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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO workplaces SELECT a.sale_revenue, b.allocation_date FROM safetytestingcounts a JOIN marine_life_data b ON a.delivery_time = b.delivery_time"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO canada_tech SELECT dissolved_oxygen, coalid, customer_country, submission_id FROM continents WHERE dissolved_oxygen > 218"


# model reservations depends on player
dbt build --models reservations --vars '{"src":"player"}'


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO open_data_initiatives (min_dew_point_f, salesperson_id) VALUES (%s, %s)"


spark.sql("SELECT num_pallets, call_date FROM mobile_usage LIMIT 187")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO lessons SELECT person_id, vaccine_name, quality_rank FROM ingredientsvegancrueltyfree WHERE person_id > 100")


# model defenseprojects depends on veterans
dbt run -s defenseprojects --vars '{"src":"veterans"}'


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


df = extract_input(ctx, "ucl_top10")
export_to_sink(df, "companies_extended", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO mart.vendors_full SELECT school_colors, athlete, co2_emission FROM chemical_concentration WHERE school_colors > 134")


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


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


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


sqoop export --connect "$JDBC" --table restaurant_type --columns service_name,monthlyactiveusers --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.council_id > 454).all()
# src table: city.community_policing
engine.execute("INSERT INTO artprograms SELECT * FROM city.community_policing")


psql -h "$PGHOST" -U etl -c "INSERT INTO mining.company SELECT a.vendor_state, b.built_year FROM animal_population_status a JOIN culturalcompetencytraining b ON a.savings = b.savings"


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


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


# model green_buildings depends on donations
dbt run --models green_buildings --vars 'source: donations'


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


trap 'echo failed' ERR
hive -e "INSERT INTO menu_engineering SELECT therapy_id, song_name, event FROM calibration_data2 WHERE therapy_id > 364"


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


# model research_staff depends on school
dbt run --models research_staff --vars '{"source_table":"school"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO military_personnel_africa (city_name, service_type_code) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO bi.inventory_daily SELECT zip, organization FROM route_fares WHERE zip > 53"


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO busmaintenance SELECT education_id, store_email_address, framework_id FROM pollutionincidents WHERE education_id > 358")


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


cur.execute("SELECT tank, brand_id FROM roles LIMIT 426")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


# TODO: 旧逻辑 INSERT INTO tree_habitat_associations SELECT * FROM legacy
cur.execute("SELECT vessel_name, operating_system FROM baseball_teams LIMIT 496")


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


src = spark.read.table("docking")
src.write.insertInto("product_details", overwrite=True)


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


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


rows = session.query(Src).filter(Src.cust_id > 54).all()
# src table: weather_record
engine.execute("INSERT INTO shared_ebikes SELECT * FROM weather_record")


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


# model humanitarianassistanceoperations depends on regions
dbt run -s humanitarianassistanceoperations --vars '{"source_table":"regions"}'


# TODO: 旧逻辑 INSERT INTO genetic_research SELECT * FROM legacy
cur.execute("SELECT access_date, asset_type FROM autonomousdriving LIMIT 450")


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


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


psql "$DB_URL" <<SQL
SELECT port_id, event_type_id FROM innovation_trends LIMIT 274;
INSERT INTO storage SELECT complaint_id, license_type, concert_id, decision FROM genetics_stats.research_projects WHERE complaint_id > 231;
SQL


sqoop export --connect "$JDBC" --table donorprograms --columns trade,ota_name --export-dir /warehouse/stage


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bookings SELECT sustainable_practice, trip_duration FROM files WHERE sustainable_practice > 315"


spark-sql --master yarn -e "INSERT INTO mart_events_full SELECT project_education, label_id, specialty, prod_id FROM dw_payments WHERE project_education > 389"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO carbon_prices_3 SELECT document_status_description, instructor, performance_id, document_structure_code FROM laborstatistics WHERE document_status_description > 246"], check=True)


df = source_table(ctx, "climate_monitoring_stations")
push_to_output(df, "item", mode="overwrite")


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


cur.execute("SELECT level, destroyed_by_employee_id FROM dwd.campaigns LIMIT 58")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)


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


psql "$DB_URL" <<SQL
SELECT trip_start_time, bname FROM packages LIMIT 410;
INSERT INTO research SELECT founder_country, mealid FROM tourismproviders WHERE founder_country > 300;
SQL


df = pd.read_sql("SELECT funding_source_type, stu_gpa FROM cybersecurity_vulnerabilities", engine)
result = value * ratio + offset
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("stg.campaigns_df", engine, if_exists="append", index=False)


threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO police_officers_tx SELECT a.project_name, b.problem_description FROM safety_research a JOIN assets b ON a.popularity = b.popularity"
spark.sql(sql)


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


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


psql "$DB_URL" <<SQL
SELECT track_id, province_id FROM city_properties LIMIT 131;
INSERT INTO levees SELECT professionalid, premise_id, purchase_transaction_id FROM mart.mart_users_df WHERE professionalid > 222;
SQL


cur.execute("SELECT bikes_available, innovation FROM fireincidents LIMIT 46")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


psql "$DB_URL" <<SQL
SELECT attorney, highscore FROM insurancetype LIMIT 343;
INSERT INTO player_sessions SELECT hoursspent, resolution, student_id FROM zip_codes WHERE hoursspent > 145;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO regulatoryframeworksbycountry SELECT tech_id, memberid FROM constructorstandings WHERE tech_id > 123"], check=True)


psql "$DB_URL" <<SQL
SELECT graphics_mode, year_built FROM cosmetic_sales LIMIT 251;
INSERT INTO military_expenditure SELECT pipeline_name, brand_mentioned FROM mobile_usage WHERE pipeline_name > 376;
SQL


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


sqoop export --connect "$JDBC" --table attack_outcomes --columns visitorid,publication_year --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO staff SELECT a.categoryid, b.room FROM leo_missions a JOIN organization b ON a.followers = b.followers"


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


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO heritagesites SELECT a.num_attendees, b.lipstick_id FROM marine_life_populations a JOIN artcollection b ON a.pilot_name = b.pilot_name"
spark.sql(sql)


import logging
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO labor_practices SELECT updatedate, mappinglength FROM conservation_programs WHERE updatedate > 255")


export TZ=Asia/Shanghai
hive -e "INSERT INTO dw.shipments_df SELECT host_city, skill_description, tree_type_id FROM fan_purchases WHERE host_city > 470"


rows = session.query(Src).filter(Src.brand > 362).all()
# src table: dws.events
engine.execute("INSERT INTO stg.device_log_df SELECT * FROM dws.events")


src = spark.read.table("urban_transportation")
src.write.insertInto("claims_processing_stages", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO artist SELECT approach, resident_id, grade FROM tech_accessibility_funding WHERE approach > 246"


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
set -euo pipefail
sqoop import --connect "$JDBC" --table dwd.events_daily --target-dir /tmp/land


df = spark.read.table("victims").toPandas()
df[["visitdate", "waste_generation"]].to_sql("stg.stg_coupon_use_di", engine, index=False)


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


psql "$DB_URL" <<SQL
SELECT devices, closuredate FROM billstatus LIMIT 76;
INSERT INTO team_franchise SELECT total_distance, monthly_rental, winning_aircraft FROM immunization WHERE total_distance > 57;
SQL


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO innovation_projects (users_engaged, plant_name) VALUES (%s, %s)"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO user_stats SELECT amount_waste, fleet_series FROM state_energy WHERE amount_waste > 450"], check=True)


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO city_waste_generation SELECT num_solo_exhibitions, stat_id, donor_program FROM bi_shipments_daily WHERE num_solo_exhibitions > 74")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO bi.payments_daily SELECT ratingdate, vendor, opname, account_number FROM tracks WHERE ratingdate > 158"], check=True)


mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO suppliersfairlabor SELECT investmentid, clientid, tour_type, next_entry_id FROM residents_services WHERE investmentid > 49"


echo "job start: $(date +%F)"
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO renewable_power SELECT is_safe, character, budget_allocation FROM companies WHERE is_safe > 447"


# TODO: 旧逻辑 INSERT INTO sustainability_metrics SELECT * FROM legacy
cur.execute("SELECT initiative_region, resource_id FROM hydro_power LIMIT 404")


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


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


spark.sql("SELECT years_played, app_name FROM race LIMIT 20")
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO healthcare_centers SELECT signupdate, max_temperature_f FROM brands WHERE signupdate > 407")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO stg.cart_item_full SELECT albumname, donation_id, age_group_id FROM mart.mart_member_point_df WHERE albumname > 41"


rows = session.query(Src).filter(Src.response_received_date > 200).all()
# src table: document_locations
engine.execute("INSERT INTO trains SELECT * FROM document_locations")


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


echo "dry-run: INSERT INTO concentrateprices SELECT 1"
set -euo pipefail
echo "job start: $(date +%F)"


psql "$DB_URL" <<SQL
SELECT headquarters, incident_category FROM atlantic_ocean_fish LIMIT 239;
INSERT INTO taxi_data SELECT matchdate, stu_phone, membership_amount FROM gamestats WHERE matchdate > 180;
SQL


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


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


result = value * ratio + offset
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))


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


beeline -u "$HS2_URL" -e "INSERT INTO crop_temperature SELECT course_name, founder_country, attorneyid, esg_factor FROM artsheritage WHERE course_name > 420"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO budget_allocations SELECT opening_year, first_year FROM clothingsales WHERE opening_year > 402;
EOF


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


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


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO consumer SELECT a.loan_amount, b.staff_id FROM storage_tech a JOIN sports b ON a.materialname = b.materialname"
spark.sql(sql)


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


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


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO item_prices SELECT day_of_week, policyid, collection_id FROM drugs WHERE day_of_week > 398"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO apartments (membership, location_code) VALUES (%s, %s)"


df = pd.read_sql("SELECT certified, generation_date FROM premises", engine)
if not rows:
    logger.warning('empty result')
import logging
result = value * ratio + offset
df.to_sql("leo_missions", engine, if_exists="append", index=False)


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


# model shariahfinance depends on spacecraft_manufacturing
dbt run --models shariahfinance --vars '{"src":"spacecraft_manufacturing"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO co_ownership SELECT a.business_zone, b.development_name FROM workforce_development_programs a JOIN communityhealthworkerscanada b ON a.class_senator_vote = b.class_senator_vote"


df = read_input(ctx, "draft_copies")
push_to_warehouse(df, "restorative_justice_center", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO skills SELECT energy_efficiency_kwh_m2_year, did, stu_gpa FROM artists_valuation WHERE energy_efficiency_kwh_m2_year > 126"


metrics.append(round(score, 4))
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))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO host (case_status, share_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("route_fares").toPandas()
df[["video_id", "headquarter"]].to_sql("maintenance", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO educationprograms SELECT a.fastestlapspeed, b.workshop_name FROM apartments a JOIN bi.bi_sessions_daily b ON a.cname = b.cname"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO landfills (resource_type, daily_consumption) VALUES (%s, %s)", (uid, amt))
conn.commit()


# TODO: 旧逻辑 INSERT INTO stg.stg_coupon_use_di SELECT * FROM legacy
cur.execute("SELECT creation, settlement_amount FROM expenses LIMIT 221")


rows = session.query(Src).filter(Src.product_stock_number > 37).all()
# src table: crime_stats
engine.execute("INSERT INTO stellar_transactions SELECT * FROM crime_stats")


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


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


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


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


TBL="ads_report_${BIZ_DATE}"
hive -e "INSERT INTO $TBL SELECT * FROM field5"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO wta_serves SELECT mental_health_score, played, hospital_id FROM autonomous_testing WHERE mental_health_score > 163"], check=True)


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


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


spark-sql --master yarn -e "INSERT INTO bi.inventory_daily SELECT laborproductivity, neighborhoodid, start, union_members FROM zipcodes WHERE laborproductivity > 206"

laborproductivity neighborhoodid start union_members


df = spark.read.table("dws.inventory_daily").toPandas()
df[["contract_address", "job"]].to_sql("claims", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO veterans SELECT dose, marketing_region_descriptrion, truck_licence_number FROM ads.ads_campaigns_full WHERE dose > 82"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO hair_care_sales SELECT target_u_id, manufacturerid FROM seamounts WHERE target_u_id > 476"


# TODO: 旧逻辑 INSERT INTO eia_schedule SELECT * FROM legacy
cur.execute("SELECT email_address, virtual_tour_engagement_time FROM teacher_professional_development LIMIT 171")


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


# model waste depends on hosting_city
dbt build --select waste --vars 'source: hosting_city'


spark-sql --master yarn -e "INSERT INTO council_tax SELECT stay, asset_make FROM trains WHERE stay > 209"


src = spark.read.table("infantmortalitydata")
src.write.insertInto("heritage_sites", overwrite=True)


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


df = spark.read.table("ads.ads_users_hourly").toPandas()
df[["date_in_location_from", "time_of_day"]].to_sql("sustainable_sourcing", engine, index=False)


# model accessible_tech_categories depends on communityhealthworkers
dbt build --models accessible_tech_categories --vars 'source: communityhealthworkers'


df = pd.read_sql("SELECT stu_dob, workshop_name FROM hotel_reviews", engine)
import logging
df.to_sql("government.region", engine, if_exists="append", index=False)


df = spark.read.table("co_ownership").toPandas()
df[["appointment_time", "garment_id"]].to_sql("prescribes", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO climate_data SELECT openning_year, field, policy_id, equipment_id FROM producers WHERE openning_year > 226"


echo "dry-run: INSERT INTO tickets_3 SELECT 1"
echo "job start: $(date +%F)"
trap 'echo failed' ERR


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


df = spark.read.table("mentalhealthparityscores").toPandas()
df[["product_size", "platform"]].to_sql("ancient_artifacts", engine, index=False)


src = spark.read.table("decentralized_applications")
src.write.insertInto("ods_member_point_full", overwrite=True)


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


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO strandings SELECT min_dew_point_f, code, catalog_name, consider_rate FROM sustainability_metrics WHERE min_dew_point_f > 349")


psql "$DB_URL" <<SQL
SELECT creation_year, gameid FROM open_pedagogy_courses LIMIT 199;
INSERT INTO timed_locations_of_things SELECT max_gust_speed_mph, squadron FROM home_game WHERE max_gust_speed_mph > 145;
SQL


spark-sql --master yarn -e "INSERT INTO humanitarian_aid SELECT field_id, fault_log_entry_id, vendorid FROM athlete_wellbeing WHERE field_id > 490"


trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO water_conservation SELECT citizens, bioreactor_id, playlist_id, num_libraries FROM portfolios WHERE citizens > 277"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO project_timelines SELECT contract_number, releaseyear, dispensary, fault_status FROM seafoodsouthafricakenya WHERE contract_number > 110"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO mart.mart_products_hourly SELECT workshop_name, exhibitions FROM mart.mart_device_log_hourly WHERE workshop_name > 282"


df = spark.read.table("water_distribution").toPandas()
df[["status_of_thing_code", "participant"]].to_sql("miningoperations", engine, index=False)


cur.execute("SELECT gender_mf, worker FROM machinery LIMIT 169")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


src = spark.read.table("labour_productivity")
src.write.insertInto("vehiclemodels", overwrite=True)


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


src = spark.read.table("astronautmedicaldata")
src.write.insertInto("defense_contractors", overwrite=True)


df = spark.read.table("policyanalysis").toPandas()
df[["inclusive_housing_policy", "end_station_id"]].to_sql("mart.mart_payments_df", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO ref_incident_type SELECT a.mouse_id, b.text FROM ticketsales a JOIN player_coach b ON a.attack_count = b.attack_count"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO excavation_sites SELECT data_usage, course_id FROM buildings WHERE data_usage > 287;
EOF


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO retailerg SELECT a.player, b.fleet_series FROM trenches a JOIN department_publications b ON a.sale_revenue = b.sale_revenue"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO fair_trade_brands SELECT host_city, contract_type, subject_area_id FROM wind_energy WHERE host_city > 257"], check=True)


src = spark.read.table("feed")
src.write.insertInto("bi.bi_inventory_di", overwrite=True)


src = spark.read.table("tours")
src.write.insertInto("drilling_rigs", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO defenseprojects SELECT recipient_id, rows, restypename, state_province_county FROM dwd.dwd_member_point_full WHERE recipient_id > 280"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO hospitals SELECT payment_method, form_id, tournament_id FROM dwd.coupon_use_daily WHERE payment_method > 166"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO co2_emission (reason, sales_billion) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


psql "$DB_URL" <<SQL
SELECT intervention_type, customer_country FROM culturalcompetencytrainings LIMIT 10;
INSERT INTO contract_negotiations_un SELECT date_of_latest_revision, eliminated_by FROM smart_cities WHERE date_of_latest_revision > 245;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ma_inspections SELECT veteran_unemployment_rate, fleet_id FROM management WHERE veteran_unemployment_rate > 68"], check=True)


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO budget_allocations SELECT monthlyactiveusers, regionid FROM industry_funding WHERE monthlyactiveusers > 286"


df = pull_table(ctx, "job_postings")
save_to_output(df, "staff_roles", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO cultural_heritage (policyname, review_rating) VALUES (%s, %s)"


cur.execute("SELECT strain_name, personnel FROM workplaces LIMIT 211")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


metrics.append(round(score, 4))
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')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO instructor SELECT shipping_mode, product_details, volunteerdate FROM mart.mart_device_log_delta WHERE shipping_mode > 482")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO seafood (image_url, staff_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


src = spark.read.table("shrimp_farms")
src.write.insertInto("innovation_grants", overwrite=True)


df = get_table(ctx, "ais")
write_to_warehouse(df, "eventdates", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dishes SELECT hotel_name, store_name, sqft FROM nomination WHERE hotel_name > 461"], check=True)


cur.execute("SELECT mealid, emp_fname FROM ytterbiumproduction LIMIT 266")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
metrics.append(round(score, 4))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO facility_production SELECT category, date_stored, vegetable FROM human_resources WHERE category > 281;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO renewable_energy_projects (volunteer_id, range) VALUES (%s, %s)"


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


# TODO: 旧逻辑 INSERT INTO appliances SELECT * FROM legacy
cur.execute("SELECT funding_received, classtype FROM vehiclemodels LIMIT 201")


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


df = pd.read_sql("SELECT nominee, compatible_since_year FROM foodsafetyrecords", engine)
import logging
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("membership_register_branch", engine, if_exists="append", index=False)


msg = "would run: INSERT INTO news_views SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


result = value * ratio + offset
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO expenditure SELECT a.salinity, b.amount_payment FROM whale_sightings a JOIN bridgeconstruction b ON a.line_id = b.line_id"
spark.sql(sql)


threshold = cfg.get('threshold', 0.5)
import logging
metrics.append(round(score, 4))
sql = "INSERT INTO courtcases SELECT a.manufacturer, b.countryname FROM menu_items a JOIN developers b ON a.transaction_value = b.transaction_value"
spark.sql(sql)


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO systems SELECT era, employee, sustainability_initiative_id FROM film_actor WHERE era > 197")


df = load_frame(ctx, "claims_documents")
save_to_sink(df, "co2_sequestration", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO dws_events_df SELECT * FROM legacy
cur.execute("SELECT unique_founders, mascot FROM bi.events_delta LIMIT 49")


spark.sql("SELECT paintingid, artist_name FROM well_production LIMIT 412")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO communitycourtcases SELECT waste_id, disability_type, energy_generated FROM mental_health_parity WHERE waste_id > 167")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO nba_games SELECT dock_count, total_donation_amount, sessiondate FROM host WHERE dock_count > 477;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO port_visits SELECT asset_details, mode, fleet_id, account_type FROM heart_rate_data WHERE asset_details > 259"


# TODO: 旧逻辑 INSERT INTO schools SELECT * FROM legacy
cur.execute("SELECT contract_end_date, coverage_type FROM weapons LIMIT 360")


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


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


# TODO: 旧逻辑 INSERT INTO biosensors.projects SELECT * FROM legacy
cur.execute("SELECT quantity_sold, journalist_id FROM readership LIMIT 392")


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


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


src = spark.read.table("investment_strategies")
src.write.insertInto("cultivators", overwrite=True)


psql "$DB_URL" <<SQL
SELECT workshop_id, gname FROM budgets LIMIT 254;
INSERT INTO latam_schema.education_budget SELECT experience_id, savingsid FROM emergencies WHERE experience_id > 459;
SQL


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO cargo_tracking (amount_waste, date_of_ceremony) VALUES (%s, %s)"


# TODO: 旧逻辑 INSERT INTO bi.events_delta SELECT * FROM legacy
cur.execute("SELECT lender_id, building_id FROM playersessions LIMIT 489")


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


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


trap 'echo failed' ERR
set -euo pipefail
hive -e "INSERT INTO ocean_species SELECT routeid, active_to_date, clean_date, built FROM state_energy WHERE routeid > 161"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO legal_precedents SELECT financial_wellbeing_score, time_id, contractorid FROM ods.ods_payments_full WHERE financial_wellbeing_score > 289"


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


spark-sql --master yarn -e "INSERT INTO mart_shipments_full SELECT habitat_name, date_incident_start FROM restaurant_revenue WHERE habitat_name > 261"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO facility SELECT savingsid, manufacturer_name FROM excavations WHERE savingsid > 470;
EOF


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sustainable_practices_2 SELECT gross_worldwide, typical_selling_price FROM part_faults WHERE gross_worldwide > 149;
EOF


cur.execute("SELECT manufacturer_id, grant_type FROM support_programs LIMIT 397")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


src = spark.read.table("paris_train")
src.write.insertInto("countryintelligenceops", overwrite=True)


df = spark.read.table("travel_advisory").toPandas()
df[["replacement_cost", "transaction_amount"]].to_sql("virtual_tour_revenue", engine, index=False)


sqoop export --connect "$JDBC" --table college --columns strat_id,individual_last_name --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO reo_production SELECT project_number, programid, took_office FROM dwd.dwd_cart_item_di WHERE project_number > 88"


src = spark.read.table("workers")
src.write.insertInto("menu_item", overwrite=True)


rows = session.query(Src).filter(Src.event_type > 14).all()
# src table: exhibitiondetails
engine.execute("INSERT INTO pollution_initiatives SELECT * FROM exhibitiondetails")


psql -h "$PGHOST" -U etl -c "INSERT INTO public_transportation_sydney SELECT a.speciesid, b.bike_id FROM arcticocean a JOIN container_ships b ON a.vaccine_type = b.vaccine_type"


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


df = extract_frame(ctx, "urban_agriculture_initiatives")
push_to_warehouse(df, "overwatch_scores", mode="overwrite")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO open_pedagogy_exam SELECT crs_credit, assessmentname FROM pitstops WHERE crs_credit > 218"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.ads_payments SELECT dish_name, subject FROM genre_songs WHERE dish_name > 266"], check=True)


df = pd.read_sql("SELECT health_equity_metric_3, time_month FROM market_share", engine)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
df.to_sql("precipitation_data", engine, if_exists="append", index=False)


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


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


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


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO bi.bi_payments_df SELECT city_population, organizationid, funding_source, training_id FROM industry_funding WHERE city_population > 336")


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO available_policies SELECT a.tonnage, b.marketing_region_code FROM stg.stg_users a JOIN org_donation b ON a.investor_name = b.investor_name"
spark.sql(sql)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ais SELECT contract_start_date, industry_4_0 FROM public_transportation_sydney WHERE contract_start_date > 400;
EOF


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


sqoop export --connect "$JDBC" --table workout_sessions --columns topic,attendees --export-dir /warehouse/stage


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO news_report (stu_fname, reo_type) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO carbon_prices_3 (inspection_date, installation_year) VALUES (%s, %s)"


cur.execute("SELECT operation_count, product_category FROM elimination LIMIT 202")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


sqoop export --connect "$JDBC" --table operation --columns region_code,card_type_code --export-dir /warehouse/stage


df = spark.read.table("climber").toPandas()
df[["monthlyactiveusers", "acc_bal"]].to_sql("bikerental", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO fireincidents SELECT facid, contributorid, gamename, reported_by_staff_id FROM academic_publications WHERE facid > 368"], check=True)

facid contributorid gamename reported_by_staff_id


spark.sql("SELECT delivery_time, judge_state FROM document_sections_images LIMIT 387")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ads.inventory_di SELECT claim_header_id, singer_id, time_hour FROM tech_workers_union WHERE claim_header_id > 32")


spark-sql --master yarn -e "INSERT INTO categories SELECT totalprice, sport, profits_billion FROM crimes WHERE totalprice > 258"


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


psql "$DB_URL" <<SQL
SELECT extraction_amount, oil_production_q4_2021 FROM disaster_response_donations LIMIT 62;
INSERT INTO bi.device_log SELECT strainname, guest_id, record_id FROM economic_diversification WHERE strainname > 359;
SQL


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


# TODO: 旧逻辑 INSERT INTO fashion_trend_data SELECT * FROM legacy
cur.execute("SELECT funding_year, excavation_site FROM space_missions_2 LIMIT 468")


# TODO: 旧逻辑 INSERT INTO mediterranean_salinity SELECT * FROM legacy
cur.execute("SELECT technique, monthly_rental FROM view_unit_status LIMIT 118")


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


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO climate_communication_projects SELECT date_opened, sustainability_id FROM militarycyberops WHERE date_opened > 499")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO restaurant_type (units_owned, heritage_site) VALUES (%s, %s)"


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO animal_species SELECT a.check_in_date, b.submission_id FROM tourism_activities a JOIN bridge b ON a.bioprocess_name = b.bioprocess_name"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO farmers (partid, catalog_entry_id) VALUES (%s, %s)"


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


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


sqoop export --connect "$JDBC" --table languages --columns governor,hire_date --export-dir /warehouse/stage


df = get_input(ctx, "vessels")
dump_to_store(df, "socialimpactinvestments", mode="overwrite")


sqoop export --connect "$JDBC" --table property_community --columns assets_billion,clublocation --export-dir /warehouse/stage


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


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


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


df = extract_source(ctx, "arcticocean")
write_to_warehouse(df, "document_functional_areas", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO urban_agriculture_initiatives SELECT a.cultural_competency_score, b.factory_id FROM labor_statistics a JOIN spacecraft_manufacturing b ON a.treatment_type = b.treatment_type"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart_events_full SELECT fleet_id, capacity_percentage, concert_name FROM attendee_demographics WHERE fleet_id > 18"


df = pd.read_sql("SELECT vin, reports_to FROM member_details", engine)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
result = value * ratio + offset
df.to_sql("ods.ods_risk_score_delta", engine, if_exists="append", index=False)


cur.execute("SELECT i_id, events FROM circular_economy LIMIT 275")
rows = cur.fetchall()
import logging
retries = int(os.environ.get('RETRIES', '3'))


# TODO: 旧逻辑 INSERT INTO atlantic_ocean_fish SELECT * FROM legacy
cur.execute("SELECT vessel, device_name FROM wildlife_sanctuaries LIMIT 92")


df = pull_input(ctx, "health_equity_metrics")
save_to_warehouse(df, "dws.dws_member_point_df", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dw_users_full (workout_name, region_code) VALUES (%s, %s)"


df = load_source(ctx, "traffic_violations")
sink_to_sink(df, "high_risk", mode="overwrite")


# model ads_orders depends on skills
dbt run --models ads_orders --vars '{"src":"skills"}'


df = pd.read_sql("SELECT occupancy_rate, other_details FROM student_access", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("bank_info", engine, if_exists="append", index=False)


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO vessels_2 SELECT task_details, destruction_authorised_by_employee_id, min_dew_point_f FROM postseason WHERE task_details > 441")


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


spark.sql("SELECT ironid, accommodation_id FROM platform_production LIMIT 300")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO workforce_development SELECT co_id, budget FROM healthcare WHERE co_id > 242")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO donors_region (date_valid_to, production_cost) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql "$DB_URL" <<SQL
SELECT ethnicity, trade FROM justice_schemas.legal_tech_providers LIMIT 197;
INSERT INTO posts_per_day SELECT engagementid, treatment_date, shipmentid FROM creative_ai_applications WHERE engagementid > 494;
SQL


sqoop export --connect "$JDBC" --table stg.stg_users_full --columns video_id,strainname --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO haircaresales SELECT total, cause_name, workshop_name, users_engaged FROM supplier_ethics WHERE total > 258"


spark.sql("SELECT dockingid, other_item_details FROM customer_policies LIMIT 127")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
import logging
spark.sql("INSERT INTO assignedto SELECT eventdate, productionrate, effort_name, budget_allocated FROM ads.risk_score WHERE eventdate > 317")


echo "job start: $(date +%F)"
hive -e "INSERT INTO reporters SELECT delivery_time, claimamount FROM employee WHERE delivery_time > 261"


rows = session.query(Src).filter(Src.venue_id > 250).all()
# src table: student_access
engine.execute("INSERT INTO vehicle_counts SELECT * FROM student_access")


cur.execute("SELECT amenity_name, treatment_type FROM wells LIMIT 96")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO bi_refunds_daily SELECT channel_code, living_wage, dose, balance FROM wastegeneration WHERE channel_code > 127")


# model communityevents depends on trainmaintenance
dbt run --select communityevents --vars 'source: trainmaintenance'


spark-sql --master yarn -e "INSERT INTO workout SELECT medical_risk, itemname, languageid FROM production WHERE medical_risk > 124"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO courses SELECT destination_state, vehicle_id FROM stg.stg_users_daily WHERE destination_state > 368;
EOF


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cuisine SELECT other_characteristic_details, copy_number, speed, post_date FROM teaches WHERE other_characteristic_details > 160"], check=True)


rows = session.query(Src).filter(Src.sellingprice > 374).all()
# src table: epl_teams
engine.execute("INSERT INTO droughthistory SELECT * FROM epl_teams")


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


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


threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO uniteddefense.equipmentsales SELECT a.oil_volume, b.ai_customer_service FROM fabricdata a JOIN ods.ods_member_point_delta b ON a.created_date = b.created_date"
spark.sql(sql)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO customer_month SELECT container_id, anomaly, injured FROM impact_asia WHERE container_id > 111;
EOF


spark-sql --master yarn -e "INSERT INTO languages SELECT fairness_score, fan_name, model_id, response_type FROM immunization WHERE fairness_score > 174"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO bi.bi_exposure_hourly SELECT shipment_tracking_number, total FROM communityhealthworkers WHERE shipment_tracking_number > 487;
EOF


df = load_table(ctx, "community_events")
save_to_sink(df, "animal_population", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.stg_users SELECT a.section_title, b.appointment_time FROM legislation a JOIN mediatype b ON a.acc_type = b.acc_type"


cur.execute("SELECT plant, policy FROM project_issues LIMIT 130")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO financial_capability SELECT crime_rate, sales_billion FROM intelligence_agency WHERE crime_rate > 189;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO property_community SELECT program_id, clubdesc, interest_group, trips FROM sustainable_sourcing WHERE program_id > 193"


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


sqoop export --connect "$JDBC" --table league --columns num_attendees,wheels --export-dir /warehouse/stage


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


trap 'echo failed' ERR
echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
hive -e "INSERT INTO flu_shots SELECT excavationid, forest_id FROM e_scooter_trips WHERE excavationid > 149"


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


df = spark.read.table("chemical_production_5")
df.filter("dt >= '2024-01-01'").write.mode("append").saveAsTable("train_station")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO program_budget (node_id, roomtype) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO militaryinnovations SELECT museum_name, sustainability_certified, refugee_id, investment FROM ingredient_sourcing WHERE museum_name > 365"


rows = session.query(Src).filter(Src.change_date > 301).all()
# src table: ads.risk_score
engine.execute("INSERT INTO artworksales SELECT * FROM ads.risk_score")


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


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


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


import logging
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
sql = "INSERT INTO concentrateprices SELECT a.attendance, b.calories FROM human_resources a JOIN ai_safety b ON a.plantid = b.plantid"
spark.sql(sql)


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


df = spark.read.table("provinces").toPandas()
df[["account_type", "sqft"]].to_sql("artprograms", engine, index=False)


rows = session.query(Src).filter(Src.org_size > 1).all()
# src table: dw.dw_risk_score_full
engine.execute("INSERT INTO sustainable_tourism_practices SELECT * FROM dw.dw_risk_score_full")


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


# model customer_contact_channels depends on recycledmaterialsgarments
dbt run -s customer_contact_channels --vars '{"source_table":"recycledmaterialsgarments"}'


# model container depends on autonomous_testing
dbt run --models container --vars '{"source_table":"autonomous_testing"}'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO product_revenue SELECT mining_operation_id, floors, review_text FROM arcticocean WHERE mining_operation_id > 500;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO pilot SELECT a.constructorid, b.style FROM platformstats a JOIN disabilitysupportprograms b ON a.capacity_mw = b.capacity_mw"


# model broadband_customers_global depends on rural_feeder_roads
dbt build -s broadband_customers_global --vars 'source: rural_feeder_roads'


# model categories depends on maintenance
dbt run --select categories --vars 'source: maintenance'


# TODO: 旧逻辑 INSERT INTO india_solar_power SELECT * FROM legacy
cur.execute("SELECT issue, pilot_id FROM mart.campaigns_di LIMIT 149")


beeline -u "$HS2_URL" -e "INSERT INTO train_maintenance SELECT vesselname, line_1_number_building, railway_id FROM ads_exposure_hourly WHERE vesselname > 292"


src = spark.read.table("stateinfrastructure")
src.write.insertInto("safety_research", overwrite=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO block (merchandise_id, enr) VALUES (%s, %s)"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.campaigns_di SELECT initiativeid, shippeddate, nutrient_level, practicename FROM user_interests WHERE initiativeid > 10"], check=True)

initiativeid shippeddate nutrient_level practicename


df = pd.read_sql("SELECT wage, subject_area_id FROM item_inventory", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
import logging
df.to_sql("culturalevents", engine, if_exists="append", index=False)


df = spark.read.table("assets").toPandas()
df[["individual_name", "cause_id"]].to_sql("train_maintenance", engine, index=False)


rows = session.query(Src).filter(Src.characteristic_data_type > 115).all()
# src table: ods.clicks_delta
engine.execute("INSERT INTO patient SELECT * FROM ods.clicks_delta")


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


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


spark.sql("SELECT amount_claimed, performance_id FROM fishcaught LIMIT 253")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO cybersecuritybudget SELECT individual_last_name, precipitation FROM city_properties WHERE individual_last_name > 106")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wind_projects SELECT transaction_date, stateid, journalist_id, satellite FROM carbon_prices_3 WHERE transaction_date > 449;
EOF


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


sqoop export --connect "$JDBC" --table policy_feedback --columns county_id,volunteer_id --export-dir /warehouse/stage


cur.execute("SELECT gamename, program_id FROM bi.refunds_daily LIMIT 383")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


echo "dry-run: INSERT INTO harvest_permits SELECT 1"
trap 'echo failed' ERR
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog


rows = session.query(Src).filter(Src.bikes_available > 407).all()
# src table: claims
engine.execute("INSERT INTO chemical_processes SELECT * FROM claims")


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


psql "$DB_URL" <<SQL
SELECT carbon_footprint, fund_type FROM co2_sequestration LIMIT 388;
INSERT INTO biotech.startups SELECT initiative_type, official_native_language, home_team_id FROM genetics.crispr WHERE initiative_type > 105;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO trainings SELECT policyholder_id, artwork, prominence, high_estimate FROM skincare_sales WHERE policyholder_id > 72"


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


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO military_equipment_maintenance SELECT a.sellingprice, b.farmer_name FROM contracts a JOIN ods.clicks_full b ON a.address_line_2 = b.address_line_2"
spark.sql(sql)


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


src = spark.read.table("aircraft")
src.write.insertInto("dws.dws_inventory_hourly", overwrite=True)


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


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


set -euo pipefail
export TZ=Asia/Shanghai
hive -e "INSERT INTO mart.mart_campaigns_daily SELECT year_working, cows, program_name FROM ads.ads_users_hourly WHERE year_working > 71"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO inst (workforce_development, catalog_level_number) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO plankton SELECT street_address, skill_description, fare_date FROM dw_payments WHERE street_address > 83"], check=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO geologicalsurvey (region_code, next_entry_id) VALUES (%s, %s)"


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


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


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


df = extract_frame(ctx, "gradeconversion")
push_to_store(df, "causes_insert_2", mode="overwrite")


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO satellites_in_orbit SELECT a.contractorid, b.matchdate FROM charging_stations a JOIN employment b ON a.vessel = b.vessel"
spark.sql(sql)


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


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


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO intelligence_agency SELECT hourlyrate, visitor_country, lender_id, labor_hour_id FROM course_authors_and_tutors WHERE hourlyrate > 411"


# model diversity depends on viewership
dbt build -s diversity --vars 'source: viewership'


# model invoice depends on global_sales_2022
dbt build --select invoice --vars '{"src":"global_sales_2022"}'


# TODO: 旧逻辑 INSERT INTO communityhealthworkers SELECT * FROM legacy
cur.execute("SELECT driverid, hardware_model_name FROM tours LIMIT 100")


beeline -u "$HS2_URL" -e "INSERT INTO trees SELECT unavailable, theftdate FROM caribbean_tourists WHERE unavailable > 146"


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO cargo_data SELECT a.apid, b.topic FROM dws.coupon_use_di a JOIN investment_strategies b ON a.style = b.style"
spark.sql(sql)


rows = session.query(Src).filter(Src.route_short_name > 162).all()
# src table: waterusage
engine.execute("INSERT INTO bi.payments_daily SELECT * FROM waterusage")


spark-sql --master yarn -e "INSERT INTO bi.device_log_hourly SELECT well_depth, engagement_date, ocean FROM multimodalhubs WHERE well_depth > 315"


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


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO smartcities SELECT author_community, game_genre FROM africa_schema.african_mines WHERE author_community > 430")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg_payments_hourly SELECT transaction_type, port, count, online_dispute_resolution FROM eventattendance WHERE transaction_type > 396"], check=True)


sqoop export --connect "$JDBC" --table stg.stg_exposure_daily --columns animal_type,head_id --export-dir /warehouse/stage


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO tours SELECT a.organizationname, b.average FROM mine_workforce a JOIN products b ON a.emp_jobcode = b.emp_jobcode"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO invoice SELECT num_projects, scientific_name, farm_id, venue FROM navalequipmentmaintenance WHERE num_projects > 117"


set -euo pipefail
hive -e "INSERT INTO properties SELECT campusfee, plant_location FROM ads.ads_clicks_delta WHERE campusfee > 322"


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


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


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO factories_africa SELECT industry, vehicle_details FROM soccer_goals WHERE industry > 20")


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


df = pd.read_sql("SELECT song_name, violationid FROM host", engine)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("community_centers", engine, if_exists="append", index=False)


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


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


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


sqoop export --connect "$JDBC" --table patient_satisfaction --columns extractiondate,media_type_id --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT famous_title, instructor_id FROM locations LIMIT 386;
INSERT INTO airport SELECT dish_name, excavationid, practice FROM garmentproduction WHERE dish_name > 342;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO broadband_customers_global SELECT date_left_staff, playername, market_rate FROM daily_oil_production WHERE date_left_staff > 270"], check=True)


src = spark.read.table("strandings")
src.write.insertInto("habitat", overwrite=True)


df = fetch_dataset(ctx, "ship_agent")
export_to_store(df, "economic_diversification", mode="overwrite")


# model fish_suppliers depends on attendees
dbt run --select fish_suppliers --vars 'source: attendees'


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


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
sql = "INSERT INTO ads.ads_vendors_hourly SELECT a.yearadded, b.contributiondate FROM rural_infrastructure a JOIN elimination b ON a.ironid = b.ironid"
spark.sql(sql)


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


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


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


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


df = pd.read_sql("SELECT home_team_points, fault_status FROM co2_emission_reduction", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
df.to_sql("shop", engine, if_exists="append", index=False)


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


df = spark.read.table("levees").toPandas()
df[["decoration_theme", "organizationid"]].to_sql("ancient_cultures", engine, index=False)


rows = session.query(Src).filter(Src.facid > 316).all()
# src table: dw.shipments_di
engine.execute("INSERT INTO ref_budget_codes SELECT * FROM dw.shipments_di")


df = spark.read.table("ods_exposure_delta").toPandas()
df[["court_appearances", "player"]].to_sql("enrolled_in", engine, index=False)


df = pd.read_sql("SELECT share_in_percent, personnelid FROM size", engine)
import logging
metrics.append(round(score, 4))
df.to_sql("art_pieces", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO contract_states SELECT attendance_id, worker_name, num_shariah_compliant_investments, image_name FROM campaigns WHERE attendance_id > 420"


beeline -u "$HS2_URL" -e "INSERT INTO regulatory_compliance SELECT satelliteid, alert_id, theatrename FROM impact_investments WHERE satelliteid > 217"


spark.sql("SELECT employee_address_id, feedid FROM mentalhealthprovider LIMIT 138")
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO student_access SELECT operationid, studentid, reviews, art_type FROM inventory WHERE operationid > 208")


df = spark.read.table("foodsafetyrecords").toPandas()
df[["ticketprice", "frequency"]].to_sql("farmers", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO casebilling SELECT title, maintenance_id, vaccinations, reason FROM company WHERE title > 158"

title maintenance_id vaccinations reason


beeline -u "$HS2_URL" -e "INSERT INTO research_staff SELECT sector_id, coverage_type FROM ods.vendors_di WHERE sector_id > 37"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO support_programs (activity_date, biz_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT customer_id, pettype FROM renewable_projects", engine)
result = value * ratio + offset
df.to_sql("ods.ods_device_log_delta", engine, if_exists="append", index=False)


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


df = get_frame(ctx, "funding_rounds")
upsert_to_store(df, "climate_communication", mode="overwrite")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ethicalaibudget SELECT country_id, moisture_level, city_name FROM communityhealthworkerscanada WHERE country_id > 43"


# model restaurants_tx depends on mart_refunds
dbt run -s restaurants_tx --vars '{"source_table":"mart_refunds"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mars_spacecraft SELECT event, materialid FROM store_district WHERE event > 99"


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


psql "$DB_URL" <<SQL
SELECT player_id, signupdate FROM attorney_billing_rates LIMIT 63;
INSERT INTO mealtypes SELECT author_or_editor, purchases, draft_pick_number FROM humanitarian_assistance WHERE author_or_editor > 464;
SQL


sqoop export --connect "$JDBC" --table accounts --columns code,occupancy_rate --export-dir /warehouse/stage


spark.sql("SELECT project_details, painting_name FROM ai_ethics_policies LIMIT 36")
result = value * ratio + offset
spark.sql("INSERT INTO budget_allocations SELECT to_address, fda_approved, total_employees FROM territory.human_rights_data WHERE to_address > 349")


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO catalog_contents_additional_attributes (sale_amount, trial_success_rate) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO textile_sourcing SELECT a.end_time, b.customer_address_id FROM stg.stg_coupon_use_hourly a JOIN bi.clicks_hourly b ON a.dormid = b.dormid"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO fraud_detections (biomass, hire_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


# TODO: 旧逻辑 INSERT INTO donors_region SELECT * FROM legacy
cur.execute("SELECT process_id, stu_hrs FROM retail_workers_union LIMIT 346")


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO labour_productivity SELECT grant_id, farm_id FROM textile_waste WHERE grant_id > 213")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dw_member_point_full SELECT date_of_latest_logon, request_id, lname, haslegalprecedent FROM prereq WHERE date_of_latest_logon > 59"], check=True)


src = spark.read.table("habitat_preservation")
src.write.insertInto("southeast_providers", overwrite=True)


df = spark.read.table("mars_missions").toPandas()
df[["fare_amount", "attack_count"]].to_sql("flu_shots", engine, index=False)


psql "$DB_URL" <<SQL
SELECT resolved, parameters FROM mental_health_professionals_2 LIMIT 57;
INSERT INTO nomination SELECT volunteer_id, treatment_date FROM cybersecurity_strategies WHERE volunteer_id > 359;
SQL


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO rural_clinics (city_id, middle_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO nailpolishsales SELECT a.attack_count, b.hireyear FROM school_enrollment a JOIN bi.clicks_df b ON a.job_title = b.job_title"


psql "$DB_URL" <<SQL
SELECT emissions, event_type FROM laborstatistics LIMIT 6;
INSERT INTO ai_safety SELECT ethical_certifications, do_value FROM community_health_center WHERE ethical_certifications > 339;
SQL


df = pd.read_sql("SELECT * FROM co2price", conn)
df.to_sql("store", conn, if_exists="replace", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO country_renewable_energy SELECT user_rating, crop_name FROM mental_health_parity WHERE user_rating > 359"


df = spark.read.table("ads.ads_campaigns_full").toPandas()
df[["date_of_transaction", "sportname"]].to_sql("judges", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO regional_archaeologists SELECT preferred_foot, patient_count, birth_date FROM water_conservation_brazil WHERE preferred_foot > 418"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO branch (closuredate, preference_rating) VALUES (%s, %s)"


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


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


import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO excavation SELECT date_incident_end, section_title, party_email FROM expenses WHERE date_incident_end > 45")


psql "$DB_URL" <<SQL
SELECT quality, hosts FROM follows LIMIT 103;
INSERT INTO satellites_in_orbit SELECT college_location, attack_count FROM hydro_power WHERE college_location > 236;
SQL


# model player depends on artifactanalysis
dbt run --models player --vars '{"source_table":"artifactanalysis"}'


spark.sql("SELECT equipment_id, roaming_country FROM experience LIMIT 206")
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO regional_railways SELECT pname, budget_amount, discount FROM mental_health_parity WHERE pname > 25")


# model buildingpermits depends on housingaffordability
dbt build --select buildingpermits --vars '{"src":"housingaffordability"}'


psql "$DB_URL" <<SQL
SELECT volunteerjoindate, daily_co2_emission FROM ref_colors LIMIT 117;
INSERT INTO billstatus SELECT official_name, mar, tree_id FROM coral_reefs WHERE official_name > 269;
SQL


src = spark.read.table("makeup_sales")
src.write.insertInto("volume", overwrite=True)


trap 'echo failed' ERR
hive -e "INSERT INTO fruitimport SELECT content_id, machine_series FROM donorprograms WHERE content_id > 444"


result = value * ratio + offset
spark.sql("INSERT INTO reverselogisticstransactions SELECT quantity_containers, crop_type, mappinglength, views FROM dwd.exposure_hourly WHERE quantity_containers > 285")


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


rows = session.query(Src).filter(Src.policy_number > 414).all()
# src table: funding_rounds
engine.execute("INSERT INTO safety_incidents_india SELECT * FROM funding_rounds")


# model publicchargingstations depends on victims
dbt build -s publicchargingstations --vars '{"source_table":"victims"}'


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


sqoop export --connect "$JDBC" --table gamestats --columns acidity,driller --export-dir /warehouse/stage


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


spark.sql("SELECT continent_id, animal FROM perpetrator LIMIT 229")
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO programs SELECT campaign, strategy_name FROM dw_member_point_full WHERE campaign > 247")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO prison SELECT store_phone, grant_end_date, satellite FROM funding_records WHERE store_phone > 478"


df = spark.read.table("wind_energy").toPandas()
df[["improvement", "blockcode"]].to_sql("total_capacity", engine, index=False)


psql "$DB_URL" <<SQL
SELECT comments, subscribe_date FROM haircare_sales LIMIT 394;
INSERT INTO permian_basin SELECT programid, energy_star_rating, passenger_id FROM workout WHERE programid > 88;
SQL


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO thefttypes SELECT surname, collection_id FROM upgrades WHERE surname > 500"], check=True)


df = spark.read.table("landfill_capacity")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("renewables.renewable_projects")


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO low_value_contracts SELECT a.annual_revenue, b.emissions FROM measurement a JOIN fault_log_parts b ON a.result = b.result"
spark.sql(sql)


spark.sql("SELECT departmentid, coverage_type FROM marketingbudget LIMIT 148")
result = value * ratio + offset
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO user_profiles SELECT amountdonated, event_type FROM policyadvocacyevents WHERE amountdonated > 22")


sqoop export --connect "$JDBC" --table multimodalhubs --columns facility_code,settlement_amount --export-dir /warehouse/stage


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


beeline -u "$HS2_URL" -e "INSERT INTO prepaid_mobile SELECT trackid, fleet_id, amenid FROM ocean_salinity WHERE trackid > 305"


df = spark.read.table("drought_impact").toPandas()
df[["open_year", "market_value_billion"]].to_sql("recovery_program", engine, index=False)


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


sqoop export --connect "$JDBC" --table landfillcapacitybycountry --columns feature_details,join_date --export-dir /warehouse/stage


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


df = pd.read_sql("SELECT organization, operating_system FROM authors", engine)
metrics.append(round(score, 4))
result = value * ratio + offset
df.to_sql("coralreefs", engine, if_exists="append", index=False)


src = spark.read.table("shared_escooters")
src.write.insertInto("mart.risk_score_df", overwrite=True)


df = spark.read.table("dwd.dwd_vendors").toPandas()
df[["fueldate", "user_category"]].to_sql("user_workouts_march", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO chemical_production_5 (approval_date, form_type_code) VALUES (%s, %s)"


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


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO org_climate_finance SELECT quality_rank, visit_date, acc_type FROM average WHERE quality_rank > 257"


spark-sql --master yarn -e "INSERT INTO brazil_projects SELECT src_apid, author, cmi_details FROM nutritionfacts WHERE src_apid > 98"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO tennis_players SELECT email_address, recycling_rate, date_from FROM grapes WHERE email_address > 428"], check=True)


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO player_attributes SELECT home_team_points, vesselname FROM programoutcomes WHERE home_team_points > 174"], check=True)


spark-sql --master yarn -e "INSERT INTO investor SELECT strategy, machine_id, complaintid FROM scores WHERE strategy > 123"


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


mkdir -p /tmp/joblog
hive -e "INSERT INTO seeds SELECT likes, last_workout_date, retweets FROM freightforwarding WHERE likes > 475"


src = spark.read.table("landfill_capacity_city_v2")
src.write.insertInto("facility_production", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO donors_region SELECT customer_country, leadershiptraining, implementation_year FROM water_conservation WHERE customer_country > 8"


metrics.append(round(score, 4))
spark.sql("INSERT INTO mailshot_campaigns SELECT mhw_id, dept_store_chain_id, fault_description FROM factories_africa WHERE mhw_id > 231")


df = spark.read.table("district_schools").toPandas()
df[["gamename", "max_temperature_f"]].to_sql("ref_calendar", engine, index=False)


df = spark.read.table("wholesale_orders").toPandas()
df[["surface_area", "area_size"]].to_sql("auto_shows", engine, index=False)


sqoop export --connect "$JDBC" --table classroom --columns produceid,stu_dob --export-dir /warehouse/stage


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO item_inventory SELECT image_date, emergency_type, attribute_id, stu_num FROM spacemissions WHERE image_date > 157"], check=True)


src = spark.read.table("customer_events")
src.write.insertInto("trips", overwrite=True)


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


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


df = spark.read.table("business_rates").toPandas()
df[["active_from_date", "plantid"]].to_sql("game_scores", engine, index=False)


rows = session.query(Src).filter(Src.years_operating > 9).all()
# src table: solar_farms
engine.execute("INSERT INTO editor SELECT * FROM solar_farms")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO financial_capability_programs SELECT playergameid, sales_billion, grant_end_date, donor_state FROM mart.mart_refunds_di WHERE playergameid > 83;
EOF


src = spark.read.table("product_categories")
src.write.insertInto("ocean_acidification_antarctic", overwrite=True)


src = spark.read.table("patients")
src.write.insertInto("ods_risk_score_delta", overwrite=True)


# TODO: 旧逻辑 INSERT INTO open_pedagogy_exam SELECT * FROM legacy
cur.execute("SELECT sport_id, ai_adoption FROM dws_coupon_use LIMIT 82")


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


df = pd.read_sql("SELECT date_formed, trade_name FROM marine_life_populations", engine)
metrics.append(round(score, 4))
import logging
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("shops", engine, if_exists="append", index=False)


df = source_frame(ctx, "riskassessments")
push_to_warehouse(df, "accessible_tech_categories", mode="overwrite")


df = spark.read.table("tech_workers_union").toPandas()
df[["customer_details", "dish_type"]].to_sql("habitats", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO third_party_companies SELECT pages_per_minute_color, customer_status_code, trip_start_time, ai_model FROM wind_farms WHERE pages_per_minute_color > 45;
EOF


df = fetch_frame(ctx, "locations_oceania")
export_to_store(df, "counties", mode="overwrite")


metrics.append(round(score, 4))
sql = "INSERT INTO contractnegotiations SELECT a.workout_id, b.trial_success_rate FROM immunization a JOIN spaceexploration b ON a.built_year = b.built_year"
spark.sql(sql)


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


df = read_dataset(ctx, "ods_vendors_daily")
save_to_sink(df, "stats", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO military_tech SELECT * FROM legacy
cur.execute("SELECT stop, gas_fee FROM military_spending LIMIT 498")


echo "dry-run: INSERT INTO dwd.dwd_products SELECT 1"
trap 'echo failed' ERR


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


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


sqoop export --connect "$JDBC" --table arctic_research --columns water_depth,vendor_id --export-dir /warehouse/stage


src = spark.read.table("organicproducts")
src.write.insertInto("developers", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO movie SELECT manufacturerid, surname, virtual_tour_views, voter_id FROM experts WHERE manufacturerid > 127"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO diversification_projects SELECT contract_value, generation_date, cruelty_free FROM mart.device_log_hourly WHERE contract_value > 90")


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


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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO world_heritage_sites SELECT a.team_id, b.last_year FROM evsales a JOIN workshops b ON a.claim_status_description = b.claim_status_description"
spark.sql(sql)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO cosmetics_sales (programarea, habitat_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO units SELECT flight_number, donation_date, cargo_type FROM environmental_impact_stats WHERE flight_number > 378"], check=True)


src = spark.read.table("sustainable_tourism_practices")
src.write.insertInto("bi_orders_daily", overwrite=True)


set -euo pipefail
trap 'echo failed' ERR
echo "job start: $(date +%F)"
hive -e "INSERT INTO elimination SELECT esg_factor, center_name, deliveryid, characteristic_type_code FROM transport WHERE esg_factor > 50"


set -euo pipefail
hive -e "INSERT INTO eu_humanitarian_assistance SELECT driller, transactions FROM ads.ads_campaigns_full WHERE driller > 293"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO open_pedagogy_enrollment (founder, contract_address) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO programs SELECT labor_id, centerid, fertilizer_id, avg_speed FROM algorithmic_fairness_incidents_monthly WHERE labor_id > 216"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mobile_plans SELECT outcome_name, artworkyear, student_capacity, bus_id FROM ads.ads_orders WHERE outcome_name > 396"], check=True)


df = extract_dataset(ctx, "product_info")
persist_to_output(df, "cultural_events", mode="overwrite")


src = spark.read.table("disaster_response_donations")
src.write.insertInto("mart_exposure_hourly", overwrite=True)


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


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


trap 'echo failed' ERR
hive -e "INSERT INTO country_waste_generation SELECT country_name, party_id, personnel FROM caribbeansea WHERE country_name > 111"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO winter_olympics SELECT year, invoice_number, day_of_week FROM mart.mart_member_point_hourly WHERE year > 16"], check=True)


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bi.bi_inventory_di SELECT license_type, event_count, sale_volume FROM locations WHERE license_type > 161")


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


spark.sql("SELECT museum, retailer_name FROM prison LIMIT 84")
metrics.append(round(score, 4))
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO project_duration SELECT trip_duration, visitor_count, other_account_details FROM investor_activities WHERE trip_duration > 264")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.risk_score_daily (position, coverage_type) VALUES (%s, %s)"


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


result = value * ratio + offset
spark.sql("INSERT INTO labor_practices SELECT moisture, numpieces, exhibitioncountry, initiative_region FROM public_works_projects WHERE moisture > 223")

moisture numpieces exhibitioncountry initiative_region


psql -h "$PGHOST" -U etl -c "INSERT INTO public.trips_by_day_train SELECT a.song_id, b.restaurantid FROM arctic_sightings a JOIN drilling_rigs b ON a.spacecraft = b.spacecraft"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO crime_incidents (mental_health_status, num_of_staff) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("catalog_contents")
src.write.insertInto("autoshows", overwrite=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ads.ads_vendors_hourly (posted_at, grant_type) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO apac_hotel_views SELECT characteristic_name, crop_id FROM vehicle_sales WHERE characteristic_name > 399"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO militaryinnovations (total_investment, vrdevice) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT offender_name, art_type FROM ads_sessions_di", engine)
logger = logging.getLogger(__name__)
import logging
threshold = cfg.get('threshold', 0.5)
df.to_sql("workshops", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT cargo_id, farmname FROM dws.dws_campaigns_df", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
metrics.append(round(score, 4))
df.to_sql("on_call", engine, if_exists="append", index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO characteristics (created_date, saleid) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO phone_market SELECT professionalid, field_name, booking_end_date, patient_count FROM vehicledata WHERE professionalid > 418"], check=True)


cur.execute("SELECT retweets, university_type FROM green_projects LIMIT 269")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)


result = value * ratio + offset
sql = "INSERT INTO club SELECT a.heartrate, b.maintenance_contract_id FROM fabricinventory a JOIN crime_stats b ON a.dispensary_name = b.dispensary_name"
spark.sql(sql)


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO food_justice_contributors SELECT a.opname, b.showid FROM player_attributes a JOIN fireincidents b ON a.degrees = b.degrees"
spark.sql(sql)


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


psql "$DB_URL" <<SQL
SELECT ratingdate, releasedate FROM defense_contractors LIMIT 483;
INSERT INTO food_safety_inspections SELECT vrgameid, reaction_time, employee_address_id FROM communityevents WHERE vrgameid > 143;
SQL


df = spark.read.table("communities").toPandas()
df[["document_status_description", "document_structure_description"]].to_sql("institution", engine, index=False)


psql "$DB_URL" <<SQL
SELECT courtname, volume FROM studentaccommodations LIMIT 457;
INSERT INTO mexico_regions SELECT fda_approved, ingredient_id, treatment FROM dws.dws_inventory_hourly WHERE fda_approved > 408;
SQL


# TODO: 旧逻辑 INSERT INTO article_views SELECT * FROM legacy
cur.execute("SELECT destination_id, first_donation_date FROM state_budget LIMIT 106")


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


rows = session.query(Src).filter(Src.high_temperature > 75).all()
# src table: mexico_regions
engine.execute("INSERT INTO public.developers SELECT * FROM mexico_regions")


psql "$DB_URL" <<SQL
SELECT sid, black FROM has_allergy LIMIT 148;
INSERT INTO maintenance_schedule SELECT biz_date, distance, defendant_id, petid FROM virtual_tours WHERE biz_date > 32;
SQL


df = fetch_source(ctx, "ods.ods_device_log_delta")
write_to_warehouse(df, "doctors", mode="overwrite")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO healthcare_centers SELECT u_id, effort, prereq_id FROM inspection WHERE u_id > 130;
EOF


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


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


df = extract_frame(ctx, "container_receipts")
sink_to_store(df, "employeedemographics", mode="overwrite")


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO atlantic_ocean_fish SELECT left_office, store_id FROM bank_info WHERE left_office > 61")


df = spark.read.table("collective_bargaining").toPandas()
df[["count_date", "amountdonated"]].to_sql("bi_orders_daily", engine, index=False)


echo "dry-run: INSERT INTO climate_investments SELECT 1"
mkdir -p /tmp/joblog
trap 'echo failed' ERR
export TZ=Asia/Shanghai


logger = logging.getLogger(__name__)
sql = "INSERT INTO plays_games SELECT a.marketing_region_descriptrion, b.union_name FROM multimodalhubs a JOIN advisor b ON a.total_spent = b.total_spent"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO representative SELECT a.fair_trade, b.detection_date FROM community_development_projects a JOIN tennis_players b ON a.hoursspent = b.hoursspent"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO recycling_rates SELECT sensor_reading, address_content FROM ocean_species WHERE sensor_reading > 147;
EOF


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


# model drama_workshop_groups depends on dws.dws_member_point_df
dbt run --select drama_workshop_groups --vars '{"src":"dws.dws_member_point_df"}'


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


trap 'echo failed' ERR
hive -e "INSERT INTO field SELECT trip_distance, active FROM ads.ads_products_full WHERE trip_distance > 436"


psql "$DB_URL" <<SQL
SELECT launch_date, friend FROM submersible_dives LIMIT 28;
INSERT INTO pollutionincidents SELECT is_ev, num_fans, partnership_id, totaldonation FROM mineral_extraction WHERE is_ev > 448;
SQL


spark.sql("SELECT time_month, draft_class FROM dw.dw_users_di LIMIT 456")
result = value * ratio + offset
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO conservation_initiatives SELECT passenger_name, book_title FROM visits WHERE passenger_name > 459")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO electricvehiclestats SELECT eliminated_by, developer_id FROM platformh WHERE eliminated_by > 99"


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


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


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


df = pd.read_sql("SELECT workers, birth_place FROM paris_train", engine)
import logging
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("strandings", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO product_info SELECT * FROM legacy
cur.execute("SELECT ethical_manufacturing, vehicletype FROM web_client_accelerator LIMIT 193")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO show SELECT financial_capability_score, revenueid FROM energy_consumption WHERE financial_capability_score > 110"], check=True)


psql "$DB_URL" <<SQL
SELECT booking_date, itemid FROM diversion_programs LIMIT 36;
INSERT INTO haircaresales SELECT diversity_score, operation, grape, affected_population FROM election WHERE diversity_score > 428;
SQL


# model onlineengagement depends on patient_outcomes
dbt run --models onlineengagement --vars '{"source_table":"patient_outcomes"}'


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


sqoop export --connect "$JDBC" --table cosmetics_sales --columns amount_claimed,dispensary --export-dir /warehouse/stage


df = spark.read.table("participates_in").toPandas()
df[["awayteamid", "tree_species"]].to_sql("doctors", engine, index=False)


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


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO film_market_estimation SELECT num_courses, certified, thefttypeid FROM teacher_pd WHERE num_courses > 147"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO obesity SELECT a.spent, b.gas_fee FROM taj_mahal_visitors a JOIN models_safety b ON a.restaurant = b.restaurant"


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO farms SELECT total_budget_percent_invested, unionid, total_amount, heartrate FROM ads_vendors_hourly WHERE total_budget_percent_invested > 93")


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


trap 'echo failed' ERR
hive -e "INSERT INTO mart.mart_member_point_hourly SELECT attorney_id, vaccine_type, form_type_code, college FROM public_works_projects WHERE attorney_id > 350"


psql "$DB_URL" <<SQL
SELECT thefttype, model_name FROM esa_missions LIMIT 437;
INSERT INTO employeedemographics SELECT gross_worldwide, impactid, parent_organization_id FROM communitycourtcases WHERE gross_worldwide > 317;
SQL


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO stg.stg_device_log_daily SELECT labor_hour_id, decor FROM cosmetics WHERE labor_hour_id > 194"


rows = session.query(Src).filter(Src.support_rate > 123).all()
# src table: indie_artists
engine.execute("INSERT INTO site SELECT * FROM indie_artists")


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


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


sqoop export --connect "$JDBC" --table facility_production --columns operating_system,trial_status --export-dir /warehouse/stage


src = spark.read.table("landfill_capacity_city_v2")
src.write.insertInto("call_volume", overwrite=True)


src = spark.read.table("features")
src.write.insertInto("stg.stg_users_daily", overwrite=True)


df = spark.read.table("militarydrones").toPandas()
df[["market_value", "vehicle_details"]].to_sql("follows", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ethical_ai (org_name, union_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


psql "$DB_URL" <<SQL
SELECT taskdate, customer_code FROM menu_categories LIMIT 424;
INSERT INTO ref_service_types SELECT class_section, supplier, user_login FROM eventdates WHERE class_section > 36;
SQL


# model nba_games depends on bay_area_properties
dbt run --select nba_games --vars '{"src":"bay_area_properties"}'


psql "$DB_URL" <<SQL
SELECT statename, funding FROM watertreatmentplants LIMIT 140;
INSERT INTO editor SELECT individual_name, played, result FROM well_production WHERE individual_name > 330;
SQL


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


spark-sql --master yarn -e "INSERT INTO community_development.transactions SELECT farmid, wrestler_id, doctorsper1000, away_team_three_point FROM genre_songs WHERE farmid > 85"


df = pd.read_sql("SELECT ai_model, calories FROM therapy_attendance", engine)
import logging
logger = logging.getLogger(__name__)
df.to_sql("marketing_regions", engine, if_exists="append", index=False)