sqoop export --connect "$JDBC" --table stock --columns minesite,theme --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO maintenancerequests SELECT rank_in_round, interest_group, volume FROM crop_temperature WHERE rank_in_round > 25"


spark-sql --master yarn -e "INSERT INTO mentalhealthparityviolations SELECT facultyid, student FROM aircraft WHERE facultyid > 57"


psql -h "$PGHOST" -U etl -c "INSERT INTO consumer_preference SELECT a.year_working, b.neighborhood FROM workers a JOIN courts b ON a.event_details = b.event_details"


df = pd.read_sql("SELECT video_id, network FROM org_volunteer", engine)
metrics.append(round(score, 4))
df.to_sql("school_bus", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO farmer_details SELECT clientid, financially_capable FROM student_program_mapping WHERE clientid > 333"


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


export TZ=Asia/Shanghai
set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO projectemployees SELECT subscribe_date, principal_activities, studio, first_name FROM equipment_maintenance WHERE subscribe_date > 480"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO party_forms (num_sessions, asset_disposed_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO military_personnel_africa (address_line_2, carbon_offset_tons) VALUES (%s, %s)"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO transaction SELECT outcome, asset_make, document_date, decor FROM skincareinventory WHERE outcome > 56"


# model machine depends on traffic_violations
dbt build -s machine --vars '{"src":"traffic_violations"}'


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


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


sqoop export --connect "$JDBC" --table cargo_tracking --columns account_type,collection_id --export-dir /warehouse/stage


spark.sql("SELECT shipmentid, zone_name FROM train_station LIMIT 471")
retries = int(os.environ.get('RETRIES', '3'))
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO market_access SELECT service_id, authid FROM trees WHERE service_id > 398")


psql "$DB_URL" <<SQL
SELECT customer_details, num_tools FROM membership_register_branch LIMIT 229;
INSERT INTO baseball_teams SELECT years_played, customer_code, treatment_id, updatedate FROM trust WHERE years_played > 124;
SQL


rows = session.query(Src).filter(Src.contractid > 413).all()
# src table: gamegenres
engine.execute("INSERT INTO marine_life_populations SELECT * FROM gamegenres")


cur.execute("SELECT playtime, blockcode FROM team LIMIT 219")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_payments_df SELECT a.jobcategory, b.fuelconsumed FROM student_addresses a JOIN economic_diversification_efforts b ON a.intervention_type = b.intervention_type"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ads_users_hourly SELECT a.restaurant_id, b.state_id FROM fleet_management a JOIN network_infrastructure b ON a.focal_length_mm = b.focal_length_mm"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO startup_founders SELECT cost_id, black, founder_group FROM jupiter_spacecraft WHERE cost_id > 5;
EOF


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


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
sql = "INSERT INTO video_content SELECT a.theftdate, b.winning_aircraft FROM projecttimeline a JOIN endowment b ON a.student_id = b.student_id"
spark.sql(sql)


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO therapy_session (advocate_name, num_of_audience) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table emergencies --columns subject_area_id,playerregion --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT dno, date_in_location_from FROM student LIMIT 380;
INSERT INTO sportsinfo SELECT episode_number, peakhourid, customer_name FROM geologicalsurvey WHERE episode_number > 183;
SQL


cur.execute("SELECT satelliteid, health_equity_metric_1 FROM dw.dw_events_di LIMIT 176")
rows = cur.fetchall()
result = value * ratio + offset


# TODO: 旧逻辑 INSERT INTO dw_vendors_di SELECT * FROM legacy
cur.execute("SELECT total_donation_amount, community_id FROM recyclingcenters LIMIT 169")


psql "$DB_URL" <<SQL
SELECT incident_id, classtype FROM eco_materials LIMIT 368;
INSERT INTO battery_projects SELECT game_name, projectid, dateundergoes FROM carbon_emissions WHERE game_name > 427;
SQL


df = fetch_frame(ctx, "gamesessions")
write_to_target(df, "waterconservationbudget", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO organization SELECT media_outlet, stationid, asset_acquired_date, vaccination_status FROM bi_products WHERE media_outlet > 326"], check=True)


msg = "would run: INSERT INTO pollutionincidents SELECT 1"
logger.info(msg)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))


df = pd.read_sql("SELECT avg_usage, vesselid FROM prepaid_mobile", engine)
logger = logging.getLogger(__name__)
df.to_sql("beauty_products", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO songs SELECT inclusive_housing_policy, enrollment_date, average FROM sustainable_practices WHERE inclusive_housing_policy > 484"


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


spark-sql --master yarn -e "INSERT INTO cinema SELECT claim_type, stockid, survey_id FROM ports WHERE claim_type > 92"


rows = session.query(Src).filter(Src.openning_year > 103).all()
# src table: bi.events_delta
engine.execute("INSERT INTO wastewatertreatment SELECT * FROM bi.events_delta")


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


spark-sql --master yarn -e "INSERT INTO pharmasales SELECT pet_age, evaluated_for_fairness FROM tourism_activities WHERE pet_age > 485"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO recycling_stats SELECT market_rate, artifact_id FROM yoga WHERE market_rate > 272")


src = spark.read.table("initiatives")
src.write.insertInto("totalenergyproduction", overwrite=True)


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


trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO store SELECT suppliername, date_payment_made FROM fields WHERE suppliername > 33"


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


df = pd.read_sql("SELECT * FROM global_sales_2022", conn)
df.to_sql("publicchargingstations", conn, if_exists="replace", index=False)


result = value * ratio + offset
sql = "INSERT INTO program_funding_2 SELECT a.principal_activities, b.iata FROM economic_diversification a JOIN strains b ON a.oil_production = b.oil_production"
spark.sql(sql)


src = spark.read.table("initiatives")
src.write.insertInto("space_exploration", overwrite=True)


spark.sql("SELECT surname, observation_id FROM forms LIMIT 217")
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO bi.bi_inventory_full SELECT school_id, school_code, productivity FROM chemicals_annual WHERE school_id > 12")


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


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


# TODO: 旧逻辑 INSERT INTO paris_train SELECT * FROM legacy
cur.execute("SELECT platformid, classtype FROM hotel_tech_adoptions LIMIT 133")


df = spark.read.table("machinery").toPandas()
df[["problem_description", "testtypeid"]].to_sql("mart.mart_device_log", engine, index=False)


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


psql "$DB_URL" <<SQL
SELECT donortype, album FROM total_consumption LIMIT 114;
INSERT INTO station_company SELECT participant_type_code, equipment_type, booking_end_date, trial_id FROM mart.shipments_delta WHERE participant_type_code > 270;
SQL


spark.sql("SELECT garment_id, value FROM inventory LIMIT 87")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO people SELECT sector_id, route_name, event_id FROM satellitedata WHERE sector_id > 158")


beeline -u "$HS2_URL" -e "INSERT INTO astronauts SELECT vendorname, participated_in_open_pedagogy FROM investment WHERE vendorname > 222"


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


# model dws_inventory_di depends on seamounts
dbt build --models dws_inventory_di --vars '{"src":"seamounts"}'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO malicious_activity SELECT mine_type, vulnerability_name FROM industry_funding WHERE mine_type > 406"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sitem SELECT plant_name, scan_date, garment_type FROM ma_inspections WHERE plant_name > 427;
EOF


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


rows = session.query(Src).filter(Src.staff_id > 253).all()
# src table: vehicle_registrations
engine.execute("INSERT INTO investments SELECT * FROM vehicle_registrations")


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


psql "$DB_URL" <<SQL
SELECT faculty_id, member_in_charge_id FROM shipment LIMIT 358;
INSERT INTO security_incidents SELECT editor_id, amount_due FROM waterconsumptionbyoperation WHERE editor_id > 296;
SQL


psql "$DB_URL" <<SQL
SELECT production_date, calendar FROM ads.ads_cart_item_hourly LIMIT 464;
INSERT INTO reporters SELECT num_shariah_compliant_investments, quantity_sold, main_services, mission_id FROM reservations WHERE num_shariah_compliant_investments > 335;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO invoice_lines SELECT a.quantity_sold, b.borough FROM trainingprograms a JOIN vesselfuel b ON a.years_played = b.years_played"


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


cur.execute("SELECT daily_consumption, eventname FROM uel_top10 LIMIT 469")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


sqoop export --connect "$JDBC" --table animals --columns inclusivehousing,digital --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO properties SELECT studio_name, claim_id, review_score, typical_buying_price FROM uel_top10 WHERE studio_name > 349"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO field5 SELECT primaryaffiliation, complaint_type_code FROM az_drought_impact WHERE primaryaffiliation > 222;
EOF


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


spark.sql("SELECT cases_count, sustainability_score FROM stg.stg_exposure_daily LIMIT 212")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO art_workshops SELECT max_temperature_f, class_senator_vote, restaurantname FROM disabilitysupportprograms WHERE max_temperature_f > 134")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO roles SELECT institution_name, store_id FROM cinema WHERE institution_name > 246"], check=True)


logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO taj_mahal_visitors SELECT main_industry, porphyria, major, factory_name FROM pipelines WHERE main_industry > 40")


df = source_dataset(ctx, "stg.member_point_df")
sink_to_store(df, "disasters", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO yttrium_production SELECT a.ingredient, b.wildlife_type_id FROM skills a JOIN usdaviolations b ON a.employee_id = b.employee_id"


rows = session.query(Src).filter(Src.drugname > 255).all()
# src table: labor_statistics
engine.execute("INSERT INTO innovation_trends SELECT * FROM labor_statistics")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO player_college SELECT materialtype, ai_adoption_date, asset_make, investment FROM stg.campaigns_df WHERE materialtype > 388;
EOF


# model spacecrafts depends on vehicle
dbt run --select spacecrafts --vars '{"src":"vehicle"}'


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


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO sustainableprojects SELECT uk_vat_number, left_office, savingsid FROM sustainable_building WHERE uk_vat_number > 45"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO animals SELECT certification, unit_id, statement_id FROM otas WHERE certification > 207"], check=True)


spark.sql("SELECT complaintid, furniture_id FROM cargos LIMIT 281")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO zipcodes SELECT manager_name, cargo_weight, sustainable, tech_id FROM waste_data WHERE manager_name > 205")


spark-sql --master yarn -e "INSERT INTO membership_register_branch SELECT certification, dysprosium_prod, stock FROM sites WHERE certification > 196"


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


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


beeline -u "$HS2_URL" -e "INSERT INTO canada_tech SELECT crime_rate, founder_identifies_as_lgbtq, garmentid, discovered_date FROM taj_mahal_visitors WHERE crime_rate > 207"


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


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


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


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


df = pd.read_sql("SELECT base_id, ethnicity FROM papers", engine)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
df.to_sql("dw_payments", engine, if_exists="append", index=False)


cur.execute("SELECT teacher_id, patentexpirationdate FROM garments LIMIT 249")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


echo "dry-run: INSERT INTO donations_insert_2 SELECT 1"
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}


# TODO: 旧逻辑 INSERT INTO product SELECT * FROM legacy
cur.execute("SELECT manager_id, genre FROM ingredientsvegancrueltyfree LIMIT 32")


df = pd.read_sql("SELECT * FROM global_tournament", conn)
df.to_sql("genetics_stats.research_projects", conn, if_exists="replace", index=False)


# TODO: 旧逻辑 INSERT INTO stateinfrastructure SELECT * FROM legacy
cur.execute("SELECT acc_bal, destination_id FROM therapy LIMIT 41")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO eco_hotels (investor_name, review_text) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT lender_id, sustainabilityid FROM mine LIMIT 449")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO party_events SELECT maintenance_date, sea FROM donations2022 WHERE maintenance_date > 479")


cur.execute("SELECT round_date, mappinglength FROM participates_in LIMIT 284")
rows = cur.fetchall()
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO renewable_projects SELECT num_schools, measurement_date FROM public_transportation_routes WHERE num_schools > 55")


df = load_frame(ctx, "ads.ads_inventory_df")
save_to_target(df, "emerging_markets.digital_assets", mode="overwrite")


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO wildlife_sanctuaries SELECT grade, co2_reduction_tons, electoral_register_id FROM behavior_incident WHERE grade > 128"


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO climate_finance_re SELECT online_dispute_resolution, college_id, prereq_id, galleryid FROM exhibition_record WHERE online_dispute_resolution > 193")


spark-sql --master yarn -e "INSERT INTO ods_member_point_full SELECT hours_played, framework_name FROM ads.ads_vendors_hourly WHERE hours_played > 202"


# TODO: 旧逻辑 INSERT INTO vehicle SELECT * FROM legacy
cur.execute("SELECT has_aloe_vera, resolved FROM course LIMIT 322")


retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO transportation_union SELECT a.roomtype, b.menu_category FROM procedures a JOIN mart.mart_users b ON a.num_employees = b.num_employees"
spark.sql(sql)


metrics.append(round(score, 4))
sql = "INSERT INTO stg.stg_products_full SELECT a.building_full_name, b.fanid FROM coowners a JOIN waste b ON a.membergender = b.membergender"
spark.sql(sql)


df = spark.read.table("tickets_3").toPandas()
df[["authors", "heritage_site_id"]].to_sql("platformg", engine, index=False)


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO pipelines SELECT budget_million, country, assets, organisation_type_description FROM gender WHERE budget_million > 312;
EOF


df = get_source(ctx, "rural_hospitals")
export_to_output(df, "field_production", mode="overwrite")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO document_structures SELECT animal, date_complaint_raised FROM dwd_coupon_use_hourly WHERE animal > 410;
EOF


src = spark.read.table("ref_calendar")
src.write.insertInto("hires", overwrite=True)


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


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


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


# model consumer_preference depends on efforts
dbt build --models consumer_preference --vars '{"src":"efforts"}'


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


# model musicgenre depends on debris
dbt run --models musicgenre --vars '{"source_table":"debris"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO musical (roomid, fish_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO match SELECT artwork, event_type_id, individual_id, hometeam FROM gamesessions WHERE artwork > 443;
EOF


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


src = spark.read.table("climate_finance_organizations")
src.write.insertInto("fireincidents", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO healthcare_centers SELECT union_member_id, floor_exercise_points, attack_country FROM blockchain_tech WHERE union_member_id > 118"


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


psql "$DB_URL" <<SQL
SELECT payment_method_code, ironquantity FROM marine_life_research LIMIT 28;
INSERT INTO animal_budget SELECT museum, negotiation_date FROM host WHERE museum > 217;
SQL


sqoop export --connect "$JDBC" --table bi.refunds_daily --columns bus_id,policyholderid --export-dir /warehouse/stage


result = value * ratio + offset
metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO drug_approval SELECT product, medical_professional_id FROM artsales WHERE product > 370")


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


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


psql "$DB_URL" <<SQL
SELECT subscribe_date, month FROM body_builder LIMIT 54;
INSERT INTO dailyapplestreams SELECT bookings, trip_end_time FROM train_station WHERE bookings > 265;
SQL


msg = "would run: INSERT INTO professionals SELECT 1"
logger.info(msg)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


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


sqoop export --connect "$JDBC" --table ingredients --columns rate,attendees --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO design_standards SELECT tonnage, course_completion, winning_pilot, professional_development_programs FROM new_schedules WHERE tonnage > 114"


echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO daily_production SELECT customer, skill_id, yield FROM drivers WHERE customer > 182"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO discount_coupons (authors, school) VALUES (%s, %s)"


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


cur.execute("SELECT trainingyear, class_section FROM artifactanalysis LIMIT 367")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


cur.execute("SELECT contract_count, lastname FROM spaceexploration LIMIT 496")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
if not rows:
    logger.warning('empty result')


spark.sql("SELECT products_this_year, trip_end_time FROM underwater_cables LIMIT 362")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO textileworkers SELECT invested, treasurer_vote, game_genre FROM spaceexploration WHERE invested > 362")


result = value * ratio + offset
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO feed SELECT a.nurse, b.appointment_date FROM ods.ods_campaigns_delta a JOIN district_schools b ON a.brandid = b.brandid"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO calibration_data2 SELECT a.hardware_colours, b.satelliteid FROM australia_offset_programs a JOIN labor_hours b ON a.founder_lgbtq = b.founder_lgbtq"


# model totalenergyproduction depends on policyimpact
dbt run --select totalenergyproduction --vars 'source: policyimpact'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO train_maintenance SELECT petid, dob FROM nasa_mars_program WHERE petid > 395;
EOF


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


df = spark.read.table("pets")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("habitat3")


df = source_input(ctx, "bi.bi_events_daily")
dump_to_sink(df, "ref_document_status", mode="overwrite")


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


spark-sql --master yarn -e "INSERT INTO dw_payments SELECT maintenancedate, donator_name FROM ads_cart_item_hourly WHERE maintenancedate > 32"


src = spark.read.table("decentralized_apps")
src.write.insertInto("dwd_payments_delta", overwrite=True)


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


rows = session.query(Src).filter(Src.destination_state > 58).all()
# src table: field_production
engine.execute("INSERT INTO artworks SELECT * FROM field_production")


psql "$DB_URL" <<SQL
SELECT orderid, last_service FROM bi.bi_payments_delta LIMIT 186;
INSERT INTO deep_sea_expeditions SELECT dispensaryid, menuid, total_amount FROM affordablehousing WHERE dispensaryid > 390;
SQL


# model program_outcomes depends on autonomousvehicles
dbt build --select program_outcomes --vars 'source: autonomousvehicles'


rows = session.query(Src).filter(Src.paperid > 198).all()
# src table: recyclednylongarments
engine.execute("INSERT INTO biodiversity SELECT * FROM recyclednylongarments")


df = spark.read.table("exhibition_visits").toPandas()
df[["organisation_id", "method_id"]].to_sql("jupiter_missions", engine, index=False)


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


# TODO: 旧逻辑 INSERT INTO address SELECT * FROM legacy
cur.execute("SELECT card_number, amount_donated FROM tourist_destinations LIMIT 289")


df = read_input(ctx, "smartcities")
dump_to_target(df, "productivity", mode="overwrite")


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


result = value * ratio + offset
spark.sql("INSERT INTO euroavev SELECT tourist_id, metric_id, violation_type, component_name FROM food_justice WHERE tourist_id > 215")


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


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


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


spark.sql("SELECT dispensary_id, postal_code FROM livestock LIMIT 42")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO ca_menu_items SELECT invoice_details, missionid, dock_status FROM energy_production WHERE invoice_details > 76")


psql -h "$PGHOST" -U etl -c "INSERT INTO ods.ods_coupon_use_di SELECT a.workshop_id, b.submission_id FROM contract_timeline a JOIN gamesales b ON a.unavailable = b.unavailable"


cur.execute("SELECT catalog_entry_id, co2_reduction_tons FROM livestock LIMIT 106")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO languages SELECT item, extraction_date FROM workplace_safety WHERE item > 414;
EOF


src = spark.read.table("first_notification_of_loss")
src.write.insertInto("investments", overwrite=True)


trap 'echo failed' ERR
hive -e "INSERT INTO daily_transaction_volume SELECT building_full_name, centername FROM baseball_teams WHERE building_full_name > 91"


spark.sql("SELECT trainingname, average_age FROM ods.sessions_daily LIMIT 500")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO location SELECT date_of_latest_logon, order_id FROM dw.dw_member_point_hourly WHERE date_of_latest_logon > 19")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO flight_safety SELECT bname, first_name, communityid, ihsaa_football_class FROM sustainabilityratings WHERE bname > 167"


psql "$DB_URL" <<SQL
SELECT hearingdate, student_details FROM excavationsites LIMIT 303;
INSERT INTO chemical_production_3 SELECT vendorid, average, subject FROM ods.ods_exposure_delta WHERE vendorid > 110;
SQL


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO animal_species SELECT a.primary_advisor, b.trial_success_rate FROM recall_reports a JOIN smart_city_projects b ON a.vehicle_id = b.vehicle_id"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO consumer SELECT a.dispensaryid, b.highscore FROM circular_economy a JOIN projects b ON a.mine_name = b.mine_name"


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


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


spark.sql("SELECT committee, menuname FROM safety_violations LIMIT 116")
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO airlines SELECT created_date, songid, unionid FROM maintenance_requests WHERE created_date > 201")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO taj_mahal_visitors SELECT retailer_id, color_description, resolution FROM salary WHERE retailer_id > 494"], check=True)


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO displaced_people SELECT trip_id, recycling_rate FROM dw.dw_payments_full WHERE trip_id > 385")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vessel SELECT registered_date, reaction_time FROM water_usage WHERE registered_date > 66"


psql -h "$PGHOST" -U etl -c "INSERT INTO atlantic_plate SELECT a.portname, b.menu_type FROM device_usage a JOIN ucl_top10 b ON a.mhw_id = b.mhw_id"


# model exam_results depends on drills
dbt build -s exam_results --vars '{"src":"drills"}'


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


# model dorm depends on textileworkers
dbt build --models dorm --vars 'source: textileworkers'


# TODO: 旧逻辑 INSERT INTO water_sources SELECT * FROM legacy
cur.execute("SELECT customer_first_name, zone FROM collections LIMIT 226")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO musical (tourist_id, issue_month) VALUES (%s, %s)"


df = spark.read.table("dw.inventory_delta").toPandas()
df[["calendar", "nurse"]].to_sql("chemical_processes", engine, index=False)


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO strains (production, news_story_id) VALUES (%s, %s)"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO innovation_metrics SELECT date_of_birth, element, spill_name, date_became_customer FROM healthcareaccess WHERE date_of_birth > 35;
EOF


rows = session.query(Src).filter(Src.detention_type_description > 278).all()
# src table: investment_rounds
engine.execute("INSERT INTO labor_hours SELECT * FROM investment_rounds")


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO african_union_countries SELECT partitionid, fault_short_name, initiative_type FROM station_company WHERE partitionid > 135")


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO road_construction SELECT contactid, assessmentdate, mining_operation, donor FROM indie_artists WHERE contactid > 91")

contactid assessmentdate mining_operation donor


mkdir -p /tmp/joblog
trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO shared_rides_tokyo SELECT mailing_date, foreign, advocate_name FROM donation WHERE mailing_date > 155"


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


# TODO: 旧逻辑 INSERT INTO climate_adaptation_re SELECT * FROM legacy
cur.execute("SELECT low_estimate, phase FROM music_festival LIMIT 185")


# TODO: 旧逻辑 INSERT INTO ads.ads_users_hourly SELECT * FROM legacy
cur.execute("SELECT media_outlet, maintenance_id FROM crypto_transactions LIMIT 397")


src = spark.read.table("eu_data_usage")
src.write.insertInto("mart.campaigns_di", overwrite=True)


# TODO: 旧逻辑 INSERT INTO paris_train SELECT * FROM legacy
cur.execute("SELECT contract_start_date, total_value_purchased FROM vehicle_registrations LIMIT 239")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mart_exposure_di SELECT a.organization_id, b.permitid FROM teachers a JOIN nasa_mars_program b ON a.numhearings = b.numhearings"


# model caribbeansea depends on emerging_markets.digital_assets
dbt run --models caribbeansea --vars '{"source_table":"emerging_markets.digital_assets"}'


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


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


# model ads_vendors_hourly depends on stg.events_hourly
dbt run -s ads_vendors_hourly --vars '{"src":"stg.events_hourly"}'


df = get_table(ctx, "assets")
sink_to_sink(df, "water_sources", mode="overwrite")


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


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


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


# TODO: 旧逻辑 INSERT INTO ads.ads_payments_delta SELECT * FROM legacy
cur.execute("SELECT business_size, city FROM mart.mart_sessions_di LIMIT 41")


# TODO: 旧逻辑 INSERT INTO dw_vendors_di SELECT * FROM legacy
cur.execute("SELECT game, enrollment_date FROM traditionalarts LIMIT 170")


import logging
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO clinic_2022 SELECT deliveryaddress, length_feet FROM dws.dws_orders WHERE deliveryaddress > 319")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.mart_products_hourly (prof_num, origin) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = get_table(ctx, "euroavev")
sink_to_sink(df, "smart_grids", mode="overwrite")


df = spark.read.table("race_ethnicity").toPandas()
df[["health_equity_metric_2", "item"]].to_sql("nailpolishsales", engine, index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO staff_roles (emp_jobcode, year_opened) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO epl_teams SELECT completed, menu_name, incident, lat FROM renewables.renewable_projects WHERE completed > 204"], check=True)


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


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO nba SELECT num_projects, shipment_year FROM tracks WHERE num_projects > 459")


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO expenses SELECT a.retweets, b.total_donation_amount FROM trees a JOIN collections b ON a.decision = b.decision"
spark.sql(sql)


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


metrics.append(round(score, 4))
sql = "INSERT INTO urban_transportation SELECT a.network_name, b.violation_id FROM engineer_visits a JOIN arrivals b ON a.available_yn = b.available_yn"
spark.sql(sql)


rows = session.query(Src).filter(Src.open_year > 394).all()
# src table: broadband_plans
engine.execute("INSERT INTO stars SELECT * FROM broadband_plans")


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


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


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


df = spark.read.table("arcticwildlifereserve").toPandas()
df[["purchase_details", "studio"]].to_sql("florida_conservation_initiatives", engine, index=False)


df = spark.read.table("tasks").toPandas()
df[["sentence_id", "museum"]].to_sql("call_volume", engine, index=False)


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


psql "$DB_URL" <<SQL
SELECT sport_id, kills FROM basketball_match LIMIT 102;
INSERT INTO pacific_ocean SELECT membership_id, component_name, type_of_thing_code FROM mart.mart_users_delta WHERE membership_id > 394;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO video_games (extraction_date, contributorname) VALUES (%s, %s)", (uid, amt))
conn.commit()


beeline -u "$HS2_URL" -e "INSERT INTO crypto_transactions SELECT statename, market_share, meal_name FROM pilot WHERE statename > 233"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO project_timelines SELECT shipment_tracking_number, student FROM exhibition_visits WHERE shipment_tracking_number > 161"], check=True)


df = pd.read_sql("SELECT savings, employee_id FROM council_tax", engine)
result = value * ratio + offset
df.to_sql("ingredient", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO behavior_incident SELECT labordate, artifact_id, vessel_id FROM visitordemographics WHERE labordate > 351"


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


psql "$DB_URL" <<SQL
SELECT negative, genderid FROM eu_data_usage LIMIT 38;
INSERT INTO maintenance SELECT dependent_name, planned_delivery_date, official_native_language, playtime FROM band WHERE dependent_name > 231;
SQL


psql -h "$PGHOST" -U etl -c "INSERT INTO government.region SELECT a.dnumber, b.movie FROM publication a JOIN smartcontracts b ON a.hireid = b.hireid"


src = spark.read.table("climateresearch")
src.write.insertInto("ods_shipments_df", overwrite=True)


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


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


df = pd.read_sql("SELECT years_working, year FROM regulatory_compliance", engine)
threshold = cfg.get('threshold', 0.5)
import logging
df.to_sql("safety_incident", engine, if_exists="append", index=False)


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


import logging
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO safety_testing SELECT a.section_id, b.editor_id FROM london.stations a JOIN co2emissions b ON a.wellname = b.wellname"
spark.sql(sql)


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


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


# model ref_locations depends on fieldd_info
dbt build --select ref_locations --vars 'source: fieldd_info'


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


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


result = value * ratio + offset
import logging
logger = logging.getLogger(__name__)
sql = "INSERT INTO movie SELECT a.transaction_date, b.model FROM sustainabilityratings a JOIN high_risk b ON a.mouse_id = b.mouse_id"
spark.sql(sql)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO architect SELECT trainingid, organic, caseid FROM ocean_floor_mapping WHERE trainingid > 279"


df = source_table(ctx, "producersnewmexico")
write_to_output(df, "tv_shows_genre", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO tourism SELECT * FROM legacy
cur.execute("SELECT governor, fabricid FROM recyclingrates LIMIT 359")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO faculty_participates_in (average_attendance, devices) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO labor_practices SELECT algorithm, labor_hour_id, extraction_date, city FROM fairness_scores WHERE algorithm > 279"


# TODO: 旧逻辑 INSERT INTO feedback SELECT * FROM legacy
cur.execute("SELECT stuid, art_type FROM studies LIMIT 159")


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


psql "$DB_URL" <<SQL
SELECT treatment_date, star_rating_description FROM eventattendance LIMIT 92;
INSERT INTO exhibitionattendance SELECT programoutcomeid, traveler_id, submission_id FROM arctic_sightings WHERE programoutcomeid > 21;
SQL


df = pd.read_sql("SELECT algorithm_name, eventname FROM cargos", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
df.to_sql("stores", engine, if_exists="append", index=False)


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


beeline -u "$HS2_URL" -e "INSERT INTO mental_health_parity SELECT statement_id, system_id, dorm_name FROM soccer_goals WHERE statement_id > 196"


src = spark.read.table("book")
src.write.insertInto("hydro_power", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO transportation_fleet (advisor, diet) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("labor_hours").toPandas()
df[["inclusive", "exhibitioncountry"]].to_sql("dwd.dwd_campaigns_df", engine, index=False)


spark-sql --master yarn -e "INSERT INTO rural_development.agriculture_projects SELECT milestone, language FROM courts WHERE milestone > 497"


spark.sql("SELECT vice_president_vote, sales_count FROM mart.mart_users_di LIMIT 393")
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO artsandcrafts SELECT medium, shelter_id FROM vesselfuel WHERE medium > 353")


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


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
sql = "INSERT INTO green_energy_lending_programs SELECT a.completed_course, b.date_to FROM highest_scores a JOIN mailshot_campaigns b ON a.birth_date = b.birth_date"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO classroom SELECT assets, budgeted FROM properties WHERE assets > 393"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO affiliated_with SELECT a.document_name, b.saleamount FROM trends_2022 a JOIN circular_economy_companies b ON a.end_date = b.end_date"


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


spark-sql --master yarn -e "INSERT INTO geologicalsurvey SELECT trainingdate, asset_type, avg_depth, dec FROM artwork_styles WHERE trainingdate > 246"


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO train_lines SELECT issues, date_of_completion, water_temp FROM cargo_tracking WHERE issues > 83;
EOF


cur.execute("SELECT mine_type, machine_series FROM student_addresses LIMIT 381")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


df = spark.read.table("soil_moisture").toPandas()
df[["product_description", "order_shipping_charges"]].to_sql("enzyme", engine, index=False)


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


cur.execute("SELECT time_hour, cargoid FROM tryout LIMIT 473")
rows = cur.fetchall()
import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


src = spark.read.table("shared_rides_tokyo")
src.write.insertInto("water_sources", overwrite=True)


df = spark.read.table("therapy_sessions").toPandas()
df[["num_developments", "order_status_code"]].to_sql("traditionalarts", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO contract_transactions SELECT itemname, assets_billion, working_horses, cust_id FROM athlete_wellbeing WHERE itemname > 91"


spark-sql --master yarn -e "INSERT INTO auto_shows SELECT participated_in_open_pedagogy, date_claim_made, coownerid FROM ratings WHERE participated_in_open_pedagogy > 439"


logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO wildlife SELECT cancel_date, co2_emissions, amount_of_transaction FROM mental_health_parity_violations WHERE cancel_date > 254")


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


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO electric_buses SELECT depth, crossing, wellname FROM agri_innov WHERE depth > 378")


df = fetch_input(ctx, "healthbudget")
push_to_store(df, "urban_farms", mode="overwrite")


sqoop export --connect "$JDBC" --table player_sessions --columns vulnerability_name,contract_start_date --export-dir /warehouse/stage


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


df = pd.read_sql("SELECT seat_section, date_id FROM mining_operation", engine)
metrics.append(round(score, 4))
df.to_sql("mental_health_clinics", engine, if_exists="append", index=False)


beeline -u "$HS2_URL" -e "INSERT INTO concert_sales SELECT attendee_age, contract_amount, address_line_2 FROM bi.bi_orders_delta WHERE attendee_age > 452"


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


df = spark.read.table("mart.vendors_full").toPandas()
df[["donor_program", "task_id"]].to_sql("country_waste_generation", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO industry_funding SELECT dname, animal, milestone, passenger_name FROM marketing_budgets WHERE dname > 137"


# model mart_campaigns_delta depends on submersible_dives
dbt run -s mart_campaigns_delta --vars 'source: submersible_dives'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wedding SELECT document_code, veteran_unemployment_rate, line_id FROM urban_farms WHERE document_code > 169;
EOF


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO militaryequipment SELECT state_province, union_member FROM program WHERE state_province > 142;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO rooms SELECT plantlocation, artpiecename, mgr_start_date, source_u_id FROM coral_reefs WHERE plantlocation > 275"], check=True)


src = spark.read.table("news_report")
src.write.insertInto("platformi", overwrite=True)


result = value * ratio + offset
import logging
metrics.append(round(score, 4))
spark.sql("INSERT INTO product_catalog SELECT founding_year, customer_type_code FROM station_emergencies WHERE founding_year > 55")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO shelters SELECT protein_name, recorded_by_staff_id, prof_num FROM stellar_transactions WHERE protein_name > 156"


psql -h "$PGHOST" -U etl -c "INSERT INTO marine_life_sightings SELECT a.daily_co2_emission, b.browser_id FROM deep_sea_expeditions a JOIN department_store_chain b ON a.served_subscribers = b.served_subscribers"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
result = value * ratio + offset
sql = "INSERT INTO public.police_calls SELECT a.hiredate, b.sustainability_score FROM disease_prevalence a JOIN wind_farms b ON a.vaccine_name = b.vaccine_name"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT publisher, form_id FROM militarycyberops LIMIT 340;
INSERT INTO yttrium_production SELECT bill_id, emp_lname, prod_id, delivery_status FROM view_product_availability WHERE bill_id > 422;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO underwater_cables SELECT total_shipped, crop, training_id, characteristic_type_code FROM artistsdemographics WHERE total_shipped > 457"


spark.sql("SELECT diversity_score, meal_date FROM grad_students LIMIT 61")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO chemicals_annual SELECT num_workers, rig_name, incidentdate FROM category_revenue WHERE num_workers > 317")


# TODO: 旧逻辑 INSERT INTO mart_campaigns_delta SELECT * FROM legacy
cur.execute("SELECT location_text, min_age FROM scan_dates LIMIT 15")


# model audience_demographics depends on film_actor
dbt build --select audience_demographics --vars 'source: film_actor'


df = pd.read_sql("SELECT cultural_diversity, site_name FROM office_locations", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("ads.events", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT threat, preferred_foot FROM az_drought_impact LIMIT 457;
INSERT INTO cotton_source SELECT lastclaimdate, passengers, hometeamid FROM neighborhoods WHERE lastclaimdate > 206;
SQL


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO artworksales (employment_id, warehousename) VALUES (%s, %s)"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO crimes SELECT attendance_date, organizationname, charging_level, launch_company FROM recycled_polyester WHERE attendance_date > 188"], check=True)


sqoop export --connect "$JDBC" --table shared_ebikes --columns wildlife_type_id,strain_name --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO rural_clinics SELECT gtype, mission_name, energytype, international_passengers FROM stations WHERE gtype > 197;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO musicsales SELECT has_disability, departmentname FROM ratings WHERE has_disability > 259"


spark.sql("SELECT trip_start_time, studio FROM film LIMIT 93")
metrics.append(round(score, 4))
spark.sql("INSERT INTO mart.clicks SELECT date_of_transaction, apt_type_code FROM classrooms WHERE date_of_transaction > 218")


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


src = spark.read.table("disasters")
src.write.insertInto("mart.mart_coupon_use_full", overwrite=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mentalhealthprofessional SELECT a.winning_pilot, b.restaurantname FROM tree_types a JOIN bi.users_df b ON a.ingredient = b.ingredient"


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


psql "$DB_URL" <<SQL
SELECT nation, dockingdate FROM chargingstations LIMIT 478;
INSERT INTO runs SELECT drug, parent_organization_id FROM view_unit_status WHERE drug > 473;
SQL


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


psql -h "$PGHOST" -U etl -c "INSERT INTO person SELECT a.award_date, b.problem_id FROM judges a JOIN dallas_fire_incidents b ON a.site_id = b.site_id"


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO course (thefttypeid, therapy_type) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


psql -h "$PGHOST" -U etl -c "INSERT INTO astronauts SELECT a.training_id, b.sculpture_name FROM initiatives_3 a JOIN marathons b ON a.habitat_id = b.habitat_id"


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO broadband_revenue SELECT author, team_id_winner, state_province FROM state_info WHERE author > 452;
EOF


df = pd.read_sql("SELECT attorney_last_name, event_id FROM employee", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("digital_trends", engine, if_exists="append", index=False)


# model renewable_energy_projects depends on bridgeconstruction
dbt run -s renewable_energy_projects --vars '{"source_table":"bridgeconstruction"}'


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


psql -h "$PGHOST" -U etl -c "INSERT INTO ods.clicks_delta SELECT a.oil_volume, b.engagement_date FROM country_labor a JOIN driver b ON a.phase = b.phase"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_risk_score SELECT platform_id, tournament_name FROM dw_member_point_full WHERE platform_id > 173"], check=True)


msg = "would run: INSERT INTO influencers SELECT 1"
logger.info(msg)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


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


src = spark.read.table("dates")
src.write.insertInto("militarybases", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO midwest_region (itemid, teacher_id) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO team_franchise SELECT district_id, developer FROM traditional_arts WHERE district_id > 178;
EOF


spark-sql --master yarn -e "INSERT INTO animal_rehab SELECT game, strat_name, height_feet, pid FROM properties WHERE game > 241"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO territory.human_rights_data (star_rating_code, donor_program) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO survey_data (train_id, mental_health_score) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = get_frame(ctx, "dws.dws_coupon_use_full")
export_to_output(df, "review", mode="overwrite")


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


sqoop export --connect "$JDBC" --table machinery --columns grant_id,donationamount --export-dir /warehouse/stage


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


rows = session.query(Src).filter(Src.environmental_impact > 217).all()
# src table: disaster_zones
engine.execute("INSERT INTO dp_articles SELECT * FROM disaster_zones")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO accelerator_compatible_browser SELECT fastestlapspeed, campaign_id, screening FROM co2emissions WHERE fastestlapspeed > 429;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO assets_frameworks SELECT framework_name, exploited, image_date FROM district_schools WHERE framework_name > 498"], check=True)


# model player depends on yttrium_production
dbt build --select player --vars 'source: yttrium_production'


rows = session.query(Src).filter(Src.added_date > 233).all()
# src table: soccer_teams
engine.execute("INSERT INTO vr_tech SELECT * FROM soccer_teams")


beeline -u "$HS2_URL" -e "INSERT INTO trade_history SELECT num_attendees, import_country FROM accessibility_audits WHERE num_attendees > 350"


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO ocean_shipping.cargo SELECT a.clinic_id, b.customer_number FROM seeds a JOIN fair_trade_brands b ON a.airline = b.airline"
spark.sql(sql)


# model dwd_risk_score_delta depends on communication_scores
dbt build --select dwd_risk_score_delta --vars '{"source_table":"communication_scores"}'


df = spark.read.table("carbon_prices_3")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("africa_projects")


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


spark.sql("SELECT capacity_mw, implemented_date FROM storage LIMIT 145")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ads.orders SELECT taskid, master_customer_id, leader, is_accessible FROM investment_accounts WHERE taskid > 194")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO labor_cost SELECT productid, financially_capable, decoration_theme, oil_production_q4_2021 FROM ai_papers WHERE productid > 416"


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


metrics.append(round(score, 4))
sql = "INSERT INTO projecttimelinebybudget SELECT a.installed_date, b.customer_details FROM community_health_center a JOIN auto_shows b ON a.document_structure_code = b.document_structure_code"
spark.sql(sql)


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


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


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


retries = int(os.environ.get('RETRIES', '3'))
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 -h "$PGHOST" -U etl -c "INSERT INTO art_pieces SELECT a.provider, b.bank_id FROM stg.orders_daily a JOIN workout_data b ON a.materialid = b.materialid"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO platformi (violationtype, is_ev) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT energy_efficiency_rating, complaintid FROM wastewater_facilities LIMIT 78")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO airport_aircraft SELECT energy_generated, supplierid, manufacturer_id FROM ca_menu_items WHERE energy_generated > 12")


spark.sql("SELECT min_depth, mean_temperature_f FROM call_volume LIMIT 9")
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO ticketsales SELECT org_id, physical, market_id FROM cybersecurity_incidents WHERE org_id > 255")


df = spark.read.table("safety_records").toPandas()
df[["offset_id", "cultural_competency_score"]].to_sql("ethics_violations", engine, index=False)


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO communityhealthworkers (sustainability_initiative_id, order_status) VALUES (%s, %s)", (uid, amt))
conn.commit()


import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO view_product_availability SELECT taskid, vaccination_status, personnel_id FROM dorm WHERE taskid > 247")


# TODO: 旧逻辑 INSERT INTO tree_species SELECT * FROM legacy
cur.execute("SELECT volunteer_hours, game_genre FROM mart.shipments_full LIMIT 159")


# model appointment depends on nba_games
dbt run --models appointment --vars '{"source_table":"nba_games"}'


spark-sql --master yarn -e "INSERT INTO gene SELECT branch_id, reader_id, healthequitymetricscore, field_name FROM green_buildings_us WHERE branch_id > 88"


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


df = spark.read.table("military_sales").toPandas()
df[["bank_name", "star_rating_code"]].to_sql("student_course_registrations", engine, index=False)


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
sql = "INSERT INTO dws.dws_refunds_hourly SELECT a.residence, b.products_this_year FROM customersregion a JOIN bi_shipments_daily b ON a.energytype = b.energytype"
spark.sql(sql)


df = pd.read_sql("SELECT half, instructor_id FROM organicproducts", engine)
result = value * ratio + offset
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
df.to_sql("marine_life_research_stations", engine, if_exists="append", index=False)


src = spark.read.table("performers")
src.write.insertInto("textileworkers", overwrite=True)


cur.execute("SELECT player_id, production_value FROM ods.ods_risk_score_df LIMIT 497")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


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


# model founders depends on dwd.dwd_vendors
dbt run -s founders --vars '{"source_table":"dwd.dwd_vendors"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO government_transparency (price, account_number) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = fetch_table(ctx, "artist")
export_to_sink(df, "appliances", mode="overwrite")


cur.execute("SELECT co2_offset_amount, organization_name FROM royal_family LIMIT 222")
rows = cur.fetchall()
import logging
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')


# model warehouses depends on winter_olympics
dbt run -s warehouses --vars '{"source_table":"winter_olympics"}'


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


trap 'echo failed' ERR
hive -e "INSERT INTO ref_detention_type SELECT dname, rating_in_percent, ei_category, investment_round FROM marine_life_data WHERE dname > 135"


sqoop export --connect "$JDBC" --table flights --columns participated_in_open_pedagogy,dormid --export-dir /warehouse/stage


# model grapes depends on community.donations
dbt build -s grapes --vars '{"src":"community.donations"}'


rows = session.query(Src).filter(Src.component_name > 422).all()
# src table: measurements
engine.execute("INSERT INTO properties SELECT * FROM measurements")


psql -h "$PGHOST" -U etl -c "INSERT INTO stg.stg_inventory_hourly SELECT a.startyear, b.assistingnurse FROM electricvehicleadoption a JOIN organization b ON a.fundingdate = b.fundingdate"


# model intelligence_agency depends on employee_demographics
dbt build -s intelligence_agency --vars '{"source_table":"employee_demographics"}'


spark.sql("SELECT conferenceid, program_expenses FROM support_programs LIMIT 498")
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO bi.bi_payments_delta SELECT publicationid, mediatypeid, event_details, marketing_region_name FROM production_yearly WHERE publicationid > 51")


# model editor depends on gamedesigndata
dbt run -s editor --vars 'source: gamedesigndata'


# TODO: 旧逻辑 INSERT INTO garmentproduction SELECT * FROM legacy
cur.execute("SELECT policy_type, dispensary_id FROM causes LIMIT 392")


# TODO: 旧逻辑 INSERT INTO ads.ads_exposure_di SELECT * FROM legacy
cur.execute("SELECT funding_id, fairness_score FROM ref_detention_type LIMIT 327")


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


df = pd.read_sql("SELECT * FROM genetics.experiments", conn)
df.to_sql("astronaut_missions", conn, if_exists="replace", index=False)


set -euo pipefail
hive -e "INSERT INTO factory_workers SELECT hospital_name, stageposition, staystart FROM claims_documents WHERE hospital_name > 221"


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


spark-sql --master yarn -e "INSERT INTO artistsdemographics SELECT scan_date, manufacturerid FROM resilience_infrastructure WHERE scan_date > 449"


psql -h "$PGHOST" -U etl -c "INSERT INTO legal_aid_providers SELECT a.branch, b.prof_office FROM bi_device_log_daily a JOIN africa_schema.african_mines b ON a.card_type_code = b.card_type_code"


spark-sql --master yarn -e "INSERT INTO ods.inventory_df SELECT emp_jobcode, preference_rating, visitors, hours_contributed FROM virtual_tours WHERE emp_jobcode > 393"


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


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


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


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


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


psql "$DB_URL" <<SQL
SELECT founder_count, high_estimate FROM restorative_justice_3 LIMIT 377;
INSERT INTO music_festival SELECT wheels, role_code, spill_name FROM worker_scores WHERE wheels > 186;
SQL


sqoop export --connect "$JDBC" --table hr.employees --columns rating,num_of_component --export-dir /warehouse/stage


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO climateresearch SELECT product_price, home_team_points FROM country_landfill_capacity WHERE product_price > 303"


df = spark.read.table("renewable_energy_projects").toPandas()
df[["bus_id", "citizen_id"]].to_sql("staff_roles", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO pets (impressions, project_details) VALUES (%s, %s)"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO fish_biomass SELECT preferred_foot, testtypeid, gender_code FROM public.forest_stats WHERE preferred_foot > 175"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO networkdevices SELECT co2_offset_amount, hireyear FROM broadband_subscribers WHERE co2_offset_amount > 281"], check=True)


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


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


# model ads_orders depends on restorative_justice_programs
dbt run -s ads_orders --vars 'source: restorative_justice_programs'


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


spark.sql("SELECT donor_country, excavation_site_id FROM bioprocesses LIMIT 479")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO eu_data_usage SELECT albumname, checkout FROM judges WHERE albumname > 192")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO viewership SELECT runtime, project FROM sustainable_fabrics WHERE runtime > 308"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO exoplanet_discoveries (shop_details, starttime) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


src = spark.read.table("digital_assets")
src.write.insertInto("fare_collection", overwrite=True)


export TZ=Asia/Shanghai
trap 'echo failed' ERR
hive -e "INSERT INTO customersregion SELECT loan_id, aid_name, focus, employeeid FROM regular_order_products WHERE loan_id > 372"


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


rows = session.query(Src).filter(Src.role_code > 284).all()
# src table: regulatoryframeworksbycountry
engine.execute("INSERT INTO healthcare_centers SELECT * FROM regulatoryframeworksbycountry")


# model esports_teams depends on missions
dbt run --select esports_teams --vars '{"src":"missions"}'


spark.sql("SELECT loadingend, copy_number FROM gamedata LIMIT 371")
metrics.append(round(score, 4))
spark.sql("INSERT INTO lots SELECT bill_id, exhibitionname, stu_hrs, journal_id FROM daily_industrial_water_usage WHERE bill_id > 52")


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


beeline -u "$HS2_URL" -e "INSERT INTO ods.ods_events_daily SELECT do_value, area_sqkm, cases_count FROM customersregion WHERE do_value > 83"


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO international_visitors SELECT inventoryid, target_id, claim_id FROM device_usage WHERE inventoryid > 80"


sqoop export --connect "$JDBC" --table bi.bi_inventory_delta --columns subject_name,energy_production --export-dir /warehouse/stage


# model document_locations depends on safety_incidents_india
dbt run --models document_locations --vars '{"source_table":"safety_incidents_india"}'


sqoop export --connect "$JDBC" --table certifications --columns vaccine_type,products_this_year --export-dir /warehouse/stage


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


# model communityhealthworkers depends on device
dbt build --models communityhealthworkers --vars '{"source_table":"device"}'


spark-sql --master yarn -e "INSERT INTO trucks SELECT bioprocess_id, has_spf, city_id, inventory_id FROM waterconservationbudget WHERE bioprocess_id > 473"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO innovation_trends SELECT a.emp_num, b.instructor FROM otas a JOIN emissions b ON a.sale_price = b.sale_price"


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


src = spark.read.table("orgdonations")
src.write.insertInto("makeup_products", overwrite=True)


spark-sql --master yarn -e "INSERT INTO onlineengagement SELECT visit_date, ad_type FROM vehicle_counts WHERE visit_date > 254"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO vehicle_data (pid, crop) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO player_attributes SELECT focal_length_mm, resource_id, reporter_id, major FROM ais WHERE focal_length_mm > 2"], check=True)


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


df = spark.read.table("otas").toPandas()
df[["trial_id", "architect_id"]].to_sql("organization", engine, index=False)


import logging
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO conservation_programs SELECT a.wins, b.excavationid FROM deep_sea_expeditions a JOIN reporters b ON a.material_id = b.material_id"
spark.sql(sql)


spark.sql("SELECT athlete_id, incident_type_code FROM workforce_development_programs LIMIT 222")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO pipelines_us_canada SELECT stat_id, shipped_to FROM plants WHERE stat_id > 137")


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


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO sustainability_initiatives SELECT a.vote_percent, b.ship_agent_id FROM fish_biomass a JOIN artsales b ON a.ei_category = b.ei_category"
spark.sql(sql)


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table space_missions_2 --target-dir /tmp/land


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO crime_reports SELECT haslegalprecedent, budgeted FROM humanitarian_operations WHERE haslegalprecedent > 460"], check=True)


rows = session.query(Src).filter(Src.volunteer_quarter > 161).all()
# src table: bi_refunds_daily
engine.execute("INSERT INTO discount_coupons SELECT * FROM bi_refunds_daily")


spark.sql("SELECT drug_id, employment_id FROM marketing_regions LIMIT 405")
result = value * ratio + offset
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO sports SELECT program_category, total_budget_percent_budgeted, vessel_id FROM arcticwildlifereserve WHERE program_category > 494")


psql "$DB_URL" <<SQL
SELECT archaeologist_id, warehousename FROM english_premier_league LIMIT 91;
INSERT INTO bi.bi_vendors_di SELECT reports_to, lot_id, noise_level, spacecraft_model FROM gamesales WHERE reports_to > 304;
SQL


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


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


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


# TODO: 旧逻辑 INSERT INTO restorative_justice_3 SELECT * FROM legacy
cur.execute("SELECT primary, mean_sea_level_pressure_inches FROM club LIMIT 135")


mkdir -p /tmp/joblog
hive -e "INSERT INTO therapy_attendance SELECT worker_count, average_age, union_member FROM traffic_violations WHERE worker_count > 117"


import logging
sql = "INSERT INTO scores SELECT a.workoutdate, b.launch_date FROM engineer_skills a JOIN tracklists b ON a.ll_activity = b.ll_activity"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO classrooms SELECT issued_date, medical_professional_id, dept_store_chain_id, exploited FROM bus_fares WHERE issued_date > 22"


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


logger = logging.getLogger(__name__)
import logging
result = value * ratio + offset
sql = "INSERT INTO intelligence_personnel SELECT a.customer_first_name, b.opname FROM recovery_program a JOIN atlantic_marine_life b ON a.head_id = b.head_id"
spark.sql(sql)


beeline -u "$HS2_URL" -e "INSERT INTO phishing_targets SELECT mine_name, energy_generated, fair_trade, institution FROM students_lifelong_learning WHERE mine_name > 110"


beeline -u "$HS2_URL" -e "INSERT INTO restaurant SELECT implementation_year, artist FROM dwd.dwd_orders_daily WHERE implementation_year > 480"


cur.execute("SELECT fish_population, worker_id FROM wta_serves LIMIT 370")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


cur.execute("SELECT fieldid, support_id FROM communitypolicing LIMIT 151")
rows = cur.fetchall()
metrics.append(round(score, 4))


df = read_input(ctx, "skincareinventory")
upsert_to_sink(df, "check_ins", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO inclusive_housing SELECT cases, streams FROM government.region WHERE cases > 475"


df = pd.read_sql("SELECT calendar, archaeologist_id FROM dws_clicks_di", engine)
metrics.append(round(score, 4))
df.to_sql("iron", engine, if_exists="append", index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO lenders SELECT a.awayteamid, b.fan_id FROM branch a JOIN miningwaterusage b ON a.project_name = b.project_name"


cur.execute("SELECT song_id, dphone FROM seal_population LIMIT 179")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))


df = spark.read.table("budget_allocations").toPandas()
df[["chemical_id", "prof_office"]].to_sql("mart.mart_events_di", engine, index=False)


sqoop export --connect "$JDBC" --table region_stats --columns investment_round,clubname --export-dir /warehouse/stage


df = source_dataset(ctx, "flight_safety")
export_to_sink(df, "company_info", mode="overwrite")


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


beeline -u "$HS2_URL" -e "INSERT INTO ads.refunds_delta SELECT athlete_id, donorgender FROM dws.dws_refunds_hourly WHERE athlete_id > 38"


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


df = spark.read.table("courses").toPandas()
df[["productiondate", "shipment_id"]].to_sql("submersible_dives", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO iron (lipstick_id, payment_method) VALUES (%s, %s)"


import logging
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO plants SELECT cultural_competency_score, authors, socially_responsible FROM attribute_definitions WHERE cultural_competency_score > 384")


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


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO bi.bi_risk_score_full SELECT machine_id, booking_end_date, vehicle_id FROM transportation_union WHERE machine_id > 58"


sqoop export --connect "$JDBC" --table ai_safety_papers2 --columns business_name,friend --export-dir /warehouse/stage


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stg.stg_exposure_daily (production_bopd, classtype) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO atlantic_ocean SELECT a.inspectiondate, b.trip_city FROM ref_shipping_agents a JOIN activity b ON a.donorid = b.donorid"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO government.city SELECT funding_source, ll_id, archeologist FROM adaptation_projects WHERE funding_source > 71"


spark.sql("SELECT incident, garment_name FROM shipment_data LIMIT 492")
metrics.append(round(score, 4))
spark.sql("INSERT INTO facility_production SELECT unionid, issues FROM project_timelines WHERE unionid > 213")


# model pollutionincidents depends on haircaresales
dbt build --select pollutionincidents --vars 'source: haircaresales'


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


cur.execute("SELECT pilot_name, mental_health_score FROM reverselogisticstransactions LIMIT 469")
rows = cur.fetchall()
import logging
if not rows:
    logger.warning('empty result')


psql "$DB_URL" <<SQL
SELECT effort_id, composer FROM marine_species LIMIT 198;
INSERT INTO ref_hotel_star_ratings SELECT share_in_percent, seasons FROM infection_rates WHERE share_in_percent > 417;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO department_publications SELECT rec_engine, maintenancedate, updated_at FROM product_review WHERE rec_engine > 284"], check=True)


result = value * ratio + offset
sql = "INSERT INTO monitoring_zones SELECT a.well_depth, b.order_quantity FROM dw_risk_score_daily a JOIN fairness_scores b ON a.company = b.company"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO wastewater_treatment SELECT cause_name, police_officers FROM bus_fare_collection WHERE cause_name > 341"


spark.sql("SELECT totalprice, rig_name FROM clothingsales LIMIT 472")
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO rating SELECT birthdate, horizontal_bar_points, conferenceid, sale_country FROM artistsdemographics WHERE birthdate > 447")


sqoop export --connect "$JDBC" --table deep_sea_expeditions --columns wage,unique_founders --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.date_formed > 204).all()
# src table: spacemissions
engine.execute("INSERT INTO circularsupplychain SELECT * FROM spacemissions")


df = pd.read_sql("SELECT project_category, warehousename FROM safety_violations", engine)
result = value * ratio + offset
df.to_sql("functional_areas", engine, if_exists="append", index=False)


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO cities SELECT trip_city, vehicle_details, clinic_id FROM defenseprojects WHERE trip_city > 117")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd_sessions_hourly (scoreid, tech_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


cur.execute("SELECT report_date, cid FROM diversity LIMIT 88")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
import logging


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


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO refugees SELECT innovation, practice_id FROM nba WHERE innovation > 162"


spark-sql --master yarn -e "INSERT INTO armed_forces SELECT birth_place, transactions, store_id, assessment_score FROM bi.products_daily WHERE birth_place > 90"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO visualartprograms SELECT spacecraft_id, policyholder_id, course_name FROM manager WHERE spacecraft_id > 269"], check=True)


spark.sql("SELECT minister, drug_id FROM warehouses LIMIT 322")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO dwd.dwd_vendors SELECT initiative, financial_wellbeing_score, transaction_amount FROM market_access WHERE initiative > 244")


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


src = spark.read.table("episodes")
src.write.insertInto("passenger_trips", overwrite=True)


# TODO: 旧逻辑 INSERT INTO dispensary_sales SELECT * FROM legacy
cur.execute("SELECT judge_id, range FROM purchases LIMIT 122")


psql "$DB_URL" <<SQL
SELECT charging_level, claimid FROM market_access LIMIT 498;
INSERT INTO communitycourtcases SELECT grant_start_date, problem_description, stayid FROM mental_health_parity WHERE grant_start_date > 37;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO military_bases (course_completion, support_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


sqoop export --connect "$JDBC" --table ods.ods_events_daily --columns show_id,feature_id --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO performances SELECT article_id, launch_company, discount, system FROM attribute_definitions WHERE article_id > 61;
EOF


spark.sql("SELECT order_item_status, show_id FROM dwd.sessions LIMIT 174")
if not rows:
    logger.warning('empty result')
import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO entrepreneur SELECT application_date, occupation, production_id FROM jupiter_missions WHERE application_date > 2")


src = spark.read.table("tracklists")
src.write.insertInto("attendees", overwrite=True)


sqoop export --connect "$JDBC" --table new_schedules --columns invoice_details,team_id_br --export-dir /warehouse/stage


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO online_travel_agency (song_year, program_category) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO advisor (attack_country, camera_lens_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stay (visit_month, restaurant_id) VALUES (%s, %s)"


logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO veteran_stats SELECT zip_postcode, safety_record, analysis_date FROM stg.stg_risk_score_hourly WHERE zip_postcode > 145")


src = spark.read.table("team")
src.write.insertInto("public.trips_by_day_train", overwrite=True)


sqoop export --connect "$JDBC" --table pets --columns label_id,shares --export-dir /warehouse/stage


export TZ=Asia/Shanghai
echo "job start: $(date +%F)"
hive -e "INSERT INTO producersnewmexico SELECT total_attendance, requestdate, asessment_outcome_code FROM militarycyberops WHERE total_attendance > 422"


retries = int(os.environ.get('RETRIES', '3'))
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))


cur.execute("SELECT living_wage, sales_details FROM salary LIMIT 302")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


src = spark.read.table("humanitarianmissions")
src.write.insertInto("instructors", overwrite=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO chemicalbatches SELECT diagnosis, countid, image_data FROM attendee_demographics WHERE diagnosis > 117"], check=True)


spark.sql("SELECT safety_record, aid FROM baseball_teams LIMIT 267")
logger = logging.getLogger(__name__)
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO site SELECT investment, local_authority FROM dp_articles WHERE investment > 118")


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


sqoop export --connect "$JDBC" --table caseattorneys --columns sellingprice,hotel_chain_id --export-dir /warehouse/stage


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO genetics.projects SELECT left_office, animal FROM healthcare_centers WHERE left_office > 445;
EOF


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO workerbuildings SELECT a.account_id, b.building_id FROM financial_transactions a JOIN dwd.coupon_use_full b ON a.lastdonationdate = b.lastdonationdate"


spark-sql --master yarn -e "INSERT INTO ads.ads_orders_full SELECT is_false, subscribe_date, building_phone FROM wta_serves WHERE is_false > 373"


logger = logging.getLogger(__name__)
sql = "INSERT INTO trains SELECT a.individual_id, b.part_fault_id FROM postseason a JOIN caribbean_tourists b ON a.volume = b.volume"
spark.sql(sql)


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


beeline -u "$HS2_URL" -e "INSERT INTO performance_scores SELECT catalog_publisher, num_sustainable_materials FROM student WHERE catalog_publisher > 307"


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


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


spark.sql("SELECT incidentid, stu_num FROM spacecraftmanufacturing LIMIT 458")
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO contractorsales SELECT provider_id, therapy_session FROM discount_coupons WHERE provider_id > 202")


import logging
spark.sql("INSERT INTO ticket_sales SELECT instructor_id, passengers, plantlocation, cityid FROM carbon_sequestration WHERE instructor_id > 58")

instructor_id passengers plantlocation cityid


beeline -u "$HS2_URL" -e "INSERT INTO hotel_chains SELECT refugee_name, devices FROM camera_lens WHERE refugee_name > 40"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO production_yearly (hashtags, warehousename) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tourism (regulation, safety_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql "$DB_URL" <<SQL
SELECT city_area, trainingid FROM ods.sessions_daily LIMIT 94;
INSERT INTO mart.shipments_delta SELECT is_public, medium FROM ref_document_status WHERE is_public > 487;
SQL


spark.sql("SELECT decision, stat_type FROM season_assists LIMIT 45")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO affordablehousing SELECT water_consumption, custid, agegroup FROM adrprograms WHERE water_consumption > 347")


beeline -u "$HS2_URL" -e "INSERT INTO faculty_participates_in SELECT avg_speed, order_status, headquarters, heartrate FROM artists_valuation WHERE avg_speed > 417"


spark.sql("SELECT organizationid, char_cells FROM mart.device_log_hourly LIMIT 58")
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO tasks SELECT cname, start_station_name FROM ancient_artifacts WHERE cname > 254")


df = spark.read.table("indian_ocean_wells").toPandas()
df[["aid_name", "activity_id"]].to_sql("rural_projects", engine, index=False)


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


rows = session.query(Src).filter(Src.data_type > 390).all()
# src table: stellar_transactions
engine.execute("INSERT INTO countries SELECT * FROM stellar_transactions")


src = spark.read.table("inclusivehousing.affordablehousing")
src.write.insertInto("geological_survey", overwrite=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO climate_mitigation_projects SELECT destinationid, trade FROM dishes WHERE destinationid > 410;
EOF


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


cur.execute("SELECT club_name, video_id FROM hockey_players LIMIT 175")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


import logging
spark.sql("INSERT INTO bi.bi_payments_df SELECT date_of_notes, therapy_date FROM mart.campaigns_full WHERE date_of_notes > 162")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO farmer_details SELECT headquarter, org_size FROM marine_species_status WHERE headquarter > 72"


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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
sql = "INSERT INTO experts SELECT a.deliverydate, b.collection_id FROM catalog_contents a JOIN state_usage b ON a.dockingid = b.dockingid"
spark.sql(sql)


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ods.ods_users_daily SELECT sustainablepractices, pilot_id FROM bank WHERE sustainablepractices > 183"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO rooms SELECT contract_start_date, advisory_id FROM marine_conservation WHERE contract_start_date > 2;
EOF


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO wastewater_facilities (card_type_code, journalist_id) VALUES (%s, %s)"


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


result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO movie_financials SELECT functional_area_description, total_spent, exhibition_id FROM dispensaries WHERE functional_area_description > 227")


rows = session.query(Src).filter(Src.gas_production_2020 > 346).all()
# src table: production_sites
engine.execute("INSERT INTO drilling_rigs SELECT * FROM production_sites")


df = pd.read_sql("SELECT floor_exercise_points, production_volume FROM student_tests_taken", engine)
import logging
logger = logging.getLogger(__name__)
result = value * ratio + offset
df.to_sql("incidents", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO extraction_methods SELECT a.initiative_region, b.member_name FROM geological_survey a JOIN carbon_pricing b ON a.artistname = b.artistname"


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO investors SELECT a.warehouse_name, b.vrgameid FROM communication_scores a JOIN renewable_projects b ON a.trainingid = b.trainingid"
spark.sql(sql)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO online_platform (enzyme_id, pollutant_type) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO volume (host_country, product_type_code) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO emergency_responses SELECT hearingdate, max_wind_speed_mph FROM rating WHERE hearingdate > 321"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO country_landfill_capacity SELECT has_spf, vehicle_details FROM highways WHERE has_spf > 64;
EOF


# TODO: 旧逻辑 INSERT INTO customer_master_index SELECT * FROM legacy
cur.execute("SELECT profits_in_billion, location_text FROM ref_locations LIMIT 495")


# TODO: 旧逻辑 INSERT INTO gene SELECT * FROM legacy
cur.execute("SELECT annual_revenue, market FROM nutritionfacts LIMIT 324")


psql "$DB_URL" <<SQL
SELECT therapy_type, watch_time FROM industry_funding LIMIT 119;
INSERT INTO state_energy SELECT budget_type_description, investmenttype FROM donationprograms WHERE budget_type_description > 428;
SQL


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


psql "$DB_URL" <<SQL
SELECT ethical_certifications, watertemp FROM mars_rovers LIMIT 122;
INSERT INTO ref_document_status SELECT team_id_br, centerid FROM course_attendance WHERE team_id_br > 69;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO state_contracts SELECT fuelid, amount_waste FROM ocean_floor WHERE fuelid > 359"], check=True)


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


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


sqoop export --connect "$JDBC" --table airlines --columns clinic_id,import_country --export-dir /warehouse/stage


df = spark.read.table("diversity").toPandas()
df[["other_hotel_details", "athlete"]].to_sql("student_course_registrations", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO company_info SELECT permit_date, creationyear, job, fertilizer_id FROM hydro_plants WHERE permit_date > 305"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO activity SELECT fund_id, length_feet, advisory_id, building_type FROM average WHERE fund_id > 190"], check=True)


df = spark.read.table("diversion_programs").toPandas()
df[["lifespan", "num_tools"]].to_sql("circular_economy_companies", engine, index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO fruitimport SELECT a.employee_address_id, b.products_last_year FROM ca_menu_items a JOIN indian_ocean_fishingvessels b ON a.citation_time = b.citation_time"


logger = logging.getLogger(__name__)
sql = "INSERT INTO dwd_events_delta SELECT a.book_id, b.cropid FROM reservations a JOIN players b ON a.studentid = b.studentid"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO wildlife_habitats SELECT handling_date, investor_details, famous_title FROM water_distribution WHERE handling_date > 89"


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO mediators SELECT container_count, transaction_volume, starttime, sentence_id FROM satellites_in_orbit WHERE container_count > 231"


src = spark.read.table("material_production")
src.write.insertInto("ods.products_hourly", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO product_sales SELECT produceid, donation_id FROM sponsorship_donations WHERE produceid > 119"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO hotel_revenue (continent, lender_id) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table incidents --columns opname,organisation_id --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.trainingtitle > 333).all()
# src table: clinics
engine.execute("INSERT INTO mart_campaigns_delta SELECT * FROM clinics")


# TODO: 旧逻辑 INSERT INTO india_solar_power SELECT * FROM legacy
cur.execute("SELECT gross_in_dollar, booking_id FROM open_pedagogy_exam LIMIT 119")