FROM debris LIMIT 121")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO employeedata SELECT organic_ingredients_percentage, averagespeed, governor, menu_id FROM mental_health_clinics WHERE organic_ingredients_percentage > 209")


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ads_users_hourly SELECT a.exploited, b.restorative_justice FROM customerorders a JOIN ai_safety_incidents b ON a.team_name = b.team_name"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO station SELECT period, support_rep_id, brandname, cultural_significance FROM genre_songs WHERE period > 217"


df = pd.read_sql("SELECT used_kb, pettype FROM mart.shipments_delta", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("market", engine, if_exists="append", index=False)


src = spark.read.table("race")
src.write.insertInto("mart.mart_device_log", overwrite=True)


sqoop export --connect "$JDBC" --table guests --columns min_dew_point_f,entryid --export-dir /warehouse/stage


src = spark.read.table("music")
src.write.insertInto("wind_farms", overwrite=True)


rows = session.query(Src).filter(Src.impactid > 34).all()
# src table: environmentalimpact
engine.execute("INSERT INTO match SELECT * FROM environmentalimpact")


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO green_buildings_us SELECT fair_labor, registration_id FROM drug_approvals WHERE fair_labor > 20"], check=True)


spark-sql --master yarn -e "INSERT INTO australia_offset_programs SELECT inspection_date, completion_status, donor_country, shippingmethod FROM languagesatrisk WHERE inspection_date > 288"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO artifactanalysis (invoice_date, num_of_component) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model suburbs depends on fan_purchases
dbt build --models suburbs --vars '{"source_table":"fan_purchases"}'


src = spark.read.table("container")
src.write.insertInto("livestock", overwrite=True)


df = pd.read_sql("SELECT visitor_id, peakhourid FROM waste", engine)
metrics.append(round(score, 4))
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("player_sessions", engine, if_exists="append", index=False)


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


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO safety_records SELECT a.is_ev, b.supplier_id FROM sitem a JOIN renewableenergyprojects b ON a.theftid = b.theftid"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO hotel_chains SELECT innovation, item_id, role_name FROM restorative_justice_programs WHERE innovation > 235"


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO songs SELECT a.goal_date, b.categoryid FROM exit_strategy a JOIN patient b ON a.membergender = b.membergender"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO settlements SELECT professional_development, galleryid, threat_type, shipmenttype FROM threat_intelligence WHERE professional_development > 42"


export TZ=Asia/Shanghai
hive -e "INSERT INTO ods.inventory_df SELECT assets, program_id, stu_fname, share_in_percent FROM campaigns WHERE assets > 32"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO satellite_deployment SELECT crop_name, enrollment_date FROM ods_payments_delta WHERE crop_name > 193"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mobile_usage SELECT fair_labor, region FROM erc20_transactions WHERE fair_labor > 99"], check=True)


msg = "would run: INSERT INTO communityengagementmetrics SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO department_publications SELECT cmi_cross_ref_id, aircraft, owner, training_name FROM therapy_session WHERE cmi_cross_ref_id > 79;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO daily_oil_production SELECT fleet_series, aircraft FROM ai_systems WHERE fleet_series > 158;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO co2_sequestration (founding_location, pettype) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT virtual_tour_sessions, trench_name FROM dw.inventory_delta LIMIT 135")
rows = cur.fetchall()
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO nomination (item_type, make) VALUES (%s, %s)"


cur.execute("SELECT shipping_agent_code, is_electric FROM stg.stg_device_log_daily LIMIT 420")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


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


rows = session.query(Src).filter(Src.movie > 343).all()
# src table: inclusivehousing.affordablehousing
engine.execute("INSERT INTO contracts SELECT * FROM inclusivehousing.affordablehousing")


sqoop export --connect "$JDBC" --table bioreactor --columns shelter_id,annual_interchanges --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO vehicle_safety_testing SELECT impact_id, num_of_staff FROM military_expenditure WHERE impact_id > 241"


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


cur.execute("SELECT host_country, eco_friendly FROM drought_impact LIMIT 122")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


df = pd.read_sql("SELECT gas_production_2020, state_code FROM arctic_marine_species", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("dw.exposure_di", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO defense_project_timelines (offset_id, yearadded) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO militaryequipmentsales SELECT name_full, sales_id FROM investment_rounds WHERE name_full > 26;
EOF


src = spark.read.table("safety_data")
src.write.insertInto("bi.bi_member_point", overwrite=True)


df = spark.read.table("space_agencies_2")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("clothingitems")


# model electricvehicleadoption depends on divisions
dbt run --select electricvehicleadoption --vars 'source: divisions'


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


psql "$DB_URL" <<SQL
SELECT mine_id, crs_credit FROM rural_areas LIMIT 108;
INSERT INTO eu_humanitarian_assistance SELECT call_id, stream_id, weight, stocking_density FROM tourism_activities WHERE call_id > 32;
SQL


# model veteran_employment depends on albums
dbt build -s veteran_employment --vars 'source: albums'


sqoop export --connect "$JDBC" --table dws_cart_item --columns scoreid,available_yn --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.investors > 180).all()
# src table: financialwellbeing
engine.execute("INSERT INTO companies_extended SELECT * FROM financialwellbeing")


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


psql "$DB_URL" <<SQL
SELECT job_title, conservation_status FROM sfc_articles LIMIT 169;
INSERT INTO ship SELECT i_id, baseprice, date_of_attendance FROM worker_scores WHERE i_id > 488;
SQL


spark.sql("SELECT songid, billing_country FROM militaryoperations LIMIT 64")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO ocean_floor_depth SELECT playername, applicant, sales_billion FROM rainfall_data WHERE playername > 59")


df = pd.read_sql("SELECT * FROM phishing_targets", conn)
df.to_sql("trends_2022", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO volunteerhours SELECT * FROM legacy
cur.execute("SELECT veteran_unemployment_rate, heritage_site FROM attorney_billing_rates LIMIT 252")


df = pull_table(ctx, "org_volunteer")
sink_to_target(df, "atlantic_plate", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO algorithmic_fairness_incidents_monthly (vegetable, initiative_id) VALUES (%s, %s)"


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


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO judges SELECT mean_visibility_miles, fault_short_name, worker_id, city_code FROM ods.sessions WHERE mean_visibility_miles > 33"


df = read_source(ctx, "distributors")
sink_to_sink(df, "state_budget", mode="overwrite")


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


sqoop export --connect "$JDBC" --table cinema --columns production_usage,animal_id --export-dir /warehouse/stage


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


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


psql "$DB_URL" <<SQL
SELECT topic, digital FROM factories LIMIT 456;
INSERT INTO ods_shipments_df SELECT born_state, neighborhood_id, fare_amount, billing FROM ratings WHERE born_state > 347;
SQL


metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO exam_results SELECT shipment_date, astronaut_name FROM product_details WHERE shipment_date > 110")


# model al_jazeera_data depends on supply_chain
dbt run --models al_jazeera_data --vars '{"src":"supply_chain"}'


psql "$DB_URL" <<SQL
SELECT policyid, end_date FROM autoshow LIMIT 495;
INSERT INTO marine_species_arctic_ocean SELECT gametype, school_id, model_name FROM volume WHERE gametype > 412;
SQL


df = get_source(ctx, "complaints")
upsert_to_store(df, "ref_product_categories", mode="overwrite")


# model protein depends on territory.human_rights_data
dbt run --models protein --vars '{"src":"territory.human_rights_data"}'


psql "$DB_URL" <<SQL
SELECT day_number, election_cycle FROM textile_waste LIMIT 483;
INSERT INTO dwd.dwd_users_hourly SELECT workout_duration, model_name FROM fossil_fuel_vehicles WHERE workout_duration > 476;
SQL


psql "$DB_URL" <<SQL
SELECT sqft, competition_type FROM train_lines LIMIT 31;
INSERT INTO artifactanalysis SELECT vessel_id, strain_id, tree_species, streamid FROM food_items WHERE vessel_id > 446;
SQL


psql "$DB_URL" <<SQL
SELECT machine_series, inventor_name FROM trips LIMIT 370;
INSERT INTO bike_station_info SELECT is_unionized, observation_date FROM textile_suppliers WHERE is_unionized > 257;
SQL


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


spark.sql("SELECT submission_id, crime_date FROM ticket_sales LIMIT 454")
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO part_faults SELECT circuitid, amountdonated, dept_id FROM school_districts WHERE circuitid > 102")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd.dwd_risk_score_delta (socially_responsible, restock_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO nutrition_facts SELECT entryid, flno, leadershiptraining FROM visitor_exhibition WHERE entryid > 130;
EOF


spark.sql("SELECT engagement_count, accreditation_level FROM city LIMIT 58")
metrics.append(round(score, 4))
spark.sql("INSERT INTO culturalcompetencytrainings SELECT vessel_id, first_donation_date FROM material WHERE vessel_id > 459")


rows = session.query(Src).filter(Src.order_item_id > 98).all()
# src table: mart_orders_di
engine.execute("INSERT INTO circular_economy_companies SELECT * FROM mart_orders_di")


sqoop export --connect "$JDBC" --table marine_mammals --columns effort_name,mediatorid --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO esportsteamsafrica (incident_name, document_status_description) VALUES (%s, %s)"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO league_x SELECT concert_id, sale_amount, fate, online_dispute_resolution FROM asia_events WHERE concert_id > 273")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO incidents (operationname, color_description) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO vehicle_safety_testing SELECT disaster_type, ll_activity FROM fossil_fuel_vehicles WHERE disaster_type > 305"


psql -h "$PGHOST" -U etl -c "INSERT INTO ocean_pollution SELECT a.living_wage, b.initiative_type FROM space_agencies_2 a JOIN military_personnel_africa b ON a.mission_name = b.mission_name"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO permit SELECT showid, completed_course, engagementid, attack_count FROM pacific_ocean WHERE showid > 242;
EOF


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


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


df = pd.read_sql("SELECT fare_amount, assessmentname FROM consumer", engine)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
df.to_sql("organizations", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO climateresearch SELECT support_rate, bikes_available, has_aloe_vera FROM weapons WHERE support_rate > 66"


set -euo pipefail
hive -e "INSERT INTO defense_diplomacy SELECT condition, company_name, jan FROM fabrics WHERE condition > 38"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO wta_serves SELECT school_type, pilot_id, lesson_id, languages FROM water_distribution WHERE school_type > 85"


spark-sql --master yarn -e "INSERT INTO staff_roles SELECT donator_name, route_short_name, special_features FROM student WHERE donator_name > 490"


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


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


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


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


df = fetch_table(ctx, "chemicals_annual")
export_to_store(df, "invoice", mode="overwrite")


metrics.append(round(score, 4))
sql = "INSERT INTO mart.mart_users_df SELECT a.model_id, b.nickname FROM sustainability_metrics a JOIN students_enrollment b ON a.implementation_date = b.implementation_date"
spark.sql(sql)


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


df = extract_table(ctx, "dwd.dwd_products")
write_to_sink(df, "dw.dw_risk_score_full", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO aid_missions SELECT matchid, daily_visitors, seal_species FROM submission WHERE matchid > 290;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO stores_2 SELECT staff_details, seal_species FROM bi.bi_shipments WHERE staff_details > 395"


df = pd.read_sql("SELECT element_id, schedule_id FROM ytterbium_supply", engine)
logger = logging.getLogger(__name__)
df.to_sql("biosensor.patents", engine, if_exists="append", index=False)


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


psql "$DB_URL" <<SQL
SELECT has_access, instid FROM production LIMIT 209;
INSERT INTO developers SELECT cell_mobile_phone_number, case_burden FROM farms WHERE cell_mobile_phone_number > 486;
SQL


df = source_source(ctx, "materials_usage")
save_to_warehouse(df, "completed_training", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO trainers SELECT strain_type, expertise, strategy_id, prereq_id FROM soil_moisture WHERE strain_type > 399"], check=True)


src = spark.read.table("mediators")
src.write.insertInto("dws.dws_member_point_di", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vessel SELECT sighting_date, visitorid FROM mentalhealthprofessional WHERE sighting_date > 245"


echo "job start: $(date +%F)"
hive -e "INSERT INTO workerbuildings SELECT watertemp, birth_place FROM agricultural_projects WHERE watertemp > 107"


src = spark.read.table("orders")
src.write.insertInto("virtual_tours_oceania", overwrite=True)


cur.execute("SELECT velocity, crime_id FROM community_leaders LIMIT 152")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
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))


# model electricvehicleadoption depends on trainingprograms
dbt run --models electricvehicleadoption --vars '{"src":"trainingprograms"}'


msg = "would run: INSERT INTO dapps SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO irrigation_systems SELECT priceid, dose, season FROM exam_results WHERE priceid > 5"], check=True)


df = spark.read.table("support_programs").toPandas()
df[["elevation", "material_name"]].to_sql("ca_menu_items", engine, index=False)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mammals SELECT store_name, furniture_id, shipment_year, dose FROM fish_purchases WHERE store_name > 202"], check=True)


cur.execute("SELECT donortype, lanes FROM residents_services LIMIT 7")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.ods_risk_score_df SELECT granteeid, member_id FROM landfill_capacity WHERE granteeid > 454;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO pets SELECT volume_id, bus_number FROM ods_products_delta WHERE volume_id > 482"


psql "$DB_URL" <<SQL
SELECT occupation, market_details FROM device_accessibility LIMIT 362;
INSERT INTO ref_locations SELECT condition, word_count, sid, genreid FROM public_works_projects WHERE condition > 496;
SQL


beeline -u "$HS2_URL" -e "INSERT INTO road_construction SELECT manufacturername, date_joined_staff, measurement FROM stg.stg_risk_score_df WHERE manufacturername > 322"


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


spark-sql --master yarn -e "INSERT INTO user_stats SELECT people_id, spending, signup_date, operationid FROM dws.shipments_daily WHERE people_id > 75"


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO foodaid SELECT a.individual_middle_name, b.vaccination_status FROM collective_bargaining a JOIN virtual_tours b ON a.product_type = b.product_type"
spark.sql(sql)


sqoop export --connect "$JDBC" --table marine_life_research --columns trade_name,status_code --export-dir /warehouse/stage


df = spark.read.table("astronaut_missions").toPandas()
df[["payment_method", "sale_price"]].to_sql("vrusers", engine, index=False)


sqoop export --connect "$JDBC" --table military_equipment_maintenance --columns enable_dm,testdate --export-dir /warehouse/stage


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


sqoop export --connect "$JDBC" --table africa_schema.african_mines --columns added_date,negotiation_date --export-dir /warehouse/stage


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO tour_guides SELECT profits_billion, investment_round, effort_id FROM spacecraft_components WHERE profits_billion > 415")


psql -h "$PGHOST" -U etl -c "INSERT INTO coralreefs SELECT a.representative_name, b.account_name FROM climate_adaptation a JOIN tennis_players b ON a.workshop_group_id = b.workshop_group_id"


df = spark.read.table("event_attendance").toPandas()
df[["outcome_name", "model_name"]].to_sql("trafficviolations", engine, index=False)


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


src = spark.read.table("container_ships")
src.write.insertInto("assessment_notes", overwrite=True)


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


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO african_tourism SELECT menuname, market_value_in_billion, farmname FROM financial_capability_id WHERE menuname > 337")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO jupiter_spacecraft SELECT exoplanet, poll_source FROM mexico_regions WHERE exoplanet > 95"], check=True)


psql "$DB_URL" <<SQL
SELECT starting_year, trial_status FROM schoolc LIMIT 208;
INSERT INTO container_receipts SELECT fouls, destination, chemical_id FROM member_data WHERE fouls > 253;
SQL


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO attack_outcomes (team_name, sustainability_score) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO customer_master_index SELECT * FROM legacy
cur.execute("SELECT bname, trend_id FROM training_programs LIMIT 381")


# TODO: 旧逻辑 INSERT INTO ods_clicks_df SELECT * FROM legacy
cur.execute("SELECT scores, tasktype FROM dw.dw_campaigns_di LIMIT 349")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO pollutionincidents SELECT expertise, billid, attorney_id FROM sustainable_materials WHERE expertise > 356;
EOF


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO cybersecuritybudget SELECT a.practice_id, b.filingdate FROM communities a JOIN seeds b ON a.society = b.society"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO college SELECT case_burden, artwork, role, has_parabens FROM space_exploration WHERE case_burden > 489"


spark-sql --master yarn -e "INSERT INTO defense_diplomacy SELECT stockid, problem_description, is_hybrid FROM fish_biomass WHERE stockid > 240"


df = spark.read.table("continent").toPandas()
df[["mealname", "party"]].to_sql("restaurants", engine, index=False)


df = pd.read_sql("SELECT match_id, outcome_name FROM player", engine)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("store", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO nz_tourism (long, faculty) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mountain SELECT claim_status_name, container_id, sellingprice FROM drug_approval WHERE claim_status_name > 72"


trap 'echo failed' ERR
set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO home_game SELECT injury_date, quantity_sold, dorm_name, name_full FROM divisions WHERE injury_date > 453"


# TODO: 旧逻辑 INSERT INTO tourist_attractions SELECT * FROM legacy
cur.execute("SELECT num_investments, agency_id FROM platform_production LIMIT 296")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO parties SELECT state_province, base_name FROM units WHERE state_province > 432"], check=True)


psql "$DB_URL" <<SQL
SELECT company_name, date_of_attendance FROM tourist_attraction_features LIMIT 162;
INSERT INTO incidents SELECT clubdesc, report FROM police_stations WHERE clubdesc > 370;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.coupon_use_delta SELECT a.asset_details, b.length FROM aquaculture_farms a JOIN grapes b ON a.date_claim_made = b.date_claim_made"


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


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


sqoop export --connect "$JDBC" --table african_tourism --columns ship_agent_id,share_in_percent --export-dir /warehouse/stage


df = pd.read_sql("SELECT dispensary_name, number_cities FROM competition", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("tech_workers_union", engine, if_exists="append", index=False)


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.bi_campaigns_daily SELECT statement_details, ethical_certifications, exhibition_name, item_sold FROM crime_stats WHERE statement_details > 230"], check=True)


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


df = spark.read.table("producesupplier").toPandas()
df[["long", "state_province_county"]].to_sql("recruiters", engine, index=False)


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


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


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


df = spark.read.table("riskassessments").toPandas()
df[["borough", "trip_city"]].to_sql("labor_unions", engine, index=False)


spark.sql("SELECT src_apid, state FROM co2price LIMIT 108")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO underwater_trenches SELECT account_details, attraction_name FROM wastewatertreatment WHERE account_details > 451")


metrics.append(round(score, 4))
spark.sql("INSERT INTO military_expenditure SELECT orderdate, acc_bal, contractorname FROM ods.inventory_df WHERE orderdate > 68")


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


rows = session.query(Src).filter(Src.funding > 263).all()
# src table: publications
engine.execute("INSERT INTO tourist_destinations SELECT * FROM publications")


psql -h "$PGHOST" -U etl -c "INSERT INTO education_programs SELECT a.is_operational, b.county_name FROM dwd.coupon_use_daily a JOIN reservations b ON a.transact_date = b.transact_date"


df = extract_source(ctx, "gamedesigndata")
export_to_warehouse(df, "geothermal_power_plants", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO pilot SELECT policy_description, class_president_vote, crop FROM uniteddefense.equipmentsales WHERE policy_description > 350")


rows = session.query(Src).filter(Src.initiativename > 98).all()
# src table: union_membership
engine.execute("INSERT INTO premises SELECT * FROM union_membership")


df = spark.read.table("ods.campaigns_di").toPandas()
df[["outcome_type", "practice"]].to_sql("communitydevelopment", engine, index=False)


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


# model service_budget depends on renewables.renewable_projects
dbt build --models service_budget --vars '{"source_table":"renewables.renewable_projects"}'


beeline -u "$HS2_URL" -e "INSERT INTO peacekeeping_units SELECT store_phone, time_year FROM waste WHERE store_phone > 263"


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


df = spark.read.table("ads.refunds")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("social_good_education")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tourist_attraction_features (projecttype, director) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO textile_sourcing SELECT initiative_region, time_id, rank_in_round FROM dwd.dwd_exposure_full WHERE initiative_region > 44"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO safety_incidents (arrival_date, log_entry_description) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_events_hourly SELECT membership_type, clubdesc, goldquantity, donationid FROM platformh WHERE membership_type > 491;
EOF

membership_type clubdesc goldquantity donationid


spark.sql("SELECT pieces, contributor FROM soil_moisture LIMIT 60")
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO parts SELECT batting_average, container_count, productname, component_name FROM biotech_startups WHERE batting_average > 413")


result = value * ratio + offset
import logging
sql = "INSERT INTO airportdata SELECT a.payment_method, b.tour_name FROM canals a JOIN urbanagricrop b ON a.ngo_name = b.ngo_name"
spark.sql(sql)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO weights (funding_round_id, financing_date) VALUES (%s, %s)"


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


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


spark-sql --master yarn -e "INSERT INTO tree_species SELECT capital, driller FROM donationprograms WHERE capital > 281"


metrics.append(round(score, 4))
spark.sql("INSERT INTO auto_shows SELECT strategy_id, social_impact_score, workout_duration, water_temp FROM circularsupplychain WHERE strategy_id > 240")


psql -h "$PGHOST" -U etl -c "INSERT INTO africa_projects SELECT a.hiv, b.course_id FROM has_amenity a JOIN safetytests b ON a.transaction_product = b.transaction_product"


df = extract_source(ctx, "ai_for_social_good")
persist_to_target(df, "manufacturing_processes", mode="overwrite")


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO temperature SELECT donorgender, amount_paid, reported_date FROM ads_users_hourly WHERE donorgender > 100"], check=True)


spark.sql("SELECT led_by, publish_date FROM innovation_projects LIMIT 199")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO bi_orders_daily SELECT speed, g_name FROM otas WHERE speed > 354")


# TODO: 旧逻辑 INSERT INTO climatedata SELECT * FROM legacy
cur.execute("SELECT region, checkout FROM mammals LIMIT 390")


spark-sql --master yarn -e "INSERT INTO student_lifelong_learning SELECT claimid, roomid FROM total_capacity WHERE claimid > 30"


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


df = pd.read_sql("SELECT is_male, attendance_date FROM mart.clicks_delta", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("acceptance", engine, if_exists="append", index=False)


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


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


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


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO city_properties SELECT streamid, assessment_date FROM school_bus WHERE streamid > 5")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO haircaresales SELECT is_eco_friendly, container_id, launch_company FROM broadband_plans WHERE is_eco_friendly > 107"


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


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


# TODO: 旧逻辑 INSERT INTO exhibition_visitors SELECT * FROM legacy
cur.execute("SELECT exit_date, museum_id FROM territory.human_rights_data LIMIT 217")


spark-sql --master yarn -e "INSERT INTO academic_publications SELECT document_structure_description, domestic_passengers, precedent_id, role_code FROM categories WHERE document_structure_description > 161"


spark.sql("SELECT visit_date, apt_number FROM dws.exposure LIMIT 212")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO research_grants SELECT personnelbranch, policy_type_code, incidents, lot_details FROM public.trips_by_day_train WHERE personnelbranch > 115")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cuisine (claim_number, trip_duration) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT subject_area_id, brand_id FROM party_host LIMIT 197")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


sqoop export --connect "$JDBC" --table building --columns event_name,location_code --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO stg.stg_inventory_hourly SELECT low_estimate, train_type, mealname FROM journal WHERE low_estimate > 14"


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


df = spark.read.table("department_publications").toPandas()
df[["complaint_id", "dates_active"]].to_sql("bi.bi_events_df", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO government.region SELECT nutrient_level, petid, transact_date, installed_date FROM emergency_responses WHERE nutrient_level > 16"


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


spark.sql("SELECT claim_date, damage_millions_usd FROM furniture LIMIT 468")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ingredient_sourcing SELECT cell_mobile_phone_number, pd_id, tripdatetime, cropid FROM aircraft_flights WHERE cell_mobile_phone_number > 466")


sqoop export --connect "$JDBC" --table stg.inventory_df --columns union_name,song_release_year --export-dir /warehouse/stage


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
result = value * ratio + offset
sql = "INSERT INTO storage_tech SELECT a.low_temperature, b.volunteerhourid FROM design_standards a JOIN nba b ON a.chip_model = b.chip_model"
spark.sql(sql)


# model product_catalog depends on mappinglengths
dbt build --models product_catalog --vars 'source: mappinglengths'


psql -h "$PGHOST" -U etl -c "INSERT INTO flight_safety SELECT a.energy_consumption, b.omim FROM vulnerabilities a JOIN ref_document_status b ON a.end_speed = b.end_speed"


df = source_input(ctx, "research.species")
upsert_to_store(df, "constructors", mode="overwrite")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO tencel_sources SELECT bias_score, customer FROM landfill_capacity WHERE bias_score > 498;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO tech_accessibility_funding (document_description, park_name) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT songid, spacecraft_id FROM dws.dws_orders LIMIT 5;
INSERT INTO investor_activities SELECT host_id, has_spf, energy_generated, enzyme_id FROM freshwaterfinfish WHERE host_id > 441;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO field SELECT salesperson_id, materialtype FROM party_forms WHERE salesperson_id > 237;
EOF


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


spark.sql("SELECT stateid, order_quantity FROM stores LIMIT 219")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO ods.clicks_delta SELECT activity_date, customer_address, incident_type, material_id FROM swimmer WHERE activity_date > 459")


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


psql "$DB_URL" <<SQL
SELECT investment, individual_middle_name FROM industrial_customers LIMIT 268;
INSERT INTO education SELECT cid, labordate FROM monthly_temp WHERE cid > 440;
SQL


df = pull_table(ctx, "stg_users_daily")
write_to_output(df, "jupiter_missions", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO management SELECT vendorid, manager_id FROM researchgrants WHERE vendorid > 440"


# TODO: 旧逻辑 INSERT INTO veteran_occupations SELECT * FROM legacy
cur.execute("SELECT aid, product_category_code FROM teams LIMIT 216")


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


metrics.append(round(score, 4))
spark.sql("INSERT INTO yoga SELECT countryid, attorney, trader_id, capacity_mw FROM ods.ods_exposure_delta WHERE countryid > 67")


df = pd.read_sql("SELECT amount_due, garment FROM dw.member_point_daily", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
df.to_sql("recruiters", engine, if_exists="append", index=False)


df = spark.read.table("cerium_production").toPandas()
df[["lieutenant_governor", "city_traffic_speed"]].to_sql("train_station", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.ads_payments_delta SELECT pilot, typical_buying_price, exit_type, count_id FROM bookings WHERE pilot > 257;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO flights SELECT machine, num_attendees, next_maintenance, process_id FROM carbon_offset_programs WHERE machine > 306"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO drama_workshop_groups (payment_id, prepnurse) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO influencers SELECT supplier_company_id, market_id FROM manager_award WHERE supplier_company_id > 127"], check=True)


# model therapy_attendance depends on stg.stg_risk_score_df
dbt build --select therapy_attendance --vars 'source: stg.stg_risk_score_df'


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


spark-sql --master yarn -e "INSERT INTO bank_info SELECT accreditation_type, enable_location_tracking FROM climateresearch WHERE accreditation_type > 276"


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


psql "$DB_URL" <<SQL
SELECT lat, decision FROM vocals LIMIT 408;
INSERT INTO researchprojects SELECT used_kb, claim_status_name, date FROM satellite_missions_large WHERE used_kb > 193;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO industry_funding (framework_id, claim_status_description) VALUES (%s, %s)"


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


import logging
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO city.community_policing SELECT bike_id, missions, evaluationid, completed FROM shipments WHERE bike_id > 224")


logger = logging.getLogger(__name__)
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO appointments SELECT days, date_and_date FROM rnd_budget WHERE days > 325")


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO organic_products SELECT days_held, stu_gpa FROM unions WHERE days_held > 352")


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
import logging
sql = "INSERT INTO phone_market SELECT a.case_type, b.violation_id FROM investor_activities a JOIN vessel_capacity b ON a.stat_id = b.stat_id"
spark.sql(sql)


import logging
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO vessel_incident_count SELECT amount_due, height, contract_id, policy_count FROM storage_tech WHERE amount_due > 355")


sqoop export --connect "$JDBC" --table research_staff --columns authorder,asset_model --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table movie --columns environmental_impact_score,cruelty_free --export-dir /warehouse/stage


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


df = spark.read.table("danceevents").toPandas()
df[["noise_level", "minutes"]].to_sql("endowment", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO demographics SELECT date_of_birth, total_value_purchased FROM wells WHERE date_of_birth > 46"


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


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO training_programs SELECT games, schedule_date, ei_category FROM bike_stations WHERE games > 425")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_events_hourly SELECT artist, attack_id, union_members, trial_status FROM membership_data WHERE artist > 312;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO imagery_archive SELECT amount_waste, settlement_amount, editor_id, label FROM food_justice_orgs WHERE amount_waste > 289"


cur.execute("SELECT shipping_agent_code, building_manager FROM issues LIMIT 420")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
import logging


sqoop export --connect "$JDBC" --table satellites --columns musical_id,primary_conference --export-dir /warehouse/stage


spark.sql("SELECT subscription_start_date, circular_supply_chain FROM mart.risk_score_df LIMIT 205")
import logging
spark.sql("INSERT INTO sales_quarterly SELECT beds, date_of_notes, height FROM reporters WHERE beds > 119")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO timed_status_of_things (customer_status_code, asset_details) VALUES (%s, %s)"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO green_certification SELECT profits_in_billion, phone_id, volunteerhourid, fault_status FROM movies WHERE profits_in_billion > 478"


spark-sql --master yarn -e "INSERT INTO fans SELECT pricepergram, salary FROM veterans WHERE pricepergram > 399"


# model ai_for_social_good depends on satellites_by_country
dbt run --models ai_for_social_good --vars 'source: satellites_by_country'


cur.execute("SELECT contractor_id, width FROM climate_projects LIMIT 495")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


sqoop export --connect "$JDBC" --table portfolios --columns character,is_commercial --export-dir /warehouse/stage


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


# TODO: 旧逻辑 INSERT INTO pollution_control_initiatives SELECT * FROM legacy
cur.execute("SELECT sales_transaction_id, trips FROM volunteer_hours LIMIT 209")


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))


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO daily_industrial_water_usage SELECT a.indigenous, b.policyname FROM flight_emissions a JOIN drugs b ON a.excavationid = b.excavationid"
spark.sql(sql)


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO exit_strategies SELECT a.reported, b.value FROM aid_missions a JOIN production b ON a.founder_race = b.founder_race"
spark.sql(sql)


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


df = get_dataset(ctx, "mental_health_parity")
upsert_to_output(df, "bi.bi_inventory_delta", mode="overwrite")


rows = session.query(Src).filter(Src.participatedinesports > 113).all()
# src table: county
engine.execute("INSERT INTO ods.shipments_df SELECT * FROM county")


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO animal_populations SELECT volume_id, mental_health_resource_access, communityname, safety_id FROM al_jazeera_data WHERE volume_id > 157"


set -euo pipefail
hive -e "INSERT INTO ads.ads_exposure_di SELECT siteid, green_building_id FROM mission WHERE siteid > 126"


metrics.append(round(score, 4))
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO field SELECT recycler_id, asset_model, goal_id, stream_id FROM mentalhealthprovider WHERE recycler_id > 441")


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO musicgenre SELECT doctor_id, total_distance, date_left_staff, destinationid FROM criminalcases WHERE doctor_id > 473")


df = source_input(ctx, "dw.dw_orders_hourly")
write_to_warehouse(df, "bi.clicks_hourly", mode="overwrite")


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


beeline -u "$HS2_URL" -e "INSERT INTO vessel_capacity SELECT era, birthdate, pricepergram FROM bi.bi_payments_df WHERE era > 444"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO vocals SELECT tourists, death_year, schedule_id FROM shrimp_farms WHERE tourists > 221"], check=True)


sqoop export --connect "$JDBC" --table onlineengagement --columns sales,partid --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ethicalaibudget (hospitalid, effort) VALUES (%s, %s)"


# model habitat depends on courtcases
dbt run -s habitat --vars '{"source_table":"courtcases"}'


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO classicgame SELECT a.jan, b.incident_category FROM weekly_weather a JOIN workforce_training b ON a.comments = b.comments"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO org_donation SELECT * FROM legacy
cur.execute("SELECT volume, fund_type FROM workforce_development LIMIT 215")


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


df = extract_source(ctx, "dws_clicks_di")
upsert_to_target(df, "coal_reserves", mode="overwrite")


if not rows:
    logger.warning('empty result')
import logging
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO manager_award SELECT a.menuitemid, b.item_id FROM apartments a JOIN phone_market b ON a.vaccine_name = b.vaccine_name"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO artcollection SELECT working_horses, labor_hour_id FROM construction_labor_stats WHERE working_horses > 29"


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


msg = "would run: INSERT INTO monitoring_zones SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO experts SELECT build_date, artworkyear, views, person_id FROM genetics.experiments WHERE build_date > 399")


spark.sql("SELECT num_shariah_compliant_investments, excavation_site FROM player_demographics LIMIT 349")
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO circularsupplychain SELECT founder_lgbtq, vrgameid, mappingid FROM council_tax WHERE founder_lgbtq > 22")


cur.execute("SELECT faculty_id, campaign_id FROM game_sessions LIMIT 402")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
import logging


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO researchgrants SELECT trial_id, hours_served, zone_id FROM marine_life_sightings WHERE trial_id > 488"


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_sessions_hourly SELECT a.dorm_name, b.ssn FROM songs a JOIN expenditure b ON a.length_meters = b.length_meters"


metrics.append(round(score, 4))
sql = "INSERT INTO attorneylocationyear SELECT a.contract_value, b.artworkid FROM staff_members a JOIN automation_tech b ON a.county_name = b.county_name"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO manufacturersustainability SELECT * FROM legacy
cur.execute("SELECT location_id, lawyer_name FROM public_participation LIMIT 60")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO gold SELECT ticket_price, creator, production_date, component_type FROM electric_taxis WHERE ticket_price > 21"


spark-sql --master yarn -e "INSERT INTO orders SELECT country_of_origin, producerid FROM benefits_overpayments WHERE country_of_origin > 106"


psql "$DB_URL" <<SQL
SELECT valuation, mental_health_score FROM contract_transactions LIMIT 113;
INSERT INTO tech_volunteers SELECT artist, grade, years_working FROM emerging_markets.digital_assets WHERE artist > 404;
SQL


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO patient_satisfaction (transaction_product, energy_generated) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO bi.member_point_full SELECT launch_id, workername, years_operating FROM seafood WHERE launch_id > 149"


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


spark-sql --master yarn -e "INSERT INTO safety_incidents_india SELECT productionrate, total_distance, registration_id, injury FROM conservation WHERE productionrate > 444"


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


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


# model satellites depends on mart.mart_products_hourly
dbt run -s satellites --vars '{"src":"mart.mart_products_hourly"}'


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


# TODO: 旧逻辑 INSERT INTO coffee_prices SELECT * FROM legacy
cur.execute("SELECT date_of_attendance, premise_details FROM clinics_sa LIMIT 222")


# model wrestler depends on dysprosiumproduction
dbt run -s wrestler --vars '{"source_table":"dysprosiumproduction"}'


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.ads_refunds_hourly SELECT a.site, b.reo_type FROM climate_adaptation_projects a JOIN mining_operation b ON a.votes = b.votes"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO tech_for_social_good SELECT supply_volume, energytype FROM model_data WHERE supply_volume > 408"


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


src = spark.read.table("bi.bi_member_point")
src.write.insertInto("waste_types", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO platform (material_date, farm_id) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO sustainable_tourism_practices SELECT circularsupplychain, support_rep_id, program_name, violation_count FROM authenticationlogs WHERE circularsupplychain > 66"


df = spark.read.table("bi.bi_exposure_hourly")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("ods.ods_sessions_df")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO resource_extraction SELECT participant, transaction_type_code, date_formed, section_title FROM forest_species WHERE participant > 390"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO permit SELECT fine, membership FROM autonomous_testing WHERE fine > 435"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg_payments_hourly SELECT meter_300, emp_fname, practiceid FROM e_scooter_trips WHERE meter_300 > 359"], check=True)


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


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


df = load_input(ctx, "regulatoryframeworksbycountry")
push_to_output(df, "invoice_lines", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO community_development.transactions SELECT * FROM legacy
cur.execute("SELECT countryname, visitor_id FROM intelligence_personnel LIMIT 235")


# model yoga depends on regulatory_compliance
dbt build --models yoga --vars '{"source_table":"regulatory_compliance"}'


rows = session.query(Src).filter(Src.trial_id > 355).all()
# src table: passengers
engine.execute("INSERT INTO performance_scores SELECT * FROM passengers")


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


df = fetch_table(ctx, "takes")
save_to_warehouse(df, "platform", mode="overwrite")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO areas SELECT archaeologist_id, waste_amount, grant_end_date, membership_amount FROM art WHERE archaeologist_id > 140"], check=True)


df = pd.read_sql("SELECT budgeted, organic FROM gamedata", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("auto_show", engine, if_exists="append", index=False)


spark.sql("SELECT county_id, gross_worldwide FROM ethicalaibudget LIMIT 351")
if not rows:
    logger.warning('empty result')
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO genderdistribution SELECT hoursspent, productid, excavationid FROM mental_health_center WHERE hoursspent > 499")


df = pd.read_sql("SELECT * FROM na_schema.hospitals", conn)
df.to_sql("sales_by_quarter", conn, if_exists="replace", index=False)


metrics.append(round(score, 4))
sql = "INSERT INTO lenders SELECT a.ship_date, b.menu_id FROM healthcare_access_v2 a JOIN drama_workshop_groups b ON a.athlete_id = b.athlete_id"
spark.sql(sql)


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


src = spark.read.table("match_result")
src.write.insertInto("storage_projects", overwrite=True)


src = spark.read.table("temperaturerecords")
src.write.insertInto("vessel_tracking", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dispensary_sales (sales_details, participant_id) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO haircaresales SELECT artifact_id, course_id, employer_organisation_id FROM bi.device_log_hourly WHERE artifact_id > 44;
EOF


# model playerscores depends on deliveryaddresses
dbt build --select playerscores --vars '{"src":"deliveryaddresses"}'


spark.sql("SELECT incident_region, element FROM union_membership LIMIT 433")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO maintenance_requests SELECT festival_id, artworkid, staff_address_id, ad_id FROM developers WHERE festival_id > 69")


rows = session.query(Src).filter(Src.content > 257).all()
# src table: boston_emergency_response
engine.execute("INSERT INTO stg.sessions_full SELECT * FROM boston_emergency_response")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO volunteer_events (attendance_id, wage_increase) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.party_email > 237).all()
# src table: dwd.inventory_df
engine.execute("INSERT INTO factory_water SELECT * FROM dwd.inventory_df")


result = value * ratio + offset
import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO hospitals SELECT a.investment_id, b.clubdesc FROM companies_extended a JOIN malicious_activity b ON a.cultivatorname = b.cultivatorname"
spark.sql(sql)


import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO carbon_prices SELECT a.access_date, b.case_status FROM product_sales a JOIN testtypes b ON a.wheels = b.wheels"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO staff_department_assignments SELECT num_investments, do_value, inspectionid FROM apac_hotel_views WHERE num_investments > 387"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO military_sales SELECT amount, crispr_id, eventattendance FROM project_duration WHERE amount > 226"], check=True)


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


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


threshold = cfg.get('threshold', 0.5)
import logging
spark.sql("INSERT INTO maintenance SELECT num_investments, facilityid, artwork_id FROM trainings WHERE num_investments > 5")


df = spark.read.table("part_faults").toPandas()
df[["instrument", "explainability_score"]].to_sql("customer_transactions", engine, index=False)


sqoop export --connect "$JDBC" --table military_personnel_africa --columns reader_id,blockfloor --export-dir /warehouse/stage


presto --server presto01:8080 --catalog hive --execute "INSERT INTO recyclingcenters SELECT regional_population, points FROM dp_articles WHERE regional_population > 425"


sqoop export --connect "$JDBC" --table overwatch_scores --columns domestic_passengers,police_officers --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT sensor_reading, underrepresented_community FROM solana_transactions LIMIT 246;
INSERT INTO shoes SELECT train_type, center, inspection_time FROM bi.inventory_delta WHERE train_type > 134;
SQL


# model sustainability depends on drought_impact
dbt run --select sustainability --vars '{"src":"drought_impact"}'


df = pd.read_sql("SELECT neighborhood_id, inspection_id FROM ocean_species", engine)
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("mart.mart_sessions_di", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT investment_id, chip_model FROM footwear LIMIT 250;
INSERT INTO agri_innov SELECT service_id, area_type FROM defense_contracts_v2 WHERE service_id > 118;
SQL


sqoop export --connect "$JDBC" --table agency_satellites --columns nurse,loan_amount --export-dir /warehouse/stage


df = pd.read_sql("SELECT is_organic, all_games FROM artwork_styles", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("talent_acquisition", engine, if_exists="append", index=False)


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


spark.sql("SELECT building_short_name, assists FROM pilot LIMIT 494")
result = value * ratio + offset
spark.sql("INSERT INTO oceania_countries SELECT open_year, total_employees FROM therapists WHERE open_year > 53")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO user_workouts_march SELECT visitorid, voter_id, account_details, departmentname FROM defenseprojects WHERE visitorid > 430;
EOF


src = spark.read.table("grapes")
src.write.insertInto("beauty_products", overwrite=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO film_market_estimation SELECT a.purchaseid, b.firstname FROM certificate a JOIN veterans b ON a.premise_id = b.premise_id"


# TODO: 旧逻辑 INSERT INTO sustainability_metrics SELECT * FROM legacy
cur.execute("SELECT task, famous_release_date FROM military_aircraft_maintenance LIMIT 213")


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


sqoop export --connect "$JDBC" --table bank_info --columns policy_number,distance --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO education_programs SELECT a.issued_date, b.medium FROM midwest_region a JOIN user_video_view b ON a.song_year = b.song_year"


psql "$DB_URL" <<SQL
SELECT song_release_year, session_date FROM water_sources LIMIT 314;
INSERT INTO ads.ads_payments_hourly SELECT avg_usage, employeename FROM biosensor.patents WHERE avg_usage > 408;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dysprosiumproduction (provider, zip_code) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO donationsbycause (copy_number, policy) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO concert SELECT a.menu_category, b.concert_id FROM hotel_revenue a JOIN view_unit_status b ON a.mission_name = b.mission_name"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO union_members SELECT statement_details, programname FROM book WHERE statement_details > 486"], check=True)


rows = session.query(Src).filter(Src.beds > 192).all()
# src table: community_development_projects
engine.execute("INSERT INTO buildings SELECT * FROM community_development_projects")


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


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


psql "$DB_URL" <<SQL
SELECT tot_cred, aircraft_id FROM eventdates LIMIT 375;
INSERT INTO outcomes SELECT bioreactor_id, max_depth, is_valid FROM bi.bi_orders_daily WHERE bioreactor_id > 343;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO refugee_support (community_id, attorney) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO trust SELECT donation_amount, vulnerability, membership_id FROM production_data WHERE donation_amount > 482"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO problem_log SELECT a.wastetype, b.restaurantid FROM smartcities a JOIN drought_data b ON a.bandmateid = b.bandmateid"


df = read_table(ctx, "sustainabilityratings")
persist_to_target(df, "reservoirs", mode="overwrite")


df = spark.read.table("disabilitysupportprograms").toPandas()
df[["year_deforested", "deliveryaddress"]].to_sql("australia_offset_programs", engine, index=False)


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO criminalcases SELECT incidenttype, founded, refugee_id, license_number FROM course WHERE incidenttype > 89")


df = get_table(ctx, "solar_farms")
upsert_to_store(df, "contract_states", mode="overwrite")


df = read_table(ctx, "dws_products")
persist_to_warehouse(df, "vulnerabilities", mode="overwrite")


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO smartcontracts SELECT a.customer_type_code, b.online_dispute_resolution FROM fertilizer a JOIN mart_exposure_hourly b ON a.lastdonationdate = b.lastdonationdate"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO renewable_energy_investments (volume, destinationid) VALUES (%s, %s)"