import subprocess
subprocess.run(["hive", "-e", "INSERT INTO engineer_visits SELECT last_year, treatment_date, reign FROM sustainableprojects WHERE last_year > 18"], check=True)


sqoop export --connect "$JDBC" --table grapes --columns contract_type,route_short_name --export-dir /warehouse/stage


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


psql -h "$PGHOST" -U etl -c "INSERT INTO lenders SELECT a.fda_approved, b.date_valid_to FROM rebounds a JOIN worker_union b ON a.district = b.district"


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


spark.sql("SELECT profits_billion, restaurant_id FROM dwd.dwd_risk_score_delta LIMIT 450")
import logging
spark.sql("INSERT INTO marine_species_arctic_ocean SELECT practiceid, reports_to FROM passengers WHERE practiceid > 352")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dwd.dwd_member_point_di SELECT outcome_id, completed, digital_channel, vessel_id FROM circular_economy_initiatives WHERE outcome_id > 443"], check=True)


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO environmentalimpact SELECT num_pallets, socialimpactscore, county_name, community_name FROM legalaidrequests WHERE num_pallets > 420"], check=True)


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


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO shark_biomass SELECT a.people_id, b.visitid FROM rental a JOIN lenders b ON a.destination_id = b.destination_id"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO design_standards SELECT is_autonomous, purchase_date, book_club_id FROM sustainability_metrics WHERE is_autonomous > 160;
EOF


spark-sql --master yarn -e "INSERT INTO european_healthcare SELECT start_time, carrierid FROM resilience_infrastructure WHERE start_time > 438"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO reviews (chw_id, detected_at) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT book_title, impactid FROM london.stations", engine)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
df.to_sql("visitor_statistics", engine, if_exists="append", index=False)


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO therapy_attendance SELECT speed, bridgetype, port_name FROM biosensors.readings WHERE speed > 2"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO obesity SELECT jan, updatedate, co_owner_count FROM climber WHERE jan > 121")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO phishing_targets SELECT trips, policy_name, album_id, artifactname FROM restorative_justice_center WHERE trips > 222;
EOF


df = load_table(ctx, "ads.ads_vendors_hourly")
dump_to_sink(df, "city_budgets", mode="overwrite")


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


sqoop export --connect "$JDBC" --table flu_cases --columns production_budget,id --export-dir /warehouse/stage


src = spark.read.table("nursing_homes")
src.write.insertInto("stg.member_point_df", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dw.dw_products_delta SELECT vesselname, highscore, promotiondate FROM ods_payments_delta WHERE vesselname > 26"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO price_data SELECT a.transportation_method, b.neighborhoodid FROM stores_2 a JOIN lives_in b ON a.trend = b.trend"


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


beeline -u "$HS2_URL" -e "INSERT INTO heart_rate_data SELECT testtypeid, cityid, treatment_date FROM healthequitymetrics WHERE testtypeid > 243"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.dws_users_hourly (class_president_vote, start_station_id) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO gymnast SELECT regionid, cropname, ship_id FROM coralreefs WHERE regionid > 258"


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


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
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 fruitimport SELECT document_name, personnelid, destinationid FROM movie_ratings WHERE document_name > 499"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO marinespeciesobservations SELECT campaign_name, intervention_type FROM navalvessels WHERE campaign_name > 159;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dws.dws_inventory_di SELECT product_type, import_country, labor_practice FROM founder WHERE product_type > 54"


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


set -euo pipefail
hive -e "INSERT INTO cycling SELECT bridgetype, labor_id FROM ads.ads_exposure_di WHERE bridgetype > 476"


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


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


import logging
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO vehicle_registrations SELECT a.nid, b.u_id FROM community_leaders a JOIN tourist_attraction_features b ON a.product_stock_number = b.product_stock_number"
spark.sql(sql)


# model cycling depends on apartments
dbt run --models cycling --vars 'source: apartments'


# model item_prices depends on device_usage
dbt build --models item_prices --vars '{"src":"device_usage"}'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO production_sites SELECT claimtype, plant_name, acc_percent FROM vehicle_data WHERE claimtype > 135;
EOF


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO defense_diplomacy SELECT policyid, last_year, credits, employee_id FROM co_ownership WHERE policyid > 412;
EOF


echo "job start: $(date +%F)"
hive -e "INSERT INTO movie_financials SELECT co2_emissions, crs_description FROM tencel_sources WHERE co2_emissions > 286"


df = spark.read.table("travel_advisory").toPandas()
df[["claimdate", "clicks"]].to_sql("safety_violations", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO offender_demographics SELECT gameid, parent_organization_id, donor_name FROM mart.mart_vendors WHERE gameid > 105;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO medals SELECT f_id, launch_date, vessel_id FROM neighborhoods WHERE f_id > 52"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO communities SELECT price_in_dollar, genderid, competition_type FROM competition WHERE price_in_dollar > 101"], check=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.dwd_campaigns (vrgameid, founder_identity) VALUES (%s, %s)"


df = spark.read.table("shipment_data").toPandas()
df[["cause_id", "exhibit_location"]].to_sql("timed_status_of_things", engine, index=False)


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


psql "$DB_URL" <<SQL
SELECT digital_asset, supplychainid FROM attorney_billing LIMIT 162;
INSERT INTO climate_adaptation_re SELECT exhibitionname, amount_due, staystart FROM movie_financials WHERE exhibitionname > 418;
SQL


src = spark.read.table("bi.clicks_hourly")
src.write.insertInto("bi.risk_score_df", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO communication_scores (district_name, dept_store_chain_id) VALUES (%s, %s)"


cur.execute("SELECT monthly_rental, safety_id FROM geological_survey LIMIT 484")
rows = cur.fetchall()
result = value * ratio + offset
import logging
metrics.append(round(score, 4))


df = extract_frame(ctx, "community_development.transactions")
sink_to_target(df, "supportprograms", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO player_demographics SELECT headquarter, forename, province_id FROM results WHERE headquarter > 313"


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


# TODO: 旧逻辑 INSERT INTO ods.clicks_full SELECT * FROM legacy
cur.execute("SELECT habitat_name, party_email FROM dws.inventory_daily LIMIT 166")


sqoop export --connect "$JDBC" --table states --columns mission_count,researcher --export-dir /warehouse/stage


import logging
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 virtual_tourism SELECT catalog_id, mining_operation, device_id FROM economic_diversification_projects WHERE catalog_id > 486;
EOF


cur.execute("SELECT water_depth, spending FROM venture LIMIT 44")
rows = cur.fetchall()
metrics.append(round(score, 4))
import logging


threshold = cfg.get('threshold', 0.5)
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))


spark.sql("SELECT contributiondate, customer_address_id FROM medical_professionals LIMIT 444")
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO marine_life_data SELECT outcome, claim_amount, email FROM student_addresses WHERE outcome > 200")


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


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


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


df = spark.read.table("bi.bi_events_full").toPandas()
df[["project_type", "line_1_number_building"]].to_sql("healthequitymetrics", engine, index=False)


psql "$DB_URL" <<SQL
SELECT screening_id, shipped_date FROM grant LIMIT 382;
INSERT INTO platformg SELECT date_claim_made, claim_date, playtime, method_id FROM ma_inspections WHERE date_claim_made > 91;
SQL


spark.sql("SELECT numcases, cultural_significance FROM project_timelines LIMIT 201")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO company SELECT connection, breed FROM broadband_providers WHERE connection > 270")


spark.sql("SELECT candidate_id, policy_name FROM ma_inspections LIMIT 227")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO industrial_customers SELECT crop_id, astronautid, date_of_publication, institution_id FROM vehicle_counts WHERE crop_id > 100")


df = spark.read.table("field4_precip")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


beeline -u "$HS2_URL" -e "INSERT INTO investment_strategies SELECT attendance, average FROM skincareinventory WHERE attendance > 324"


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


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


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


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO tourism (venue_id, exhibitions) VALUES (%s, %s)"


df = pd.read_sql("SELECT * FROM stg.campaigns_df", conn)
df.to_sql("shelters", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO aid_missions SELECT * FROM legacy
cur.execute("SELECT route_id, incorporated_in FROM furniture LIMIT 294")


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))


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO community.donors SELECT a.district_id, b.f_id FROM tour_guides a JOIN bi.bi_payments b ON a.discovered_date = b.discovered_date"
spark.sql(sql)


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


spark.sql("SELECT incident_type_code, damage_millions_usd FROM travel_advisory LIMIT 412")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO county_public_safety SELECT credit_score, document_date, head_id FROM artistsales WHERE credit_score > 256")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO forests (center_name, petid) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table artprograms --columns post_id,pilot_name --export-dir /warehouse/stage


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


result = value * ratio + offset
sql = "INSERT INTO player SELECT a.district_id, b.clicks FROM unions a JOIN materials_usage b ON a.developer = b.developer"
spark.sql(sql)


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


df = pull_dataset(ctx, "management")
push_to_output(df, "checking", mode="overwrite")


df = fetch_input(ctx, "green_buildings")
write_to_store(df, "startup_founders", mode="overwrite")


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


# model player_coach depends on productivity
dbt build --models player_coach --vars 'source: productivity'


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


cur.execute("SELECT draft_class, produceid FROM socially_responsible_lending LIMIT 7")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


src = spark.read.table("dispensaries")
src.write.insertInto("customers_policies", overwrite=True)


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO artist_demographics SELECT generation_date, sales_billion, org_name, session_date FROM leo_missions WHERE generation_date > 181"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO manufacturersustainability SELECT team_id_br, request_date FROM residents_services WHERE team_id_br > 414;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO urban_agriculture_initiatives SELECT lot_id, organisation_details FROM caribbeansea WHERE lot_id > 408"


df = spark.read.table("match_result").toPandas()
df[["hospitalname", "totalamount"]].to_sql("vessel_capacity", engine, index=False)


df = source_table(ctx, "culturalpractices")
save_to_warehouse(df, "school_roster", mode="overwrite")


cur.execute("SELECT device_id, gender_diversity FROM donors_region LIMIT 485")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


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


rows = session.query(Src).filter(Src.case_number > 396).all()
# src table: aquaculture_farms
engine.execute("INSERT INTO prices SELECT * FROM aquaculture_farms")


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


# model waterconservation depends on browser
dbt build -s waterconservation --vars 'source: browser'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO influencers SELECT opponent_id, garment, s_id FROM affiliated_with WHERE opponent_id > 201;
EOF


rows = session.query(Src).filter(Src.date_complaint_raised > 323).all()
# src table: electric_vehicle_stats
engine.execute("INSERT INTO student_access SELECT * FROM electric_vehicle_stats")


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


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


# model patient_satisfaction depends on climateresearch
dbt build --models patient_satisfaction --vars '{"src":"climateresearch"}'


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO recruiters SELECT observation_date, pieces, time FROM opendatainitiatives WHERE observation_date > 108"


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


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


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO timber_sales SELECT salesperson_id, half, discovered_date, faculty_id FROM conditions WHERE salesperson_id > 465")


psql "$DB_URL" <<SQL
SELECT involved_in_lifelong_learning, professional_development_programs FROM genetics.crispr LIMIT 173;
INSERT INTO business_rates SELECT bridgetype, partnership_id, served_subscribers, watertemp FROM teacher_development_race WHERE bridgetype > 309;
SQL


sqoop export --connect "$JDBC" --table machines --columns round,adoption_date --export-dir /warehouse/stage


# model circuits depends on green_building_materials
dbt run --select circuits --vars '{"src":"green_building_materials"}'


spark.sql("SELECT implementation_year, pollution_id FROM cultivators LIMIT 185")
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO water_treatment_facilities SELECT project_name, gamename, fairtrade FROM stock_levels WHERE project_name > 296")


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


# TODO: 旧逻辑 INSERT INTO complaints SELECT * FROM legacy
cur.execute("SELECT ad_id, avg_speed FROM smart_cities LIMIT 59")


sqoop export --connect "$JDBC" --table safety_incidents_india --columns meal_name,payment_id --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT customername, max_aperture FROM singer_in_concert LIMIT 481;
INSERT INTO ads.ads_users_hourly SELECT user_account, accident_date, investment_round, medical_condition FROM animal_rehab WHERE user_account > 188;
SQL


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO drug_sales SELECT date_formed, defense_contractor_id, wellname, totalprice FROM ticketspending WHERE date_formed > 75;
EOF


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


psql "$DB_URL" <<SQL
SELECT call_date, price_in_dollar FROM space_telescopes LIMIT 26;
INSERT INTO waste_generation SELECT involved_in_lifelong_learning, costid FROM defense_spending_3 WHERE involved_in_lifelong_learning > 401;
SQL


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


# model online_platform depends on infrastructurebudget
dbt run --select online_platform --vars 'source: infrastructurebudget'


import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO virtual_tours SELECT a.success, b.prof_num FROM hotel_ratings a JOIN bi.bi_orders_hourly b ON a.enddate = b.enddate"
spark.sql(sql)


df = source_dataset(ctx, "labor_unions")
upsert_to_sink(df, "job_postings", mode="overwrite")


df = pd.read_sql("SELECT last_maintenance, q1_2022_views FROM uniteddefense.equipmentsales", engine)
result = value * ratio + offset
df.to_sql("policy_feedback", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO associatedheritages SELECT interest_group, customer_details FROM resilience_infrastructure WHERE interest_group > 477"


logger = logging.getLogger(__name__)
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO runs SELECT center, street_address, amount_settled, railway_id FROM canals WHERE center > 442")


# model factories depends on urban_initiatives
dbt run -s factories --vars '{"source_table":"urban_initiatives"}'


df = read_table(ctx, "ethicalaibudget")
dump_to_sink(df, "transportation_per_country", mode="overwrite")


sqoop export --connect "$JDBC" --table airport_aircraft --columns enddate,vendor_id --export-dir /warehouse/stage


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO vehicle SELECT principal_activities, workerid, ocean_name, asset_name FROM clinics_sa WHERE principal_activities > 298")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO electric_vehicle_stats SELECT target_name, certification_id, port_id FROM food_justice_orgs WHERE target_name > 303"], check=True)


src = spark.read.table("multimodal_trips")
src.write.insertInto("suppliersfairlabor", overwrite=True)


# TODO: 旧逻辑 INSERT INTO employee_demographics SELECT * FROM legacy
cur.execute("SELECT paper_id, awayteamid FROM safety_incidents_india LIMIT 357")


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


df = load_frame(ctx, "intelligence_agents")
export_to_output(df, "hotel_tech_adoptions", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO housing_investments SELECT individual_name, classid, airport_name FROM beauty_products WHERE individual_name > 460;
EOF


export TZ=Asia/Shanghai
set -euo pipefail
echo "job start: $(date +%F)"
hive -e "INSERT INTO buildings SELECT mountain_id, totaldonation, duration_ms FROM ods.sessions_daily WHERE mountain_id > 50"


df = spark.read.table("fish_biomass").toPandas()
df[["scores", "farmid"]].to_sql("country_sustainable_chains", engine, index=False)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mobile_usage (dates_active, rec_engine) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


sqoop export --connect "$JDBC" --table fireincidents --columns contract_number,destruction_authorised_by_employee_id --export-dir /warehouse/stage


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


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


# model marketing_regions depends on renewable_projects
dbt build -s marketing_regions --vars '{"src":"renewable_projects"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO renewableprojects (year_join, price_in_dollar) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ai_ethics_policies SELECT how_to_get_there, shariah_compliant_investment_amount FROM wastewatertreatment WHERE how_to_get_there > 39"], check=True)


sqoop export --connect "$JDBC" --table educationprograms --columns hotel_name,labordate --export-dir /warehouse/stage


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


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


spark-sql --master yarn -e "INSERT INTO apac_hotel_views SELECT park_id, certification_name FROM labor_stats WHERE park_id > 409"


src = spark.read.table("smart_city_projects")
src.write.insertInto("hydro_plants", overwrite=True)


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


df = pull_table(ctx, "mobile_customers_global")
upsert_to_warehouse(df, "habitat_preservation", mode="overwrite")


# model visits_restaurant depends on dali
dbt run -s visits_restaurant --vars '{"source_table":"dali"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO investmentsesg (trainingtitle, lifespan) VALUES (%s, %s)"


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


df = pd.read_sql("SELECT price, nid FROM customers", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("articles", engine, if_exists="append", index=False)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO marathons (playerid, strain_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.contract_type > 117).all()
# src table: mentalhealthparityscores
engine.execute("INSERT INTO restaurant_revenue SELECT * FROM mentalhealthparityscores")


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


spark-sql --master yarn -e "INSERT INTO fleet_management SELECT is_electric, reported_by_staff_id, total_amount, transaction_date FROM climate_investments WHERE is_electric > 6"


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


sqoop export --connect "$JDBC" --table skincareinventory --columns totaldonation,cultivatorname --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dysprosiumproduction SELECT crs_description, used_kb, aircraft, assessmentname FROM undergoes WHERE crs_description > 340"], check=True)


cur.execute("SELECT fish_population, sustainability_certified FROM esports_teams LIMIT 133")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
import logging


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


psql "$DB_URL" <<SQL
SELECT trainingyear, cvid FROM healthcare_access_v2 LIMIT 366;
INSERT INTO convictions SELECT channel_code, artifact_id FROM safetytestingcounts WHERE channel_code > 118;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO vocals SELECT brand_name, org_size FROM productsafety WHERE brand_name > 492"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO mart.clicks SELECT movieid, bikes_available FROM location WHERE movieid > 359"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.stg_risk_score_hourly (call_date, created_at) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table aircraftsquadrons --columns hispanic,program_type --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT region_id, change_date FROM europium_exports LIMIT 307;
INSERT INTO patents SELECT fund_id, partner FROM product_review WHERE fund_id > 429;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO membership_data SELECT a.sent_date, b.park_id FROM attendees a JOIN trees b ON a.facility_id = b.facility_id"


src = spark.read.table("justice_schemas.legal_tech_providers")
src.write.insertInto("eco_materials", overwrite=True)


src = spark.read.table("ods.ods_member_point_df")
src.write.insertInto("awards", overwrite=True)


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO singer SELECT swimmer_id, fair_trade, funding_year FROM recyclingprogram WHERE swimmer_id > 220")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO biosensors.patents (accessibility, f_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


src = spark.read.table("product_review")
src.write.insertInto("union_members", overwrite=True)


spark.sql("SELECT material_type, mgr_start_date FROM shared_rides_tokyo LIMIT 26")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO document_locations SELECT num_volunteers, implementation_date, booking_start_date, city_population FROM songs WHERE num_volunteers > 94")


spark-sql --master yarn -e "INSERT INTO chemical_processes SELECT appelation, wage, analysis_date FROM time_dim WHERE appelation > 421"


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


beeline -u "$HS2_URL" -e "INSERT INTO salary SELECT booking_start_date, genre, product FROM facility_production WHERE booking_start_date > 147"


trap 'echo failed' ERR
export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO labor_statistics SELECT apid, tour_id, product_size FROM disaster_response WHERE apid > 252"


df = pd.read_sql("SELECT audienceid, program FROM camera_lens", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("associatedheritages", engine, if_exists="append", index=False)


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


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


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


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


df = spark.read.table("infantmortalitydata")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("healthcare_access_v2")


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


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


cur.execute("SELECT water_temp, mgr_start_date FROM patient_outcomes LIMIT 78")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


sqoop export --connect "$JDBC" --table checking --columns promotionid,gender_mf --export-dir /warehouse/stage


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


cur.execute("SELECT type, donationdate FROM infrastructure_projects LIMIT 44")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


spark-sql --master yarn -e "INSERT INTO intelligencesatellites SELECT num_students, maintenanceid, medium FROM green_buildings WHERE num_students > 317"


psql "$DB_URL" <<SQL
SELECT cultural_diversity, booking_id FROM race_ethnicity LIMIT 488;
INSERT INTO community_centers SELECT university_type, task_details, max_cargo_weight, host_city_id FROM emergencyservices WHERE university_type > 324;
SQL


spark.sql("SELECT mine_name, customer_details FROM railway LIMIT 63")
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO block SELECT crime_date, enrollment FROM bi.bi_sessions_df WHERE crime_date > 284")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO clinics_sa SELECT channel_code, log_entry_description, employee_id FROM sustainable_materials WHERE channel_code > 406"


psql "$DB_URL" <<SQL
SELECT state_county, communitytype FROM runs LIMIT 132;
INSERT INTO dws.dws_coupon_use_di SELECT contract_value, concert_id, incidentdate FROM zip_codes WHERE contract_value > 322;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO jupiter_spacecraft SELECT a.mission, b.topic FROM submission a JOIN salesdata b ON a.state_name = b.state_name"


sqoop export --connect "$JDBC" --table esa_missions --columns store_name,num_attendees --export-dir /warehouse/stage


presto --server presto01:8080 --catalog hive --execute "INSERT INTO housingaffordability SELECT document_date, game_count FROM gameattendance WHERE document_date > 183"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO vrgames SELECT case_status, claim_outcome_code, other_characteristic_details FROM student_program_mapping WHERE case_status > 493;
EOF


src = spark.read.table("conservation_projects")
src.write.insertInto("train_lines", overwrite=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO appointment (stream_date, follow_up_date) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO military_equipment_maintenance SELECT active_from_date, energy_source FROM episodes WHERE active_from_date > 301"], check=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO film_category SELECT retailer_id, loadingstart, player_name, cows FROM ai_papers WHERE retailer_id > 470"


# model canals depends on mart.mart_refunds_di
dbt run --models canals --vars '{"src":"mart.mart_refunds_di"}'


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO indie_artists SELECT cell_mobile_number, allocation_type FROM stg.device_log_df WHERE cell_mobile_number > 333;
EOF


sqoop export --connect "$JDBC" --table mart_refunds_delta --columns casestatus,continent --export-dir /warehouse/stage


# model garmentproduction depends on dwd.users_daily
dbt run --select garmentproduction --vars '{"src":"dwd.users_daily"}'


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


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


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


spark-sql --master yarn -e "INSERT INTO budgets SELECT claimamount, cityname, sighting_id FROM vehicle_sales WHERE claimamount > 464"


df = pull_table(ctx, "mappinglengths")
upsert_to_store(df, "inmates", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO animals SELECT a.vegan, b.community FROM game_sales a JOIN arcticwildlifereserve b ON a.review_id = b.review_id"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mine_workforce (characteristic_name, coach_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = extract_frame(ctx, "bi.member_point_full")
sink_to_output(df, "wastewater_treatment_plants", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO ods_member_point_full SELECT a.asset_details, b.detention_type_code FROM therapy_attendance a JOIN mart.mart_coupon_use_full b ON a.campaign_name = b.campaign_name"
spark.sql(sql)


spark.sql("SELECT cultivatorid, sessiondate FROM ads.ads_member_point_daily LIMIT 351")
result = value * ratio + offset
spark.sql("INSERT INTO baseball_teams SELECT unit_of_measure, review_rating, is_vegan, volunteer_hours FROM laborstatistics WHERE unit_of_measure > 19")


# TODO: 旧逻辑 INSERT INTO marine_species_status SELECT * FROM legacy
cur.execute("SELECT centerid, vesselid FROM dws.dws_clicks_full LIMIT 192")


df = pd.read_sql("SELECT cinema_id, size FROM ads.refunds", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("bustrips", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO dws.cart_item_di SELECT * FROM legacy
cur.execute("SELECT defense_contractor_id, request_date FROM matches LIMIT 137")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO city_budgets SELECT shoe_brand, online_dispute_resolution FROM attorneylocationyear WHERE shoe_brand > 52;
EOF


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO races SELECT a.equipment_id, b.patentexpirationdate FROM water_sources a JOIN co_ownership b ON a.made_in_usa = b.made_in_usa"
spark.sql(sql)


src = spark.read.table("material")
src.write.insertInto("contractorsales", overwrite=True)


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


# model authenticationlogs depends on biotech.startups
dbt run --models authenticationlogs --vars '{"source_table":"biotech.startups"}'


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


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


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


spark-sql --master yarn -e "INSERT INTO airport_aircraft SELECT postal_code, store_name FROM market_trends WHERE postal_code > 183"


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


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO carbon_sequestration SELECT a.fundingamount, b.cost FROM wind_turbines a JOIN restaurants b ON a.measurement_id = b.measurement_id"
spark.sql(sql)


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


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


df = source_frame(ctx, "auto_shows")
dump_to_target(df, "satellitedata", mode="overwrite")


cur.execute("SELECT effort, institution FROM volunteers LIMIT 384")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset
import logging


spark-sql --master yarn -e "INSERT INTO bioreactor SELECT share_count, athlete_name FROM driver WHERE share_count > 271"


result = value * ratio + offset
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO teacher_professional_development SELECT a.theme, b.stop FROM carbon_offset_programs a JOIN budget b ON a.date_of_enrolment = b.date_of_enrolment"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO dws.dws_users_hourly SELECT employer_organisation_id, green_building_id FROM satisfaction WHERE employer_organisation_id > 291"


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


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


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO sector_incidents SELECT a.contributorid, b.policy_id FROM taj_mahal_visitors a JOIN pipelines_us_canada b ON a.participant_type_code = b.participant_type_code"


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


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


df = get_source(ctx, "military_tech")
dump_to_target(df, "stg.risk_score_di", mode="overwrite")


mkdir -p /tmp/joblog
hive -e "INSERT INTO experience SELECT apid, num_of_audience, recruitername FROM military_innovation WHERE apid > 497"


psql "$DB_URL" <<SQL
SELECT athleteid, official_native_language FROM government.city LIMIT 303;
INSERT INTO habitats SELECT artist_id, subscriber_id, eventattendance FROM judges WHERE artist_id > 172;
SQL


# model job_postings depends on container_receipts
dbt build --models job_postings --vars '{"source_table":"container_receipts"}'


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO music_festival SELECT strategy_name, field_id FROM dws.dws_clicks_full WHERE strategy_name > 68")


spark-sql --master yarn -e "INSERT INTO carbon_offset_initiatives SELECT characteristic_data_type, startdate, review_score FROM mars_rovers WHERE characteristic_data_type > 15"


threshold = cfg.get('threshold', 0.5)
import logging
spark.sql("INSERT INTO dwd.dwd_payments_di SELECT industry_4_0, start_time, investors, amount_waste FROM vessel_incident_count WHERE industry_4_0 > 258")


rows = session.query(Src).filter(Src.isfirstattendee > 112).all()
# src table: fish_suppliers
engine.execute("INSERT INTO incidents SELECT * FROM fish_suppliers")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tourism_centers (degrees, date_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO genetic.projects SELECT away_team_id, algorithm_name, title, artworkid FROM ods.ods_campaigns_delta WHERE away_team_id > 88"


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


rows = session.query(Src).filter(Src.policy > 91).all()
# src table: forest_species
engine.execute("INSERT INTO station_company SELECT * FROM forest_species")


cur.execute("SELECT community_center_id, breed FROM humanitarian_aid LIMIT 197")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


spark-sql --master yarn -e "INSERT INTO aid_missions SELECT caloric_content, dispensary_id, projecttype FROM explainable_ai WHERE caloric_content > 364"


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO algorithmic_fairness_incidents SELECT a.programtype, b.circular_supply_chain FROM country_labor a JOIN stations b ON a.facility_code = b.facility_code"
spark.sql(sql)


metrics.append(round(score, 4))
spark.sql("INSERT INTO ods.products_hourly SELECT safety_score, biome_id, waste_type, programarea FROM products WHERE safety_score > 74")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cb_agreements SELECT method_name, detention_type_description, pricepergram FROM developers WHERE method_name > 407"


logger = logging.getLogger(__name__)
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))


sqoop export --connect "$JDBC" --table ads.refunds_delta --columns gold,end_time --export-dir /warehouse/stage


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO royal_family SELECT official_native_language, altitude, visitid FROM fireincidents WHERE official_native_language > 129"


df = spark.read.table("workforce_development_programs").toPandas()
df[["orgid", "asset_type"]].to_sql("bus_fare_collection", engine, index=False)


metrics.append(round(score, 4))
spark.sql("INSERT INTO candidates SELECT usage, project, vendorid FROM food_safety_inspections WHERE usage > 210")


cur.execute("SELECT union_id, cust_name FROM transportation_union LIMIT 439")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO school_bus SELECT violation_type, time_hour, reported_by_staff_id, customer_type_code FROM ocean_acidification_antarctic WHERE violation_type > 42"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mentalhealthscores SELECT artworkname, game FROM sustainability WHERE artworkname > 463"


rows = session.query(Src).filter(Src.gameid > 383).all()
# src table: elimination
engine.execute("INSERT INTO plays_games SELECT * FROM elimination")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO geological_survey SELECT last_year, carrierid FROM news_views WHERE last_year > 393"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO weather SELECT health_equity_metric_2, delivery_date, county_name FROM accelerator_compatible_browser WHERE health_equity_metric_2 > 358"


metrics.append(round(score, 4))
import logging
sql = "INSERT INTO garmentproduction SELECT a.vehicle_flight_number, b.astronaut FROM stats a JOIN athlete_wellbeing b ON a.inventor_name = b.inventor_name"
spark.sql(sql)


spark.sql("SELECT budget, completion_status FROM spending LIMIT 45")
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO fishcaught SELECT donortype, production_volume, artworkyear, party_name FROM otas WHERE donortype > 44")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO brandrevenue SELECT flight_number, complaint_type_code, route_short_name FROM ads_payments_di WHERE flight_number > 312;
EOF


cur.execute("SELECT budgeted, business_size FROM party_host LIMIT 163")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


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


df = read_frame(ctx, "workercontactinfo")
export_to_warehouse(df, "ref_budget_codes", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO species_data SELECT item, item_name, home_city FROM az_drought_impact WHERE item > 4;
EOF


spark-sql --master yarn -e "INSERT INTO ads.ads_payments SELECT transact_date, i_id, publication_id FROM funding_records WHERE transact_date > 35"


spark.sql("SELECT suppliername, account_id FROM arctictemperature LIMIT 235")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ai_papers SELECT ethnicity, session_date FROM programoutcomes WHERE ethnicity > 9")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO item SELECT menu_item, activity_id FROM military_tech WHERE menu_item > 157"], check=True)


cur.execute("SELECT nickname, drug_name FROM playersessions LIMIT 50")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))


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


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


rows = session.query(Src).filter(Src.profession > 124).all()
# src table: foodaid
engine.execute("INSERT INTO device_usage SELECT * FROM foodaid")


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


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


rows = session.query(Src).filter(Src.diet > 432).all()
# src table: travel_advisory
engine.execute("INSERT INTO ods.ods_member_point_delta SELECT * FROM travel_advisory")


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


rows = session.query(Src).filter(Src.speed > 287).all()
# src table: head
engine.execute("INSERT INTO contract_negotiations SELECT * FROM head")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO manufacturing_processes SELECT well_depth, thing_id, num_developments FROM cases WHERE well_depth > 277"


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO lead_mines SELECT a.dst_apid, b.status_of_thing_code FROM social_impact_bonds a JOIN production b ON a.role_code = b.role_code"
spark.sql(sql)


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


# TODO: 旧逻辑 INSERT INTO deep_sea_species SELECT * FROM legacy
cur.execute("SELECT eco_certified, state_code FROM runs LIMIT 170")


df = fetch_dataset(ctx, "ods.clicks_delta")
upsert_to_sink(df, "intelligenceoperations", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO exam_results SELECT safety_id, purchase_date, trial_name, cvid FROM dwd.coupon_use_full WHERE safety_id > 317;
EOF


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


df = pd.read_sql("SELECT dorm_name, is_electric FROM algorithmic_fairness_incidents", engine)
import logging
threshold = cfg.get('threshold', 0.5)
df.to_sql("player_stats", engine, if_exists="append", index=False)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO daily_revenue SELECT investor, museum_id FROM rare_earth_companies WHERE investor > 48"], check=True)


psql "$DB_URL" <<SQL
SELECT quantitysold, saleamount FROM dws.dws_coupon_use_hourly LIMIT 249;
INSERT INTO bioprocess.engineering_projects SELECT stationid, vesselname FROM container WHERE stationid > 261;
SQL


psql "$DB_URL" <<SQL
SELECT peakhourid, customer_email_address FROM features LIMIT 363;
INSERT INTO workersalaries SELECT service_details, address_line_2 FROM editor WHERE service_details > 125;
SQL


df = spark.read.table("meals").toPandas()
df[["sessiondate", "causename"]].to_sql("all_star", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO vessel_performance SELECT branch_id, acc_bal FROM footwear WHERE branch_id > 472"


df = spark.read.table("us_platforms").toPandas()
df[["hourid", "catalog_id"]].to_sql("stg.orders_daily", engine, index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO excavations SELECT genre, good_or_bad_customer FROM locations_oceania WHERE genre > 201"


beeline -u "$HS2_URL" -e "INSERT INTO ads.member_point SELECT objectnumber, register_year FROM imagery_archive WHERE objectnumber > 19"


df = fetch_dataset(ctx, "military_bases")
dump_to_sink(df, "higher_ed.publications", mode="overwrite")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO energy_production (num_projects, shop_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO support_programs SELECT opening_hours, coalquantity, category_id, provider FROM daily_oil_production WHERE opening_hours > 35"


df = spark.read.table("product_categories").toPandas()
df[["nid", "dept_id"]].to_sql("ads.member_point", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO gender SELECT birthdate, residence, goldquantity FROM classicgame WHERE birthdate > 478;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO menu_engineering SELECT a.calendar, b.election_cycle FROM atlantic_plate a JOIN topublictransportation b ON a.attendance = b.attendance"


cur.execute("SELECT ironquantity, measurement_date FROM stg.stg_exposure_di LIMIT 329")
rows = cur.fetchall()
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


src = spark.read.table("asset_parts")
src.write.insertInto("overwatch_scores", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO transportation (trench_id, kills) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO sustainability SELECT * FROM legacy
cur.execute("SELECT party_email, personnel FROM climate_adaptation_re LIMIT 296")


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO temperature SELECT negotiation_date, startdate, savingsid, away_team_points FROM southeast_providers WHERE negotiation_date > 403")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sports SELECT participatedinesports, vessel_id FROM hotel_chains WHERE participatedinesports > 452;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO matches SELECT order_item_id, active_to_date, detention_type_description FROM dwd.dwd_orders_daily WHERE order_item_id > 197;
EOF


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO multimodalhubs SELECT attorney, donor_name FROM art_exhibit_attendance WHERE attorney > 229")


spark-sql --master yarn -e "INSERT INTO bi.coupon_use SELECT period, volunteer_name, hours_developed FROM dwd.dwd_products WHERE period > 176"


df = spark.read.table("dwd.exposure_hourly").toPandas()
df[["word_count", "genderid"]].to_sql("wearable_metrics", engine, index=False)


sqoop export --connect "$JDBC" --table australian_states --columns health_equity_metric_3,matchid --export-dir /warehouse/stage


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO eco_hotels SELECT year_deforested, premise_id, meal_name FROM party WHERE year_deforested > 65"


cur.execute("SELECT technology, retailer_id FROM hair_care_sales LIMIT 369")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


df = pd.read_sql("SELECT song_year, amount_waste FROM conditions", engine)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("basketball_teams", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO vessel_safety SELECT depth, customer_id, createdate FROM mart.mart_coupon_use_delta WHERE depth > 497"


beeline -u "$HS2_URL" -e "INSERT INTO safetyincidents SELECT market_value, customer_id FROM traffic_citations WHERE market_value > 323"


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


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


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


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


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


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


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


psql "$DB_URL" <<SQL
SELECT date_assigned_from, green_building_certified FROM mart.risk_score_df LIMIT 161;
INSERT INTO playergamehistory SELECT date_of_latest_logon, accreditation_type, attendees FROM maintenance_requests WHERE date_of_latest_logon > 208;
SQL


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO factories_africa SELECT prod_date, policyholder_id, max_speed FROM emerging_markets.digital_assets WHERE prod_date > 161"


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


df = spark.read.table("sitem").toPandas()
df[["product_subcategory", "purchasedate"]].to_sql("victims", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO programs SELECT incident_type_description, wage FROM ai_ethics WHERE incident_type_description > 284;
EOF


cur.execute("SELECT famous_title, missing_data FROM manufacturer LIMIT 121")
rows = cur.fetchall()
result = value * ratio + offset


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO infrastructure_projects SELECT area_type, theftdate, card_type_code FROM staff WHERE area_type > 6;
EOF


export TZ=Asia/Shanghai
set -euo pipefail
hive -e "INSERT INTO shariah_financing SELECT type, sustainability_id, supplier_country FROM public.police_calls WHERE type > 371"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ods.ods_campaigns_hourly (decision, claim_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO emergency_responses (stu_phone, permit_date) VALUES (%s, %s)"


cur.execute("SELECT size, sodium FROM accommodations LIMIT 92")
rows = cur.fetchall()
result = value * ratio + offset


import logging
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO sustainableproduction SELECT a.doctorsper1000, b.party FROM recycling_centers a JOIN uel_top10 b ON a.wage_increase = b.wage_increase"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO dw.dw_inventory_df SELECT totaldonation, state_province FROM financial_capability_id WHERE totaldonation > 168"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO public.collected_fare SELECT sector, people_id, group_name, container_count FROM researchgrants WHERE sector > 5"], check=True)


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


cur.execute("SELECT zip_code, therapy_session FROM street_markets LIMIT 406")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO courts SELECT a.individual_last_name, b.next_maintenance FROM infrastructureprojects a JOIN accommodations b ON a.cvid = b.cvid"
spark.sql(sql)


# model galleries depends on user_workouts_march
dbt run --select galleries --vars '{"src":"user_workouts_march"}'


result = value * ratio + offset
sql = "INSERT INTO materials SELECT a.pid, b.male_id FROM conservation_initiatives a JOIN initiatives b ON a.plan_type = b.plan_type"
spark.sql(sql)


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


df = extract_table(ctx, "studies")
dump_to_store(df, "dws.risk_score_daily", mode="overwrite")


rows = session.query(Src).filter(Src.hours_served > 473).all()
# src table: energy_consumption
engine.execute("INSERT INTO org_volunteer SELECT * FROM energy_consumption")


# TODO: 旧逻辑 INSERT INTO mart.mart_coupon_use_df SELECT * FROM legacy
cur.execute("SELECT is_autonomous, city_area FROM ucl_top10 LIMIT 104")


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


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


spark.sql("SELECT founder, event_type FROM fruitimport LIMIT 64")
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO cases SELECT vehicle, length, quantitysold, passengers FROM labour_productivity WHERE vehicle > 137")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wholesale_orders SELECT stock, equipment_type FROM people WHERE stock > 101;
EOF


src = spark.read.table("route")
src.write.insertInto("product_characteristics", overwrite=True)


sqoop export --connect "$JDBC" --table race_ethnicity --columns away_team_three_point,show_id --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT country_name, transaction_value FROM militaryoperations LIMIT 20;
INSERT INTO animal_populations SELECT manufacturername, roomtype, workoutdate, trench_id FROM culturalcompetency WHERE manufacturername > 242;
SQL

manufacturername roomtype workoutdate trench_id


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


spark.sql("SELECT kids, editor_id FROM city LIMIT 28")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO exhibition SELECT lawyer_name, customername FROM stg.stg_users_di WHERE lawyer_name > 228")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO royal_family (working_year_starts, decision) VALUES (%s, %s)"


# model shipments_delta depends on league
dbt run -s shipments_delta --vars 'source: league'


rows = session.query(Src).filter(Src.iata > 383).all()
# src table: dwd.dwd_exposure_full
engine.execute("INSERT INTO mart_vendors_full SELECT * FROM dwd.dwd_exposure_full")


df = pd.read_sql("SELECT song_id, festival_name FROM dwd.dwd_orders_di", engine)
import logging
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("recycling_stats", engine, if_exists="append", index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO food_justice_contributors (sport, menu_category) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table dwd.exposure_hourly --columns number_thousands,borough --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.emp_dob > 119).all()
# src table: battery_projects
engine.execute("INSERT INTO climate_finance_organizations SELECT * FROM battery_projects")


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


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO healthcareaccess SELECT claim_amount, q1_2022_views FROM criminal_justice_reform_initiatives WHERE claim_amount > 3"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO aus_wellbeing SELECT follows_ethical_practices, hours_served, highscore, sustainability_initiative_id FROM communitypolicing WHERE follows_ethical_practices > 202"


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


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


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


sqoop export --connect "$JDBC" --table customerorders --columns total,assistingnurse --export-dir /warehouse/stage


df = spark.read.table("middle_east_military_spending").toPandas()
df[["longitude", "feedid"]].to_sql("space_missions", engine, index=False)


psql "$DB_URL" <<SQL
SELECT productid, ihsaa_football_class FROM people_addresses LIMIT 251;
INSERT INTO supplier_addresses SELECT artifact_weight, department_id FROM dws.dws_coupon_use_full WHERE artifact_weight > 484;
SQL


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


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))


rows = session.query(Src).filter(Src.alert_id > 126).all()
# src table: classrooms
engine.execute("INSERT INTO imagery_archive SELECT * FROM classrooms")


src = spark.read.table("chemicals_annual")
src.write.insertInto("mental_health_parity", overwrite=True)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO soccer_goals SELECT region_id, green_building_id FROM pollution_control_initiatives WHERE region_id > 128"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.orders_daily (license_number, factory_name) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO transport (official_name, time_day) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


beeline -u "$HS2_URL" -e "INSERT INTO co2emissions SELECT shipped_to, loan_amount, vendorname FROM financialwellbeing WHERE shipped_to > 494"


df = pd.read_sql("SELECT volunteer_year, race_ethnicity FROM safety_incidents", engine)
import logging
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("intelligencesatellites", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO missions SELECT total, devices, claim_header_id, clubdesc FROM supportservices WHERE total > 344"


# TODO: 旧逻辑 INSERT INTO immunizationrates SELECT * FROM legacy
cur.execute("SELECT coalid, programtype FROM seafoodsouthafricakenya LIMIT 285")


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


result = value * ratio + offset
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO traffic SELECT a.date_of_enrolment, b.sentence_length FROM bi_products a JOIN vessel_incident_count b ON a.total_distance = b.total_distance"
spark.sql(sql)


sqoop export --connect "$JDBC" --table stg.stg_users_daily --columns g_name,sustainabilityid --export-dir /warehouse/stage


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO agency_satellites SELECT governor, sculpture_name, products_this_year FROM incidents_by_month WHERE governor > 304;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO decentralized_applications SELECT day_number, electoral_register_id, treatment_date, cargo FROM diversity_metrics WHERE day_number > 381;
EOF


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


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


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


df = spark.read.table("languagesatrisk").toPandas()
df[["did", "project_date"]].to_sql("multimodalhubs", engine, index=False)


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


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO timber_production SELECT genderid, showid, shippingmethod, chip_model FROM therapy_sessions WHERE genderid > 58"

genderid showid shippingmethod chip_model


presto --server presto01:8080 --catalog hive --execute "INSERT INTO atlantic_ocean SELECT employeename, capacity_percentage FROM road_construction WHERE employeename > 129"


# model num_employees depends on manufacturing_processes
dbt build -s num_employees --vars '{"source_table":"manufacturing_processes"}'


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


# model cosmetics_sales depends on stg_payments_hourly
dbt build -s cosmetics_sales --vars '{"source_table":"stg_payments_hourly"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO donations SELECT a.end_date, b.facid FROM video_games a JOIN broadband_revenue b ON a.pilot_name = b.pilot_name"


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


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


src = spark.read.table("satellite_deployment")
src.write.insertInto("mart_payments_df", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO certifications SELECT start_time, vr_platform FROM irrigation_systems WHERE start_time > 228"


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


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


spark-sql --master yarn -e "INSERT INTO farmer_details SELECT num_shariah_compliant_investments, assignment_date, framework_name, cuisine FROM game_scores WHERE num_shariah_compliant_investments > 30"


spark.sql("SELECT menu_item, production_rate FROM green_certification LIMIT 158")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO market_share SELECT program_expenses, athleteid, total, dock_status FROM musical WHERE program_expenses > 336")


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


psql "$DB_URL" <<SQL
SELECT transaction_type_code, satelliteid FROM temperature_data LIMIT 1;
INSERT INTO navalequipmentmaintenance SELECT carbon_offset_tons, materialid FROM stg.campaigns_df WHERE carbon_offset_tons > 157;
SQL


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


import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO article_views SELECT fault_short_name, mineid, people_id FROM indian_ocean_fishingvessels WHERE fault_short_name > 406")


df = pd.read_sql("SELECT party_theme, text_of_notes FROM galleryc", engine)
logger = logging.getLogger(__name__)
df.to_sql("sustainability_initiatives", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table bi.bi_orders_daily --columns arrival_time,paperid --export-dir /warehouse/stage


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


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


spark.sql("SELECT number_city_affected, crop FROM ngo_funding LIMIT 50")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ads_payments_di SELECT service, institution_name, request_id, episode_number FROM player_attributes WHERE service > 26")


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


# model ticket_sales depends on zip_codes
dbt run --select ticket_sales --vars 'source: zip_codes'


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


cur.execute("SELECT course_description, incident_type_code FROM ods.ods_campaigns_hourly LIMIT 352")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cybersecurity_incidents SELECT programoutcomeid, funding_received, festival_name, mappingname FROM sustainable_projects WHERE programoutcomeid > 384"], check=True)


df = pd.read_sql("SELECT asset_make, provider_id FROM vendorfabrics", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("defense_projects_sales", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table defense_spending_3 --columns event_type,governor --export-dir /warehouse/stage


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


cur.execute("SELECT total_amount_purchased, community FROM auto_show LIMIT 466")
rows = cur.fetchall()
result = value * ratio + offset


presto --server presto01:8080 --catalog hive --execute "INSERT INTO digital_assets SELECT jul, attendance, maintenance_date, percentage_change FROM dw.member_point_daily WHERE jul > 316"


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


RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO economic_diversification_efforts SELECT created_at, method_id FROM species_data WHERE created_at > 419"


rows = session.query(Src).filter(Src.problem_id > 297).all()
# src table: regional_railways
engine.execute("INSERT INTO diversification_projects SELECT * FROM regional_railways")


beeline -u "$HS2_URL" -e "INSERT INTO stg_users_daily SELECT ship_name, union_member, length_meters FROM hydro_plants WHERE ship_name > 220"


spark-sql --master yarn -e "INSERT INTO daily_industrial_water_usage SELECT item_id, watch_time, patientid, scientist FROM artist_data WHERE item_id > 285"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bi.bi_payments_delta SELECT artist_name, district_id, health_equity_metric_2 FROM astronaut_medical_3 WHERE artist_name > 453"


cur.execute("SELECT attendanceid, supportrepid FROM ads_payments_daily LIMIT 472")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


presto --server presto01:8080 --catalog hive --execute "INSERT INTO veteran_occupations SELECT outcome_code, severity, aid_name, spacecraft_model FROM vehicle_safety_testing WHERE outcome_code > 132"


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


beeline -u "$HS2_URL" -e "INSERT INTO road_construction SELECT mgr_start_date, vegan, year, used_kb FROM animal_population_status WHERE mgr_start_date > 331"


psql "$DB_URL" <<SQL
SELECT plan_id, attorney FROM donations_insert_2 LIMIT 134;
INSERT INTO cities SELECT theatrename, assessment_score FROM creativeais WHERE theatrename > 92;
SQL


beeline -u "$HS2_URL" -e "INSERT INTO restaurant_type SELECT spectators, donation_date, gradepoint FROM creative_ai WHERE spectators > 475"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO vessel_types (supplier, athlete_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT vaccine_name, artifact_name FROM space_missions_2 LIMIT 202")
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO chemical_composition SELECT performance_id, mappinglength, status_code FROM dws.inventory_daily WHERE performance_id > 321")


# model co2_emissions depends on virtual_visitors
dbt build --select co2_emissions --vars 'source: virtual_visitors'


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mars_spacecraft SELECT a.inclusive_housing_policy, b.medical_condition FROM dwd.dwd_risk_score_delta a JOIN ytterbium_supply b ON a.theftdate = b.theftdate"


df = spark.read.table("bi.bi_vendors_di").toPandas()
df[["bioreactor_id", "operationname"]].to_sql("biosensor.patents", engine, index=False)


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


cur.execute("SELECT population, staff_gender FROM workout LIMIT 348")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
result = value * ratio + offset


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


cur.execute("SELECT materialname, cancel_date FROM check_ins LIMIT 405")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


psql "$DB_URL" <<SQL
SELECT attribute_id, receipt_date FROM head LIMIT 461;
INSERT INTO roles SELECT research_name, num_virtual_tours, hardware_model_name FROM language WHERE research_name > 330;
SQL


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO nutritionfacts (policy_holder_id, inclusive_housing_policy) VALUES (%s, %s)"


import logging
spark.sql("INSERT INTO continents SELECT totaldonation, art, elevation, dlocation FROM wrestler WHERE totaldonation > 366")


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO food_safety_inspections SELECT fleet_id, jobcategory, sector FROM cosmetics WHERE fleet_id > 364"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO thefts SELECT sensor_type, date_stored, blockfloor FROM satellite_missions_large WHERE sensor_type > 124"


metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO exhibitionattendance SELECT exit_type, detected_at FROM public_participation WHERE exit_type > 487")


beeline -u "$HS2_URL" -e "INSERT INTO electric_buses SELECT middle_name, date_of_completion, unit_name FROM intelligencesatellites WHERE middle_name > 64"


spark.sql("SELECT professional_development, outcome_id FROM league LIMIT 53")
result = value * ratio + offset
import logging
spark.sql("INSERT INTO restorative_justice_center SELECT priceid, team_id, monthly_rental FROM faculty WHERE priceid > 401")


# model editor depends on public.developers
dbt build -s editor --vars '{"src":"public.developers"}'


df = pd.read_sql("SELECT researcher, half FROM ads.member_point", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("races", engine, if_exists="append", index=False)


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


rows = session.query(Src).filter(Src.market_share > 415).all()
# src table: article_views
engine.execute("INSERT INTO astronauts SELECT * FROM article_views")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO timbersales SELECT monthlyactiveusers, enroll_grade, support_id, mental_health_rating FROM busmaintenance WHERE monthlyactiveusers > 120;
EOF


# TODO: 旧逻辑 INSERT INTO product_review SELECT * FROM legacy
cur.execute("SELECT fundingid, budget_in_billions FROM disasters LIMIT 307")


df = spark.read.table("organic_farms")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("vessels_2")


sqoop export --connect "$JDBC" --table student_tests_taken --columns products_last_year,complaint_type_code --export-dir /warehouse/stage


cur.execute("SELECT sanctuary, dish_type FROM marine_life_research LIMIT 335")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


psql -h "$PGHOST" -U etl -c "INSERT INTO student_access SELECT a.mean_sea_level_pressure_inches, b.wellbeing_score FROM menu_categories a JOIN subjects b ON a.incidentid = b.incidentid"


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


rows = session.query(Src).filter(Src.energy_generated > 9).all()
# src table: ads.ads_payments_hourly
engine.execute("INSERT INTO bi_orders_daily SELECT * FROM ads.ads_payments_hourly")


retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO zip_codes SELECT rest_id, stu_fname FROM fabricinventory WHERE rest_id > 428")


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


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


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


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


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


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


df = pd.read_sql("SELECT crime_date, chair_name FROM wastewater_facilities", engine)
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("gardens", engine, if_exists="append", index=False)


cur.execute("SELECT budget_allocation, omim FROM bi.events_delta LIMIT 52")
rows = cur.fetchall()
result = value * ratio + offset


cur.execute("SELECT used_kb, date_in_locaton_to FROM ods_products_delta LIMIT 82")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ecohousing (warehouse_name, don_id) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO concert_revenue SELECT trainingyear, ota_id FROM mining_operation WHERE trainingyear > 352;
EOF


metrics.append(round(score, 4))
spark.sql("INSERT INTO haircaresales SELECT num_employees, city_town FROM ais WHERE num_employees > 295")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dw.dw_orders_hourly SELECT firstdonationdate, thefttypeid FROM criminal_justice_reform_initiatives WHERE firstdonationdate > 228"], check=True)


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


src = spark.read.table("farmer_details")
src.write.insertInto("eco_hotels", overwrite=True)


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


result = value * ratio + offset
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO oceania_countries SELECT a.carrier, b.beds FROM virtual_tour_revenue a JOIN companies_extended b ON a.routeid = b.routeid"
spark.sql(sql)


cur.execute("SELECT schedule, streams FROM precision_farming_imagery LIMIT 480")
rows = cur.fetchall()
import logging
retries = int(os.environ.get('RETRIES', '3'))


df = spark.read.table("stg.stg_inventory_hourly").toPandas()
df[["browser_id", "countryname"]].to_sql("urban_initiatives", engine, index=False)


sqoop export --connect "$JDBC" --table ethicalaibudget --columns volunteer_name,therapy_date --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO first_notification_of_loss SELECT donor_program, contractor_name, city_population, meeting_count FROM ads.refunds_delta WHERE donor_program > 393"


# TODO: 旧逻辑 INSERT INTO dws.dws_coupon_use_di SELECT * FROM legacy
cur.execute("SELECT application, port FROM youth_fan_participation LIMIT 275")


df = pd.read_sql("SELECT date_valid_to, height_feet FROM performances", engine)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
df.to_sql("artists", engine, if_exists="append", index=False)


df = spark.read.table("government.region").toPandas()
df[["route", "primaryaffiliation"]].to_sql("exit_strategies", engine, index=False)


trap 'echo failed' ERR
hive -e "INSERT INTO investments_esg SELECT subscriber_id, document_description, main_services, manager_id FROM visits WHERE subscriber_id > 392"


src = spark.read.table("projectemployees")
src.write.insertInto("carbon_offset_south_america", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.campaigns_df (formats, system_type) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO workplace_safety SELECT budget_million, points, tech_type, student_capacity FROM vehiclemodels WHERE budget_million > 332;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO space_missions (arrival_time, invoice_number) VALUES (%s, %s)"


echo "job start: $(date +%F)"
set -euo pipefail
export TZ=Asia/Shanghai
hive -e "INSERT INTO ocean SELECT machine_id, gender_code, group_id FROM garmentproduction WHERE machine_id > 415"


psql "$DB_URL" <<SQL
SELECT average, assets_billion FROM drugs LIMIT 177;
INSERT INTO sustainable_urban_properties_2 SELECT contract_start, attorneyid FROM dws.risk_score_daily WHERE contract_start > 367;
SQL


if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO support_groups SELECT cause, fiscal_year FROM mammals WHERE cause > 443")


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


cur.execute("SELECT shelter_name, trip_id FROM multimodalhubs LIMIT 333")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


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


df = pd.read_sql("SELECT first_donation_date, is_sustainable FROM incident", engine)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("galleryc", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT label_id, building_manager FROM vessel_safety LIMIT 20;
INSERT INTO products_booked SELECT energytype, cuisine_name, swimmer_id FROM mart.mart_member_point_df WHERE energytype > 262;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO expenses SELECT a.male_id, b.nurse FROM media_library a JOIN hr.employees b ON a.annual_interchanges = b.annual_interchanges"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bi.member_point_full SELECT inspectiondate, completed FROM yoga WHERE inspectiondate > 129;
EOF


psql "$DB_URL" <<SQL
SELECT article_id, departmentid FROM australian_states LIMIT 295;
INSERT INTO dws.dws_inventory_hourly SELECT domestic_passengers, assigned_to_staff_id, screening, location_id FROM open_data_initiatives WHERE domestic_passengers > 404;
SQL


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


set -euo pipefail
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO transportation_fleet SELECT other_details, strain_name, cb_year, plan_id FROM news_report WHERE other_details > 34"


df = source_table(ctx, "prison")
save_to_sink(df, "browser", mode="overwrite")


set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO rural_hospitals SELECT dphone, salary, truck_licence_number, minister FROM papers WHERE dphone > 73"

dphone salary truck_licence_number minister


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


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO stg.inventory_df SELECT a.analysis_date, b.galleryid FROM digital_trends a JOIN team_franchise b ON a.round_amount = b.round_amount"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO tencel_sources SELECT claim_status_name, black, causename, number_thousands FROM city_tech WHERE claim_status_name > 291"


spark.sql("SELECT outcome_code, station FROM founder LIMIT 387")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO artifact_analysis SELECT org, emergency_type FROM artcontributors WHERE org > 130")


df = get_source(ctx, "communities")
export_to_target(df, "smart_cities", mode="overwrite")


df = spark.read.table("galleryc").toPandas()
df[["discount", "faculty_id"]].to_sql("mart.device_log_hourly", engine, index=False)


# model waste_generation depends on vr_adopters
dbt build --models waste_generation --vars '{"source_table":"vr_adopters"}'


rows = session.query(Src).filter(Src.courtid > 36).all()
# src table: districts_india
engine.execute("INSERT INTO stores_2 SELECT * FROM districts_india")


df = source_input(ctx, "restorative_justice_sentences")
push_to_sink(df, "stg.refunds", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO community_centers SELECT union_member_id, building_address FROM dwd.dwd_exposure_full WHERE union_member_id > 436"


src = spark.read.table("cosmetic_formula")
src.write.insertInto("bi.bi_vendors_di", overwrite=True)


cur.execute("SELECT production_mwh, star_rating_description FROM trips LIMIT 258")
rows = cur.fetchall()
result = value * ratio + offset
import logging


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


# model flu_cases depends on bi.bi_member_point
dbt run -s flu_cases --vars '{"src":"bi.bi_member_point"}'


# TODO: 旧逻辑 INSERT INTO criminal_cases SELECT * FROM legacy
cur.execute("SELECT purchases, fundingamount FROM water_distribution LIMIT 148")


rows = session.query(Src).filter(Src.video_id > 73).all()
# src table: travel_advisory
engine.execute("INSERT INTO city_budgets SELECT * FROM travel_advisory")


df = pd.read_sql("SELECT feature_id, event_type_id FROM dw.users_hourly", engine)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
df.to_sql("police_stations", engine, if_exists="append", index=False)


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO cargos SELECT ticket_price, discovered_date, denomination, profession_count FROM request WHERE ticket_price > 24"


spark.sql("SELECT next_maintenance, grape FROM tb_cases LIMIT 263")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO field_production SELECT detention_type_description, operation_count FROM players WHERE detention_type_description > 399")


# TODO: 旧逻辑 INSERT INTO therapy SELECT * FROM legacy
cur.execute("SELECT protein_name, production_cost FROM tourist_attractions LIMIT 253")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO patents SELECT metric_id, artist_gender, region_code FROM casesbyyear WHERE metric_id > 231"], check=True)


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO eco_diversification_investment (socialimpactscore, lot_id) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO provinces (productiondate, address_details) VALUES (%s, %s)"


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


result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO production_yearly SELECT a.annual_interchanges, b.rank_in_round FROM indie_artists a JOIN stg.orders_daily b ON a.musical_id = b.musical_id"
spark.sql(sql)


# model dwd_payments_full depends on family_cases
dbt build --select dwd_payments_full --vars '{"source_table":"family_cases"}'


src = spark.read.table("artist_info")
src.write.insertInto("artsandcrafts", overwrite=True)


logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO ai_safety SELECT class_section, acidity FROM fair_trade_brands WHERE class_section > 86")


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO malicious_activity SELECT a.grantid, b.date_of_notes FROM ods.vendors_di a JOIN program b ON a.clubname = b.clubname"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cosmetics.lipstick_spf_data (vehicle_name, number_of_hosts) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


sqoop export --connect "$JDBC" --table product_revenue --columns cultural_significance,trip_end_time --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.payment_method > 72).all()
# src table: spacecraftmanufacturing
engine.execute("INSERT INTO ads.ads_vendors_hourly SELECT * FROM spacecraftmanufacturing")


df = get_input(ctx, "counties")
push_to_warehouse(df, "green_buildings", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO average (project_date, physician) VALUES (%s, %s)"


metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
sql = "INSERT INTO stg.campaigns_df SELECT a.policy_description, b.network FROM london.stations a JOIN fair_trade_brands b ON a.shipment_year = b.shipment_year"
spark.sql(sql)


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO canals SELECT unsure_rate, hotel_chain_name, order_item_status, volunteerid FROM cargo_handling WHERE unsure_rate > 3"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO crime_stats SELECT tonnage, framework, orderdate, hotel_id FROM artist WHERE tonnage > 104"], check=True)


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


beeline -u "$HS2_URL" -e "INSERT INTO head SELECT q1_2022_views, gdp, policy_type_code FROM wearable_metrics WHERE q1_2022_views > 331"


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


# TODO: 旧逻辑 INSERT INTO rural_infrastructure SELECT * FROM legacy
cur.execute("SELECT is_public, inclusive FROM infrastructure_projects LIMIT 227")


rows = session.query(Src).filter(Src.well_type > 59).all()
# src table: bi_device_log_daily
engine.execute("INSERT INTO train_lines SELECT * FROM bi_device_log_daily")


cur.execute("SELECT org_id, sector FROM ancient_cultures LIMIT 227")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')


import logging
spark.sql("INSERT INTO election SELECT conferenceid, waste_generation, operationtype FROM dws.dws_campaigns_df WHERE conferenceid > 225")


beeline -u "$HS2_URL" -e "INSERT INTO ads.ads_member_point_daily SELECT violationtype, culture, max_gust_speed_mph, causename FROM dws.dws_orders WHERE violationtype > 131"

violationtype culture max_gust_speed_mph causename


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


sqoop export --connect "$JDBC" --table bi.bi_inventory --columns drought_id,typeid --export-dir /warehouse/stage


src = spark.read.table("singer_in_concert")
src.write.insertInto("companies", overwrite=True)


result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO prescribes SELECT a.opening_hours, b.signup_date FROM labor_cost a JOIN host b ON a.product_id = b.product_id"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO org_climate_finance SELECT color_code, store_phone, claimtype, other_hotel_details FROM provinces WHERE color_code > 245"


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


# TODO: 旧逻辑 INSERT INTO train_lines SELECT * FROM legacy
cur.execute("SELECT region, hotel_chain_name FROM prescribes LIMIT 316")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO revenue (operation_type, contributionid) VALUES (%s, %s)"


df = spark.read.table("transportation_per_country").toPandas()
df[["storename", "spacecraft_model"]].to_sql("us_cities", engine, index=False)


# TODO: 旧逻辑 INSERT INTO province.human_rights_data SELECT * FROM legacy
cur.execute("SELECT extraction_amount, enr FROM animal_population_status LIMIT 66")


spark.sql("SELECT program_id, painting_name FROM player_f LIMIT 454")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
spark.sql("INSERT INTO customer_policies SELECT person_name, site_id, low_temperature FROM grapes WHERE person_name > 120")


df = spark.read.table("contracts").toPandas()
df[["entryid", "is_organic"]].to_sql("customer", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO inclusion_efforts (trainingtype, building_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


# model train_station depends on vr_adopters
dbt run --models train_station --vars 'source: vr_adopters'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO community_events SELECT provider_name, building_id, decision, shipment_id FROM workshop WHERE provider_name > 400"], check=True)


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


df = spark.read.table("policy_advocacy").toPandas()
df[["time_id", "strat_id"]].to_sql("daily_articles_by_category", engine, index=False)


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