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


spark.sql("SELECT passengers, treatment_id FROM forestry_practices LIMIT 166")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO jupiter_spacecraft SELECT produceid, login_name, completion_date FROM dwd.dwd_orders_daily WHERE produceid > 260")


src = spark.read.table("stg.risk_score_di")
src.write.insertInto("project_duration", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO disabilityadvocacy (hotel_name, name_full) VALUES (%s, %s)"


df = pd.read_sql("SELECT floor_exercise_points, watch_time FROM libraries", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("indie_artists", engine, if_exists="append", index=False)


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


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


sqoop export --connect "$JDBC" --table medicine --columns content_id,commodity --export-dir /warehouse/stage


df = source_frame(ctx, "stg.stg_events_hourly")
save_to_output(df, "articles_es", mode="overwrite")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO status SELECT a.attraction_type_description, b.faculty FROM communityengagement a JOIN solana_transactions b ON a.other_item_details = b.other_item_details"


df = source_frame(ctx, "carbon_prices")
sink_to_store(df, "perpetrator", mode="overwrite")


cur.execute("SELECT sessiondate, ironid FROM ads_exposure_hourly LIMIT 133")
rows = cur.fetchall()
result = value * ratio + offset


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


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


spark-sql --master yarn -e "INSERT INTO explainable_ai SELECT wins, satellite FROM prison WHERE wins > 240"


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


spark-sql --master yarn -e "INSERT INTO eu_humanitarian_assistance SELECT safety_record, away_team_three_point FROM safety_incidents WHERE safety_record > 76"


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


psql "$DB_URL" <<SQL
SELECT acc_regular_season, port_code FROM community_events LIMIT 301;
INSERT INTO ads.orders_daily SELECT end_station_id, classroom, exit_strategy FROM student WHERE end_station_id > 327;
SQL


df = pd.read_sql("SELECT attraction_name, registered_date FROM bustrips", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("casesbyyear", engine, if_exists="append", index=False)


cur.execute("SELECT community, tree_id FROM donation LIMIT 223")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


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


spark-sql --master yarn -e "INSERT INTO soccer_teams SELECT category_name, policyholderid, museumid, volunteerdate FROM parties WHERE category_name > 353"

category_name policyholderid museumid volunteerdate


# TODO: 旧逻辑 INSERT INTO cultural_competency_training SELECT * FROM legacy
cur.execute("SELECT crop_name, accreditation_level FROM workout_sessions LIMIT 469")


spark.sql("SELECT date_assigned_to, archaeologist_id FROM un_peacekeeping_operations LIMIT 436")
import logging
spark.sql("INSERT INTO athletes SELECT assists, tourist_attraction_id FROM electricvehicleadoption WHERE assists > 477")


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO equipment SELECT era, plantid FROM coal_reserves WHERE era > 391")


# TODO: 旧逻辑 INSERT INTO iron SELECT * FROM legacy
cur.execute("SELECT reported_date, mhw_id FROM manufacturingplants LIMIT 356")


metrics.append(round(score, 4))
sql = "INSERT INTO veteran_employment SELECT a.lifespan, b.sale_date FROM countryintelligenceops a JOIN sales_quarterly b ON a.property_id = b.property_id"
spark.sql(sql)


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


df = pd.read_sql("SELECT passenger_count, date_id FROM waste", engine)
logger = logging.getLogger(__name__)
df.to_sql("scientists", engine, if_exists="append", index=False)


spark.sql("SELECT representative_name, vegetable FROM eu_humanitarian_assistance LIMIT 92")
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO stg.refunds SELECT vessel_name, characteristic_id, school FROM ocean_acidification_antarctic WHERE vessel_name > 17")


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO teams SELECT countid, water_depth, activity_name, account_name FROM stg.sessions_full WHERE countid > 287"


psql -h "$PGHOST" -U etl -c "INSERT INTO ads.payments_di SELECT a.writer, b.destruction_authorised_by_employee_id FROM province.human_rights_data a JOIN ngo_funding b ON a.semester = b.semester"


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


df = spark.read.table("education_programs").toPandas()
df[["consumption", "state_id"]].to_sql("employee", engine, index=False)


logger = logging.getLogger(__name__)
import logging
result = value * ratio + offset
spark.sql("INSERT INTO climate_mitigation_projects SELECT inspection_id, medication FROM mart_cart_item_di WHERE inspection_id > 23")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads SELECT record_id, gender FROM project_timeline WHERE record_id > 239;
EOF


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


# TODO: 旧逻辑 INSERT INTO recreation_centers SELECT * FROM legacy
cur.execute("SELECT meal_id, clean_jerk FROM trip LIMIT 202")


beeline -u "$HS2_URL" -e "INSERT INTO digital_divide_initiatives SELECT snatch, fleet_id, num_sustainable_materials, number_cities FROM marketing_regions WHERE snatch > 250"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO professionals SELECT name_first, kills, build_date FROM bike_stations WHERE name_first > 319;
EOF


sqoop export --connect "$JDBC" --table shariah_compliant_finance --columns accessible,base_id --export-dir /warehouse/stage


trap 'echo failed' ERR
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO playergamedata SELECT number_of_vessels, spacecraft_id, property_id FROM winter_olympics WHERE number_of_vessels > 91"


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


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


df = pd.read_sql("SELECT exhibitionid, platform_id FROM student_tests_taken", engine)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("game_results", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.maintenance_type > 330).all()
# src table: characteristics
engine.execute("INSERT INTO region_stats SELECT * FROM characteristics")


psql -h "$PGHOST" -U etl -c "INSERT INTO iron SELECT a.product_name, b.architect_id FROM energy_efficiency_programs a JOIN storage_projects b ON a.usage = b.usage"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO cyber_incidents SELECT a.other_item_details, b.emp_lname FROM team_members a JOIN streams b ON a.date_in_locaton_to = b.date_in_locaton_to"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO artist SELECT users_engaged, gamegenre, date_incident_end FROM fish_biomass WHERE users_engaged > 346"], check=True)


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


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO status SELECT a.currency, b.feature_id FROM policy_feedback a JOIN sustainable_projects b ON a.num_songs = b.num_songs"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO foodsafetyrecords SELECT avg_depth, emissions FROM vessel_safety WHERE avg_depth > 129"


src = spark.read.table("animal_population_status")
src.write.insertInto("has_amenity", overwrite=True)


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


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


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


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


spark-sql --master yarn -e "INSERT INTO match SELECT ticketprice, uk_vat_number, hoursperweek FROM lessons WHERE ticketprice > 148"


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


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


df = fetch_input(ctx, "safetytestingcounts")
persist_to_sink(df, "threat_intel", mode="overwrite")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO acidification_data (network, severity) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT assessmentdate, actual_order_id FROM bi_refunds_daily LIMIT 492")
retries = int(os.environ.get('RETRIES', '3'))
import logging
result = value * ratio + offset
spark.sql("INSERT INTO sustainability_initiatives SELECT statename, nominee, service_name, coupon_id FROM dorm_amenity WHERE statename > 264")


# TODO: 旧逻辑 INSERT INTO stg.stg_campaigns SELECT * FROM legacy
cur.execute("SELECT subscription_start_date, contractor_id FROM flight_safety LIMIT 471")


df = pd.read_sql("SELECT cmi_cross_ref_id, inspectionid FROM warehouses", engine)
import logging
threshold = cfg.get('threshold', 0.5)
df.to_sql("shared_scooters", engine, if_exists="append", index=False)


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


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


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO ods.ods_exposure_delta SELECT a.join_year, b.trackid FROM mentalhealthproviders a JOIN nailpolishsales b ON a.pass_fail = b.pass_fail"
spark.sql(sql)


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


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


spark.sql("SELECT char_cells, element FROM ref_document_status LIMIT 451")
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO street_markets SELECT gender_mf, location, group_equity_shareholding FROM vr_tech WHERE gender_mf > 424")


psql -h "$PGHOST" -U etl -c "INSERT INTO movie_financials SELECT a.bioreactor_id, b.sustainable_practice FROM ethics_violations a JOIN mart.mart_refunds_di b ON a.visit_month = b.visit_month"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO fair_trade_suppliers (stockid, artworkname) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = read_frame(ctx, "incarcerated")
upsert_to_target(df, "mining_operation_data", mode="overwrite")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.risk_score_df (railway_id, airline) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.bname > 280).all()
# src table: labor_unions
engine.execute("INSERT INTO railway SELECT * FROM labor_unions")


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


echo "dry-run: INSERT INTO restorative_justice_programs SELECT 1"
mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}


df = load_dataset(ctx, "production_rare_earth_elements")
dump_to_target(df, "office_locations", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO trainmaintenance SELECT shop_name, asset_disposed_date, grantid FROM india_ingredient_sourcing WHERE shop_name > 167"], check=True)


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


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


set -euo pipefail
hive -e "INSERT INTO justice_schemas.legal_tech_providers SELECT mine_id, employees, launched_year FROM mart.mart_vendors WHERE mine_id > 280"


df = fetch_dataset(ctx, "rooms")
save_to_sink(df, "leo_missions", mode="overwrite")


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO hospitallocations SELECT form_id, numhearings FROM pilot_record WHERE form_id > 166"


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


df = pd.read_sql("SELECT enr, ingredient FROM ods.ods_risk_score_full", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("player_f", engine, if_exists="append", index=False)


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


src = spark.read.table("dw.clicks_di")
src.write.insertInto("communityhealthworkers", overwrite=True)


spark-sql --master yarn -e "INSERT INTO sustainable_practices_2 SELECT case_id, hospitalname, semester FROM climate_finance WHERE case_id > 43"


rows = session.query(Src).filter(Src.sentence_id > 370).all()
# src table: investor_activities
engine.execute("INSERT INTO service_budget SELECT * FROM investor_activities")


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


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


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


df = spark.read.table("languagesatrisk").toPandas()
df[["carbon_offset_tons", "review_date"]].to_sql("tracklists", engine, index=False)


export TZ=Asia/Shanghai
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO public_participation SELECT oppose_rate, fundingagency FROM shipment_data WHERE oppose_rate > 208"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.ods_coupon_use_delta SELECT releaseyear, claimtype FROM autonomousvehicleaccidents WHERE releaseyear > 288;
EOF


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO review SELECT playerid, mission_name FROM dw.dw_users_di WHERE playerid > 134"], check=True)


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


df = pd.read_sql("SELECT region_id, completed FROM bi.bi_exposure_hourly", engine)
metrics.append(round(score, 4))
df.to_sql("decentralized_applications", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO farmer_details SELECT strainid, incident_type_code, sales_amount, rural_area FROM company WHERE strainid > 245"


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO cargo_data SELECT a.rating_in_percent, b.unit_of_measure FROM levees a JOIN reporters b ON a.percentage_change = b.percentage_change"
spark.sql(sql)


df = spark.read.table("sustainable_warehouses").toPandas()
df[["salesperson", "contract_start"]].to_sql("indian_ocean_wells", engine, index=False)


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))


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


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO mentalhealthproviders SELECT speciesid, rig_id, physical FROM miningoperations WHERE speciesid > 128"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO microfinance_clients SELECT restypedescription, reported_date, county, pressure FROM dysprosium_mines WHERE restypedescription > 373"

restypedescription reported_date county pressure


df = spark.read.table("fish_feed_factories").toPandas()
df[["assists", "start_station_name"]].to_sql("midwest_materials", engine, index=False)


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


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


sqoop export --connect "$JDBC" --table military_personnel --columns environmental_impact_score,opening_year --export-dir /warehouse/stage


spark.sql("SELECT incidentdate, num_volunteers FROM fertilizer LIMIT 382")
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO hotel_chains SELECT coal_reserve_remaining, period, wage, inventoryid FROM concert_revenue WHERE coal_reserve_remaining > 324")

coal_reserve_remaining period wage inventoryid


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_vendors_hourly SELECT safetytestdate, leadershiptraining FROM parties WHERE safetytestdate > 425"


sqoop export --connect "$JDBC" --table atlantic_ocean_fish --columns issue_month,stock --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO incident_region (doctor_id, ticket_id) VALUES (%s, %s)"


spark.sql("SELECT attack_count, class FROM bi.events_df LIMIT 124")
import logging
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO debris SELECT participation_id, communityname, organisation_id, bioprocess_id FROM member_activity WHERE participation_id > 403")


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


rows = session.query(Src).filter(Src.school_code > 168).all()
# src table: economic_diversification_argentina
engine.execute("INSERT INTO materials SELECT * FROM economic_diversification_argentina")


df = spark.read.table("performingartsprograms").toPandas()
df[["training_name", "oil_volume"]].to_sql("researchpapers", engine, index=False)


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


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


set -euo pipefail
echo "job start: $(date +%F)"
trap 'echo failed' ERR
hive -e "INSERT INTO food_justice_contributors SELECT team_id_loser, staff_first_name, match_id, veteran_id FROM workforce_training WHERE team_id_loser > 141"


sqoop export --connect "$JDBC" --table stg.stg_shipments_hourly --columns tourist_id,health_equity_metric_3 --export-dir /warehouse/stage


df = get_source(ctx, "financial_capability_program")
push_to_store(df, "transportation_union", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO parts (ssn, matchdate) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO swimmer SELECT train_number, publication_id FROM donors_region WHERE train_number > 353"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO driver SELECT stu_gpa, lastname, warehousename FROM cybersecurity_incidents WHERE stu_gpa > 373"], check=True)


spark.sql("SELECT pilot_id, classid FROM traffic_accidents LIMIT 416")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO mart.mart_payments_hourly SELECT amount_due, volume FROM product_characteristics WHERE amount_due > 21")


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO tb_reports SELECT response_time, clientid FROM eco_hotels WHERE response_time > 446"


rows = session.query(Src).filter(Src.task > 190).all()
# src table: construction_labor_stats
engine.execute("INSERT INTO seafoodsouthafricakenya SELECT * FROM construction_labor_stats")


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


retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO dws.dws_campaigns_df SELECT a.shale_play, b.prof_office FROM spending a JOIN carbon_prices b ON a.zone_id = b.zone_id"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO exhibition_visits SELECT established_date, leader_name, support_id FROM street_markets WHERE established_date > 259"


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


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


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


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


cur.execute("SELECT aid_id, ticket_price FROM employment LIMIT 36")
rows = cur.fetchall()
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd.dwd_exposure_full SELECT art, airport FROM safetytesting WHERE art > 305;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO forms SELECT a.diversity_score, b.count_date FROM exhibition_record a JOIN dw.inventory_delta b ON a.startup_id = b.startup_id"


sqoop export --connect "$JDBC" --table student_tests_taken --columns gender_code,acc_percent --export-dir /warehouse/stage


cur.execute("SELECT loan_id, country FROM emergency_categories LIMIT 471")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


cur.execute("SELECT ota_name, donor_program FROM monitoring_zones LIMIT 271")
rows = cur.fetchall()
result = value * ratio + offset


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO songs (unit_price, artpiecename) VALUES (%s, %s)"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO patient_outcomes SELECT hotel_chain_name, individual_middle_name, workoutdate, animal_species FROM heart_rate_data WHERE hotel_chain_name > 449")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO biodiversity SELECT sustainability_initiative_id, away_team_id, onscholarship, num_fans FROM tech_accessibility_funding WHERE sustainability_initiative_id > 99;
EOF


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO spaceradar (spacecraft_name, concertid) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = get_source(ctx, "materials")
save_to_output(df, "mart.mart_coupon_use_full", mode="overwrite")


mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO patient SELECT trip_duration, menuitemid, investors, rebounds FROM manufacturer WHERE trip_duration > 422"

trip_duration menuitemid investors rebounds


# model body_builder depends on hotel_revenue
dbt run --select body_builder --vars 'source: hotel_revenue'


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO agricultural_projects SELECT funding_received, crime_rate, treasurer_vote, time_hour FROM caribbeansea WHERE funding_received > 217")


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


spark-sql --master yarn -e "INSERT INTO civilcases SELECT employment_id, collection_id, publication_id, calories FROM dw.shipments_di WHERE employment_id > 287"


result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO collectivebargaining SELECT a.shipmentid, b.engagementid FROM product_details a JOIN courtcases b ON a.organization_id = b.organization_id"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO pediatricians SELECT incident_type, service, directed_by FROM news_stories WHERE incident_type > 185;
EOF


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO apartment_bookings SELECT asset_name, invoice_number FROM forests WHERE asset_name > 377")


beeline -u "$HS2_URL" -e "INSERT INTO mart.mart_member_point_df SELECT customer_email_address, well_depth, ll_hours, materialid FROM news_reporting WHERE customer_email_address > 38"


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


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


df = source_table(ctx, "dw.shipments_di")
sink_to_sink(df, "ads_payments_di", mode="overwrite")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO beverages (item, num_attendees) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = read_source(ctx, "mineral_extraction")
sink_to_target(df, "mining_companies", mode="overwrite")


df = read_source(ctx, "canada_tech")
persist_to_store(df, "policyholders", mode="overwrite")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bi.bi_inventory_full SELECT success, bdate FROM marine_species_indian WHERE success > 300"


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


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


RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO mart.mart_coupon_use_full SELECT communityid, preference_rating, opponent_id, healthcareid FROM ref_budget_codes WHERE communityid > 196"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO hotel_chains SELECT strainname, college_location FROM ads.member_point WHERE strainname > 45"


psql "$DB_URL" <<SQL
SELECT sportname, gas_production_2020 FROM mart.mart_coupon_use_delta LIMIT 132;
INSERT INTO az_drought_impact SELECT total_donation_amount, park, rating_in_percent FROM fertilizer WHERE total_donation_amount > 421;
SQL


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


# model shoes depends on student_courses
dbt run --select shoes --vars 'source: student_courses'


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


trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO temperature_data SELECT product_stock_number, agency, budget_amount, q1_2022_views FROM legislation WHERE product_stock_number > 366"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO claims_processing_stages (pilot, service_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO esports_teams (size, local) VALUES (%s, %s)"


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


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


df = pd.read_sql("SELECT institution_name, contract_type FROM midwest_region", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
df.to_sql("trenches", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO seafoodsouthafricakenya SELECT * FROM legacy
cur.execute("SELECT detection_id, last_year FROM healthequitymetrics LIMIT 277")


sqoop export --connect "$JDBC" --table course_authors_and_tutors --columns steps,ll_activity --export-dir /warehouse/stage


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


psql "$DB_URL" <<SQL
SELECT is_compliant, volunteerdate FROM investment LIMIT 366;
INSERT INTO ai_for_social_good SELECT tickets_sold, patient_id, case_type FROM whale_sightings WHERE tickets_sold > 111;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO navalvessels SELECT is_accessible, installation_year FROM latam_schema.education_budget WHERE is_accessible > 115;
EOF


psql "$DB_URL" <<SQL
SELECT electoral_register_id, attraction_type_code FROM weather LIMIT 347;
INSERT INTO affiliated_with SELECT restaurant, closure_authorised_by_staff_id, plant_name FROM ads.ads_exposure_daily WHERE restaurant > 493;
SQL


cur.execute("SELECT meter_300, neighborhood FROM circular_economy LIMIT 139")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset


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


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO crop_temperature SELECT a.fabricid, b.drug_id FROM goals a JOIN stores b ON a.vaccine_name = b.vaccine_name"
spark.sql(sql)


df = get_frame(ctx, "mine_workforce")
save_to_store(df, "artsales", mode="overwrite")


rows = session.query(Src).filter(Src.volunteername > 218).all()
# src table: classroom
engine.execute("INSERT INTO platformstats SELECT * FROM classroom")


# TODO: 旧逻辑 INSERT INTO languages SELECT * FROM legacy
cur.execute("SELECT attack_date, record_id FROM sportsinfo LIMIT 426")


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


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


sqoop export --connect "$JDBC" --table militaryinnovations --columns meter_100,occupancy_rate --export-dir /warehouse/stage


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


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


psql "$DB_URL" <<SQL
SELECT report_type, response_received_date FROM endowment LIMIT 339;
INSERT INTO stg.cart_item_full SELECT attendee_id, bias_score, winning_aircraft FROM incarcerated WHERE attendee_id > 282;
SQL


spark-sql --master yarn -e "INSERT INTO veteran_employment SELECT occupancy_rate, cost_id, streamid, daily_hire_cost FROM safe_dataset WHERE occupancy_rate > 13"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO total_consumption SELECT hire_date, origin, treasurer_vote, num_projects FROM satellites_in_orbit WHERE hire_date > 450;
EOF


import logging
result = value * ratio + offset
sql = "INSERT INTO evidence_based_policies SELECT a.personnelid, b.segment_id FROM immunization a JOIN stores_2 b ON a.supplier_name = b.supplier_name"
spark.sql(sql)


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO road_construction SELECT temporary_acting, attendees FROM bi_shipments_daily WHERE temporary_acting > 253")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO safetytestingcounts SELECT facid, eco_certified FROM ods.shipments_df WHERE facid > 489;
EOF


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


sqoop export --connect "$JDBC" --table restorative_justice_3 --columns cases_handled,device --export-dir /warehouse/stage


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO irrigation_systems SELECT network, bank_name FROM sustainable_menu_items WHERE network > 193"


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


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ai_ethics_policies SELECT container_id, violation_id, hashtags, coach_name FROM wins WHERE container_id > 271")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO florida_conservation_initiatives SELECT value_points, tournament_id, rainfall, countid FROM libraries WHERE value_points > 378"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO tencel_sources SELECT ssn, account_details, faculty FROM marine_species_indian WHERE ssn > 36;
EOF


cur.execute("SELECT dataset, observation_id FROM financial_capability LIMIT 235")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO taxi_data SELECT coowner_name, claim_status_description, city_area FROM dws.dws_events_df WHERE coowner_name > 430;
EOF


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


df = spark.read.table("bustrips").toPandas()
df[["apt_id", "reason"]].to_sql("africa_projects", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mining_operation_data SELECT loan_id, election_cycle FROM community_policing_events WHERE loan_id > 38"], check=True)


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


metrics.append(round(score, 4))
sql = "INSERT INTO host SELECT a.expertise, b.host_city FROM artifactanalysis a JOIN disinformation_detection b ON a.quality_rank = b.quality_rank"
spark.sql(sql)


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


threshold = cfg.get('threshold', 0.5)
import logging
result = value * ratio + offset
spark.sql("INSERT INTO stg.stg_products_delta SELECT strain, party_name, detection_id FROM infra_diversification WHERE strain > 32")


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


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


src = spark.read.table("school_bus")
src.write.insertInto("gold", overwrite=True)


df = pull_dataset(ctx, "articles_es")
export_to_output(df, "vr_tech", mode="overwrite")


spark.sql("SELECT total, well_type FROM mobile_customers_global LIMIT 298")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO ocean SELECT healthequitymetricscore, individual_last_name, functional_area_code FROM concert_sales WHERE healthequitymetricscore > 352")


df = pull_table(ctx, "cargo_handling")
save_to_store(df, "social_issues", mode="overwrite")


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


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


psql "$DB_URL" <<SQL
SELECT max_aperture, bikes_available FROM bias_categories LIMIT 227;
INSERT INTO invoices SELECT co2_amount, restaurant_name, recycling_rate FROM dorm_amenity WHERE co2_amount > 186;
SQL


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


beeline -u "$HS2_URL" -e "INSERT INTO financial_capability_id SELECT sustainability_rating, university_type, item_name FROM mart.mart_payments_delta WHERE sustainability_rating > 313"


spark-sql --master yarn -e "INSERT INTO cultural_competency_program SELECT artworkid, town_city, round_date, ai_model FROM space_telescopes WHERE artworkid > 151"


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO reservations SELECT a.base_name, b.industry FROM trains a JOIN repair_assignment b ON a.is_valid = b.is_valid"
spark.sql(sql)


df = pd.read_sql("SELECT publisher, stream_id FROM fuel_consumption", engine)
import logging
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
df.to_sql("publicchargingstations", engine, if_exists="append", index=False)


df = spark.read.table("defense_diplomacy").toPandas()
df[["continent_id", "budget_allocated"]].to_sql("military_innovation", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO game_sales SELECT coalquantity, ties, cargoid, team FROM drills WHERE coalquantity > 461"


cur.execute("SELECT image_url, member_name FROM erc20_transactions LIMIT 245")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging
retries = int(os.environ.get('RETRIES', '3'))


spark.sql("SELECT airport_id, sellingprice FROM state_budget LIMIT 161")
result = value * ratio + offset
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO stg.stg_users_di SELECT yield, market_rate FROM researchers WHERE yield > 278")


rows = session.query(Src).filter(Src.cityname > 25).all()
# src table: cybersecurity_vulnerabilities
engine.execute("INSERT INTO inclusivehousingpolicies SELECT * FROM cybersecurity_vulnerabilities")


export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO branch SELECT facid, hiv, population, booking_status_code FROM canals WHERE facid > 443"

facid hiv population booking_status_code


df = spark.read.table("na_schema.hospitals").toPandas()
df[["contractor_name", "contract_number"]].to_sql("crime_incidents", engine, index=False)


# model usdaviolations depends on fault_log
dbt build --select usdaviolations --vars 'source: fault_log'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO org_volunteer (unsure_rate, scooter_id) VALUES (%s, %s)"


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


rows = session.query(Src).filter(Src.production_qty > 189).all()
# src table: financial_transactions
engine.execute("INSERT INTO member SELECT * FROM financial_transactions")


sqoop export --connect "$JDBC" --table bi.bi_campaigns_daily --columns diversity_score,marketing_region_code --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.school > 113).all()
# src table: province.human_rights_data
engine.execute("INSERT INTO city_department SELECT * FROM province.human_rights_data")


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


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


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


import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO ods.ods_sessions_df SELECT a.sportname, b.method_name FROM person a JOIN ads.vendors_delta b ON a.investment = b.investment"
spark.sql(sql)


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


sqoop export --connect "$JDBC" --table communitycourtcases --columns permits_issued,fund_type --export-dir /warehouse/stage


cur.execute("SELECT flight_number, dept_name FROM sustainablebrands LIMIT 250")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
echo "job start: $(date +%F)"
hive -e "INSERT INTO game_sessions SELECT start_date, dates_active FROM community_health_center WHERE start_date > 327"


cur.execute("SELECT profession_count, cinema_id FROM exhibitionattendance LIMIT 334")
rows = cur.fetchall()
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


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


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


# model student_tests_taken depends on clothingitems
dbt run --select student_tests_taken --vars '{"src":"clothingitems"}'


import logging
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO resource_extraction SELECT a.school_id, b.extraction_date FROM stg.campaigns_daily a JOIN bi_products b ON a.policy_holder_id = b.policy_holder_id"
spark.sql(sql)


# model staff_members depends on tourism_activities
dbt build --models staff_members --vars '{"source_table":"tourism_activities"}'


# TODO: 旧逻辑 INSERT INTO bike_station_info SELECT * FROM legacy
cur.execute("SELECT price_in_dollars, mission_date FROM gene LIMIT 222")


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


df = pd.read_sql("SELECT coverage_type, performancedate FROM news_views", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("eco_diversification_investment", engine, if_exists="append", index=False)


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


# TODO: 旧逻辑 INSERT INTO stg.member_point_df SELECT * FROM legacy
cur.execute("SELECT numcases, time_day FROM production_data LIMIT 493")


trap 'echo failed' ERR
hive -e "INSERT INTO dw.inventory_delta SELECT diagnosis, asset_make, approach, accessible FROM degrees WHERE diagnosis > 433"

diagnosis asset_make approach accessible


psql -h "$PGHOST" -U etl -c "INSERT INTO trains SELECT a.vegan, b.completed FROM conservation_initiatives a JOIN mart.mart_coupon_use_full b ON a.track_id = b.track_id"


psql "$DB_URL" <<SQL
SELECT investmentid, retweets FROM farmers LIMIT 88;
INSERT INTO epl_teams SELECT spacecraft_name, quantity_containers, hourdate, organisation_type FROM wastewater_treatment WHERE spacecraft_name > 402;
SQL


metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO heart_rate_data SELECT crime_type, studentid, funding_round_id FROM sustainable_building WHERE crime_type > 152")


df = read_source(ctx, "soccer_goals")
write_to_sink(df, "customer_contact_channels", mode="overwrite")


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


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


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


sqoop export --connect "$JDBC" --table europium_exports --columns form_name,date_opened --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO productsafety SELECT stu_hrs, singer_id FROM community_health_center WHERE stu_hrs > 212"], check=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO aircraft (personnel_id, mean_sea_level_pressure_inches) VALUES (%s, %s)"


df = spark.read.table("defense_contracts_v2").toPandas()
df[["aid_id", "writer"]].to_sql("incarcerated", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO rent_arrears SELECT num_volunteers, class_president_vote FROM pilot_record WHERE num_volunteers > 180"


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


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO products SELECT a.extraction_amount, b.lesson_status_code FROM passenger_trips a JOIN agriculturalinnovations b ON a.order_id = b.order_id"
spark.sql(sql)


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


df = pd.read_sql("SELECT schedule_date, opening_year FROM screen_mode", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("electric_vehicles", engine, if_exists="append", index=False)


spark.sql("SELECT grant_amount, likes FROM students_lifelong_learning LIMIT 94")
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO department_publications SELECT number_of_vessels, coownerid FROM property_community WHERE number_of_vessels > 476")


# model stg_risk_score_df depends on public_participation
dbt run --models stg_risk_score_df --vars 'source: public_participation'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO producersnewmexico (num_cases, domestic_passengers) VALUES (%s, %s)", (uid, amt))
conn.commit()


set -euo pipefail
trap 'echo failed' ERR
hive -e "INSERT INTO ship_agent SELECT other_characteristic_details, transact_count FROM arctic_marine_species WHERE other_characteristic_details > 408"


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO train_station SELECT farm_id, chemical_name, fouls, policyholderid FROM election WHERE farm_id > 262")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO inmates SELECT total_passengers, clubname FROM fabricdata WHERE total_passengers > 405"


threshold = cfg.get('threshold', 0.5)
import logging
result = value * ratio + offset
spark.sql("INSERT INTO industrial_customers SELECT channel, relationship, station_name, institution_id FROM overwatch_scores WHERE channel > 314")


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
sql = "INSERT INTO coowners SELECT a.production_rate, b.state_id FROM education_union a JOIN government.region b ON a.crs_credit = b.crs_credit"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO safety_incidents SELECT join_date, stu_lname, event_id, driverid FROM defense_spending WHERE join_date > 44"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO hospital_visits SELECT num_of_shops, sent_date, artifact_name, offset_id FROM ref_service_types WHERE num_of_shops > 49")


# model project_timeline depends on zip_codes
dbt run -s project_timeline --vars '{"source_table":"zip_codes"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO flights SELECT a.gamepreference, b.game FROM dw.shipments_df a JOIN archaeologists b ON a.post_date = b.post_date"


beeline -u "$HS2_URL" -e "INSERT INTO orgdonations SELECT consultations, ota_id FROM invoice_lines WHERE consultations > 359"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO explainableai (product_stock_number, game) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT name_full, check_in_id FROM farmers_india", engine)
logger = logging.getLogger(__name__)
df.to_sql("concert_sales", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO list SELECT engagement_date, customer_email_address, annual_revenue FROM cosmetics.lipstick_spf_data WHERE engagement_date > 200"


df = pd.read_sql("SELECT date_contact_to, build_date FROM vesselfuel", engine)
import logging
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("cycling", engine, if_exists="append", index=False)


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


spark-sql --master yarn -e "INSERT INTO ods.shipments_df SELECT drugname, acc_bal, initiative_type FROM communitypolicing WHERE drugname > 422"


spark.sql("SELECT college_location, musical_id FROM field_production LIMIT 453")
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO city_waste_generation SELECT total_attendance, country_id, producerid, quantityproduced FROM daily_oil_production WHERE total_attendance > 253")


result = value * ratio + offset
spark.sql("INSERT INTO student_access SELECT inventor_name, strategy_id FROM sales_region WHERE inventor_name > 33")


df = read_source(ctx, "defenseprojects")
persist_to_output(df, "education_union", mode="overwrite")


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


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO artcollection SELECT co2_emission, content_type FROM drug_sales WHERE co2_emission > 311"], check=True)


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


import logging
result = value * ratio + offset
spark.sql("INSERT INTO state_energy SELECT quantityproduced, emission_date, menu_name, ad_type FROM crime_stats WHERE quantityproduced > 392")


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


rows = session.query(Src).filter(Src.product_details > 222).all()
# src table: community_events
engine.execute("INSERT INTO dw.users_hourly SELECT * FROM community_events")


beeline -u "$HS2_URL" -e "INSERT INTO diversity SELECT role_name, operationname, trial_name, sitename FROM riskassessments WHERE role_name > 69"


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


df = extract_frame(ctx, "dwd_sessions_hourly")
dump_to_warehouse(df, "dwd.dwd_campaigns", mode="overwrite")


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO mediatype SELECT low_estimate, percentage_change, opid FROM shariah_financing WHERE low_estimate > 32")


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO vessels SELECT handling_id, factory FROM brandrevenue WHERE handling_id > 482")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO playergamedata (faculty, founder_gender) VALUES (%s, %s)"


cur.execute("SELECT donationyear, volunteer_quarter FROM mart.mart_products_hourly LIMIT 412")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)


# TODO: 旧逻辑 INSERT INTO sustainable_projects SELECT * FROM legacy
cur.execute("SELECT billingid, inclusive_housing_policy FROM military_equipment LIMIT 199")


cur.execute("SELECT pilot_id, crop_name FROM accessible_tech_categories LIMIT 459")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging


# model songs depends on latam_schema.education_budget
dbt build -s songs --vars 'source: latam_schema.education_budget'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO artwork_styles (headquarter, process_id) VALUES (%s, %s)"


df = extract_table(ctx, "communities")
dump_to_output(df, "supplier_ethics", mode="overwrite")


df = pull_frame(ctx, "platformg")
persist_to_output(df, "all_star", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO advisor SELECT a.yield_per_acre, b.purchase_details FROM unesco_intangible_heritage a JOIN electricvehiclestats b ON a.airport_id = b.airport_id"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd.dwd_events_delta SELECT production_rate, dname FROM activities WHERE production_rate > 427;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sustainability SELECT partnership_id, dispensary_name FROM fraud_detections WHERE partnership_id > 318;
EOF


df = spark.read.table("public.forest_stats")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("spacecraft_components")


cur.execute("SELECT pilot_name, visit_month FROM hockey_players LIMIT 6")
rows = cur.fetchall()
result = value * ratio + offset
import logging


presto --server presto01:8080 --catalog hive --execute "INSERT INTO infrastructure SELECT race_ethnicity_id, aid_name, num_pallets FROM state_energy WHERE race_ethnicity_id > 116"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO warehouses (has_spf, electoral_register_id) VALUES (%s, %s)"


cur.execute("SELECT financially_capable, rental_rate FROM certifications LIMIT 213")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


df = spark.read.table("postseason").toPandas()
df[["market_rate", "attraction_type_description"]].to_sql("healthydelights", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO highways SELECT operationname, date_payment_made FROM contract_negotiations_un WHERE operationname > 340;
EOF


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


sqoop export --connect "$JDBC" --table mart.inventory_hourly --columns workers,account_details --export-dir /warehouse/stage


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


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


df = read_table(ctx, "education_programs")
save_to_sink(df, "measurements", mode="overwrite")


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


sqoop export --connect "$JDBC" --table engineer_visits --columns device_id,saleid --export-dir /warehouse/stage


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


df = spark.read.table("contractnegotiations").toPandas()
df[["servicename", "conferencename"]].to_sql("audience_demographics", engine, index=False)


df = pd.read_sql("SELECT date_incident_end, safety_record FROM academic_publications", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("tickets_3", engine, if_exists="append", index=False)


cur.execute("SELECT building_short_name, draft_details FROM daily_production LIMIT 259")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vrusers SELECT state_county, employees, fairness_score, serviceid FROM cultural_events WHERE state_county > 481"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO category_revenue (investor_name, seating) VALUES (%s, %s)"


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


beeline -u "$HS2_URL" -e "INSERT INTO guests SELECT workoutdate, source FROM dorm_amenity WHERE workoutdate > 359"


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO satellite_missions_large SELECT home_games, is_electric, rural_area FROM mart.mart_member_point_df WHERE home_games > 31"], check=True)


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


df = get_table(ctx, "bus_routes")
upsert_to_target(df, "game_sales", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO mine_workforce SELECT playerid, routename, park_id FROM languagesatrisk WHERE playerid > 8"


psql -h "$PGHOST" -U etl -c "INSERT INTO seamounts SELECT a.artist_gender, b.vessel_id FROM dws.cart_item_full a JOIN trends_2022 b ON a.donor = b.donor"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO research_vessels SELECT last_used_bus, hospital_name FROM weather_record WHERE last_used_bus > 110"


df = get_source(ctx, "vocals")
push_to_target(df, "humanitarian_aid", mode="overwrite")


df = spark.read.table("astronaut_medical_3")
tbl = f"dw.tmp_{ds_nodash}"
df.write.saveAsTable(tbl)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dws.dws_orders SELECT dance_form, ei_value, stat_type, virtual_tour_engagement_time FROM jupiter_missions WHERE dance_form > 131"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO restorative_justice_programs SELECT restaurant, technician_id, transact_count FROM chip_model WHERE restaurant > 117"


df = read_input(ctx, "shariah_compliant_finance")
export_to_sink(df, "event_attendance", mode="overwrite")


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


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


echo "dry-run: INSERT INTO carbon_prices_3 SELECT 1"
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
echo "job start: $(date +%F)"


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


src = spark.read.table("wind_energy")
src.write.insertInto("workersalaries", overwrite=True)


# model engineering_projects depends on wind_turbines
dbt run -s engineering_projects --vars '{"source_table":"wind_turbines"}'


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


set -euo pipefail
hive -e "INSERT INTO participation SELECT founder_country, patient_id FROM contract_states WHERE founder_country > 174"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO noise_pollution SELECT a.sessionid, b.cost_id FROM paintings a JOIN ads.payments_di b ON a.vessel = b.vessel"
spark.sql(sql)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO genre SELECT date_payment_made, video_id FROM creative_ai WHERE date_payment_made > 95"


psql -h "$PGHOST" -U etl -c "INSERT INTO energy_storage SELECT a.materialtype, b.observation_date FROM part_faults a JOIN dwd.dwd_payments_full b ON a.carbon_offset_tons = b.carbon_offset_tons"


df = pd.read_sql("SELECT aid_id, frequency FROM cultural_competency_training", engine)
if not rows:
    logger.warning('empty result')
import logging
df.to_sql("ods_shipments_df", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO legal_aid_providers SELECT * FROM legacy
cur.execute("SELECT virtual_tour_views, warehouseid FROM housing_investments LIMIT 492")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dw.dw_member_point_hourly (fan_age, debate_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO noise_pollution SELECT vehicle, credit_score, reported FROM development_hours WHERE vehicle > 400"


df = source_table(ctx, "perpetrator")
dump_to_warehouse(df, "multimodal_trips", mode="overwrite")


sqoop export --connect "$JDBC" --table bi.bi_risk_score_delta --columns rebounds,shipment_id --export-dir /warehouse/stage


result = value * ratio + offset
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO auctions SELECT a.form_type_code, b.is_dessert FROM community_health_center a JOIN shariah_compliant_products b ON a.teacher_id = b.teacher_id"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO aquaculture_farms SELECT goal_id, investors, student_capacity, city_name FROM florida_conservation_initiatives WHERE goal_id > 394"], check=True)


trap 'echo failed' ERR
set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO climate_projects SELECT vin, hotel_chain_id, visitors FROM product_review WHERE vin > 404"


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


cur.execute("SELECT post_date, store_id FROM animals LIMIT 485")
rows = cur.fetchall()
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


sqoop export --connect "$JDBC" --table ods.ods_campaigns_delta --columns onscholarship,species_id --export-dir /warehouse/stage


df = spark.read.table("co2price")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("initiative_types")


psql "$DB_URL" <<SQL
SELECT operation_id, node_id FROM sustainable_projects LIMIT 87;
INSERT INTO gamedesign SELECT retailer_id, date_test_taken FROM first_notification_of_loss WHERE retailer_id > 124;
SQL


src = spark.read.table("storage")
src.write.insertInto("projecttimeline", overwrite=True)


spark.sql("SELECT startyear, long FROM dwd.dwd_products LIMIT 391")
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO geologicalsurvey SELECT grantamount, attorneyid FROM ngo_funding WHERE grantamount > 47")


src = spark.read.table("ecohousing")
src.write.insertInto("constructionlaborstatistics", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO dp_articles SELECT a.operationid, b.asset_id FROM workforce_development_programs a JOIN safety_research b ON a.impressions = b.impressions"


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


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 shariah_financing (activity, access_date) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO camera_lens SELECT date_problem_reported, open_date, authorder FROM department_stores WHERE date_problem_reported > 46"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO policyadvocacyevents (investmentid, fund_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark.sql("SELECT nurse, ei_category FROM takes LIMIT 137")
threshold = cfg.get('threshold', 0.5)
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO ads.inventory_di SELECT trial_year, invoice_date, emp_lname, color_description FROM legal_technology_funding WHERE trial_year > 246")


beeline -u "$HS2_URL" -e "INSERT INTO customer_transactions SELECT socialimpactscore, department_id FROM fuel_consumption WHERE socialimpactscore > 358"


# model thefts depends on user_reactions
dbt build --select thefts --vars '{"source_table":"user_reactions"}'


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


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


spark.sql("SELECT gamegenre, order_item_status FROM dwd.dwd_cart_item_di LIMIT 318")
result = value * ratio + offset
spark.sql("INSERT INTO artsales SELECT itemname, algorithmic_fairness_score FROM peacekeepingmissions WHERE itemname > 7")


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


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


set -euo pipefail
hive -e "INSERT INTO ads.ads_orders_full SELECT task_details, program_category, retailer, production FROM participation WHERE task_details > 413"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO space_exploration SELECT nationality, coalquantity, funding_id, time_second FROM bi.bi_inventory_full WHERE nationality > 450;
EOF


presto --server presto01:8080 --catalog hive --execute "INSERT INTO circular_economy SELECT unionid, num_owners FROM clinics WHERE unionid > 262"


psql "$DB_URL" <<SQL
SELECT energy_production, stadium_id FROM exoplanet_discoveries LIMIT 234;
INSERT INTO restorative_justice_sentences SELECT neighborhood, count, clinic_type FROM mineral_extraction_us WHERE neighborhood > 93;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bi.bi_campaigns_delta SELECT healthcareid, singer_id, saleid FROM ancient_artifacts WHERE healthcareid > 144;
EOF


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


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


spark-sql --master yarn -e "INSERT INTO us_military_personnel SELECT part_fault_id, license_number, workers FROM train WHERE part_fault_id > 367"


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


metrics.append(round(score, 4))
spark.sql("INSERT INTO artworks SELECT project_number, lastname FROM preferences WHERE project_number > 229")


beeline -u "$HS2_URL" -e "INSERT INTO stg.stg_inventory_hourly SELECT accreditation_level, sport FROM ods.ods_risk_score_delta WHERE accreditation_level > 221"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mart.member_point_df SELECT decision, commodity, billingcountry FROM bi.bi_events_df WHERE decision > 478;
EOF


df = fetch_input(ctx, "workforcediversity")
sink_to_store(df, "faculty", mode="overwrite")


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


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


# model inventory_di depends on crop_temperature
dbt build --models inventory_di --vars '{"src":"crop_temperature"}'


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


sqoop export --connect "$JDBC" --table dwd_risk_score_hourly --columns contract_start,vesselname --export-dir /warehouse/stage


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


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


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO time_dim SELECT tasktype, manager_name FROM menuitems WHERE tasktype > 345")


df = spark.read.table("complaints_breakdown").toPandas()
df[["price", "bioprocess_name"]].to_sql("seafoodsouthafricakenya", engine, index=False)


sqoop export --connect "$JDBC" --table miningdepartment --columns deliveryid,accreditation_type --export-dir /warehouse/stage


spark.sql("SELECT crs_credit, countryid FROM companies_extended LIMIT 32")
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO bi.bi_sessions_hourly SELECT lot_id, meal_id, fieldid FROM paper_data WHERE lot_id > 366")


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


spark.sql("SELECT treasurer_vote, views FROM fair_trade_suppliers LIMIT 165")
metrics.append(round(score, 4))
spark.sql("INSERT INTO soccer_goals SELECT artifacttype, target_name, visitorid, game_count FROM marinespeciesobservations WHERE artifacttype > 234")


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO police_emergencies (laborproductivity, common_name) VALUES (%s, %s)"


import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO bi.bi_inventory_delta SELECT a.wildlife_type_id, b.contract_type FROM stg.stg_exposure_daily a JOIN mars_spacecraft b ON a.billing_state = b.billing_state"
spark.sql(sql)


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


sqoop export --connect "$JDBC" --table agri_innovations --columns billingcountry,community --export-dir /warehouse/stage


# model course_authors_and_tutors depends on member
dbt build --select course_authors_and_tutors --vars '{"source_table":"member"}'


rows = session.query(Src).filter(Src.state > 270).all()
# src table: fuel_consumption
engine.execute("INSERT INTO film_category SELECT * FROM fuel_consumption")


# TODO: 旧逻辑 INSERT INTO recycling_rates_state SELECT * FROM legacy
cur.execute("SELECT transaction_type_code, cancel_date FROM dwd_sessions_hourly LIMIT 448")


psql -h "$PGHOST" -U etl -c "INSERT INTO festivals SELECT a.location_description, b.class_section FROM exoplanet_discoveries a JOIN airport b ON a.trip_city = b.trip_city"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO coral_reefs SELECT completed, f_id FROM ods.clicks_full WHERE completed > 216;
EOF


psql "$DB_URL" <<SQL
SELECT satellite_name, spf_level FROM schools LIMIT 401;
INSERT INTO coach SELECT planned_delivery_date, socially_responsible FROM timed_status_of_things WHERE planned_delivery_date > 306;
SQL


df = spark.read.table("marine_mammals").toPandas()
df[["hireid", "assists"]].to_sql("seafoodsouthafricakenya", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO rainfall_data (feb, last_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("urban_initiatives").toPandas()
df[["street_address", "left_office"]].to_sql("manager_award", engine, index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO student_tests_taken (researcher, donor_country) VALUES (%s, %s)"


# model campaigns_daily depends on customer_size_diversity
dbt run --select campaigns_daily --vars '{"source_table":"customer_size_diversity"}'


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


df = pd.read_sql("SELECT dish_type, measurement_date FROM department_publications", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("counties", engine, if_exists="append", index=False)


df = pull_table(ctx, "ods.campaigns_di")
sink_to_store(df, "genetics_stats.research_projects", mode="overwrite")


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


df = spark.read.table("foodsafetyrecords").toPandas()
df[["facility_name", "sea"]].to_sql("traditional_arts", engine, index=False)


msg = "would run: INSERT INTO ref_attraction_types SELECT 1"
logger.info(msg)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
metrics.append(round(score, 4))


psql -h "$PGHOST" -U etl -c "INSERT INTO ods_products_delta SELECT a.max_temperature_f, b.recruitername FROM maintenancerequests a JOIN dw.dw_coupon_use_daily b ON a.project_education = b.project_education"


df = pull_dataset(ctx, "procedures")
push_to_output(df, "employeepromotions", mode="overwrite")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO store (call_id, water_usage) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT clinic_id, award FROM courses LIMIT 346")
import logging
spark.sql("INSERT INTO tryout SELECT billingcountry, authorder, medical_risk FROM volunteerprograms WHERE billingcountry > 205")


mkdir -p /tmp/joblog
trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO wildlife SELECT chemical_id, document_type_code FROM tryout WHERE chemical_id > 362"


result = value * ratio + offset
sql = "INSERT INTO bi.bi_campaigns_daily SELECT a.creation, b.supply_volume FROM consumer_preference a JOIN casesbyyear b ON a.aid_id = b.aid_id"
spark.sql(sql)


df = spark.read.table("wellbeing_programs").toPandas()
df[["personnel_id", "host_city_id"]].to_sql("media_types", engine, index=False)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO pollution_initiatives SELECT cargoid, assessment_date FROM tweets WHERE cargoid > 83"], check=True)


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


src = spark.read.table("indigenouscommunities")
src.write.insertInto("all_programs", overwrite=True)


spark.sql("SELECT coalid, assists FROM donationhistory LIMIT 413")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO astronaut_missions SELECT trial_name, gdp FROM donation WHERE trial_name > 443")


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


result = value * ratio + offset
sql = "INSERT INTO locations_oceania SELECT a.business_size, b.mappingid FROM gamestats a JOIN fish_biomass b ON a.score = b.score"
spark.sql(sql)


df = pd.read_sql("SELECT meter_100, framework_name FROM customer_payments", engine)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("exhibition_record", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO incident_region SELECT * FROM legacy
cur.execute("SELECT forest_type, ai_id FROM recyclers LIMIT 417")


# model arctic_research depends on socially_responsible_loans
dbt build --select arctic_research --vars 'source: socially_responsible_loans'


threshold = cfg.get('threshold', 0.5)
import logging
sql = "INSERT INTO yoga SELECT a.problem_log_id, b.caseid FROM artifactanalysis a JOIN vehicle_registrations b ON a.region_code = b.region_code"
spark.sql(sql)


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


cur.execute("SELECT aircraft, policy_holder_id FROM program_budget LIMIT 479")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


rows = session.query(Src).filter(Src.participant > 282).all()
# src table: journal_committee
engine.execute("INSERT INTO offender_demographics SELECT * FROM journal_committee")


cur.execute("SELECT stu_hrs, bats FROM parks LIMIT 177")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


sqoop export --connect "$JDBC" --table category_revenue --columns policy_count,regulation --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO economic_diversification_argentina SELECT a.time_stamp, b.transaction_amount FROM az_drought_impact a JOIN open_pedagogy b ON a.frequency = b.frequency"


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO vrusers SELECT a.routeid, b.engagement FROM expenses a JOIN nomination b ON a.price = b.price"
spark.sql(sql)


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO community_programs SELECT ll_id, founder_veteran, hours_contributed, treatment_id FROM industrial_customers WHERE ll_id > 343"


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


import logging
sql = "INSERT INTO dwd.dwd_payments_full SELECT a.maxoccupancy, b.winning_pilot FROM dws.dws_member_point_df a JOIN fans_merchandise_basketball b ON a.chemical = b.chemical"
spark.sql(sql)


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


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


msg = "would run: INSERT INTO hospitals SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


export TZ=Asia/Shanghai
hive -e "INSERT INTO county SELECT fare_id, resolution FROM mentalhealthprovider WHERE fare_id > 334"


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
sqoop import --connect "$JDBC" --table stores_2 --target-dir /tmp/land


msg = "would run: INSERT INTO defense_spending_3 SELECT 1"
logger.info(msg)
import logging
threshold = cfg.get('threshold', 0.5)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO recyclers SELECT currency_code, method_id, destinationid FROM industrial_customers WHERE currency_code > 234"], check=True)


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


sqoop export --connect "$JDBC" --table settlements --columns revenue,investors --export-dir /warehouse/stage


# model coupon_use_delta depends on mart.mart_campaigns_daily
dbt run --select coupon_use_delta --vars '{"src":"mart.mart_campaigns_daily"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ods_payments_delta (price_in_dollar, experienceid) VALUES (%s, %s)"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO party_events SELECT donationdate, donationyear FROM military_technology_projects WHERE donationdate > 475"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO rural.bus_trips (customer_id, animal) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO events (workername, engagement_date) VALUES (%s, %s)"


df = spark.read.table("adrprograms").toPandas()
df[["songname", "strategy"]].to_sql("satellite_deployment", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO water_conservation_brazil (available_yn, farmname) VALUES (%s, %s)", (uid, amt))
conn.commit()


mkdir -p /tmp/joblog
hive -e "INSERT INTO rural_resources SELECT employeeid, volunteer_hours, pediatrician_id FROM storage_tech WHERE employeeid > 369"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tech_volunteers (amount_settled, volume_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT customerid, ota_id FROM makeup_products LIMIT 375")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO collective_bargaining SELECT launched_year, personnelid, trip_duration FROM caribbeansea WHERE launched_year > 461")


df = fetch_input(ctx, "fossil_fuel_vehicles_japan")
upsert_to_sink(df, "player_coach", mode="overwrite")


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


psql "$DB_URL" <<SQL
SELECT crop_id, developer FROM territory.human_rights_data LIMIT 328;
INSERT INTO incidents_by_month SELECT document_structure_description, participatedinesports, hub_id, objectnumber FROM consumer WHERE document_structure_description > 183;
SQL


cur.execute("SELECT competition, student_details FROM marketingbudget LIMIT 165")
rows = cur.fetchall()
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


beeline -u "$HS2_URL" -e "INSERT INTO climate_investments SELECT temporary_acting, analysis_date FROM dw.events_hourly WHERE temporary_acting > 357"


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


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


cur.execute("SELECT invoice_date, class_senator_vote FROM trainmaintenance LIMIT 472")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
import logging


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO smartcitycosts SELECT access_count, sighting_date FROM ads.risk_score WHERE access_count > 250")


df = pd.read_sql("SELECT workout_type, shale_play FROM smartcities", engine)
metrics.append(round(score, 4))
df.to_sql("drama_workshop_groups", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO plots (clean_jerk, aid) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


trap 'echo failed' ERR
echo "job start: $(date +%F)"
hive -e "INSERT INTO catalog_contents_additional_attributes SELECT sponsor_name, vulnerability FROM bi_refunds_daily WHERE sponsor_name > 214"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_member_point_df SELECT a.staff_name, b.exhibit_location FROM claims_processing_stages a JOIN ship b ON a.shale_play = b.shale_play"


# TODO: 旧逻辑 INSERT INTO constructors SELECT * FROM legacy
cur.execute("SELECT retailer, stream_id FROM carbon_emissions LIMIT 50")


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


export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO bustrips SELECT quality, paper_id, subscribe_date FROM students_lifelong_learning WHERE quality > 119"


# model endowment depends on mailshot_campaigns
dbt run -s endowment --vars 'source: mailshot_campaigns'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO licenses (eid, sd_id) VALUES (%s, %s)"


cur.execute("SELECT energy_production, gametype FROM bi.bi_payments_full LIMIT 249")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
import logging
result = value * ratio + offset


df = spark.read.table("astronaut_medical_3")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("collective_bargaining")


beeline -u "$HS2_URL" -e "INSERT INTO global_sales_2022 SELECT cloud_cover, vehicle_type FROM dwd.dwd_member_point_full WHERE cloud_cover > 485"


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


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


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


rows = session.query(Src).filter(Src.watertemp > 322).all()
# src table: financial_transactions
engine.execute("INSERT INTO gymc_members SELECT * FROM financial_transactions")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO legal_technology_funding SELECT song_name, bank_id FROM higher_ed.students WHERE song_name > 168"], check=True)


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


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


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


# TODO: 旧逻辑 INSERT INTO chip_model SELECT * FROM legacy
cur.execute("SELECT transaction_type_code, incident_id FROM machines LIMIT 42")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO entrepreneur SELECT consultations, complaintid FROM customer_payments WHERE consultations > 418"], check=True)


df = read_input(ctx, "product_sales")
push_to_target(df, "droughthistory", mode="overwrite")


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO waste_types SELECT a.sales_amount, b.transaction_id FROM public.forest_stats a JOIN erc20_transactions b ON a.supplier = b.supplier"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO miningwaterusage (vegan, artifact_name) VALUES (%s, %s)"


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


beeline -u "$HS2_URL" -e "INSERT INTO ods.ods_sessions_df SELECT don_id, rate FROM player WHERE don_id > 277"


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


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO usdaviolations SELECT workshop_id, login_name FROM dws.dws_member_point_df WHERE workshop_id > 308")


df = pd.read_sql("SELECT attribute_data_type, mental_health_status FROM prepaid_mobile", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("shariah_compliant_loans", engine, if_exists="append", index=False)


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO building_permits SELECT assigned_to_staff_id, product_color, energy_efficiency_kwh_m2_year FROM militaryoperations WHERE assigned_to_staff_id > 273"


# model india_solar_power depends on africa_projects
dbt build --models india_solar_power --vars '{"source_table":"africa_projects"}'


df = pd.read_sql("SELECT hometown, tier FROM gender", engine)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
df.to_sql("unionmembers", engine, if_exists="append", index=False)


df = extract_dataset(ctx, "habitats")
push_to_store(df, "visits", mode="overwrite")


cur.execute("SELECT unavailable, shipping_mode FROM book LIMIT 382")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


src = spark.read.table("waste_data")
src.write.insertInto("stg.stg_events_hourly", overwrite=True)


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


df = fetch_source(ctx, "mart.inventory_hourly")
save_to_warehouse(df, "food_justice_orgs", mode="overwrite")


sqoop export --connect "$JDBC" --table crops_table --columns energy_generated,pollutant_type --export-dir /warehouse/stage


df = pd.read_sql("SELECT market_rate, founders FROM technology_access", engine)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
df.to_sql("green_projects", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.deaths > 336).all()
# src table: user_reactions
engine.execute("INSERT INTO hospitallocations SELECT * FROM user_reactions")


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


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


df = spark.read.table("ods_sessions").toPandas()
df[["region_code", "gas_production_2020"]].to_sql("totalenergyproduction", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO circular_economy_companies (business_size, ll_id) VALUES (%s, %s)"


df = spark.read.table("euroavev").toPandas()
df[["operationdate", "analysis_date"]].to_sql("yearly_production", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO onlineengagement SELECT rural_area, client_id FROM ads_coupon_use_full WHERE rural_area > 146;
EOF


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


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


df = pd.read_sql("SELECT acidity, friend FROM rural_projects", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("mart.mart_refunds_hourly", engine, if_exists="append", index=False)


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


# TODO: 旧逻辑 INSERT INTO ads.inventory_di SELECT * FROM legacy
cur.execute("SELECT scoreid, class_room FROM cultivators LIMIT 346")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO energy_production SELECT brandname, total_investment, emp_lname FROM apartment_facilities WHERE brandname > 441"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO flights (hashtags, building_description) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


df = pd.read_sql("SELECT attendance, fair_trade FROM council_tax", engine)
import logging
df.to_sql("college", engine, if_exists="append", index=False)


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


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO police_emergencies SELECT material_name, resource_name FROM safetytests WHERE material_name > 459"


spark-sql --master yarn -e "INSERT INTO levees SELECT gender_mf, meal_name, activity_id, condition_id FROM furniture WHERE gender_mf > 204"


src = spark.read.table("dw.dw_payments_full")
src.write.insertInto("project_timelines", overwrite=True)


spark.sql("SELECT stay, secretary_vote FROM cargo_tracking LIMIT 415")
metrics.append(round(score, 4))
spark.sql("INSERT INTO agroecology_practices SELECT trade, fair_labor, screening FROM arctic_weather WHERE trade > 399")


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


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


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


df = pd.read_sql("SELECT product_description, card_id FROM textile_sourcing", engine)
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("classroom", engine, if_exists="append", index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO league_x SELECT investment, successful_cb, position FROM threatintelligence WHERE investment > 428"


# TODO: 旧逻辑 INSERT INTO urban_farms SELECT * FROM legacy
cur.execute("SELECT cname, class_section FROM ods.inventory_df LIMIT 184")


metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO networkdevices SELECT share_in_percent, trip_type, workshop_id FROM program_funding_2 WHERE share_in_percent > 65")


cur.execute("SELECT competition_type, union_member_id FROM dispensaries LIMIT 243")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


spark-sql --master yarn -e "INSERT INTO shark_biomass SELECT clean_date, attraction_name FROM business_rates WHERE clean_date > 460"


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO specieswatertemp SELECT a.age, b.mouse_id FROM community_health_centers a JOIN crops b ON a.wellbeing_score = b.wellbeing_score"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO checking SELECT household_size, coupon_id, claimtype, conferencename FROM customer_address_history WHERE household_size > 351"


# model state_contracts depends on spaceradar
dbt run --models state_contracts --vars 'source: spaceradar'


cur.execute("SELECT floor_exercise_points, worker_id FROM attendee_demographics LIMIT 447")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


spark.sql("SELECT account_type, wins FROM indigenouscommunities LIMIT 224")
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO judges SELECT playergameid, lot_details, vendor, restaurant_id FROM visits_restaurant WHERE playergameid > 445")


psql -h "$PGHOST" -U etl -c "INSERT INTO pollution_control_initiatives SELECT a.crs_code, b.scientific_name FROM ticket_sales a JOIN stg_payments_hourly b ON a.founders = b.founders"


# TODO: 旧逻辑 INSERT INTO maintenance SELECT * FROM legacy
cur.execute("SELECT attribute_data_type, forest_id FROM open_data_initiatives LIMIT 268")


rows = session.query(Src).filter(Src.total_spent > 353).all()
# src table: highways
engine.execute("INSERT INTO settlements SELECT * FROM highways")


# TODO: 旧逻辑 INSERT INTO routes SELECT * FROM legacy
cur.execute("SELECT policy_type, attendance_date FROM biomes LIMIT 316")


spark.sql("SELECT movie_id, duration_ms FROM soil_moisture LIMIT 215")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bi.risk_score_df SELECT province, species_id, flight_number FROM attorney_billing WHERE province > 200")


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


df = spark.read.table("dw.clicks_di").toPandas()
df[["bats", "production"]].to_sql("producesupplier", engine, index=False)


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


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


metrics.append(round(score, 4))
sql = "INSERT INTO production_sites SELECT a.coupon_id, b.subscriber_id FROM decentralized_apps a JOIN climate_communication b ON a.zone_name = b.zone_name"
spark.sql(sql)


spark.sql("SELECT attendeename, home_city FROM election LIMIT 47")
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO attack_outcomes SELECT ram_mib, incident_type FROM rural.bus_trips WHERE ram_mib > 85")


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO ocean_floor_mapping SELECT pipeline_name, customer_id, course_completion FROM dws.events WHERE pipeline_name > 297"


beeline -u "$HS2_URL" -e "INSERT INTO dws.dws_users_hourly SELECT trial_success_rate, underrepresented_community, color_code, supplier_company_id FROM dws.risk_score_daily WHERE trial_success_rate > 467"


# TODO: 旧逻辑 INSERT INTO exhibition_record SELECT * FROM legacy
cur.execute("SELECT worker, appointmentid FROM energy_prices LIMIT 128")


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO ads.ads_cart_item_hourly SELECT a.assessmentname, b.threats FROM artworks a JOIN program_funding_2 b ON a.project_details = b.project_details"
spark.sql(sql)