cur.execute("SELECT train_number, operationid FROM dw.member_point_daily LIMIT 72")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
result = value * ratio + offset


cur.execute("SELECT marketing_region_descriptrion, preferred_foot FROM donorgender LIMIT 27")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


# model shariahfinance depends on regional_archaeologists
dbt build --models shariahfinance --vars '{"src":"regional_archaeologists"}'


result = value * ratio + offset
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO environmentalimpact SELECT address, province FROM birds WHERE address > 410"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.dws_refunds_daily (vesselid, garment_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.shipments_daily (kids, community_members) VALUES (%s, %s)"


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


spark-sql --master yarn -e "INSERT INTO mart.mart_device_log SELECT member_name, sales, supportrepid, postal_code FROM russia_nato_diplomacy WHERE member_name > 117"


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


df = pd.read_sql("SELECT * FROM inventory", conn)
df.to_sql("mart.mart_events_di", conn, if_exists="replace", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO gamegenres SELECT num_employees, lastdonationdate, mission_date FROM coowners WHERE num_employees > 446"


df = source_table(ctx, "models_safety")
dump_to_output(df, "civilcases", mode="overwrite")


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO skincareproducts SELECT a.speed, b.max_salary FROM traffic_citations a JOIN fundings b ON a.shelter_id = b.shelter_id"
spark.sql(sql)


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


psql "$DB_URL" <<SQL
SELECT primaryaffiliation, venue_id FROM dw_payments LIMIT 360;
INSERT INTO policyadvocacyevents SELECT investmenttype, hoursspent, teamname, appointment_duration FROM satellitematerials WHERE investmenttype > 179;
SQL

investmenttype hoursspent teamname appointment_duration


# TODO: 旧逻辑 INSERT INTO vr_adopters SELECT * FROM legacy
cur.execute("SELECT product_stock_number, acidification_level FROM organisations LIMIT 337")


# model player_f depends on students
dbt build --select player_f --vars '{"src":"students"}'


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


src = spark.read.table("public_transportation_routes")
src.write.insertInto("waterconsumptionbyoperation", overwrite=True)


rows = session.query(Src).filter(Src.production_bopd > 226).all()
# src table: evidence_based_policies
engine.execute("INSERT INTO nba SELECT * FROM evidence_based_policies")


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO agriculturalinvestments SELECT a.student_details, b.province_name FROM government_transparency a JOIN agri_innov b ON a.airport = b.airport"
spark.sql(sql)


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO drama_workshop_groups SELECT case_number, emission_date FROM militaryinnovations WHERE case_number > 58"


beeline -u "$HS2_URL" -e "INSERT INTO storage SELECT equipment_type, performance_id, tournament_name FROM refugee_support WHERE equipment_type > 73"


df = pd.read_sql("SELECT claim_status_description, contact_staff_id FROM user_stats", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("supplier_addresses", engine, if_exists="append", index=False)


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO italy_culture SELECT usage, saledate, treatment_year FROM weekly_weather WHERE usage > 348"], check=True)


cur.execute("SELECT dockingdate, hiv FROM community_programs LIMIT 106")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO donorprograms SELECT inspectionscore, attendance_id, destination FROM ethicalaibudget WHERE inspectionscore > 255;
EOF


import logging
result = value * ratio + offset
spark.sql("INSERT INTO budgets SELECT funding_source, lesson_id, wins, scientist FROM bi.risk_score_df WHERE funding_source > 123")


src = spark.read.table("dws.dws_coupon_use_di")
src.write.insertInto("bioprocess.engineering_projects", overwrite=True)


src = spark.read.table("postseason")
src.write.insertInto("factory_water", overwrite=True)


psql "$DB_URL" <<SQL
SELECT vice_president_vote, investor FROM ytterbium_supply LIMIT 355;
INSERT INTO teacher_development_race SELECT code, fault_short_name, drug_name, movie FROM chemicalproducts WHERE code > 315;
SQL


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


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


# TODO: 旧逻辑 INSERT INTO concert_events SELECT * FROM legacy
cur.execute("SELECT grantamount, restypedescription FROM solar_farms LIMIT 176")


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


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


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


src = spark.read.table("unionmembers")
src.write.insertInto("products_in_events", overwrite=True)


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


psql "$DB_URL" <<SQL
SELECT handling_date, shelter_name FROM companies LIMIT 218;
INSERT INTO ods.ods_member_point_df SELECT spacecraft_model, machinery_id, timestamp, creationyear FROM dws.dws_refunds_hourly WHERE spacecraft_model > 150;
SQL


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mental_health_center SELECT is_cruelty_free, mediatorid, average_age, service_id FROM athletes_performance WHERE is_cruelty_free > 499;
EOF


# TODO: 旧逻辑 INSERT INTO wellbeing_program_participants SELECT * FROM legacy
cur.execute("SELECT concertid, therapy_type FROM procedures LIMIT 317")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO climate_finance_re SELECT injury_date, strain, is_valid, users_engaged FROM bi.bi_risk_score_df WHERE injury_date > 95;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO producers (restaurant_name, num_schools) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO sponsorship_donations (inspectiondate, workoutname) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO military_aircraft_maintenance SELECT vehicleid, other_item_details, poll_source, grant_start_date FROM smartcitycosts WHERE vehicleid > 142"], check=True)


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO manager_award SELECT reviews, accelerator_id FROM surveylocations WHERE reviews > 287")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO bi.bi_campaigns_daily (q1_2022_views, fueldate) VALUES (%s, %s)"


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


rows = session.query(Src).filter(Src.grant_amount > 283).all()
# src table: african_union_countries
engine.execute("INSERT INTO bus_routes SELECT * FROM african_union_countries")


df = read_frame(ctx, "intelligence_agents")
sink_to_store(df, "student_course_attendance", mode="overwrite")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO features SELECT college, permit_number FROM wastewater_treatment_plants WHERE college > 172;
EOF


import logging
sql = "INSERT INTO satellite_deployment SELECT a.meeting_count, b.duration_ms FROM player_sessions a JOIN category_revenue b ON a.monthly_rental = b.monthly_rental"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO schoolc SELECT floor_area_m2, country_of_origin FROM maintenance_contracts WHERE floor_area_m2 > 361"


psql -h "$PGHOST" -U etl -c "INSERT INTO genetics.projects SELECT a.porphyria, b.restaurant_name FROM virtual_tourism a JOIN ytterbium_supply b ON a.mailing_date = b.mailing_date"


df = pd.read_sql("SELECT * FROM heart_rate_data", conn)
df.to_sql("emerging_markets.digital_assets", conn, if_exists="replace", index=False)


df = pd.read_sql("SELECT stat_type, post_category FROM fare_collection", engine)
import logging
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("hires", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO wildlife_sanctuaries (issues, round_number) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO club SELECT ai_id, courtname, route_short_name FROM ticketspending WHERE ai_id > 50"


# model class depends on singer_in_concert
dbt build -s class --vars 'source: singer_in_concert'


spark.sql("SELECT fundingamount, participation_id FROM field_production LIMIT 332")
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dws.shipments_daily SELECT recipe_id, transportation_method FROM ods.clicks_full WHERE recipe_id > 210")


sqoop export --connect "$JDBC" --table chemical_composition --columns issued_date,element --export-dir /warehouse/stage


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


spark-sql --master yarn -e "INSERT INTO packages SELECT contractor_name, support_id, energy_efficiency_kwh_m2_year FROM fans_merchandise_basketball WHERE contractor_name > 184"


spark.sql("SELECT spill_name, vulnerability_score FROM workouts LIMIT 38")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO season_assists SELECT apid, round_date, games, rental_date FROM labor_productivity WHERE apid > 330")


psql -h "$PGHOST" -U etl -c "INSERT INTO crops SELECT a.awayteamid, b.session_name FROM continent a JOIN music_events b ON a.investor_id = b.investor_id"


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


df = pd.read_sql("SELECT * FROM latam_schema.education_budget", conn)
df.to_sql("defenseprojects", conn, if_exists="replace", index=False)


psql "$DB_URL" <<SQL
SELECT checkin, injury_date FROM maintenance LIMIT 398;
INSERT INTO singer_in_concert SELECT emission_date, membername, days FROM research.species WHERE emission_date > 98;
SQL


# model economic_diversification_efforts depends on culturalpractices
dbt run --models economic_diversification_efforts --vars '{"source_table":"culturalpractices"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO item_prices SELECT a.screen_mode, b.assessmentid FROM ingredientsvegancrueltyfree a JOIN dw.dw_inventory_df b ON a.wage_increase = b.wage_increase"


# TODO: 旧逻辑 INSERT INTO timber_production SELECT * FROM legacy
cur.execute("SELECT spacecraft_id, incident_type FROM ads.ads_exposure_di LIMIT 272")


trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO mining_operation_data SELECT incident_name, sales_amount, festival_name, precedent_id FROM mart.shipments_delta WHERE incident_name > 485"


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


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


# model platformstats depends on tech_accessibility_funding
dbt run --select platformstats --vars '{"source_table":"tech_accessibility_funding"}'


# TODO: 旧逻辑 INSERT INTO seafood SELECT * FROM legacy
cur.execute("SELECT num_shariah_compliant_investments, log_entry_date FROM cybersecurity_strategies LIMIT 412")


psql "$DB_URL" <<SQL
SELECT hotel_name, case_number FROM company_info LIMIT 305;
INSERT INTO cars SELECT ad_id, prof_num, screen_mode, fine FROM packages WHERE ad_id > 104;
SQL


rows = session.query(Src).filter(Src.archaeologist_id > 204).all()
# src table: ads.ads_cart_item_hourly
engine.execute("INSERT INTO contributions SELECT * FROM ads.ads_cart_item_hourly")


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO circularsupplychain SELECT county_name, end_station_id, balance FROM mart.mart_risk_score_hourly WHERE county_name > 378"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO visitordemographics SELECT savingsid, stationid, threat_type FROM party_forms WHERE savingsid > 313"


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


df = pd.read_sql("SELECT s_id, time_second FROM catalog_contents", engine)
threshold = cfg.get('threshold', 0.5)
import logging
result = value * ratio + offset
df.to_sql("dw.dw_member_point_hourly", engine, if_exists="append", index=False)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO chemical_concentration (subject, cargo_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT complaint_id, town_city FROM smart_contracts LIMIT 483")
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO characteristics SELECT fish_count, ll_hours FROM police_officers_tx WHERE fish_count > 394")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO historicalcontexts (production_value, songname) VALUES (%s, %s)"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO esports_teams SELECT approach, donorage FROM bi.bi_orders_hourly WHERE approach > 336"


df = pull_input(ctx, "footwear")
dump_to_sink(df, "minor_in", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO track SELECT num_shariah_compliant_investments, bioreactor_id, mediatypeid, mh_id FROM enrolled_in WHERE num_shariah_compliant_investments > 174"


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


df = pull_input(ctx, "policyanalysis")
dump_to_store(df, "counties", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
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 travel_advisory SELECT claim_status_description, venue, trade FROM nursing_homes WHERE claim_status_description > 449;
EOF


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


psql "$DB_URL" <<SQL
SELECT maintenance_contract_company_id, site_id FROM singer_in_concert LIMIT 74;
INSERT INTO stg.stg_users_di SELECT sd_id, date_incident_end, policy_area, marketing_region_descriptrion FROM trainingprograms WHERE sd_id > 256;
SQL


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO spacemissions SELECT course_name, vendor_name FROM clothingsales WHERE course_name > 147"


spark.sql("SELECT event_id, athlete FROM tb_reports LIMIT 285")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO militarybases SELECT typical_selling_price, station_name FROM subway WHERE typical_selling_price > 474")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO concentrateprices SELECT employee, labor_practice FROM project_timeline WHERE employee > 97;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO vehicle (painting_name, hotel_chain_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pull_frame(ctx, "flu_shots")
export_to_output(df, "fair_trade_brands", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.shipments_df SELECT team_id_winner, date_payment_made, directed_by FROM disabilityadvocacy WHERE team_id_winner > 43"


df = pd.read_sql("SELECT * FROM mart.mart_users_di", conn)
df.to_sql("legal_technology_funding", conn, if_exists="replace", index=False)


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


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


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO dwd.products_hourly SELECT a.lettergrade, b.application FROM dws_shipments_df a JOIN stg.sessions_full b ON a.fish_count = b.fish_count"
spark.sql(sql)


df = spark.read.table("cybersecuritybudget").toPandas()
df[["product_description", "complaint_status_code"]].to_sql("instructors", engine, index=False)


retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO cerium_production SELECT fleet_id, amountdonated, avg_depth, club_name FROM textileworkers WHERE fleet_id > 83")


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


# TODO: 旧逻辑 INSERT INTO virtual_tour_revenue SELECT * FROM legacy
cur.execute("SELECT nid, ai_model FROM menu_item LIMIT 287")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.stg_products_delta (transactionid, pets_allowed_yn) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO daily_oil_production (primary_conference, log_entry_date) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO community_members SELECT vegan, parameters FROM country_landfill_capacity WHERE vegan > 29"], check=True)


result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dws.cart_item_full SELECT employee_name, trend_id, maintenance_date, network FROM org_comms WHERE employee_name > 460")


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_payments_hourly SELECT a.genre_is, b.carrierid FROM tvshows a JOIN carbonoffsetinitiatives b ON a.water_type = b.water_type"


rows = session.query(Src).filter(Src.next_entry_id > 210).all()
# src table: document_structures
engine.execute("INSERT INTO dwd_sessions_hourly SELECT * FROM document_structures")


df = spark.read.table("cosmetic_sales").toPandas()
df[["element_id", "restypedescription"]].to_sql("airlines", engine, index=False)


df = spark.read.table("defense_diplomacy").toPandas()
df[["working_year_starts", "digital_channel"]].to_sql("item_inventory", engine, index=False)


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


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


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


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO tracklists (lot_details, typeid) VALUES (%s, %s)"


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


# model water_distribution depends on mars_rovers
dbt build --models water_distribution --vars '{"src":"mars_rovers"}'


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO authors SELECT virtual_tour_engagement_time, suburb FROM wind_projects WHERE virtual_tour_engagement_time > 254"


# model ref_hotel_star_ratings depends on design_standards
dbt build --models ref_hotel_star_ratings --vars '{"src":"design_standards"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO maintenance_schedule SELECT custid, workoutdate FROM rural_development.agriculture_projects WHERE custid > 184"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.mart_refunds_di SELECT roaming_country, professional_development_programs, num_transactions, theatrename FROM galleries WHERE roaming_country > 411"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO casesbyyear SELECT a.crop, b.primaryaffiliation FROM stg.stg_events_di a JOIN bi.bi_payments b ON a.contractorid = b.contractorid"


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))


psql -h "$PGHOST" -U etl -c "INSERT INTO industrial_customers SELECT a.mean_sea_level_pressure_inches, b.menuitemid FROM donationhistory a JOIN uniteddefense.equipmentsales b ON a.contractorid = b.contractorid"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ads_exposure_hourly (materialname, is_organic) VALUES (%s, %s)"


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


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


metrics.append(round(score, 4))
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO emergencyservices SELECT porphyria, app_id, sales_id, number_city_affected FROM port WHERE porphyria > 6"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO carbon_prices SELECT grant_end_date, cultural_diversity, high_temperature, account_type FROM legislation WHERE grant_end_date > 497;
EOF


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_refunds_hourly SELECT a.hometown, b.scientist FROM southeast_providers a JOIN field5 b ON a.dorm_name = b.dorm_name"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ref_incident_type SELECT assets_billion, num_cases FROM latam_schema.education_budget WHERE assets_billion > 74"], check=True)


cur.execute("SELECT claim_date, prod_id FROM timber_sales LIMIT 47")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')
result = value * ratio + offset


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


# TODO: 旧逻辑 INSERT INTO humanitarianmissions SELECT * FROM legacy
cur.execute("SELECT license_type, secretary_vote FROM animal_budget LIMIT 440")


sqoop export --connect "$JDBC" --table dws.dws_coupon_use_hourly --columns contributor,sector_id --export-dir /warehouse/stage


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO policyholders SELECT roomid, pieces FROM projectemployees WHERE roomid > 142")


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO specieswatertemp SELECT a.devices, b.portfolio_id FROM education a JOIN arrivals b ON a.detention_summary = b.detention_summary"
spark.sql(sql)


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))


result = value * ratio + offset
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO socialimpactinvestments SELECT individual_id, age_group FROM membership_data WHERE individual_id > 453")


psql -h "$PGHOST" -U etl -c "INSERT INTO revenue SELECT a.shale_play, b.audienceid FROM parking_fines a JOIN crime_incidents b ON a.sport_id = b.sport_id"


spark.sql("SELECT product_stock_number, ad_id FROM menu LIMIT 4")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO exam_results SELECT cloud_cover, production_quantity, movie FROM tree_habitat_associations WHERE cloud_cover > 140")


spark.sql("SELECT recruitername, crs_code FROM sustainability_fact LIMIT 332")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO dates SELECT budgeted, contract_value FROM dw.dw_inventory_delta WHERE budgeted > 125")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dysprosiumproduction SELECT wellname, eventid, gold, nationality FROM roads WHERE wellname > 84;
EOF


# model deep_sea_expeditions depends on grant
dbt run -s deep_sea_expeditions --vars 'source: grant'


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
import logging
sql = "INSERT INTO militaryequipment SELECT a.development_type, b.case_outcome FROM rural_resources a JOIN investor_activities b ON a.other_details = b.other_details"
spark.sql(sql)


df = pd.read_sql("SELECT gradepoint, city_area FROM mars_missions", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
df.to_sql("textile_suppliers", engine, if_exists="append", index=False)


cur.execute("SELECT emission_date, dish_id FROM teacher_pd LIMIT 7")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
import logging


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO student_tests_taken SELECT supplier_country, service FROM fields_production WHERE supplier_country > 341"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO trends_2022 (successful_cb, seal_species) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO albums SELECT * FROM legacy
cur.execute("SELECT experienceid, strain FROM wine LIMIT 339")


spark.sql("SELECT lender_name, technician_id FROM emergency_categories LIMIT 498")
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO us_military_personnel SELECT salary, item_sold, habitat_id, applicant FROM evsales WHERE salary > 165")


df = pd.read_sql("SELECT raceid, center_id FROM playerscores", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("genetics.projects", engine, if_exists="append", index=False)


src = spark.read.table("shipments")
src.write.insertInto("community_development_projects", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO project_timeline (total_horses, kids) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO arctic_sightings SELECT governor, length_feet, country_code, stayid FROM dw_member_point_full WHERE governor > 81"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO waste SELECT make, total_horses, tree_species FROM dysprosiumproduction WHERE make > 417"], check=True)


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


spark-sql --master yarn -e "INSERT INTO engineer_skills SELECT cultural_competency_score, book_title FROM equipmentsales WHERE cultural_competency_score > 331"


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


cur.execute("SELECT starttime, jobtitle FROM student_lifelong_learning LIMIT 242")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset
import logging


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO budgets SELECT park, accident_date FROM feed WHERE park > 446;
EOF


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
sql = "INSERT INTO species_forests SELECT a.policy_number, b.trip_id FROM ads.ads_refunds_hourly a JOIN storage_projects b ON a.campaign_name = b.campaign_name"
spark.sql(sql)


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


df = source_frame(ctx, "mart.mart_coupon_use_full")
upsert_to_store(df, "biomes", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT order_details, acc_regular_season FROM cybersecuritybudget LIMIT 334;
INSERT INTO climber SELECT labor_id, cell_mobile_number, coowner_name FROM dwd_coupon_use_hourly WHERE labor_id > 71;
SQL


src = spark.read.table("school_details")
src.write.insertInto("incarcerated", overwrite=True)


spark.sql("SELECT text_of_notes, inspectiondate FROM mart.mart_users_di LIMIT 123")
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO shared_rides_tokyo SELECT customername, initiative_type, grade FROM program_budget WHERE customername > 180")


psql "$DB_URL" <<SQL
SELECT contract_address, stateid FROM researchgrants LIMIT 297;
INSERT INTO veteran_stats SELECT change_date, exit_type, refugee_name, analysis_date FROM club WHERE change_date > 428;
SQL


cur.execute("SELECT fuelconsumed, incident_name FROM climate_finance_organizations LIMIT 249")
rows = cur.fetchall()
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO city SELECT total_attendance, accommodation_type, medication, feedid FROM social_good_education WHERE total_attendance > 384;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO workers SELECT editor_id, transact_date FROM bi.member_point_full WHERE editor_id > 350"


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


sqoop export --connect "$JDBC" --table transaction --columns service_name,therapy_date --export-dir /warehouse/stage


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO bike_share SELECT sent_date, materialtype FROM iron WHERE sent_date > 27"


spark.sql("SELECT startyear, bank_id FROM teacher_pd_hours LIMIT 11")
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO solana_transactions SELECT vegan, shipmentid, lot_details FROM dw.dw_member_point_di WHERE vegan > 347")


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


cur.execute("SELECT attribute_data_type, mediatypeid FROM body_builder LIMIT 165")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')


cur.execute("SELECT gender_group, mappingname FROM plays_games LIMIT 179")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


beeline -u "$HS2_URL" -e "INSERT INTO festival_detail SELECT crossing, g_name, budget_million, ei_category FROM professor WHERE crossing > 495"


psql -h "$PGHOST" -U etl -c "INSERT INTO cloud_issues SELECT a.causeid, b.form_id FROM stg.stg_campaigns_hourly a JOIN haircare_cruelty b ON a.hours_played = b.hours_played"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO eventdates SELECT waste_type, subject_area_id, i_id FROM tours WHERE waste_type > 449"


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


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


result = value * ratio + offset
import logging
sql = "INSERT INTO food_production SELECT a.cityid, b.farmer_name FROM user_workouts_march a JOIN attack_outcomes b ON a.eliminated_by = b.eliminated_by"
spark.sql(sql)


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


src = spark.read.table("wastedata")
src.write.insertInto("buildings", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ai_for_social_good SELECT farmland_id, volunteerage, studio, contract_end_date FROM useracct WHERE farmland_id > 202"], check=True)


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO dailystreams SELECT show_id, routeid, recycling_rate FROM stg.stg_users_full WHERE show_id > 402")


df = spark.read.table("forest_species").toPandas()
df[["session_name", "improvement"]].to_sql("journal", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO member_of_club SELECT museumname, vehicle_flight_number, prof_office, hours_served FROM students WHERE museumname > 130"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO gameplatforms SELECT habitat_id, explainability_score, duration FROM travel_advisory WHERE habitat_id > 262"], check=True)


df = pd.read_sql("SELECT incident_name, draft_pick_number FROM highways", engine)
metrics.append(round(score, 4))
df.to_sql("satellite_missions_large", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO bi_shipments_daily SELECT a.book_title, b.strategy FROM organisations a JOIN hires b ON a.premises_type = b.premises_type"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO virtual_visitors SELECT donation_year, judge_id, complaint_date FROM conditions WHERE donation_year > 5"], check=True)


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


# model solana_transactions depends on test_drives
dbt build --models solana_transactions --vars 'source: test_drives'


rows = session.query(Src).filter(Src.bias_score > 313).all()
# src table: bi_refunds_daily
engine.execute("INSERT INTO district_schools SELECT * FROM bi_refunds_daily")


cur.execute("SELECT area_id, document_description FROM dwd.dwd_cart_item_di LIMIT 446")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


spark.sql("SELECT trader_id, warehouseid FROM experience LIMIT 312")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ods.ods_campaigns_df SELECT stu_hrs, score, facid FROM genderdistribution WHERE stu_hrs > 192")


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


sqoop export --connect "$JDBC" --table broadband_providers --columns minename,investment_date --export-dir /warehouse/stage


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads_orders SELECT document_type_description, start_speed, soil_moisture FROM recycled_polyester WHERE document_type_description > 497"


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


df = pd.read_sql("SELECT prereq_id, booking_start_date FROM customer_transactions", engine)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
df.to_sql("tracklists", engine, if_exists="append", index=False)


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


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


df = spark.read.table("philadelphia_police_emergencies").toPandas()
df[["advisor", "clean_jerk"]].to_sql("bridgeconstruction", engine, index=False)


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


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
sqoop import --connect "$JDBC" --table defense_contracts_v2 --target-dir /tmp/land


if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO wine SELECT a.fine, b.device_id FROM dws.dws_coupon_use_hourly a JOIN daily_industrial_water_usage b ON a.passenger_name = b.passenger_name"
spark.sql(sql)


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


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


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


# TODO: 旧逻辑 INSERT INTO heritagesites SELECT * FROM legacy
cur.execute("SELECT pettype, meter_300 FROM nyc_subway LIMIT 184")


df = source_source(ctx, "ads.events")
push_to_target(df, "makeup_sales", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT county_name, jobtitle FROM nomination LIMIT 94;
INSERT INTO refugee_support SELECT cuisine, transaction_type_code, functional_area_code, team_id_br FROM road_construction WHERE cuisine > 54;
SQL


df = load_input(ctx, "tweets")
persist_to_sink(df, "weapons", mode="overwrite")


spark.sql("SELECT advisoryid, fabrictype FROM stg.stg_campaigns LIMIT 367")
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO open_pedagogy SELECT therapy_type, funding_round_id FROM state_energy WHERE therapy_type > 229")


beeline -u "$HS2_URL" -e "INSERT INTO precision_farming_imagery SELECT orgid, meter_200, game, artifact_weight FROM storage_tech WHERE orgid > 81"


df = pd.read_sql("SELECT defendant_id, task_id FROM artprograms", engine)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
df.to_sql("pollution_control_initiatives", engine, if_exists="append", index=False)


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


df = pd.read_sql("SELECT permitid, purchase_id FROM race", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("stg.risk_score_hourly", engine, if_exists="append", index=False)


spark.sql("SELECT model_id, cultivatorname FROM financial_capability_programs LIMIT 137")
result = value * ratio + offset
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO schoolc SELECT sustainabilityrating, capital, dock_id FROM autoshow WHERE sustainabilityrating > 323")


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


df = pd.read_sql("SELECT treatment_year, business_id FROM precipitation_data", engine)
import logging
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("city_tech", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bike_share SELECT is_recycled, host_country FROM aquatic_farms WHERE is_recycled > 169;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO vehicle_maintenance (energy_efficiency_savings, province) VALUES (%s, %s)"


df = get_input(ctx, "wildlife")
upsert_to_warehouse(df, "greenbuildings", mode="overwrite")


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


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


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


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


df = load_frame(ctx, "forest")
push_to_warehouse(df, "defense_project_timelines", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO habitat3 SELECT * FROM legacy
cur.execute("SELECT experience, draft_pick_number FROM communitypolicing LIMIT 296")


df = pd.read_sql("SELECT vaccination_status, feature_details FROM tech_accessibility_funding", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("fuel_consumption", engine, if_exists="append", index=False)


result = value * ratio + offset
import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO vulnerabilities SELECT a.extraction_date, b.user_id FROM clothingitems a JOIN mart_orders_di b ON a.arrival = b.arrival"
spark.sql(sql)


src = spark.read.table("opioid_overdoses")
src.write.insertInto("biodiversity", overwrite=True)


result = value * ratio + offset
spark.sql("INSERT INTO dwd.dwd_campaigns_df SELECT school, archeologist FROM diplomacy_events WHERE school > 337")


spark.sql("SELECT daily_co2_emission, dribbling FROM menu_engineering LIMIT 307")
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO sales_2 SELECT lat, tour_name FROM esportsteamsafrica WHERE lat > 104")


psql -h "$PGHOST" -U etl -c "INSERT INTO local_impact_japan SELECT a.order_status, b.health_equity_metric_3 FROM broadband_subscribers a JOIN fertilizer_usage b ON a.ranking = b.ranking"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO global_tournament (line_id, water_temp) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO supply_chain SELECT founder_identity, strat_id, missing_data FROM drug_approval WHERE founder_identity > 254"


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


# model flights depends on rigs
dbt build --models flights --vars '{"source_table":"rigs"}'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO climate_finance_asia SELECT fish_count, beds FROM energy_storage WHERE fish_count > 246"], check=True)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ocean_depths SELECT train_id, museum_name, emp_hiredate, time_minute FROM diplomacy_events WHERE train_id > 292"


df = load_source(ctx, "biosensors.readings")
save_to_output(df, "genetics.crispr", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO passengers SELECT * FROM legacy
cur.execute("SELECT closure_authorised_by_staff_id, productid FROM packages LIMIT 149")


df = source_dataset(ctx, "dw.dw_member_point_di")
push_to_target(df, "device", mode="overwrite")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ref_detention_type SELECT trader_id, fault_log_entry_datetime, manager_name FROM dw.dw_users_di WHERE trader_id > 144"], check=True)


df = spark.read.table("document_types").toPandas()
df[["program_date", "device"]].to_sql("roller_coaster", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO vehicledata SELECT billing_city, regulation, is_sustainable FROM drug_approvals WHERE billing_city > 17"


# TODO: 旧逻辑 INSERT INTO patient_outcomes SELECT * FROM legacy
cur.execute("SELECT item_type, communityid FROM ads_users_hourly LIMIT 56")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tour_guides (vulnerability_score, temporary_acting) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO accessibility_audits SELECT * FROM legacy
cur.execute("SELECT breed, staff_details FROM charging_stations LIMIT 322")


echo "job start: $(date +%F)"
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO audience SELECT fan_age, incidenttype, f_id, customer_number FROM ocean_floor_depth WHERE fan_age > 319"


spark.sql("SELECT financial_wellbeing_score, donator_name FROM dws_events_di LIMIT 430")
import logging
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO movie SELECT member, cinema_id, process_id FROM movies WHERE member > 259")


df = source_input(ctx, "draft_copies")
dump_to_sink(df, "climate_projects", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cybersecurity_strategies SELECT fouls, program_name, precip FROM coal WHERE fouls > 434"


cur.execute("SELECT negotiation_date, ai_model FROM membership_data LIMIT 127")
rows = cur.fetchall()
import logging


import logging
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO cargo_data SELECT a.num_shariah_compliant_investments, b.tier FROM carbon_offset_programs a JOIN shared_rides_tokyo b ON a.program_date = b.program_date"
spark.sql(sql)


import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO benefits_overpayments SELECT a.attraction_type_description, b.driverid FROM ads_users_hourly a JOIN shelters b ON a.effective_date = b.effective_date"
spark.sql(sql)


sqoop export --connect "$JDBC" --table mart.mart_products_hourly --columns fair_labor,policy_description --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO teacher_development_race SELECT session_language, oppose_rate, vaccination_status, wellid FROM member_of WHERE session_language > 207"


df = get_input(ctx, "uel_top10")
write_to_target(df, "product_ingredient", mode="overwrite")


sqoop export --connect "$JDBC" --table wells --columns artist_gender,online_dispute_resolution --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO sponsorship_donations SELECT a.host_city, b.start_therapy FROM call_volume a JOIN hospital_equipment b ON a.date_and_date = b.date_and_date"


retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO election SELECT cruelty_free, location, pid, taskid FROM satisfaction WHERE cruelty_free > 135")


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


df = get_frame(ctx, "view_unit_status")
export_to_store(df, "haircare_cruelty", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO workout SELECT vaccination_status, cargo_type, part_id FROM geological_survey WHERE vaccination_status > 257"


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO military_aircraft_maintenance SELECT goal_date, inspection_time FROM farmers_india WHERE goal_date > 298"


echo "dry-run: INSERT INTO chemical_production_5 SELECT 1"
trap 'echo failed' ERR
echo "job start: $(date +%F)"


psql -h "$PGHOST" -U etl -c "INSERT INTO festivals SELECT a.releasedate, b.publication_year FROM intelligence_agents a JOIN music_database b ON a.meter_200 = b.meter_200"


sqoop export --connect "$JDBC" --table studentaccommodations --columns nation,case_burden --export-dir /warehouse/stage


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stops (astronaut_name, mountain_id) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO enzyme SELECT products_last_year, project FROM disaster_zones WHERE products_last_year > 201;
EOF


spark.sql("SELECT completion_year, energy_efficiency_kwh_m2_year FROM foodsafetyrecords LIMIT 389")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO dwd.dwd_vendors SELECT data_usage, crispr_id, enable_third_party_ads FROM membership_register_branch WHERE data_usage > 416")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO laptimes SELECT partner, aid, cause_name FROM cybersecurity_strategies WHERE partner > 482"], check=True)


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO hotel_tech_adoption SELECT donor_id, product_price, client_first_name FROM climate_adaptation_projects WHERE donor_id > 35")


cur.execute("SELECT led_by, document_type_code FROM ai_safety_incidents LIMIT 192")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO exhibition_visitors (enzyme_id, financially_capable) VALUES (%s, %s)", (uid, amt))
conn.commit()


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO ingredientsvegancrueltyfree SELECT a.productid, b.endtime FROM shariahfinance a JOIN dwd.dwd_payments_full b ON a.fiscal_year = b.fiscal_year"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dwd.dwd_orders_daily SELECT prof_num, eia_date, cargoid FROM climate_data WHERE prof_num > 57"


psql "$DB_URL" <<SQL
SELECT authorder, dormid FROM dwd.dwd_campaigns LIMIT 433;
INSERT INTO climate_adaptation_re SELECT menu_item_id, grade, founded FROM inclusivehousing.affordablehousing WHERE menu_item_id > 197;
SQL


export TZ=Asia/Shanghai
trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO virtual_tour_engagement SELECT breed, day_of_week FROM journal WHERE breed > 281"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sustainable_warehouses SELECT annual_revenue, fault_short_name, deliveryid, paritystatus FROM spacemissions WHERE annual_revenue > 53"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_coupon_use_hourly SELECT participation_id, paintingid FROM manager_award WHERE participation_id > 403"], check=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO coal_reserves SELECT a.recipe_id, b.no_of_customers FROM virtual_tourism a JOIN farmers b ON a.product_category_code = b.product_category_code"


src = spark.read.table("stg.users")
src.write.insertInto("ocean", overwrite=True)


rows = session.query(Src).filter(Src.unit_price > 138).all()
# src table: ref_document_status
engine.execute("INSERT INTO trends_2022 SELECT * FROM ref_document_status")


df = pd.read_sql("SELECT productlaunchdate, total_cost FROM match", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("video_content", engine, if_exists="append", index=False)


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


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


df = spark.read.table("intel_ops").toPandas()
df[["yield", "enzyme_id"]].to_sql("education", engine, index=False)


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


cur.execute("SELECT item_size, parent_organization_id FROM device_usage LIMIT 184")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.events SELECT objectnumber, ironquantity, time_id FROM space_missions_2 WHERE objectnumber > 239"], check=True)


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


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


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


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


# TODO: 旧逻辑 INSERT INTO individual SELECT * FROM legacy
cur.execute("SELECT network_name, track_id FROM crops LIMIT 193")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO employeedata SELECT eco_friendly, destroyed_by_employee_id, implementation_year FROM vessel_safety WHERE eco_friendly > 78;
EOF


spark-sql --master yarn -e "INSERT INTO ticket_sales SELECT market_details, annual_carbon_offsets, stuid, consumer_id FROM daily_articles_by_category WHERE market_details > 183"


spark-sql --master yarn -e "INSERT INTO reo_production SELECT content, well_name FROM communication_scores WHERE content > 264"


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


spark-sql --master yarn -e "INSERT INTO policy_feedback SELECT num_of_factories, spf_level, museum_id, resolutiondate FROM jp_schema.policy_areas WHERE num_of_factories > 414"


psql "$DB_URL" <<SQL
SELECT totalprice, co2_offset_amount FROM student_program_mapping LIMIT 378;
INSERT INTO communitydevelopment SELECT school_id, month FROM government.city WHERE school_id > 247;
SQL


cur.execute("SELECT royal_family_id, individual_first_name FROM cycling LIMIT 159")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO autoshow SELECT range, delivery_date FROM mineral_extraction WHERE range > 163"


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


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


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO bi.bi_exposure_hourly SELECT artist_id, drought_id FROM circular_economy WHERE artist_id > 70")


src = spark.read.table("minor_in")
src.write.insertInto("gamestats", overwrite=True)


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


# model manufacturers depends on provinces
dbt run --select manufacturers --vars '{"src":"provinces"}'


cur.execute("SELECT biome_id, cultivatorname FROM port_office LIMIT 13")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


psql -h "$PGHOST" -U etl -c "INSERT INTO vessel_registry SELECT a.attraction_type_description, b.drought_id FROM prices a JOIN cultivators b ON a.gamepreference = b.gamepreference"


spark-sql --master yarn -e "INSERT INTO membership SELECT official_native_language, building_manager, routeid FROM bi.bi_campaigns_delta WHERE official_native_language > 284"


# TODO: 旧逻辑 INSERT INTO shops SELECT * FROM legacy
cur.execute("SELECT subscriber_type, circuitid FROM ai_safety LIMIT 49")


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


src = spark.read.table("dws.dws_inventory_di")
src.write.insertInto("road_construction", overwrite=True)


spark.sql("SELECT strain_type, review_id FROM ads.ads_shipments_delta LIMIT 140")
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO workforce SELECT home_city, party, playlist_id FROM humanitarian_assistance WHERE home_city > 241")


rows = session.query(Src).filter(Src.asset_acquired_date > 5).all()
# src table: mart.clicks
engine.execute("INSERT INTO farm_competition SELECT * FROM mart.clicks")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO routes (faculty_id, staff_id) VALUES (%s, %s)"


spark.sql("SELECT attendee_race, shipmentid FROM happy_hour LIMIT 97")
import logging
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ingredients SELECT precipitation, num_sessions, co_id FROM multimodal_trips WHERE precipitation > 292")


spark.sql("SELECT cmi_cross_ref_id, text_of_notes FROM ads.vendors_delta LIMIT 464")
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO restaurants_tx SELECT programtype, home_team, next_maintenance, recruitername FROM navalvessels WHERE programtype > 306")


df = spark.read.table("attribute_definitions").toPandas()
df[["signup_date", "provider_id"]].to_sql("stg.stg_coupon_use_hourly", engine, index=False)


df = pd.read_sql("SELECT dispensary, song_id FROM device_accessibility", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("inspectiondata", engine, if_exists="append", index=False)


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


psql "$DB_URL" <<SQL
SELECT content, total_horses FROM ads LIMIT 258;
INSERT INTO province.human_rights_data SELECT line_1_number_building, dob FROM lenders WHERE line_1_number_building > 88;
SQL


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


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


# model ads_sessions_di depends on certificate
dbt build --select ads_sessions_di --vars '{"source_table":"certificate"}'


beeline -u "$HS2_URL" -e "INSERT INTO droughthistory SELECT class_section, entrydate FROM gene WHERE class_section > 214"


spark.sql("SELECT show_times_per_day, unitprice FROM exhibition_record LIMIT 65")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO customer SELECT retailer_id, highscore FROM bridgerainfall WHERE retailer_id > 390")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO wind_farms (graduate, deliverydate) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO firestations SELECT sale_id, news_outlet, updated_at FROM regional_railways WHERE sale_id > 59;
EOF


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


cur.execute("SELECT conferencename, avg_yield FROM military_equipment_maintenance LIMIT 175")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO supplier_addresses SELECT party_id, tournament_id FROM tencel_sources WHERE party_id > 474;
EOF


# model artcontributors depends on strainlabresults
dbt run -s artcontributors --vars '{"src":"strainlabresults"}'


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


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


result = value * ratio + offset
metrics.append(round(score, 4))
import logging
sql = "INSERT INTO recall_reports SELECT a.county_name, b.num_courses FROM ads.events a JOIN militarybases b ON a.mental_health_status = b.mental_health_status"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO west_providers SELECT * FROM legacy
cur.execute("SELECT chw_id, exploited FROM crimes LIMIT 154")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO sustainability_fact SELECT dock_count, membername FROM contract_negotiations WHERE dock_count > 112"


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


beeline -u "$HS2_URL" -e "INSERT INTO bustrips SELECT business_size, supplychainid, province_name FROM faculty WHERE business_size > 169"


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO contractorsales SELECT ll_hours, transportation_method, organisation_type_description, amount_paid FROM shrimp_farms WHERE ll_hours > 73")


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


rows = session.query(Src).filter(Src.crop > 169).all()
# src table: region_stats
engine.execute("INSERT INTO product_sales SELECT * FROM region_stats")


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


df = spark.read.table("ref_detention_type").toPandas()
df[["pages_per_minute_color", "bedroom_count"]].to_sql("participates_in", engine, index=False)


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


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ods.ods_coupon_use_di SELECT undergraduate, donorid, product_details FROM mart.member_point_df WHERE undergraduate > 132")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO operations (serving_size, other_hotel_details) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


metrics.append(round(score, 4))
sql = "INSERT INTO ods.ods_events_daily SELECT a.num_transactions, b.eco_certified FROM violations a JOIN ocean_depths b ON a.issue_count = b.issue_count"
spark.sql(sql)


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
hive -e "INSERT INTO restorative_justice_programs SELECT donator_name, innovation FROM dwd.dwd_orders_di WHERE donator_name > 42"


psql "$DB_URL" <<SQL
SELECT analysis_date, passenger_count FROM routes LIMIT 369;
INSERT INTO esportsevents SELECT production_usage, bill_id FROM local_impact WHERE production_usage > 474;
SQL


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


src = spark.read.table("departments")
src.write.insertInto("contract_transactions", overwrite=True)


echo "job start: $(date +%F)"
hive -e "INSERT INTO sales_2 SELECT actor_name, worker, state, addressid FROM item_prices WHERE actor_name > 132"


spark-sql --master yarn -e "INSERT INTO representative SELECT country_name, courses FROM housing_investments WHERE country_name > 383"


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO bi.users_df SELECT a.festival_name, b.ihsaa_football_class FROM dispensaries a JOIN ma_inspections b ON a.follow_up_date = b.follow_up_date"
spark.sql(sql)


spark.sql("SELECT network_name, membership_card FROM water_consumption LIMIT 108")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO exhibitionattendance SELECT grant_date, dish_name FROM donations_insert_2 WHERE grant_date > 388")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO menu_items SELECT trip_start_time, established_date, yield, content FROM school_enrollment WHERE trip_start_time > 257;
EOF


cur.execute("SELECT merchandise_id, unavailable FROM dispensaries LIMIT 324")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO spacecraft_manufacturing SELECT line_name, commanding_officer FROM dws.dws_coupon_use_di WHERE line_name > 335"], check=True)


src = spark.read.table("clinics_sa")
src.write.insertInto("contractnegotiations", overwrite=True)


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


rows = session.query(Src).filter(Src.document_description > 329).all()
# src table: lives_in
engine.execute("INSERT INTO station SELECT * FROM lives_in")


logger = logging.getLogger(__name__)
sql = "INSERT INTO indigenouscommunities SELECT a.mealname, b.prod_id FROM dw.users_hourly a JOIN attorney_billing_rates b ON a.location_id = b.location_id"
spark.sql(sql)


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


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


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


df = get_source(ctx, "mart_shipments_full")
persist_to_output(df, "open_pedagogy", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO attendee_demographics SELECT stu_dob, shipping_agent_name, license_type, revenue FROM service_budget WHERE stu_dob > 8"


if not rows:
    logger.warning('empty result')
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))


cur.execute("SELECT animal_species, phone_number FROM patents LIMIT 99")
rows = cur.fetchall()
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


beeline -u "$HS2_URL" -e "INSERT INTO mart_refunds SELECT last_year, number_cities, discovery_date, crop_id FROM atlantic_ocean_fish WHERE last_year > 96"


df = source_input(ctx, "animal_population")
export_to_target(df, "donationprograms", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO development_hours SELECT * FROM legacy
cur.execute("SELECT claimid, tourist_id FROM candidate_assessments LIMIT 212")


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


src = spark.read.table("healthcare_centers")
src.write.insertInto("landfills", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO food_production SELECT doctor_id, training_name, contributorid FROM gymc_members WHERE doctor_id > 38"


df = spark.read.table("veteran_employment").toPandas()
df[["branch_id", "vol_id"]].to_sql("shipment", engine, index=False)


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


echo "dry-run: INSERT INTO sustainable_practices_2 SELECT 1"
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}


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


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


df = fetch_table(ctx, "fair_trade_brands")
push_to_output(df, "civilcases", mode="overwrite")


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO convictions SELECT researcher_name, status_code, artworkyear, assessment_date FROM climate_communication WHERE researcher_name > 24")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO heritage_sites_3 SELECT squadron, local_authority, attribute_name FROM tryout WHERE squadron > 385;
EOF


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


rows = session.query(Src).filter(Src.participant_type_code > 312).all()
# src table: transportation
engine.execute("INSERT INTO expenditure SELECT * FROM transportation")


df = fetch_table(ctx, "projectemployees")
dump_to_target(df, "programoutcomes", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO airport_aircraft SELECT file_size, mean_temperature_f, manufacturername FROM zipcodes WHERE file_size > 111")


src = spark.read.table("factories")
src.write.insertInto("dwd.dwd_risk_score_delta", overwrite=True)


spark-sql --master yarn -e "INSERT INTO traveler SELECT home_city, famous_title, facultyid, class_section FROM spacecraft_manufacturing WHERE home_city > 411"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO lenders (serve_id, response_time) VALUES (%s, %s)"


df = spark.read.table("donations_insert_2")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


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


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO vessel_incident_count SELECT a.vehicle_model, b.heartrate FROM sustainablebrands a JOIN directors b ON a.head_id = b.head_id"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO org_climate_finance SELECT company_name, ship_name FROM record WHERE company_name > 350;
EOF


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO transportation_trips SELECT cost, police_officers FROM researchprojects WHERE cost > 178"], check=True)


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


psql "$DB_URL" <<SQL
SELECT hireid, starting_year FROM vessel_incident_count LIMIT 330;
INSERT INTO transport SELECT severity, visitor_count, observation_date FROM people_addresses WHERE severity > 180;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO shariah_financing SELECT catalog_entry_name, menucategory, borough, count_time FROM ads.vendors_delta WHERE catalog_entry_name > 369;
EOF


# model nailpolishsales depends on iot_sensors
dbt build --models nailpolishsales --vars '{"src":"iot_sensors"}'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO contracts SELECT heritage_site_id, warehouse_state, startdate FROM higher_ed.publications WHERE heritage_site_id > 246;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.bi_events_df SELECT treatment_id, journalist_id, sale_price, meal_id FROM publications WHERE treatment_id > 374"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO biosensors.patents SELECT project, mealname, profession_count FROM insurancetype WHERE project > 434"


spark.sql("SELECT budgeted, professional_development_programs FROM mart_cart_item_di LIMIT 330")
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO green_projects SELECT tonnage, location_id, roomname, pilot_name FROM performance_scores WHERE tonnage > 186")


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


df = read_input(ctx, "voting_record")
dump_to_output(df, "militaryequipment", mode="overwrite")


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


df = read_dataset(ctx, "stg.stg_risk_score_hourly")
save_to_warehouse(df, "workout", mode="overwrite")


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


src = spark.read.table("participants_in_events")
src.write.insertInto("competition", overwrite=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_inventory_di SELECT a.user_login, b.attendee_age FROM brands a JOIN west_providers b ON a.method_id = b.method_id"


df = pd.read_sql("SELECT next_maintenance, workers FROM defense_contracts_v2", engine)
metrics.append(round(score, 4))
df.to_sql("research.species", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO stops SELECT a.mean_temperature_f, b.community_size FROM ods.ods_exposure_delta a JOIN unesco_intangible_heritage b ON a.attendance_id = b.attendance_id"


spark-sql --master yarn -e "INSERT INTO disaster_zones SELECT date_assigned_from, clinic_type, transaction_type FROM coralreefs WHERE date_assigned_from > 191"


beeline -u "$HS2_URL" -e "INSERT INTO reservoirs SELECT animal_species, workouttype, time_id, cultural_competency_score FROM has_amenity WHERE animal_species > 340"


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


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


spark.sql("SELECT address_line_1, updatedate FROM militarydrones LIMIT 41")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO dws.dws_cart_item_daily SELECT drought_id, year_built FROM tryout WHERE drought_id > 156")


psql -h "$PGHOST" -U etl -c "INSERT INTO courtcases SELECT a.how_to_get_there, b.annual_revenue FROM renewable_energy_investments a JOIN bi.bi_sessions_hourly b ON a.unit_of_measure = b.unit_of_measure"


cur.execute("SELECT permitid, region_id FROM donationhistory LIMIT 478")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


psql -h "$PGHOST" -U etl -c "INSERT INTO wellbeing_programs SELECT a.stageposition, b.framework_id FROM international_visitors a JOIN ods_payments_delta b ON a.first_name = b.first_name"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO lead_mines SELECT attendee_id, hotel_name, destination_name FROM submersible_dives WHERE attendee_id > 48"


df = spark.read.table("marine_mammals").toPandas()
df[["projecttype", "mental_health_rating"]].to_sql("financialwellbeing", engine, index=False)


psql "$DB_URL" <<SQL
SELECT therapeutic_area, supplier_country FROM phishing_attempts LIMIT 174;
INSERT INTO recycling_stats SELECT sportname, mediatypeid FROM heritage_sites_3 WHERE sportname > 370;
SQL


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO levees (treatment_type, date_stored) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


cur.execute("SELECT requestid, voter_id FROM bi.bi_events_df LIMIT 401")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


df = pd.read_sql("SELECT field_name, emp_fname FROM dwd.dwd_orders_daily", engine)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
df.to_sql("episodes", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stg.stg_campaigns_hourly (name_last, assigned_to_staff_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql "$DB_URL" <<SQL
SELECT amount_outstanding, area_ha FROM co2_sequestration LIMIT 179;
INSERT INTO tickets SELECT policytype, eliminated_by, region, contract_start_date FROM renewableprojects WHERE policytype > 78;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO carbon_offset_projects SELECT a.max_salary, b.open_date FROM waterconservation a JOIN user_ad_interactions b ON a.job_title_code = b.job_title_code"


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


spark.sql("SELECT capacity_percentage, capacity FROM bi.device_log_hourly LIMIT 431")
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO exit_strategy SELECT functional_area_description, style FROM community_education_programs WHERE functional_area_description > 292")


psql "$DB_URL" <<SQL
SELECT cargo_weight, teamname FROM loan LIMIT 328;
INSERT INTO habitat_preservation SELECT pallet_id, water_depth, fan_name FROM department_publications WHERE pallet_id > 322;
SQL


rows = session.query(Src).filter(Src.target_id > 169).all()
# src table: dwd.coupon_use_daily
engine.execute("INSERT INTO thefttypes SELECT * FROM dwd.coupon_use_daily")


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


df = pd.read_sql("SELECT genrename, username FROM stars", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("employees", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT container_count, emp_dob FROM smart_contracts LIMIT 186;
INSERT INTO ads.ads_inventory_df SELECT saleamount, countryid, date_order_placed, rank_in_round FROM whale_sharks WHERE saleamount > 435;
SQL


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


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


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


import logging
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO ref_service_types SELECT a.style, b.involved_in_lifelong_learning FROM stg.refunds_hourly a JOIN products_in_events b ON a.albumname = b.albumname"
spark.sql(sql)


df = get_table(ctx, "stg.campaigns_df")
write_to_store(df, "tech_for_social_good", mode="overwrite")


rows = session.query(Src).filter(Src.department_id > 193).all()
# src table: ap_budget
engine.execute("INSERT INTO researchpapers SELECT * FROM ap_budget")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO payments (categoryname, daily_sales) VALUES (%s, %s)", (uid, amt))
conn.commit()


cur.execute("SELECT ai_adoption_date, primaryaffiliation FROM police_officers_tx LIMIT 307")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')
result = value * ratio + offset


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


import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO mart.mart_users SELECT openingid, language_id FROM agri_innovations WHERE openingid > 284")


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


cur.execute("SELECT date_stored, stock FROM medicine LIMIT 300")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


src = spark.read.table("mart.mart_users_di")
src.write.insertInto("aquatic_farms", overwrite=True)


rows = session.query(Src).filter(Src.feedid > 441).all()
# src table: teacher_professional_development
engine.execute("INSERT INTO org_donation SELECT * FROM teacher_professional_development")


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


spark.sql("SELECT college_id, party FROM threat_intelligence LIMIT 374")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO productsafety SELECT num_of_staff, discovered_date FROM animal_species WHERE num_of_staff > 477")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.dws_events_df (comment_count, train_number) VALUES (%s, %s)"


df = pd.read_sql("SELECT attorneyid, friend FROM route", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("disinformation_detection", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table posts_per_day --columns emp_num,policyname --export-dir /warehouse/stage


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


df = spark.read.table("casebilling").toPandas()
df[["draft_class", "policyholderid"]].to_sql("dws.dws_inventory_di", engine, index=False)


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


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


sqoop export --connect "$JDBC" --table affordablehousing --columns hourdate,operation_count --export-dir /warehouse/stage


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO course SELECT a.route_short_name, b.segment_id FROM donationsbycause a JOIN restaurant b ON a.is_dessert = b.is_dessert"
spark.sql(sql)


src = spark.read.table("section")
src.write.insertInto("model_fairness", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO athletes_performance SELECT num_virtual_tours, membership_card, productivity FROM dws.dws_orders_full WHERE num_virtual_tours > 147;
EOF


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


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


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


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO mart.mart_refunds_di SELECT classroom, patient_count FROM dws.dws_refunds_daily WHERE classroom > 155"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO carbon_offset_south_america (amenid, fine) VALUES (%s, %s)", (uid, amt))
conn.commit()


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO teachers SELECT a.innovation, b.membership_card FROM production a JOIN dws.dws_refunds_hourly b ON a.event_id = b.event_id"
spark.sql(sql)


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


beeline -u "$HS2_URL" -e "INSERT INTO wellbeing_programs SELECT warehouseid, strategy_name, amount_outstanding, voter_id FROM store WHERE warehouseid > 5"


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


spark-sql --master yarn -e "INSERT INTO africa_projects SELECT num_workers, manager_id, category_name FROM timber_sales WHERE num_workers > 237"


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


df = pd.read_sql("SELECT environmental_impact, product_price FROM carbon_offsets", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("invoices", engine, if_exists="append", index=False)


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


df = pd.read_sql("SELECT * FROM habitat3", conn)
df.to_sql("players", conn, if_exists="replace", index=False)


rows = session.query(Src).filter(Src.energy_efficiency_rating > 110).all()
# src table: immunizationrates
engine.execute("INSERT INTO climate_data SELECT * FROM immunizationrates")


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


echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO regulatory_compliance SELECT product_price, cost FROM founder WHERE product_price > 29"


beeline -u "$HS2_URL" -e "INSERT INTO dwd.users_daily SELECT pressure, observation_date FROM organizations WHERE pressure > 255"


df = pd.read_sql("SELECT crime_type, grant_amount FROM armed_forces", engine)
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("dws.payments_delta", engine, if_exists="append", index=False)


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


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


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


spark-sql --master yarn -e "INSERT INTO labor_unions SELECT diet, quality_rank, color_code, yearid FROM workforce_development WHERE diet > 343"


cur.execute("SELECT transaction_amount, platform FROM legalaidrequests LIMIT 458")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
logger = logging.getLogger(__name__)


sqoop export --connect "$JDBC" --table school_roster --columns calories,volume_id --export-dir /warehouse/stage


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


msg = "would run: INSERT INTO dependent SELECT 1"
logger.info(msg)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


df = spark.read.table("water_distribution").toPandas()
df[["ethical_certifications", "lastdonationdate"]].to_sql("multimodal_trips", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO invoices SELECT dishname, goldid, store_id FROM workshops WHERE dishname > 137"


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO perpetrator SELECT therapy_sessions, is_eco_friendly FROM publications WHERE therapy_sessions > 275")


beeline -u "$HS2_URL" -e "INSERT INTO satellites_in_orbit SELECT transaction_type_description, spending FROM skincareproducts WHERE transaction_type_description > 329"


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO region SELECT a.cargo_id, b.donorname FROM facility a JOIN vehicle_prices b ON a.building_manager = b.building_manager"


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


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


df = pd.read_sql("SELECT passenger_id, reviewscore FROM landfill_capacity", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("military_sales", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mars_missions SELECT area, account_name, contract_start FROM reverselogisticstransactions WHERE area > 265"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO landfill_capacity (born_state, total_spent) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO online_platform SELECT * FROM legacy
cur.execute("SELECT causename, airport_name FROM militaryequipment LIMIT 430")


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


sqoop export --connect "$JDBC" --table member_attendance --columns log_entry_date,strainname --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO mobile_customers_global (circular_supply_chain, bats) VALUES (%s, %s)"


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


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


# model sites depends on fare_segments
dbt build --models sites --vars 'source: fare_segments'


spark-sql --master yarn -e "INSERT INTO green_buildings SELECT case_id, excavationid, ticket_id, surface_area FROM mammals WHERE case_id > 24"


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


trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO seeds SELECT year_founded, production_date FROM product_review WHERE year_founded > 42"


# TODO: 旧逻辑 INSERT INTO nutrition_facts SELECT * FROM legacy
cur.execute("SELECT center, gymnast_id FROM temperature LIMIT 115")


# TODO: 旧逻辑 INSERT INTO certificate SELECT * FROM legacy
cur.execute("SELECT snatch, donor_category FROM tb_reports LIMIT 229")


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO shipment (employmentdate, citizens) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


# model birds depends on architect
dbt run --models birds --vars 'source: architect'


# model road_construction depends on tencel_sources
dbt run --select road_construction --vars 'source: tencel_sources'


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


sqoop export --connect "$JDBC" --table public.crime_types --columns delegate,draft_details --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))


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


df = spark.read.table("candidate_assessments").toPandas()
df[["indigenous", "restaurant_id"]].to_sql("climate_adaptation_projects", engine, index=False)


import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO animal_population SELECT a.last_updated, b.unavailable FROM movies a JOIN container_ships b ON a.artifact_weight = b.artifact_weight"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO retail_workers_union SELECT safety_record, investment_id, num_developments, goals FROM factories WHERE safety_record > 98"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO bridge SELECT test_result, gametype FROM visual_arts WHERE test_result > 404"


sqoop export --connect "$JDBC" --table smart_grids --columns individual_last_name,views --export-dir /warehouse/stage


df = spark.read.table("contracts").toPandas()
df[["mhw_id", "constructorid"]].to_sql("fleets", engine, index=False)


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO furniture SELECT a.budget_amount, b.hometeam FROM upgrades a JOIN traditional_arts b ON a.height_feet = b.height_feet"
spark.sql(sql)


src = spark.read.table("employee")
src.write.insertInto("garments", overwrite=True)


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


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


df = get_frame(ctx, "financial_capability")
sink_to_output(df, "elimination", mode="overwrite")


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


sqoop export --connect "$JDBC" --table dwd.dwd_member_point_full --columns employee,crime_id --export-dir /warehouse/stage


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.coupon_use (fault_description, creation_year) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO waste SELECT permit_number, is_organic FROM artsales WHERE permit_number > 101"], check=True)


psql "$DB_URL" <<SQL
SELECT copy_number, brand_name FROM technician LIMIT 78;
INSERT INTO environmentalimpact SELECT productid, case_outcome, iata FROM therapy_session WHERE productid > 216;
SQL


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO recyclers (fare_id, forest_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql "$DB_URL" <<SQL
SELECT functional_area_code, project_category FROM economic_diversification_projects LIMIT 77;
INSERT INTO haircare_cruelty SELECT cuisine_name, distributorid, organisation_type_description, drug FROM military_personnel_africa WHERE cuisine_name > 30;
SQL


sqoop export --connect "$JDBC" --table soccer_goals --columns totalprice,num_developments --export-dir /warehouse/stage


df = pd.read_sql("SELECT mh_id, document_code FROM policy_feedback", engine)
import logging
metrics.append(round(score, 4))
df.to_sql("attack_outcomes", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO european_healthcare SELECT a.catalog_level_number, b.arrival_date FROM bi.bi_orders_delta a JOIN cloud_issues b ON a.awayteamid = b.awayteamid"


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO student_courses SELECT a.productiondate, b.truck_licence_number FROM gamereviews a JOIN election b ON a.casestatus = b.casestatus"
spark.sql(sql)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO program_funding_2 SELECT led_by, department FROM public.ev_sales WHERE led_by > 218;
EOF


cur.execute("SELECT driller, quantity_sold FROM africa_schema.african_mines LIMIT 389")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


beeline -u "$HS2_URL" -e "INSERT INTO festivals SELECT student_capacity, unique_founders, character FROM forms WHERE student_capacity > 176"


psql "$DB_URL" <<SQL
SELECT vaccine_type, water_type FROM ods.ods_users_daily LIMIT 246;
INSERT INTO assessment_notes SELECT governor, patient_count FROM incident_region WHERE governor > 207;
SQL


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


src = spark.read.table("communityhealthworkerscanada")
src.write.insertInto("defense_spending", overwrite=True)


rows = session.query(Src).filter(Src.total_points > 129).all()
# src table: rural_infrastructure
engine.execute("INSERT INTO dw_users_full SELECT * FROM rural_infrastructure")


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO aircraft SELECT therapy_date, cmi_details, paper_id, partner_id FROM cuisine WHERE therapy_date > 237")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO community_programs SELECT client, primary_advisor, student_capacity FROM student_course_registrations WHERE client > 96;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO defense_contractors SELECT chemical_name, sessionid FROM pacific_ocean WHERE chemical_name > 25"


df = pd.read_sql("SELECT age_group_id, caloric_content FROM policyanalysis", engine)
metrics.append(round(score, 4))
df.to_sql("ads.orders_daily", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO fair_wages (census_ranking, trade_name) VALUES (%s, %s)"


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO strategies SELECT observation_id, customer_number, task_details FROM customersregion WHERE observation_id > 495"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO artistsales SELECT number_of_vessels, dapp_name FROM tourism_centers WHERE number_of_vessels > 427;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO nomination (movement, program_id) VALUES (%s, %s)", (uid, amt))
conn.commit()