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


df = get_input(ctx, "ai_systems")
sink_to_sink(df, "cosmetic_sales", mode="overwrite")


cur.execute("SELECT rural_area, age_group_id FROM workplaces LIMIT 137")
rows = cur.fetchall()
import logging


src = spark.read.table("renewable_energy_investments")
src.write.insertInto("global_tournament", overwrite=True)


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


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


# TODO: 旧逻辑 INSERT INTO forests SELECT * FROM legacy
cur.execute("SELECT points_per_game, kills FROM port_visits LIMIT 268")


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


echo "dry-run: INSERT INTO artists_valuation SELECT 1"
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
trap 'echo failed' ERR


spark-sql --master yarn -e "INSERT INTO donations2022 SELECT image_date, ll_hours, volunteerjoindate, org_id FROM wells WHERE image_date > 271"


cur.execute("SELECT location, sales_id FROM complaints LIMIT 214")
rows = cur.fetchall()
import logging


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO rural_resources SELECT post_date, opid, replacement_cost FROM trade_history WHERE post_date > 489"


cur.execute("SELECT built, account_id FROM infantmortalitydata LIMIT 500")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset
import logging


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO event_attendance (circuitid, staystart) VALUES (%s, %s)"


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


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


df = pd.read_sql("SELECT customername, attraction_type_description FROM supportservices", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("bias_categories", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT userid, feedid FROM recalls", engine)
logger = logging.getLogger(__name__)
df.to_sql("stg.risk_score_hourly", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.other_details > 378).all()
# src table: market
engine.execute("INSERT INTO workforce_training SELECT * FROM market")


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO plots SELECT channel_code, brandid, certification FROM artifact_analysis WHERE channel_code > 498")


beeline -u "$HS2_URL" -e "INSERT INTO waterconsumptionbyoperation SELECT contributorid, lawyer_name, fair_trade, country FROM space_agencies_2 WHERE contributorid > 263"


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


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


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO government.region SELECT a.participant_count, b.countryid FROM authenticationlogs a JOIN audience b ON a.workout_name = b.workout_name"
spark.sql(sql)


result = value * ratio + offset
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO chemical_processes SELECT airport_name, complaint_status_code FROM ods.ods_clicks_di WHERE airport_name > 173")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mart_refunds_delta SELECT a.network_name, b.adoption_date FROM securityincidents a JOIN athletes b ON a.social_impact_score = b.social_impact_score"


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


df = spark.read.table("sustainable_fabrics").toPandas()
df[["regional_population", "directed_by"]].to_sql("investments", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO bi_shipments_daily SELECT company_type_code, claim_amount, contact_number FROM safetytestingcounts WHERE company_type_code > 129"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bi.bi_vendors_di (therapy_id, recycler_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = pull_source(ctx, "ads.ads_products_hourly")
save_to_store(df, "concert_revenue", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO investors SELECT bookings, quantitysold, visitorid FROM apac_hotel_views WHERE bookings > 401")


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
sql = "INSERT INTO skincare_sales SELECT a.initiativeid, b.assistingnurse FROM marine_conservation a JOIN minor_in b ON a.is_recycled = b.is_recycled"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO ticket_sales SELECT completion_date, staff_last_name, transaction_volume, business_size FROM organization_contact_individuals WHERE completion_date > 323"


metrics.append(round(score, 4))
import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO dwd.events_daily SELECT a.survey_id, b.emp_id FROM causes a JOIN submersible_dives b ON a.vehicle_details = b.vehicle_details"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO species_data SELECT * FROM legacy
cur.execute("SELECT online_dispute_resolution, protected FROM categories LIMIT 195")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO development_hours (trip_type, word_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO shariah_compliant_loans SELECT neighborhood_id, workout_id, sensor_reading FROM workshops WHERE neighborhood_id > 68;
EOF


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


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


sqoop export --connect "$JDBC" --table healthcare_system --columns host_city,workshop_group_id --export-dir /warehouse/stage


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


sqoop export --connect "$JDBC" --table habitat --columns amount_due,excavation_site --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO donation SELECT budgetid, round_number FROM captain WHERE budgetid > 234"


sqoop export --connect "$JDBC" --table cb_agreements --columns funding_amount,stu_dob --export-dir /warehouse/stage


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


rows = session.query(Src).filter(Src.don_name > 369).all()
# src table: education_programs
engine.execute("INSERT INTO water_sources SELECT * FROM education_programs")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO premises (mediatorid, fair_trade) VALUES (%s, %s)"


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


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


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


df = pd.read_sql("SELECT stageposition, marketing_region_code FROM customer_events", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("county", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT product_subcategory, physician FROM hotel_ratings LIMIT 166;
INSERT INTO ref_incident_type SELECT votes, appelation FROM agro_regions WHERE votes > 113;
SQL


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


# model musicgenre depends on dwd.dwd_payments
dbt build --models musicgenre --vars '{"source_table":"dwd.dwd_payments"}'


cur.execute("SELECT algorithmic_fairness_score, rehab_date FROM healthequitymetrics LIMIT 184")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ref_locations SELECT competition_type, offender_name, artist_gender FROM community_programs WHERE competition_type > 369;
EOF


spark.sql("SELECT address_road, dept_store_id FROM language LIMIT 173")
import logging
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO salinity_readings SELECT farm_name, allocation_type, aid_id, staff_gender FROM mining_operations WHERE farm_name > 169")


spark.sql("SELECT gross_worldwide, vehicle FROM assignedto LIMIT 43")
metrics.append(round(score, 4))
spark.sql("INSERT INTO station_company SELECT operating_system, model_id, official_name FROM game_results WHERE operating_system > 136")


trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO asset_parts SELECT dish_id, manufacturer_name, distance, customer_status_code FROM waste_generation_city_v2 WHERE dish_id > 165"


spark-sql --master yarn -e "INSERT INTO culturalpractices SELECT attendee_id, partid FROM immunization WHERE attendee_id > 403"


mkdir -p /tmp/joblog
set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO vessel SELECT professionalid, test_result, timestamp FROM temperature_data WHERE professionalid > 419"


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


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


sqoop export --connect "$JDBC" --table mappinglengths --columns astronaut,restaurant --export-dir /warehouse/stage


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


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


beeline -u "$HS2_URL" -e "INSERT INTO deep_sea_expeditions SELECT period, flno, subscriber_id, county_name FROM student WHERE period > 282"


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


psql "$DB_URL" <<SQL
SELECT extraction_state, area_id FROM menuitems LIMIT 447;
INSERT INTO textileworkers SELECT price, strain_name, local_authority, grant_name FROM customer WHERE price > 297;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO food_items SELECT a.royal_family_details, b.contact_number FROM water_distribution a JOIN carbon_pricing b ON a.investment_date = b.investment_date"


df = pd.read_sql("SELECT * FROM facility_production", conn)
df.to_sql("public.developers", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO ods.ods_users_di SELECT * FROM legacy
cur.execute("SELECT sales_details, games FROM workforcediversity LIMIT 4")


psql -h "$PGHOST" -U etl -c "INSERT INTO esports_teams SELECT a.bedtype, b.is_organic FROM contract_negotiations a JOIN textile_waste b ON a.port_name = b.port_name"


beeline -u "$HS2_URL" -e "INSERT INTO accessibility_audits SELECT refugee_id, metric_id, organisation_details FROM mental_health_parity_violations WHERE refugee_id > 477"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO displaced_people (ai_customer_service, checkout) VALUES (%s, %s)"


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


df = spark.read.table("danceevents").toPandas()
df[["cid", "prereq_id"]].to_sql("flu_cases", engine, index=False)


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


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


df = get_table(ctx, "smart_contracts_transactions")
write_to_store(df, "conservation_programs", mode="overwrite")


# model traffic depends on feed
dbt run --models traffic --vars '{"src":"feed"}'


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


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


df = load_table(ctx, "animal_rehab")
persist_to_target(df, "ads.ads_users_hourly", mode="overwrite")


df = spark.read.table("vendorfabrics").toPandas()
df[["working_year_starts", "inventoryid"]].to_sql("arctic_research", engine, index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO news_stories SELECT level, community_members, productionrate FROM record WHERE level > 163"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO soccer_goals (official_native_language, ingredient_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO seeds SELECT airline, num_of_factories FROM postseason WHERE airline > 485;
EOF


import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO market SELECT fare_amount, emissions, publisher FROM ods.ods_risk_score_full WHERE fare_amount > 17")


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


df = spark.read.table("playersessions").toPandas()
df[["organisation_type", "organic_matter"]].to_sql("bioprocess.engineering_projects", engine, index=False)


psql "$DB_URL" <<SQL
SELECT speed, screen_mode FROM landfill_capacity LIMIT 344;
INSERT INTO article_views SELECT altitude, caloric_content, date_formed, worker_id FROM cargo_data WHERE altitude > 445;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws.dws_events_df SELECT injury_count, equipment_id, login_name, actor_id FROM regular_order_products WHERE injury_count > 228"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO department_stores (offense, num_pallets) VALUES (%s, %s)"


psql "$DB_URL" <<SQL
SELECT member, accreditation_type FROM contract_states LIMIT 237;
INSERT INTO rural_feeder_roads SELECT district, personnelid, price_range, launch_date FROM steps WHERE district > 134;
SQL


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


df = pd.read_sql("SELECT worker, phone_number FROM development_hours", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("beverages", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT vaccine_type, address_line_2 FROM college LIMIT 43;
INSERT INTO bi.bi_inventory SELECT instructor_id, company, length_feet FROM ads.orders_daily WHERE instructor_id > 336;
SQL


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


# TODO: 旧逻辑 INSERT INTO labor_practices SELECT * FROM legacy
cur.execute("SELECT enable_dm, outcome_type FROM producersnewmexico LIMIT 234")


result = value * ratio + offset
import logging
spark.sql("INSERT INTO contracts SELECT attendees, lastclaimdate, museum_name FROM products_in_events WHERE attendees > 325")


spark.sql("SELECT catalog_name, policyholderid FROM ods.campaigns_di LIMIT 54")
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO tracklists SELECT habitat, born_state FROM clinics_sa WHERE habitat > 394")


cur.execute("SELECT response_time, charging_level FROM timed_locations_of_things LIMIT 378")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


src = spark.read.table("communitycenters")
src.write.insertInto("view_unit_status", overwrite=True)


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


spark-sql --master yarn -e "INSERT INTO donation SELECT billing_city, retailer_name, last_updated FROM vr_adopters WHERE billing_city > 383"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO astronautmedicaldata (stayid, language) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO shared_ebikes SELECT claim_status_description, negotiation_date, treatment_type, workshop_name FROM defense_contractors WHERE claim_status_description > 271"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO atlantic_ocean (safety_rating, delivery_id) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table assets --columns budget_type_description,customer_first_name --export-dir /warehouse/stage


df = pd.read_sql("SELECT track_id, attendeename FROM impact_investments", engine)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
df.to_sql("characteristics", engine, if_exists="append", index=False)


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


# TODO: 旧逻辑 INSERT INTO public.developers SELECT * FROM legacy
cur.execute("SELECT cows, goal_id FROM solar_plants LIMIT 229")


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO platformi SELECT a.trade, b.followers FROM levees a JOIN hotel_tech_adoptions b ON a.roomid = b.roomid"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO ai_papers SELECT artifact_name, spectators, approach, other_characteristic_details FROM catalogs WHERE artifact_name > 359"


df = spark.read.table("government_funding").toPandas()
df[["loan_amount", "call_count"]].to_sql("impact_investments", engine, index=False)


spark-sql --master yarn -e "INSERT INTO environmentalimpact SELECT dose, streamid FROM expensive_space_missions WHERE dose > 134"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO immunizationrates (mission_name, orderid) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO customersregion SELECT courses, production_rate, area_sqkm FROM intelligence_agents WHERE courses > 294"


df = load_dataset(ctx, "satellitedata")
push_to_target(df, "water_sources", mode="overwrite")


spark.sql("SELECT time_of_day, sex FROM bi.products_daily LIMIT 357")
import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO accounts SELECT contract_start, billing_country, material, date_of_latest_revision FROM safety_research WHERE contract_start > 190")


rows = session.query(Src).filter(Src.impressions > 211).all()
# src table: community_policing_events
engine.execute("INSERT INTO sitem SELECT * FROM community_policing_events")


df = spark.read.table("middle_east_military_spending").toPandas()
df[["artworkyear", "vesselid"]].to_sql("shipmentinfo", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO state_budget (sustainable, call_id) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO green_energy_lending_programs SELECT a.totalamount, b.number_of_hosts FROM carbon_offset_projects a JOIN all_documents b ON a.vulnerability_score = b.vulnerability_score"


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


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


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mentalhealthprofessional (excavationid, security_level) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO recyclingprogram SELECT safety_score, birthdate, team_id FROM viewership WHERE safety_score > 180"], check=True)


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ads.refunds (ai_algorithm_id, maintenance_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO publication SELECT a.g_name, b.to_address FROM ads.ads_vendors_hourly a JOIN dw.exposure_di b ON a.creationyear = b.creationyear"


spark-sql --master yarn -e "INSERT INTO bikerental SELECT inventory_id, contractor_name, reservoir_id FROM assignedto WHERE inventory_id > 102"


rows = session.query(Src).filter(Src.build_date > 28).all()
# src table: wastewater_treatment_plants
engine.execute("INSERT INTO movies SELECT * FROM wastewater_treatment_plants")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO inspection SELECT gdp, issue, concert_id, attendee_id FROM water_usage WHERE gdp > 197"


psql -h "$PGHOST" -U etl -c "INSERT INTO diversion_programs SELECT a.constructorid, b.detention_summary FROM safety_violations a JOIN farmer_details b ON a.paritystatus = b.paritystatus"


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


df = spark.read.table("marine_mammals").toPandas()
df[["dish_id", "adoption_date"]].to_sql("sports_events", engine, index=False)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO trees SELECT is_unionized, booked_count FROM talent_acquisition WHERE is_unionized > 151"], check=True)


# model circulation_history depends on public.crime_types
dbt build --models circulation_history --vars '{"src":"public.crime_types"}'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO indigenouscommunities SELECT card_number, meal_name FROM catalog_contents WHERE card_number > 88;
EOF


df = spark.read.table("budget").toPandas()
df[["total_cost", "account_name"]].to_sql("takes", engine, index=False)


# model carbon_prices_3 depends on shark_biomass
dbt build -s carbon_prices_3 --vars '{"src":"shark_biomass"}'


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


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO chemical_composition SELECT transaction_date, team_id_loser, round_number FROM products_in_events WHERE transaction_date > 495"


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO rural.bus_trips SELECT a.document_structure_code, b.staff_name FROM school_enrollment a JOIN international_visitors b ON a.destination_name = b.destination_name"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT productcategory, assessmentid FROM ads.ads_exposure_daily LIMIT 62;
INSERT INTO music_events SELECT campaign_id, contract_id, policy_name, duration_ms FROM militarydrones WHERE campaign_id > 357;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO marine_conservation (carrierid, jobtitle) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("member").toPandas()
df[["session_date", "violation_type"]].to_sql("budget", engine, index=False)


# model sales_by_quarter depends on traditionalarts
dbt run --models sales_by_quarter --vars 'source: traditionalarts'


# TODO: 旧逻辑 INSERT INTO event_attendance SELECT * FROM legacy
cur.execute("SELECT train_number, disability FROM recycledmaterialsgarments LIMIT 239")


# TODO: 旧逻辑 INSERT INTO school SELECT * FROM legacy
cur.execute("SELECT co2_offset_amount, operation_type FROM wrestler LIMIT 220")


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


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


# TODO: 旧逻辑 INSERT INTO marine_species_observations SELECT * FROM legacy
cur.execute("SELECT handling_date, decision FROM miningoperations LIMIT 287")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO military_sales SELECT a.awards, b.kills FROM global_sales_2022 a JOIN cotton_source b ON a.bicycle_id = b.bicycle_id"


beeline -u "$HS2_URL" -e "INSERT INTO trends_2022 SELECT numcases, negative FROM mart_campaigns_delta WHERE numcases > 307"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO video_content SELECT deliverydate, news_outlet, trial_id, stayid FROM user_reactions WHERE deliverydate > 341"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO contract_timeline SELECT stream_date, violation_type, bus_id FROM ocean_pollution WHERE stream_date > 172;
EOF


df = pd.read_sql("SELECT negotiation_date, date_order_placed FROM carbon_offsets", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("fans_merchandise_basketball", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table cars --columns ethical_manufacturing,num_workers --export-dir /warehouse/stage


cur.execute("SELECT extraction_state, hometeamid FROM safety_incidents LIMIT 173")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO results SELECT community_name, prof_high_degree, address_content, participant_name FROM art_workshops WHERE community_name > 480")


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO community_engagement SELECT productcategory, task, recipient_id FROM green_building_projects WHERE productcategory > 49")


spark.sql("SELECT ingredient_name, destroyed_by_employee_id FROM infrastructure_projects LIMIT 498")
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO streams SELECT approval_date, founder_count FROM tourism_centers WHERE approval_date > 309")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO architect SELECT item_price, virtual_tour_engagement_time FROM arctic_sightings WHERE item_price > 27;
EOF


cur.execute("SELECT member, temp FROM artist_demographics LIMIT 480")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO lives_in (professional_development_programs, company_type_code) VALUES (%s, %s)"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart_orders_di SELECT area_ha, height FROM animals WHERE area_ha > 436"], check=True)


spark.sql("SELECT host_id, grant_type FROM stg.stg_device_log_daily LIMIT 185")
import logging
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO rehab_centers SELECT purchaseid, job_title FROM permit WHERE purchaseid > 438")


spark.sql("SELECT hometown, track_id FROM defense_spending LIMIT 437")
import logging
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO bi.bi_vendors_di SELECT label_id, customer_code FROM ocean_pollution WHERE label_id > 432")


psql "$DB_URL" <<SQL
SELECT athlete, is_ev FROM document_locations LIMIT 46;
INSERT INTO ads.ads_campaigns_full SELECT dept_code, market_share FROM military_personnel_africa WHERE dept_code > 123;
SQL


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO galleryc SELECT financially_capable, seating, delivery_status, retweets FROM tournaments WHERE financially_capable > 461"


rows = session.query(Src).filter(Src.curator > 143).all()
# src table: research.species
engine.execute("INSERT INTO traffic_violations SELECT * FROM research.species")


rows = session.query(Src).filter(Src.funding_round_id > 31).all()
# src table: customer_size_diversity
engine.execute("INSERT INTO waterconservationbudget SELECT * FROM customer_size_diversity")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO accommodations (chip_model, trainingdate) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table defense_contractors --columns storm_id,impactid --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO visual_arts SELECT a.dphone, b.citation_time FROM crops a JOIN shrimp_farms b ON a.menu_id = b.menu_id"


df = fetch_source(ctx, "european_healthcare")
export_to_sink(df, "oil_production", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO suburbs (address, school_colors) VALUES (%s, %s)"


df = spark.read.table("student_courses").toPandas()
df[["crane_id", "opid"]].to_sql("shoes", engine, index=False)


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


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


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


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


# model address depends on classrooms
dbt build -s address --vars '{"src":"classrooms"}'


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


df = read_dataset(ctx, "textile_waste")
push_to_target(df, "journal_committee", mode="overwrite")


rows = session.query(Src).filter(Src.work_type > 219).all()
# src table: movies
engine.execute("INSERT INTO job_postings SELECT * FROM movies")


spark.sql("SELECT catalog_id, staff_first_name FROM ads.ads_payments_hourly LIMIT 131")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO voting_data SELECT domestic_passengers, address_details FROM professionals WHERE domestic_passengers > 21")


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


spark-sql --master yarn -e "INSERT INTO ads_vendors_hourly SELECT courses, follows_ethical_practices FROM ods.ods_member_point_df WHERE courses > 271"


psql "$DB_URL" <<SQL
SELECT no_of_customers, budget_amount FROM donationprograms LIMIT 492;
INSERT INTO districts SELECT debate_id, platform_id FROM mart.mart_payments_delta WHERE debate_id > 240;
SQL


df = pd.read_sql("SELECT area_sqkm, class_president_vote FROM hospitallocations", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("ticket_sales", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dws.inventory_df SELECT community_id, subject_id FROM production_sites WHERE community_id > 15"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO policyholders SELECT visitor_count, amount_funded, membership, artistid FROM employment WHERE visitor_count > 9"


spark-sql --master yarn -e "INSERT INTO contract_timeline SELECT registration_id, join_date FROM retailers WHERE registration_id > 285"


df = pd.read_sql("SELECT dateundergoes, daily_sales FROM initiative_types", engine)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
df.to_sql("preferences", engine, if_exists="append", index=False)


mkdir -p /tmp/joblog
set -euo pipefail
sqoop import --connect "$JDBC" --table animal_population --target-dir /tmp/land


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO healthequitymetrics (algorithm, patentexpirationdate) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.claimdate > 144).all()
# src table: battery_projects
engine.execute("INSERT INTO circular_economy_initiatives SELECT * FROM battery_projects")


logger = logging.getLogger(__name__)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ai_safety_papers2 SELECT nickname, asset_make, onscholarship FROM user_likes WHERE nickname > 316")


src = spark.read.table("mental_health_parity_violations")
src.write.insertInto("mammals", overwrite=True)


mkdir -p /tmp/joblog
trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO euro_champs_track_field SELECT group_id, resource_id FROM restorative_justice_sentences WHERE group_id > 15"


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


spark-sql --master yarn -e "INSERT INTO facility_production SELECT enroll_grade, school_name, dockingdate FROM guests WHERE enroll_grade > 465"


df = pd.read_sql("SELECT model, membership FROM hotel_chains", engine)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
df.to_sql("rd_expenditure", engine, if_exists="append", index=False)


import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO fair_wages SELECT mission_name, complaint_status_code, cmi_details FROM languagesatrisk WHERE mission_name > 14")


df = load_dataset(ctx, "park")
save_to_target(df, "platform", mode="overwrite")


export TZ=Asia/Shanghai
hive -e "INSERT INTO consumer SELECT inventory_id, institution_id, founder_ethnicity, invoice_date FROM climber WHERE inventory_id > 14"


cur.execute("SELECT provider_parity_score, fertilizer_id FROM budgets LIMIT 110")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


export TZ=Asia/Shanghai
hive -e "INSERT INTO product_details SELECT campaign_id, last_name, sodium, is_safe FROM smartcities WHERE campaign_id > 389"


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO city_waste_generation SELECT a.market_share, b.asset_type FROM ref_document_status a JOIN environmental_impact b ON a.disability = b.disability"
spark.sql(sql)


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


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


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


set -euo pipefail
hive -e "INSERT INTO stats SELECT visitor_country, votes, taxi_model FROM department_stores WHERE visitor_country > 298"


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


rows = session.query(Src).filter(Src.device_name > 470).all()
# src table: exhibition
engine.execute("INSERT INTO recyclingrates SELECT * FROM exhibition")


psql -h "$PGHOST" -U etl -c "INSERT INTO conservation_initiatives SELECT a.causeid, b.email FROM esportsevents a JOIN county b ON a.sustainability_id = b.sustainability_id"


psql "$DB_URL" <<SQL
SELECT role_description, bedtype FROM excavation LIMIT 382;
INSERT INTO dw_member_point_full SELECT venue, attorney_last_name, functional_area_description, sentence_length FROM water_sources WHERE venue > 489;
SQL


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


df = read_source(ctx, "vendors")
save_to_sink(df, "ratings", mode="overwrite")


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


cur.execute("SELECT sd_id, supplier_company_id FROM tracklists LIMIT 41")
rows = cur.fetchall()
metrics.append(round(score, 4))


psql -h "$PGHOST" -U etl -c "INSERT INTO accessible_tech_categories SELECT a.artifactname, b.catalog_level_number FROM cb_agreements a JOIN healthcare b ON a.home_games = b.home_games"


result = value * ratio + offset
sql = "INSERT INTO caribbeansea SELECT a.launch_company, b.destruction_authorised_by_employee_id FROM technician a JOIN courts b ON a.u_id = b.u_id"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT productionrate, event_type FROM maintenance_schedule LIMIT 286;
INSERT INTO sites SELECT number_cities, fabrictype, team_id, date_of_latest_revision FROM crime_reports WHERE number_cities > 498;
SQL


result = value * ratio + offset
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO song SELECT a.donator_name, b.asset_model FROM tree_types a JOIN travel_advisory b ON a.providerid = b.providerid"
spark.sql(sql)


df = spark.read.table("daily_revenue")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("donations2022")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO shariah_financing SELECT price_range, governor, document_status_code, max_wind_speed_mph FROM wine WHERE price_range > 455"


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


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


src = spark.read.table("construction_labor_stats")
src.write.insertInto("space_telescopes", overwrite=True)


spark-sql --master yarn -e "INSERT INTO carbon_pricing SELECT training_id, park, stu_gpa FROM ads_users_hourly WHERE training_id > 156"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO therapy_sessions SELECT date_of_ceremony, rank, hiv, initiativeid FROM waterconsumptionbyoperation WHERE date_of_ceremony > 384;
EOF


set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO ods_risk_score_delta SELECT mission_name, organisation_type_description FROM mappinglengths WHERE mission_name > 16"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart_refunds SELECT research_name, recipe_id, participation_id FROM ai_safety WHERE research_name > 163"


psql "$DB_URL" <<SQL
SELECT built_year, currency FROM cmi_cross_references LIMIT 474;
INSERT INTO show SELECT playtime, primary_conference, annual_revenue FROM renewable_energy_investments WHERE playtime > 479;
SQL


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


# TODO: 旧逻辑 INSERT INTO public_works_projects SELECT * FROM legacy
cur.execute("SELECT game_count, founded FROM inspectiondata LIMIT 118")


df = pd.read_sql("SELECT spacecraft_model, advocate_name FROM innovation_grants", engine)
import logging
df.to_sql("ads.campaigns_di", engine, if_exists="append", index=False)


src = spark.read.table("workouts")
src.write.insertInto("bi.coupon_use", overwrite=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO artwork (date_of_transaction, rank_in_round) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.avg_depth > 81).all()
# src table: stg.stg_exposure_daily
engine.execute("INSERT INTO ods.coupon_use SELECT * FROM stg.stg_exposure_daily")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO funding_rounds SELECT contractorid, meal_id, accessibility FROM equipmentsales WHERE contractorid > 70"


df = spark.read.table("subway").toPandas()
df[["attribute_data_type", "last_checkup_date"]].to_sql("user_workouts_march", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO runs SELECT dispensary_name, sustainabilityid, injury_count, avg_usage FROM waste_production WHERE dispensary_name > 208"


spark.sql("SELECT resource_id, trip_type FROM fairtradecertification LIMIT 52")
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO harvest_permits SELECT shop_details, inclusive_housing_policy FROM biosensors.readings WHERE shop_details > 465")


beeline -u "$HS2_URL" -e "INSERT INTO royal_family SELECT providerid, issue_date FROM regions WHERE providerid > 327"


beeline -u "$HS2_URL" -e "INSERT INTO tourism_centers SELECT sales_amount, call_time, chemicalid FROM login_attempts WHERE sales_amount > 170"


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


sqoop export --connect "$JDBC" --table green_projects --columns haslegalprecedent,safety_rating --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO rooms SELECT dept_store_chain_id, game_name, num_developments FROM product_reviews WHERE dept_store_chain_id > 489"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO people SELECT mealid, document_status_description, release_date, investmenttype FROM cargo_handling WHERE mealid > 75"], check=True)


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO government.region SELECT a.emp_num, b.detention_type_code FROM birds a JOIN all_programs b ON a.clinic_type = b.clinic_type"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO manufacturing_processes SELECT species, wrestler_id, movie_id FROM dws.risk_score_daily WHERE species > 369"


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


beeline -u "$HS2_URL" -e "INSERT INTO shariahfinance SELECT thefttypeid, fiscal_year, medical_risk, ship_id FROM criminal_cases WHERE thefttypeid > 322"


rows = session.query(Src).filter(Src.building_type > 205).all()
# src table: city_labor_cost
engine.execute("INSERT INTO bike_share SELECT * FROM city_labor_cost")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO atlantic_plate (taxi_model, archaeologistid) VALUES (%s, %s)"


trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO regional_archaeologists SELECT num_libraries, home_games FROM family_cases WHERE num_libraries > 139"


spark-sql --master yarn -e "INSERT INTO swimmer SELECT lettergrade, length FROM mart_campaigns_delta WHERE lettergrade > 96"


mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO market_access SELECT source, artist_id FROM audience_demographics WHERE source > 223"


cur.execute("SELECT male_id, date_moved_in FROM ads.orders LIMIT 16")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
result = value * ratio + offset


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO daily_articles_by_category (cause, wage) VALUES (%s, %s)"


df = get_dataset(ctx, "landfillcapacitybycountry")
save_to_target(df, "scan_dates", mode="overwrite")


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO country_waste_generation SELECT shipment_id, campaign_id, playtime, workers FROM ads.orders_daily WHERE shipment_id > 13"


src = spark.read.table("dwd.coupon_use_full")
src.write.insertInto("city_department", overwrite=True)


df = spark.read.table("ods_risk_score_delta").toPandas()
df[["physician", "representative_name"]].to_sql("startup_founders", engine, index=False)


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


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


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


sqoop export --connect "$JDBC" --table foodsafetyrecords --columns recycler_id,part_id --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.cause_name > 290).all()
# src table: community_development_projects
engine.execute("INSERT INTO stg.cart_item_full SELECT * FROM community_development_projects")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO navalequipmentmaintenance SELECT users_engaged, farmid, co2_emissions FROM exhibition_artworks WHERE users_engaged > 94"


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


spark.sql("SELECT artist_gender, trial_success_rate FROM user_likes LIMIT 141")
metrics.append(round(score, 4))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO inclusion_efforts SELECT player, service_type, entryid, volunteer_date FROM gymnast WHERE player > 497")


df = spark.read.table("school_details").toPandas()
df[["species", "clubid"]].to_sql("buildingpermits", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO home_game SELECT a.supplier_name, b.menu_category FROM product_catalog a JOIN healthcare_facilities b ON a.trial_year = b.trial_year"


df = spark.read.table("cybersecurity_incidents").toPandas()
df[["donor_category", "productname"]].to_sql("rural_clinics", engine, index=False)


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


mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO train_lines SELECT countryname, dormid, product_color FROM fabrics WHERE countryname > 262"


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


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO salary SELECT safety_score, frameworkcountry, number_cities, permit_id FROM communitycourts WHERE safety_score > 359"


# model weekly_weather depends on emergencies
dbt build -s weekly_weather --vars 'source: emergencies'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO rental (inventor_name, cuisine_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO teams SELECT transaction_type_description, min_salary FROM reverselogisticstransactions WHERE transaction_type_description > 378"


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


# model riskassessments depends on departments
dbt build --models riskassessments --vars 'source: departments'


psql -h "$PGHOST" -U etl -c "INSERT INTO all_documents SELECT a.condition, b.updated_at FROM ads.refunds_delta a JOIN educationprograms b ON a.thefttypeid = b.thefttypeid"


spark-sql --master yarn -e "INSERT INTO flu_cases SELECT discount, garment_type, driller, airport FROM customer WHERE discount > 405"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
logger = logging.getLogger(__name__)
sql = "INSERT INTO immunizationrates SELECT a.instructor, b.production_qty FROM screen_mode a JOIN carbonoffsetinitiatives b ON a.time_of_purchase = b.time_of_purchase"
spark.sql(sql)


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


df = source_dataset(ctx, "teaches")
persist_to_sink(df, "crime_reports", mode="overwrite")


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO ref_budget_codes SELECT license_plate, target_name, amount_donated FROM labor_practices WHERE license_plate > 178"


df = source_table(ctx, "item_prices")
write_to_output(df, "feedback", mode="overwrite")


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


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


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


df = pd.read_sql("SELECT grant_date, transit_passengers FROM state_budget", engine)
logger = logging.getLogger(__name__)
df.to_sql("flight_emissions", engine, if_exists="append", index=False)


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO paintings SELECT feature_details, paperid, ethnicity FROM ads.risk_score WHERE feature_details > 241"


df = spark.read.table("efforts").toPandas()
df[["screening", "actor_name"]].to_sql("virtual_tour_stats", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO clothingitems SELECT a.distance, b.market_value_billion FROM innovation_metrics a JOIN locations b ON a.stu_gpa = b.stu_gpa"


beeline -u "$HS2_URL" -e "INSERT INTO marine_mammals SELECT algorithmic_fairness_score, assessmentname, mineral, audienceid FROM dwd.vendors WHERE algorithmic_fairness_score > 116"

algorithmic_fairness_score assessmentname mineral audienceid


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


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


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


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


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


psql "$DB_URL" <<SQL
SELECT schedule_date, playlist_id FROM dw.dw_events_di LIMIT 99;
INSERT INTO sales SELECT insurancetype, project_name, prof_office FROM mart.campaigns_full WHERE insurancetype > 323;
SQL


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


src = spark.read.table("cargos")
src.write.insertInto("sponsorship_donations", overwrite=True)


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


sqoop export --connect "$JDBC" --table savings_programs --columns accident_date,major --export-dir /warehouse/stage


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads_users_hourly SELECT payment_method_code, material_id, hireid FROM bridge WHERE payment_method_code > 251"


spark-sql --master yarn -e "INSERT INTO sustainableprojects SELECT cargo_type, event_type_id, carrierid FROM livestock WHERE cargo_type > 96"


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


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


# TODO: 旧逻辑 INSERT INTO initiatives_3 SELECT * FROM legacy
cur.execute("SELECT diet, defense_contractor_id FROM ocean_acidification_antarctic LIMIT 191")


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


df = spark.read.table("program").toPandas()
df[["field_id", "courtid"]].to_sql("ads.member_point", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO track (job, hourid) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT attribute_id, overall_rating FROM journal_committee", engine)
import logging
df.to_sql("jupiter_missions", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO home_game SELECT system_id, eventtype, community_center_id FROM service_budget WHERE system_id > 419;
EOF


spark-sql --master yarn -e "INSERT INTO office_locations SELECT pollution_id, party_phone, enrollment, subscriber_type FROM sponsor_trials WHERE pollution_id > 335"


df = spark.read.table("university").toPandas()
df[["prereq_id", "review_text"]].to_sql("stg.users", engine, index=False)


df = pd.read_sql("SELECT dno, item_sold FROM circularsupplychain", engine)
result = value * ratio + offset
df.to_sql("public.crime_types", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO countries (num_solo_exhibitions, provider_name) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO habitat SELECT partner_id, surface_area FROM networkdevices WHERE partner_id > 352"], check=True)


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


df = spark.read.table("accelerator_compatible_browser").toPandas()
df[["num_employees", "quality"]].to_sql("papers", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO drama_workshop_groups SELECT amount_outstanding, workshop_name FROM communitydevelopment WHERE amount_outstanding > 329"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO culturalcompetency (drug_name, labor_hour_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = load_frame(ctx, "vehiclemodels")
push_to_target(df, "membership_register_branch", mode="overwrite")


trap 'echo failed' ERR
hive -e "INSERT INTO dispensary_sales SELECT denomination, contractor, potency FROM gamedesigndata WHERE denomination > 436"


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


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


psql "$DB_URL" <<SQL
SELECT district_id, is_recycled FROM brandrevenue LIMIT 479;
INSERT INTO pollution_control_initiatives SELECT head, outcome_type, garment FROM legalaidrequests WHERE head > 296;
SQL


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


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


df = pd.read_sql("SELECT * FROM dw.dw_sessions_delta", conn)
df.to_sql("staff_members", conn, if_exists="replace", index=False)


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO busmaintenance SELECT a.lesson_id, b.phase FROM e_scooter_trips a JOIN waste_generation b ON a.attraction_id = b.attraction_id"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO document_sections_images (applicant, recorded_by_staff_id) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO therapy_attendance SELECT mission_name, treatment_name, hashtags FROM maintenance_engineers WHERE mission_name > 21;
EOF


df = pd.read_sql("SELECT hourlyrate, structure_type FROM authors", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("mine_workforce", engine, if_exists="append", index=False)


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


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO rental SELECT zip, cust_id, albumname FROM railway WHERE zip > 469"


df = pd.read_sql("SELECT contributions, low_estimate FROM bus_fares", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("parking_fines", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO biosensors.readings SELECT restaurantid, trial_name, eventname FROM attorney_billing WHERE restaurantid > 309"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO community.donations SELECT room_count, claim_status_description, club_id, budget_amount FROM container WHERE room_count > 276"], check=True)


rows = session.query(Src).filter(Src.tot_cred > 209).all()
# src table: dwd.dwd_orders_di
engine.execute("INSERT INTO highest_scores SELECT * FROM dwd.dwd_orders_di")


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


# model races depends on community_development.transactions
dbt build -s races --vars '{"src":"community_development.transactions"}'


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO dw.shipments_df SELECT a.order_shipping_charges, b.invoice_id FROM marketingbudget a JOIN continents b ON a.event_details = b.event_details"
spark.sql(sql)


spark.sql("SELECT mission_count, neighborhoodid FROM passenger_trips LIMIT 407")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO greenbuildings SELECT census_ranking, ll_id, team_id_loser FROM artworksales WHERE census_ranking > 286")


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


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


rows = session.query(Src).filter(Src.mean_humidity > 391).all()
# src table: party_events
engine.execute("INSERT INTO coowners SELECT * FROM party_events")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO higher_ed.students SELECT cargoid, date_formed, is_organic FROM dwd.dwd_campaigns_df WHERE cargoid > 249"], check=True)


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


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


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


# model ai_safety depends on volunteer_hours
dbt run --models ai_safety --vars 'source: volunteer_hours'


trap 'echo failed' ERR
echo "job start: $(date +%F)"
hive -e "INSERT INTO biotech_startups SELECT spent, category_id, order_shipping_charges, connection FROM ads.orders WHERE spent > 250"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO philadelphia_police_emergencies SELECT platform_id, volunteerhourid, truck_licence_number, grape FROM astronaut_missions WHERE platform_id > 48"


# TODO: 旧逻辑 INSERT INTO scores SELECT * FROM legacy
cur.execute("SELECT date_of_birth, pcp FROM sustainable_materials LIMIT 468")


df = get_table(ctx, "environmental_impact")
save_to_target(df, "militarybases", mode="overwrite")


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO continents SELECT a.medical_professional_id, b.characteristic_id FROM fish_suppliers a JOIN storage_tech b ON a.num_sessions = b.num_sessions"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT feedback_id, consultations FROM restaurant_revenue LIMIT 150;
INSERT INTO global_tournament SELECT vulnerability_score, revenueid, building_address, number_of_observations FROM ods.ods_events_daily WHERE vulnerability_score > 493;
SQL


rows = session.query(Src).filter(Src.document_code > 429).all()
# src table: temperaturehistory
engine.execute("INSERT INTO inclusion_efforts SELECT * FROM temperaturehistory")


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


df = spark.read.table("dwd.dwd_events_delta").toPandas()
df[["goal_date", "worker_name"]].to_sql("geothermal_power_plants", engine, index=False)


# model al_jazeera_data depends on erc20_transactions
dbt build --select al_jazeera_data --vars '{"source_table":"erc20_transactions"}'


spark-sql --master yarn -e "INSERT INTO mediterranean_salinity SELECT screening_id, instrument FROM functional_areas WHERE screening_id > 110"


cur.execute("SELECT sales_in_billion, individual_last_name FROM skincareinventory LIMIT 352")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))


spark-sql --master yarn -e "INSERT INTO co2_sequestration SELECT assessment_date, show_id, dissolved_oxygen, caloric_content FROM vendors WHERE assessment_date > 486"


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO immunization SELECT city_traffic_speed, exhibition_id FROM southeast_providers WHERE city_traffic_speed > 160"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO program_funding_2 (anomaly, invoice_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT contactid, valuation FROM item_inventory", engine)
import logging
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("ocean_shipping.cargo", engine, if_exists="append", index=False)


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO habitat SELECT rating, team_id_loser FROM screen_mode WHERE rating > 340;
EOF


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO casebilling (field_id, reaction_time) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ytterbium_supply SELECT lanes, plant, exit_type, effort_id FROM countries WHERE lanes > 465;
EOF


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


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


spark-sql --master yarn -e "INSERT INTO peacekeeping_units SELECT material, award, safety_id FROM mart.campaigns_full WHERE material > 492"


threshold = cfg.get('threshold', 0.5)
import logging
spark.sql("INSERT INTO awards SELECT garmentid, building_id FROM middle_east_military_spending WHERE garmentid > 495")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO party_host SELECT campus, took_office FROM purchases WHERE campus > 421;
EOF


spark-sql --master yarn -e "INSERT INTO trafficviolations SELECT trial_success_rate, functional_area_description FROM status WHERE trial_success_rate > 62"


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


beeline -u "$HS2_URL" -e "INSERT INTO eu_data_usage SELECT astronaut_name, train_id, operating_system, password FROM sustainable_practices WHERE astronaut_name > 285"


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


# model dw_coupon_use_daily depends on ancient_cultures
dbt build --select dw_coupon_use_daily --vars '{"src":"ancient_cultures"}'


rows = session.query(Src).filter(Src.order_item_status > 234).all()
# src table: clothingitems
engine.execute("INSERT INTO swimmer SELECT * FROM clothingitems")


spark-sql --master yarn -e "INSERT INTO tourdifferences SELECT moisture, session_name FROM space_exploration WHERE moisture > 321"


src = spark.read.table("esa_missions")
src.write.insertInto("ngo_funding", overwrite=True)


df = fetch_frame(ctx, "supportprograms")
export_to_warehouse(df, "tickets_3", mode="overwrite")


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


beeline -u "$HS2_URL" -e "INSERT INTO eventlocations SELECT subject_name, precipitation, product_subcategory, review_rating FROM assets WHERE subject_name > 180"


df = spark.read.table("dwd.dwd_exposure_df").toPandas()
df[["years_played", "num_volunteers"]].to_sql("concert_events", engine, index=False)


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO drug_sales SELECT school_type, detention_summary, duration_ms FROM members WHERE school_type > 69"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.shipments_full (conservation_status, scan_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT nurse, individual_last_name FROM producers", engine)
logger = logging.getLogger(__name__)
df.to_sql("emergency_categories", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO noise_pollution SELECT gamepreference, negative, company_gender, amount_paid FROM ods.ods_exposure_delta WHERE gamepreference > 299"


sqoop export --connect "$JDBC" --table crop_temperature --columns assessment_score,account_type --export-dir /warehouse/stage


df = spark.read.table("vessel_tracking").toPandas()
df[["fleet_series", "concertid"]].to_sql("program", engine, index=False)


df = spark.read.table("members").toPandas()
df[["individual_id", "aid_id"]].to_sql("participates_in", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO recyclingprogram SELECT city, equipment_type, document_status_code FROM safetyincidents WHERE city > 372"


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


spark.sql("SELECT well_type, fan_id FROM fans LIMIT 215")
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO article_views SELECT event_type_id, type FROM body_builder WHERE event_type_id > 468")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO solana_transactions SELECT grant_end_date, dphone FROM causes_insert_2 WHERE grant_end_date > 37"


echo "job start: $(date +%F)"
hive -e "INSERT INTO thefttypes SELECT posted_at, start_therapy, goal_id FROM busmaintenance WHERE posted_at > 223"


cur.execute("SELECT gross_worldwide, siteid FROM water_sources LIMIT 101")
rows = cur.fetchall()
import logging
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


psql "$DB_URL" <<SQL
SELECT num_solo_exhibitions, reo_type FROM apartments LIMIT 21;
INSERT INTO show SELECT itemname, billingcountry, receipt_date, sustainability_id FROM market WHERE itemname > 264;
SQL


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


cur.execute("SELECT song, channel_code FROM satellite_deployment LIMIT 385")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


df = spark.read.table("ratings").toPandas()
df[["authors", "agency_id"]].to_sql("community_development_projects", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO dwd.dwd_payments_full SELECT a.gendername, b.donorid FROM tasks a JOIN mart.shipments_delta b ON a.count_date = b.count_date"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO tokyo_motor_show SELECT institution_name, competition, local_authority FROM textile_sourcing WHERE institution_name > 350;
EOF


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


spark.sql("SELECT report_type, traveler_id FROM wastewatertreatment LIMIT 245")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO exhibition_visits SELECT therapist_id, heritage_site FROM permian_basin WHERE therapist_id > 194")


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


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


df = pd.read_sql("SELECT hardware_colours, driverid FROM diversity", engine)
logger = logging.getLogger(__name__)
df.to_sql("skincare_sales", engine, if_exists="append", index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO diversification_projects SELECT date_of_enrolment, productionrate FROM albums WHERE date_of_enrolment > 309"


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO pediatricians SELECT a.data_usage, b.min_dew_point_f FROM open_pedagogy_courses a JOIN driver b ON a.community_center_id = b.community_center_id"
spark.sql(sql)


cur.execute("SELECT garment_material, added_date FROM camera_lens LIMIT 33")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


df = pd.read_sql("SELECT disaster_id, metric FROM hires", engine)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("marine_life_sightings", engine, if_exists="append", index=False)


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


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


rows = session.query(Src).filter(Src.astronaut_name > 478).all()
# src table: mart.mart_users
engine.execute("INSERT INTO province.human_rights_data SELECT * FROM mart.mart_users")


df = fetch_input(ctx, "taj_mahal_visitors")
save_to_warehouse(df, "agricultural_innovations", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO circular_supply_chain_products SELECT * FROM legacy
cur.execute("SELECT goal_date, awayteamid FROM mart_orders_di LIMIT 248")


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO militarybases SELECT unitprice, payment_type_code FROM fleets WHERE unitprice > 431")


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


df = pd.read_sql("SELECT vol_id, crane_id FROM transportation_per_country", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("teams_mascots", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO clinic_2022 SELECT sustainabilityrating, status, menu_category FROM healthcare_access_v2 WHERE sustainabilityrating > 386"


spark-sql --master yarn -e "INSERT INTO songs SELECT tot_cred, labor_id, customer_type_code, acidity FROM projects WHERE tot_cred > 439"


sqoop export --connect "$JDBC" --table producersnewmexico --columns member_name,year_opened --export-dir /warehouse/stage


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


df = pd.read_sql("SELECT head, trip_city FROM regulatory_compliance", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("maintenance_requests", engine, if_exists="append", index=False)


df = source_dataset(ctx, "hydro_power")
write_to_output(df, "supplychainemployees", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO economic_diversification_projects SELECT field_id, f_id FROM veteran_stats WHERE field_id > 434"


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


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


df = extract_source(ctx, "exhibition")
sink_to_warehouse(df, "urban_farms", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO stg.users SELECT materialid, birth_country, eliminated_by FROM donors_region WHERE materialid > 60"


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


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO communityevents SELECT product, creation_year, destination_state FROM city_labor_cost WHERE product > 282")


psql -h "$PGHOST" -U etl -c "INSERT INTO doctors SELECT a.refugee_name, b.hosts FROM categories a JOIN labor_unions b ON a.max_age = b.max_age"


spark.sql("SELECT phone_number, program_type FROM broadband_providers LIMIT 54")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ods.ods_member_point_delta SELECT booking_date, purchases, university FROM hotel_business_partnerships WHERE booking_date > 58")


psql -h "$PGHOST" -U etl -c "INSERT INTO community_health_workers SELECT a.wage, b.hometeam FROM billstatus a JOIN product_review b ON a.kids = b.kids"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mappinglengths SELECT starting_year, prod_date, country, intervention_type FROM studentaccommodations WHERE starting_year > 472"


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


import logging
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO supportservices SELECT a.asset_name, b.date_and_date FROM ods.ods_member_point_df a JOIN shops b ON a.market_details = b.market_details"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ingredient_sourcing SELECT funding_amount, bank_id FROM support_tickets WHERE funding_amount > 214"


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


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


df = spark.read.table("shariah_financing").toPandas()
df[["order_status_code", "effort"]].to_sql("ods.ods_payments_full", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO dwd.dwd_orders_daily SELECT a.carbon_footprint, b.water_depth FROM ads.events a JOIN stg.stg_campaigns b ON a.class_president_vote = b.class_president_vote"


df = load_dataset(ctx, "tokyo_water_consumption")
write_to_target(df, "artifact_analysis", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO dw.dw_events_di SELECT * FROM legacy
cur.execute("SELECT trip_end_time, transactions FROM textileworkers LIMIT 34")


sqoop export --connect "$JDBC" --table electricvehiclestats --columns avg_depth,instrument --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO communityhealthworkers SELECT grantamount, founding_year, warehouse_name FROM retailers WHERE grantamount > 413"


psql -h "$PGHOST" -U etl -c "INSERT INTO bioprocesses SELECT a.founder_identifies_as_lgbtq, b.drugname FROM bookings a JOIN landfills b ON a.ai_id = b.ai_id"


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO electric_buses SELECT order_item_id, wastetype, payment_date FROM circuits WHERE order_item_id > 136")


spark.sql("SELECT visit_details, venue FROM mining_companies LIMIT 41")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO india_solar_power SELECT address_line_1, plant_name, production_quantity FROM gymnast WHERE address_line_1 > 383")


metrics.append(round(score, 4))
import logging
sql = "INSERT INTO satellitematerials SELECT a.price, b.route FROM concert a JOIN hospital_equipment b ON a.annual_entry_exit = b.annual_entry_exit"
spark.sql(sql)


src = spark.read.table("maintenance_schedule")
src.write.insertInto("playergamehistory", overwrite=True)


rows = session.query(Src).filter(Src.contract_amount > 393).all()
# src table: gamereviews
engine.execute("INSERT INTO marine_species_status SELECT * FROM gamereviews")


rows = session.query(Src).filter(Src.team_name > 172).all()
# src table: nutritionfacts
engine.execute("INSERT INTO voting_record SELECT * FROM nutritionfacts")


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO carbonoffsetinitiatives SELECT a.labor_cost, b.stars FROM coral_reefs a JOIN candidate_assessments b ON a.esg_factor = b.esg_factor"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO canada_cosmetics_preferences (totalamount, event_attendance) VALUES (%s, %s)"


cur.execute("SELECT principal_activities, training_id FROM co2_emissions LIMIT 274")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


echo "dry-run: INSERT INTO mart.mart_device_log_delta SELECT 1"
set -euo pipefail
echo "job start: $(date +%F)"
trap 'echo failed' ERR


# model india_ingredient_sourcing depends on factories
dbt run --select india_ingredient_sourcing --vars '{"source_table":"factories"}'


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


if not rows:
    logger.warning('empty result')
import logging
sql = "INSERT INTO recalls SELECT a.change_date, b.product_category FROM mart.mart_users_delta a JOIN academic_publications b ON a.deliveryid = b.deliveryid"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO infrastructure SELECT a.host_city, b.authorder FROM nasa_mars_program a JOIN dwd.campaigns b ON a.driverid = b.driverid"


df = spark.read.table("rural_projects").toPandas()
df[["exploited", "department"]].to_sql("winter_olympics", engine, index=False)


cur.execute("SELECT workout_type, institution FROM nz_tourism LIMIT 295")
rows = cur.fetchall()
result = value * ratio + offset


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


src = spark.read.table("fertilizer")
src.write.insertInto("patient_outcomes", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO contracts (center_id, financially_capable) VALUES (%s, %s)"


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


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


psql "$DB_URL" <<SQL
SELECT roomtype, disability_type FROM industry_funding LIMIT 327;
INSERT INTO dwd.sessions SELECT is_deforested, course_id FROM food_items WHERE is_deforested > 454;
SQL


spark.sql("SELECT application, zipcode FROM reservations LIMIT 136")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO mart_campaigns_delta SELECT vaccine_type, hardware_model_name, customer_status_code, contract_id FROM contract_transactions WHERE vaccine_type > 118")


sqoop export --connect "$JDBC" --table student_lifelong_learning --columns excavationid,product_category --export-dir /warehouse/stage


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mental_health_clinics (student_details, registration_date) VALUES (%s, %s)"


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 comments (booking_date, garment_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT healthcareid, site FROM donation", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("ads.inventory_di", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO atlantic_plate SELECT * FROM legacy
cur.execute("SELECT active_from_date, review_rating FROM textile_waste LIMIT 329")


spark-sql --master yarn -e "INSERT INTO aircraft SELECT founder_veteran, project_type, coalid, athleteid FROM cargos WHERE founder_veteran > 418"


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


# TODO: 旧逻辑 INSERT INTO mart.mart_campaigns_daily SELECT * FROM legacy
cur.execute("SELECT sportname, education_id FROM tennis_players LIMIT 411")


rows = session.query(Src).filter(Src.sale_value > 84).all()
# src table: transportation_per_country
engine.execute("INSERT INTO animal_population SELECT * FROM transportation_per_country")


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


psql "$DB_URL" <<SQL
SELECT asset_acquired_date, main_industry FROM smartcityprojects LIMIT 422;
INSERT INTO animal_population_status SELECT artifactid, case_type, id, supplier_company_id FROM courtcases WHERE artifactid > 244;
SQL


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


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


trap 'echo failed' ERR
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO military_equipment_maintenance SELECT vendor_id, employeename, artworkname FROM networkdevices WHERE vendor_id > 198"


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


metrics.append(round(score, 4))
sql = "INSERT INTO premises SELECT a.vehicle, b.shipping_agent_name FROM space_exploration a JOIN vr_adopters b ON a.writer = b.writer"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO ods.ods_risk_score_full SELECT materialname, mission_count, unit_id FROM carbon_sequestration WHERE materialname > 398"


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


sqoop export --connect "$JDBC" --table reservations --columns year_opened,sport_id --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table mentalhealthparityscores --columns airport_name,decor --export-dir /warehouse/stage


sqoop export --connect "$JDBC" --table operations --columns operationname,subject_id --export-dir /warehouse/stage


src = spark.read.table("policy")
src.write.insertInto("trees", overwrite=True)


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO space_agencies_2 SELECT document_id, course_type, employmentdate FROM healthcareaccess WHERE document_id > 390"


sqoop export --connect "$JDBC" --table routes --columns waste_generation,contract_amount --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.profits_in_billion > 235).all()
# src table: ods_products_delta
engine.execute("INSERT INTO screen_mode SELECT * FROM ods_products_delta")


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


df = extract_input(ctx, "peacekeeping_units")
write_to_warehouse(df, "workout", mode="overwrite")


df = spark.read.table("wastewater_treatment_plants").toPandas()
df[["partner_id", "eia_date"]].to_sql("mart.mart_campaigns_daily", engine, index=False)


result = value * ratio + offset
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))


# TODO: 旧逻辑 INSERT INTO threats SELECT * FROM legacy
cur.execute("SELECT organization_name, claim_amount FROM climate_monitoring_stations LIMIT 419")


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


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO council_tax SELECT a.mean_humidity, b.songname FROM militarypersonnel a JOIN urban_initiatives b ON a.platformname = b.platformname"
spark.sql(sql)


msg = "would run: INSERT INTO program_funding_2 SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))


psql "$DB_URL" <<SQL
SELECT sustainability_id, routename FROM medical_facilities_nyc LIMIT 145;
INSERT INTO ref_attraction_types SELECT color_code, art, coupon_id, share_in_percent FROM communication_scores WHERE color_code > 413;
SQL


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


result = value * ratio + offset
spark.sql("INSERT INTO submersible_dives SELECT stock, funding_source FROM management WHERE stock > 370")


df = spark.read.table("healthequitymetrics").toPandas()
df[["home_team_three_point", "event"]].to_sql("restaurants", engine, index=False)


# model travel_advisory depends on on_call
dbt build --select travel_advisory --vars '{"source_table":"on_call"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ethics_violations (contract_date, case_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


echo "dry-run: INSERT INTO causes_insert_2 SELECT 1"
set -euo pipefail


# TODO: 旧逻辑 INSERT INTO interventions SELECT * FROM legacy
cur.execute("SELECT indigenous, update_date FROM india_solar_power LIMIT 328")


mkdir -p /tmp/joblog
hive -e "INSERT INTO rural_resources SELECT book_id, rooms, species_name FROM mart.mart_users_delta WHERE book_id > 481"


# model scan_dates depends on public_works_projects
dbt build -s scan_dates --vars '{"source_table":"public_works_projects"}'


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


df = source_frame(ctx, "countryintelligenceops")
dump_to_store(df, "whale_sightings", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO food_justice SELECT rehab_date, isfirstattendee, painting_name, strategy_id FROM chemicalproducts WHERE rehab_date > 94"


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


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


df = pd.read_sql("SELECT account_number, market_value_billion FROM sports", engine)
result = value * ratio + offset
import logging
df.to_sql("economic_diversification_efforts", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT composer, ram_mib FROM routes LIMIT 99;
INSERT INTO defense_contractors SELECT shipmenttype, date_from, experience, stars FROM food_items WHERE shipmenttype > 257;
SQL


beeline -u "$HS2_URL" -e "INSERT INTO ods_vendors_daily SELECT technology, contract_value FROM gender WHERE technology > 281"


# model experts depends on marine_life_research_stations
dbt run --select experts --vars 'source: marine_life_research_stations'


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


cur.execute("SELECT startup_name, manufacturer_name FROM artwork LIMIT 116")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


beeline -u "$HS2_URL" -e "INSERT INTO financial_capability_program SELECT company_id, calendar, part_fault_id, incidentid FROM virtual_tour_offers WHERE company_id > 183"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sustainability_metrics SELECT permit_number, account_balance, goal_id, date_in_locaton_to FROM research WHERE permit_number > 375"


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO spending SELECT a.market_value, b.opponent_id FROM mappinglengths a JOIN dp_articles b ON a.category = b.category"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO workforce_development SELECT custid, roomid, warehouse_name, milestone FROM wastewater_plants WHERE custid > 146"], check=True)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO transportation_per_country (sales_billion, investor_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark.sql("SELECT rig_name, color_code FROM safetytestingcounts LIMIT 385")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO autonomousvehicleaccidents SELECT fname, artworkname FROM vulnerabilities WHERE fname > 218")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO comments SELECT a.workoutdate, b.catalog_level_number FROM policyanalysis a JOIN climate_finance_organizations b ON a.itemid = b.itemid"


psql -h "$PGHOST" -U etl -c "INSERT INTO public.forest_stats SELECT a.document_description, b.hashtags FROM party_forms a JOIN dw.dw_events_di b ON a.quarter = b.quarter"


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


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


cur.execute("SELECT worker_id, decor FROM underwater_trenches LIMIT 336")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
result = value * ratio + offset


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


cur.execute("SELECT condition_id, jobcategory FROM diversification_projects LIMIT 487")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.dws_member_point_di (inspectionscore, phone_number) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO user_reactions SELECT a.watertemp, b.case_burden FROM college a JOIN virtual_tours_oceania b ON a.building_type = b.building_type"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO expenses (origin_city, color) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO communityengagements SELECT a.tot_cred, b.model_id FROM open_pedagogy_enrollment a JOIN carbon_offset_south_america b ON a.schedule_date = b.schedule_date"


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


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


set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO acceptance SELECT wind_speed_mph, physical, furniture_id, launch_agency FROM agricultural_projects WHERE wind_speed_mph > 426"


df = spark.read.table("atlantic_marine_life").toPandas()
df[["num_of_audience", "police_force"]].to_sql("election", engine, index=False)


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


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO bi.bi_sessions_hourly SELECT registered_date, platformname, truck_licence_number FROM mart.mart_risk_score_hourly WHERE registered_date > 381"


spark.sql("SELECT field, grantid FROM bay_area_properties LIMIT 290")
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO dw.dw_inventory_delta SELECT num_employees, secretary_vote, max_salary, headquarters FROM continent WHERE num_employees > 192")


df = fetch_frame(ctx, "ocean_salinity")
export_to_sink(df, "artists", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO producers SELECT a.art, b.acidity FROM climate_communication a JOIN total_capacity b ON a.initiative_region = b.initiative_region"


src = spark.read.table("social_impact_bonds")
src.write.insertInto("teachers", overwrite=True)


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


df = spark.read.table("threats").toPandas()
df[["lieutenant_governor", "dock_id"]].to_sql("infantmortalitydata", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO singer SELECT ngo_id, production_usage FROM bank_info WHERE ngo_id > 210"


df = spark.read.table("dispensaries").toPandas()
df[["transaction_date", "call_time"]].to_sql("city_properties", engine, index=False)


sqoop export --connect "$JDBC" --table visitor_statistics --columns assessmentid,dockingid --export-dir /warehouse/stage


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


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


src = spark.read.table("dws.dws_member_point_di")
src.write.insertInto("initiatives_3", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO professional_development SELECT department_id, guest_id, attendanceid, season FROM forests WHERE department_id > 319"


rows = session.query(Src).filter(Src.area > 74).all()
# src table: restaurant
engine.execute("INSERT INTO lots SELECT * FROM restaurant")


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


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


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


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


spark-sql --master yarn -e "INSERT INTO seafood SELECT trial_name, tree_id FROM invoice WHERE trial_name > 220"


psql "$DB_URL" <<SQL
SELECT investment_amount, period FROM elimination LIMIT 241;
INSERT INTO mentalhealthprofessional SELECT patient_name, event_type, cinema_id FROM pollution_control_initiatives WHERE patient_name > 462;
SQL


sqoop export --connect "$JDBC" --table project_timeline --columns claim_status_name,gdp --export-dir /warehouse/stage


mkdir -p /tmp/joblog
set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO checking SELECT patentexpirationdate, platformname, pettype FROM furniture WHERE patentexpirationdate > 118"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO restaurant_revenue SELECT supplychainid, allergy, review_score FROM trade_history WHERE supplychainid > 230;
EOF


set -euo pipefail
hive -e "INSERT INTO manufacturingplants SELECT offense, cropname, job_title_code, address_id FROM expenses WHERE offense > 94"


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO city.community_policing SELECT programname, numpieces, tx_id FROM soilmoisturedata WHERE programname > 1"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO salesdata SELECT workoutid, membername, event FROM inclusive_housing WHERE workoutid > 8"], check=True)


rows = session.query(Src).filter(Src.creator > 261).all()
# src table: ma_inspections
engine.execute("INSERT INTO stg.stg_users_full SELECT * FROM ma_inspections")


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


# model waste_generation_city_v2 depends on climate_communication_projects
dbt run --select waste_generation_city_v2 --vars '{"src":"climate_communication_projects"}'


# TODO: 旧逻辑 INSERT INTO fish_biomass SELECT * FROM legacy
cur.execute("SELECT hours_contributed, recycling_rate FROM military_expenditure LIMIT 35")


beeline -u "$HS2_URL" -e "INSERT INTO workforce_development SELECT programoutcomeid, assessmentid FROM military_innovation WHERE programoutcomeid > 330"


df = source_source(ctx, "veterans")
export_to_store(df, "patienttreatments", mode="overwrite")


# model catalogs depends on publications
dbt run -s catalogs --vars '{"src":"publications"}'


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


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


spark.sql("SELECT sessionid, contributorid FROM rental LIMIT 207")
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO asset_parts SELECT time_of_day, lipstick_id, waste_id FROM office_locations WHERE time_of_day > 400")


beeline -u "$HS2_URL" -e "INSERT INTO dw_vendors_di SELECT incidentdate, performancedate FROM musical WHERE incidentdate > 280"


psql -h "$PGHOST" -U etl -c "INSERT INTO ota_revenue SELECT a.eid, b.crs_description FROM ods.ods_campaigns_delta a JOIN building b ON a.floor_exercise_points = b.floor_exercise_points"


sqoop export --connect "$JDBC" --table policy_feedback --columns order_item_status,provider_parity_score --export-dir /warehouse/stage


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


mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO recycling_centers SELECT budget_type_description, attack_date, arrival_time, agreementid FROM renewable_projects WHERE budget_type_description > 499"


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO fabricinventory SELECT a.founder_group, b.production_rate FROM visual_arts a JOIN rural_clinics b ON a.measurement = b.measurement"
spark.sql(sql)


df = spark.read.table("microfinance_clients").toPandas()
df[["complaint_id", "attendee_race"]].to_sql("culturalpractices", engine, index=False)


sqoop export --connect "$JDBC" --table ocean_temperatures --columns launched_year,restorative_justice --export-dir /warehouse/stage


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO drama_workshop_groups SELECT registered_date, organic, duration FROM prescribes WHERE registered_date > 462")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO malicious_activity (campaign_id, safety_rating) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO farmers (ngo_id, value) VALUES (%s, %s)", (uid, amt))
conn.commit()