spark.sql("SELECT assistingnurse, incident_region FROM fish_biomass LIMIT 45")
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO stg_users_daily SELECT shippedcost, reason, publication_year, fare_amount FROM expenditure WHERE shippedcost > 49")


cur.execute("SELECT categoryname, specialty FROM rooms LIMIT 1")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))


spark-sql --master yarn -e "INSERT INTO fossil_fuel_vehicles_japan SELECT data_type, roomname, team_id_br FROM basketball_teams WHERE data_type > 419"


trap 'echo failed' ERR
hive -e "INSERT INTO projectemployees SELECT receipt_date, date_joined_staff, session_name FROM drought_impact WHERE receipt_date > 270"


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


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


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


psql "$DB_URL" <<SQL
SELECT wins, certification FROM renewableenergyprojects LIMIT 313;
INSERT INTO dwd.events_daily SELECT soil_moisture, sales_channel, conferenceid, enable_third_party_ads FROM dates WHERE soil_moisture > 212;
SQL


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


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


spark-sql --master yarn -e "INSERT INTO sourcing SELECT ranking, union_member_id, storename, start_station_id FROM gamedesign WHERE ranking > 119"


df = spark.read.table("mediatype").toPandas()
df[["virtual_tour_sessions", "skill_id"]].to_sql("government.region", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO vehiclemodels SELECT date_of_attendance, nutrient_level, date_joined_staff FROM stg.stg_exposure_daily WHERE date_of_attendance > 356"], check=True)


spark-sql --master yarn -e "INSERT INTO price_data SELECT date_valid_from, watertemp, process_id, sensor_type FROM class WHERE date_valid_from > 454"


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))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO threat_intelligence_budget SELECT number_city_affected, bathroom_count, bandmate, contractor FROM chemical_composition WHERE number_city_affected > 149"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.mart_device_log_delta (person_id, has_spf) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("birds")
src.write.insertInto("renewable_power", overwrite=True)


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO dws_coupon_use_df SELECT a.shipping_agent_name, b.userid FROM mediatype a JOIN urban_agriculture_initiatives b ON a.update_date = b.update_date"
spark.sql(sql)


df = extract_input(ctx, "stg.risk_score_hourly")
export_to_sink(df, "spending", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO academic_publications SELECT allergytype, network FROM contract_negotiations WHERE allergytype > 221"], check=True)


df = get_frame(ctx, "budget_allocations")
export_to_output(df, "casebilling", mode="overwrite")


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


result = value * ratio + offset
spark.sql("INSERT INTO community_health_workers SELECT astronaut, vrgameid, therapy_sessions FROM cargo_handling WHERE astronaut > 290")


df = read_dataset(ctx, "tweets")
push_to_warehouse(df, "cargos", mode="overwrite")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO creative_ai (courtid, director) VALUES (%s, %s)"


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


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


set -euo pipefail
hive -e "INSERT INTO video_content SELECT feb, pollution_id FROM military_expenditure WHERE feb > 393"


src = spark.read.table("biosensors.readings")
src.write.insertInto("satellite_missions_large", overwrite=True)


df = spark.read.table("climate_investments").toPandas()
df[["num_investments", "license_number"]].to_sql("rural_hospitals", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO labour_productivity SELECT trainingtype, build_date FROM season_assists WHERE trainingtype > 200;
EOF


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


psql -h "$PGHOST" -U etl -c "INSERT INTO mart.mart_member_point_hourly SELECT a.app_id, b.produceid FROM waste_generation a JOIN hotel_chains b ON a.item_price = b.item_price"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO runs (donator_name, author) VALUES (%s, %s)"


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


psql "$DB_URL" <<SQL
SELECT payment_method, college_id FROM dws_coupon_use LIMIT 128;
INSERT INTO complaints_breakdown SELECT singer_id, char_cells, artist_id, flight_number FROM cities WHERE singer_id > 281;
SQL


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO indigenous_communities SELECT running_time, signup_date, offense FROM mailshot_campaigns WHERE running_time > 310")


rows = session.query(Src).filter(Src.personal_name > 75).all()
# src table: cuisine
engine.execute("INSERT INTO gameplatforms SELECT * FROM cuisine")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO expensive_space_missions (volunteerhourid, eventattendance) VALUES (%s, %s)"


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


sqoop export --connect "$JDBC" --table measurement --columns reported_by_staff_id,museumid --export-dir /warehouse/stage


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO energy_consumption SELECT excavation_site, avg_usage, date_contact_to FROM satellites WHERE excavation_site > 443"], check=True)


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


src = spark.read.table("station_emergencies")
src.write.insertInto("bi.inventory_daily", overwrite=True)


df = spark.read.table("chemical").toPandas()
df[["camera_lens_id", "outcome_date"]].to_sql("maintenance_engineers", engine, index=False)


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


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


spark-sql --master yarn -e "INSERT INTO life_expectancy SELECT bedtype, race, race_ethnicity_id FROM training_programs WHERE bedtype > 312"


echo "job start: $(date +%F)"
set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO flu_cases SELECT payment_id, rank FROM dwd.dwd_member_point_full WHERE payment_id > 291"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO vehicle_maintenance SELECT height, bank_name FROM train_station WHERE height > 217;
EOF


# TODO: 旧逻辑 INSERT INTO union_members SELECT * FROM legacy
cur.execute("SELECT staystart, sensor_reading FROM aircraft LIMIT 72")


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))


rows = session.query(Src).filter(Src.assessment_date > 179).all()
# src table: soil_moisture
engine.execute("INSERT INTO water_usage SELECT * FROM soil_moisture")


psql "$DB_URL" <<SQL
SELECT enable_location_tracking, retweets FROM global_tournament LIMIT 370;
INSERT INTO papers SELECT attribute_id, data_usage FROM customer_payments WHERE attribute_id > 88;
SQL


presto --server presto01:8080 --catalog hive --execute "INSERT INTO college SELECT budget_allocated, exhibitionname, technique_id FROM investment WHERE budget_allocated > 135"


spark.sql("SELECT emp_fname, network FROM school_enrollment LIMIT 260")
import logging
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO agricultural_innovation SELECT pets_allowed_yn, treatment FROM fish_stock WHERE pets_allowed_yn > 280")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO militaryequipmentsales SELECT active_from_date, payment_method_code, resource_type, restorative_justice FROM dw.inventory_delta WHERE active_from_date > 445;
EOF


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dwd.exposure_hourly SELECT project_date, factory_name, postal_code FROM ads.ads_risk_score_hourly WHERE project_date > 71")


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


psql "$DB_URL" <<SQL
SELECT lieutenant_governor, apid FROM doctors LIMIT 56;
INSERT INTO carbonoffsetinitiatives SELECT mineid, height, business_name FROM leo_missions WHERE mineid > 188;
SQL


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


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


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


df = pd.read_sql("SELECT share_count, approach FROM military_contracts", engine)
if not rows:
    logger.warning('empty result')
df.to_sql("trainingprograms", engine, if_exists="append", index=False)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO events (detection_date, device) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ods_shipments_df SELECT market_value, recruiterid, contractorid FROM maintenance_schedule WHERE market_value > 353"], check=True)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws.dws_member_point_di SELECT vehicle_type, uid FROM show WHERE vehicle_type > 495;
EOF


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


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


# TODO: 旧逻辑 INSERT INTO airportdata SELECT * FROM legacy
cur.execute("SELECT founder_race, response_time FROM taj_mahal_visitors LIMIT 379")


msg = "would run: INSERT INTO algorithmic_fairness_incidents SELECT 1"
logger.info(msg)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))


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


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


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


spark.sql("SELECT train_id, bank_name FROM recalls LIMIT 203")
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO satisfaction SELECT open_date, focal_length_mm, co2_emissions FROM performingartsprograms WHERE open_date > 359")


src = spark.read.table("african_tourism")
src.write.insertInto("nutrition_facts", overwrite=True)


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


echo "dry-run: INSERT INTO donations_insert_2 SELECT 1"
trap 'echo failed' ERR
mkdir -p /tmp/joblog


psql -h "$PGHOST" -U etl -c "INSERT INTO port_office SELECT a.safety_record, b.is_accessible FROM product_details a JOIN city_waste_generation b ON a.transaction_product = b.transaction_product"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.dwd_device_log_delta (life_expectancy, certification) VALUES (%s, %s)"


cur.execute("SELECT routeid, farmer_name FROM airport LIMIT 420")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


sqoop export --connect "$JDBC" --table skincareinventory --columns writer,incidents --export-dir /warehouse/stage


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


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


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO ship SELECT city_traffic_speed, menu_name FROM artifact_analysis WHERE city_traffic_speed > 176")


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


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


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bridgeconstruction SELECT grant_id, allergy, min_depth FROM mart_vendors_full WHERE grant_id > 429")


df = spark.read.table("undergoes").toPandas()
df[["destroyed_by_employee_id", "eventtype"]].to_sql("fields_production", engine, index=False)


cur.execute("SELECT launch_date, menu_id FROM carbon_prices_3 LIMIT 488")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
result = value * ratio + offset
metrics.append(round(score, 4))


spark-sql --master yarn -e "INSERT INTO routes SELECT ngo_name, categoryid, tourist_id FROM broadband_providers WHERE ngo_name > 29"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO wedding (leader, itemname) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table usdaviolations --columns fiscal_year,well_id --export-dir /warehouse/stage


psql -h "$PGHOST" -U etl -c "INSERT INTO catalog_contents_additional_attributes SELECT a.trench_id, b.advocate_name FROM rural_feeder_roads a JOIN gene b ON a.dock_count = b.dock_count"


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO claims_documents SELECT a.balance, b.routename FROM hall_of_fame a JOIN stg.stg_coupon_use_di b ON a.name_first = b.name_first"
spark.sql(sql)


df = pd.read_sql("SELECT fault_short_name, treatment_year FROM stg.stg_events_di", engine)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("recycledmaterialsgarments", engine, if_exists="append", index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO gymnast SELECT water_temp, training_name, platformid, crop_id FROM support_programs WHERE water_temp > 413;
EOF


df = pd.read_sql("SELECT calories, clinic_id FROM nba", engine)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
df.to_sql("open_data_initiatives", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT payment_method_code, review_id FROM employeedemographics", engine)
import logging
df.to_sql("electronics_factories", engine, if_exists="append", index=False)


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


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


rows = session.query(Src).filter(Src.scan_date > 67).all()
# src table: claims_documents
engine.execute("INSERT INTO functional_areas SELECT * FROM claims_documents")


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


mkdir -p /tmp/joblog
set -euo pipefail
hive -e "INSERT INTO attorneylocationyear SELECT zone, amount, other_details, served_subscribers FROM league_x WHERE zone > 168"


spark-sql --master yarn -e "INSERT INTO renewable_energy_investments SELECT wifi, farmland_id, site_id, annual_interchanges FROM droughthistory WHERE wifi > 318"


# TODO: 旧逻辑 INSERT INTO territory.human_rights_data SELECT * FROM legacy
cur.execute("SELECT tech_type, resolved FROM militarydrones LIMIT 343")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO state_usage SELECT org_name, treatment_year FROM phishing_targets WHERE org_name > 274;
EOF


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO design_standards SELECT strat_name, area_sqkm FROM hospital WHERE strat_name > 90")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cultural_heritage SELECT valuation, route_id FROM obesity WHERE valuation > 10"], check=True)


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO traditionalarts SELECT led_by, hire_date, temperature, sustainability_rating FROM useracct WHERE led_by > 214"], check=True)


mkdir -p /tmp/joblog
hive -e "INSERT INTO mart_payments_df SELECT hospitalid, cultural_diversity FROM bi.refunds_daily WHERE hospitalid > 479"


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


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


df = pd.read_sql("SELECT balance, worker_id FROM dws.dws_events_hourly", engine)
result = value * ratio + offset
df.to_sql("animal_budget", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO southchinasea.wells SELECT a.principal_activities, b.role_description FROM wholesale_orders a JOIN public_works_projects b ON a.funding_source_type = b.funding_source_type"


cur.execute("SELECT attribute_data_type, productid FROM architect LIMIT 26")
rows = cur.fetchall()
result = value * ratio + offset
logger = logging.getLogger(__name__)
import logging


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


if not rows:
    logger.warning('empty result')
sql = "INSERT INTO bi.events_delta SELECT a.casestatus, b.openning_year FROM local_impact_japan a JOIN tracks b ON a.artist_nationality = b.artist_nationality"
spark.sql(sql)


rows = session.query(Src).filter(Src.causeid > 150).all()
# src table: bi.bi_risk_score_delta
engine.execute("INSERT INTO ods_products_delta SELECT * FROM bi.bi_risk_score_delta")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cosmetic_formula SELECT amount_claimed, gender_mf, species_name FROM volunteer_registration WHERE amount_claimed > 214"], check=True)


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO ap_budget SELECT exhibitioncountry, color, month, meal_date FROM documents WHERE exhibitioncountry > 109"


df = pd.read_sql("SELECT date_in_locaton_to, testtypeid FROM nailpolishsales", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("armed_forces", engine, if_exists="append", index=False)


trap 'echo failed' ERR
mkdir -p /tmp/joblog
export TZ=Asia/Shanghai
hive -e "INSERT INTO emergencies SELECT city_traffic_speed, council_id, is_electric FROM flight_safety WHERE city_traffic_speed > 301"


psql "$DB_URL" <<SQL
SELECT exhibition_name, initiative_type FROM clothing_brands LIMIT 25;
INSERT INTO whale_sharks SELECT vulnerability_name, product_subcategory, handling_id FROM broadband_revenue WHERE vulnerability_name > 74;
SQL


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ods.ods_risk_score_df (killed, student_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO mart.mart_device_log_delta SELECT register_year, device, claimamount, hours_developed FROM mart.campaigns_full WHERE register_year > 320")


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO energy_production SELECT build_year, suppliername, event_name, yield_id FROM flu_cases WHERE build_year > 190"


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


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


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


spark.sql("SELECT capacity_percentage, deliveryid FROM virtual_visitors LIMIT 433")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO policy_feedback SELECT cropid, claim_stage_id FROM public_works_projects WHERE cropid > 293")


# TODO: 旧逻辑 INSERT INTO cybersecuritybudget SELECT * FROM legacy
cur.execute("SELECT exhibition_name, production FROM show LIMIT 448")


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


beeline -u "$HS2_URL" -e "INSERT INTO exhibition_visitors SELECT userid, last_maintenance FROM workplaces WHERE userid > 35"


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


cur.execute("SELECT donationid, route FROM immunizationrates LIMIT 478")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


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


# TODO: 旧逻辑 INSERT INTO agri_innovations SELECT * FROM legacy
cur.execute("SELECT horizontal_bar_points, communityname FROM district LIMIT 316")


# TODO: 旧逻辑 INSERT INTO member_data SELECT * FROM legacy
cur.execute("SELECT fouls, discount FROM humanitarian_aid LIMIT 158")


beeline -u "$HS2_URL" -e "INSERT INTO timber_production SELECT budget_allocation, course_name FROM visitor_statistics WHERE budget_allocation > 409"


psql "$DB_URL" <<SQL
SELECT certification, anomaly FROM gender LIMIT 313;
INSERT INTO stellar_transactions SELECT energy_efficiency_savings, roomid, department_id FROM genre_songs WHERE energy_efficiency_savings > 22;
SQL


df = read_input(ctx, "cases")
export_to_sink(df, "vehicle_sales", mode="overwrite")


result = value * ratio + offset
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO coralreefs SELECT replacement_cost, courtname, address_details, trainingdate FROM construction_labor_stats WHERE replacement_cost > 74")


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


# TODO: 旧逻辑 INSERT INTO healthcare_centers SELECT * FROM legacy
cur.execute("SELECT plant_id, contract_id FROM underwater_cables LIMIT 63")


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


psql "$DB_URL" <<SQL
SELECT datetime_detention_start, transaction_product FROM digital_divide_initiatives LIMIT 227;
INSERT INTO fans SELECT testtypeid, laborproductivity, date_to FROM stg.stg_inventory_full WHERE testtypeid > 3;
SQL


# TODO: 旧逻辑 INSERT INTO workforce_development_programs SELECT * FROM legacy
cur.execute("SELECT asset_details, deliverydate FROM cultural_competency_training LIMIT 8")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO financial_transactions SELECT cuisine, school_code FROM weekly_weather WHERE cuisine > 422;
EOF


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


psql "$DB_URL" <<SQL
SELECT contactid, volunteerhourid FROM researchpapers LIMIT 165;
INSERT INTO medicine SELECT degrees, assists, min_dew_point_f, cmi_cross_ref_id FROM public.forest_stats WHERE degrees > 332;
SQL


df = pd.read_sql("SELECT event_type_id, student_id FROM rural_clinics", engine)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
df.to_sql("dws.payments_delta", engine, if_exists="append", index=False)


metrics.append(round(score, 4))
spark.sql("INSERT INTO features SELECT discovered_date, launch_date, department_id, studentid FROM bi_device_log_daily WHERE discovered_date > 274")


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


beeline -u "$HS2_URL" -e "INSERT INTO concentrateprices SELECT system, all_games, ota_name, coach_name FROM higher_ed.publications WHERE system > 120"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO cybersecurity.strategies SELECT spacecraft_id, observation_id FROM degrees WHERE spacecraft_id > 23"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO third_party_companies (total_beds, production) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO web_client_accelerator SELECT donorname, ranking FROM seeds WHERE donorname > 134"], check=True)


psql "$DB_URL" <<SQL
SELECT end_station_id, founder_gender FROM engineer_visits LIMIT 192;
INSERT INTO mart.mart_coupon_use_full SELECT recruiterid, outcome_description, sales_in_billion FROM canada_tech WHERE recruiterid > 246;
SQL


src = spark.read.table("classrooms")
src.write.insertInto("artists", overwrite=True)


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO rating SELECT date_became_customer, fair_trade, budgeted FROM product_catalog WHERE date_became_customer > 369"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dwd.dwd_payments_full SELECT premise_id, city_name FROM dams WHERE premise_id > 27"], check=True)


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


# TODO: 旧逻辑 INSERT INTO recycled_polyester SELECT * FROM legacy
cur.execute("SELECT funding_round_id, day_of_week FROM market_share LIMIT 349")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO rural_hospitals SELECT is_ev, menu_item, allocation_date, production_budget FROM reservations WHERE is_ev > 64"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO community_policing SELECT amount_of_refund, purchase_details FROM iot_sensors WHERE amount_of_refund > 27;
EOF


threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO art_pieces SELECT funder, authid, hotel_chain_name, billingamount FROM ais WHERE funder > 149")

funder authid hotel_chain_name billingamount


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO security_incidents SELECT specialty, max_age FROM mart.mart_sessions_di WHERE specialty > 120"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO apartment_bookings SELECT tripdatetime, facid, artworkid FROM patient_satisfaction WHERE tripdatetime > 284"], check=True)


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


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


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


rows = session.query(Src).filter(Src.don_name > 195).all()
# src table: rental
engine.execute("INSERT INTO intelligenceoperations SELECT * FROM rental")


psql "$DB_URL" <<SQL
SELECT premise_details, complaint_status_code FROM visual_arts LIMIT 353;
INSERT INTO organicproducts SELECT leader_name, sent_date, cost FROM biosensors.patents WHERE leader_name > 74;
SQL


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


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


# model courts depends on machines
dbt run --select courts --vars '{"source_table":"machines"}'


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ods.sessions SELECT daily_consumption, reporter_id FROM mediators WHERE daily_consumption > 86;
EOF


psql "$DB_URL" <<SQL
SELECT program, min_salary FROM bi.clicks_hourly LIMIT 381;
INSERT INTO training SELECT vehicle_details, attendee_race, system, casestatus FROM bike_share WHERE vehicle_details > 127;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO labor_statistics SELECT formats, stop, co2_emission, policyholder_id FROM check_ins WHERE formats > 92"], check=True)


df = pd.read_sql("SELECT market_rate, spill_name FROM document_structures", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("visualartprograms", engine, if_exists="append", index=False)


psql -h "$PGHOST" -U etl -c "INSERT INTO hospitallocations SELECT a.disability_type, b.faculty FROM investment a JOIN player_coach b ON a.bname = b.bname"


df = pd.read_sql("SELECT charging_level, publication_id FROM project_issues", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
import logging
df.to_sql("weather_record", engine, if_exists="append", index=False)


cur.execute("SELECT person_id, vesselid FROM voyages LIMIT 334")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))


threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO satelliteimagery SELECT permits_issued, tourist_id FROM energy_production WHERE permits_issued > 500")


# TODO: 旧逻辑 INSERT INTO tree_species SELECT * FROM legacy
cur.execute("SELECT roomname, publicationid FROM satellites LIMIT 290")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO social_good_education SELECT builder, certified FROM violations WHERE builder > 328;
EOF


cur.execute("SELECT trade_name, contractorid FROM iot_sensors LIMIT 22")
rows = cur.fetchall()
import logging
retries = int(os.environ.get('RETRIES', '3'))


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


src = spark.read.table("commercialbuildings")
src.write.insertInto("job_postings", overwrite=True)


cur.execute("SELECT feature_details, matchdate FROM animal_species LIMIT 473")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


# model safe_dataset depends on video_games
dbt run --models safe_dataset --vars 'source: video_games'


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


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


psql "$DB_URL" <<SQL
SELECT plant, claimtype FROM royal_family LIMIT 375;
INSERT INTO attack_outcomes SELECT played, total, mission FROM policy_feedback WHERE played > 304;
SQL


psql "$DB_URL" <<SQL
SELECT distance, author_or_editor FROM forest LIMIT 18;
INSERT INTO bi.bi_risk_score_delta SELECT menuitemid, bandmate, male_id, school_name FROM community_health_workers WHERE menuitemid > 418;
SQL


sqoop export --connect "$JDBC" --table construction_union --columns projecttype,startup_id --export-dir /warehouse/stage


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd_sessions_df (machine, mining_operation) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.application_date > 486).all()
# src table: tours
engine.execute("INSERT INTO timber_production SELECT * FROM tours")


beeline -u "$HS2_URL" -e "INSERT INTO dwd.dwd_inventory_hourly SELECT line_1, characteristic_id, unit_id, game_id FROM healthcare_centers WHERE line_1 > 144"


psql "$DB_URL" <<SQL
SELECT programtype, policy_type FROM outcomes LIMIT 392;
INSERT INTO offender_demographics SELECT provider_name, graphics_mode, build_date, researcher_name FROM gardens WHERE provider_name > 206;
SQL


export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO time_dim SELECT bioprocess_name, dept_name, working_year_starts, water_temp FROM dws.inventory_daily WHERE bioprocess_name > 371"


# model diversity depends on neighborhoods
dbt run -s diversity --vars '{"source_table":"neighborhoods"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO esportsevents SELECT a.ai_algorithm_id, b.doctor_id FROM community_members a JOIN shops b ON a.date_order_placed = b.date_order_placed"


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


spark-sql --master yarn -e "INSERT INTO disease_prevalence SELECT chemical_type, program_id, meter_100, station_name FROM customer_master_index WHERE chemical_type > 80"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ads.ads_exposure_di SELECT shipmentid, dish_type, structure_type FROM productsafety WHERE shipmentid > 152;
EOF


cur.execute("SELECT ai_id, seal_species FROM investors LIMIT 209")
rows = cur.fetchall()
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


df = spark.read.table("dwd.dwd_cart_item_di")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("public.crime_types")


df = source_table(ctx, "dws.dws_member_point_df")
dump_to_store(df, "representative", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO ticketspending SELECT killed, compatible_since_year FROM sustainable_urban_properties_2 WHERE killed > 211"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO player_demographics SELECT investment_id, plant FROM vulnerabilities WHERE investment_id > 350"], check=True)


export TZ=Asia/Shanghai
RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO fish_suppliers SELECT chemicalid, bike_id, mean_sea_level_pressure_inches, device_id FROM elimination WHERE chemicalid > 73"


psql "$DB_URL" <<SQL
SELECT vendor_state, bats FROM concert LIMIT 68;
INSERT INTO marketing_budgets SELECT supplier_id, num_investments FROM bi.bi_campaigns_delta WHERE supplier_id > 353;
SQL


cur.execute("SELECT population, project_name FROM field5 LIMIT 234")
rows = cur.fetchall()
result = value * ratio + offset


# model program_history depends on authors
dbt build --select program_history --vars '{"src":"authors"}'


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


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


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


psql "$DB_URL" <<SQL
SELECT museum_details, peakhourid FROM sports_events LIMIT 154;
INSERT INTO textile_waste SELECT total_attendance, preferred_foot, market_value_in_billion, taskdate FROM foodsafetyrecords WHERE total_attendance > 4;
SQL


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


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


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


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


src = spark.read.table("safetytests")
src.write.insertInto("flight_emissions", overwrite=True)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO stg.risk_score_hourly (donor_id, user_category) VALUES (%s, %s)"


df = spark.read.table("sales_quarterly").toPandas()
df[["production_budget", "num_cases"]].to_sql("green_buildings_us", engine, index=False)


src = spark.read.table("units")
src.write.insertInto("ods.ods_clicks_di", overwrite=True)


df = spark.read.table("attendee_demographics").toPandas()
df[["saledate", "log_entry_description"]].to_sql("waterconservation", engine, index=False)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO program_history (attendee_id, user_account) VALUES (%s, %s)"


# model grad_students depends on russia_nato_diplomacy
dbt run --models grad_students --vars '{"source_table":"russia_nato_diplomacy"}'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO city_properties SELECT time_id, donor_id FROM attack_outcomes WHERE time_id > 263"], check=True)


trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO container_ships SELECT co2_reduction_tons, media_literacy_score FROM weekly_weather WHERE co2_reduction_tons > 469"


sqoop export --connect "$JDBC" --table supplier_addresses --columns practices,trial_id --export-dir /warehouse/stage


result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO artsandcrafts SELECT budget_type_description, connection, eventname, filingdate FROM flu_cases WHERE budget_type_description > 447")

budget_type_description connection eventname filingdate


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


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


df = pd.read_sql("SELECT num_solo_exhibitions, views FROM upgrades", engine)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
df.to_sql("public.ev_sales", engine, if_exists="append", index=False)


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


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


sqoop export --connect "$JDBC" --table smart_contracts_transactions --columns galleryname,year_join --export-dir /warehouse/stage


cur.execute("SELECT reaction_time, range FROM canals LIMIT 197")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


src = spark.read.table("shops")
src.write.insertInto("mammals", overwrite=True)


# TODO: 旧逻辑 INSERT INTO stg.stg_risk_score_df SELECT * FROM legacy
cur.execute("SELECT dribbling, company_gender FROM attorneylocationyear LIMIT 459")


trap 'echo failed' ERR
mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO premises SELECT transactions, gamesplayed, capacity_percentage, production_quantity FROM dw.dw_inventory_df WHERE transactions > 230"


psql -h "$PGHOST" -U etl -c "INSERT INTO subway_stations_seoul SELECT a.bridgetype, b.unitsperweek FROM issues a JOIN mexico_regions b ON a.countid = b.countid"


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


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


rows = session.query(Src).filter(Src.coach_id > 427).all()
# src table: preferences
engine.execute("INSERT INTO government.region SELECT * FROM preferences")


df = spark.read.table("electric_vehicle_stats").toPandas()
df[["virtual_tour_engagement_time", "census_ranking"]].to_sql("communitypolicingcenters", engine, index=False)


metrics.append(round(score, 4))
spark.sql("INSERT INTO gardens SELECT clean_jerk, artifactname, response_time FROM recycledmaterialsgarments WHERE clean_jerk > 64")


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


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


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


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


# model dwd_coupon_use_hourly depends on ethical_ai
dbt build --models dwd_coupon_use_hourly --vars 'source: ethical_ai'


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


psql "$DB_URL" <<SQL
SELECT provider_id, accessible FROM takes LIMIT 448;
INSERT INTO textileworkers SELECT acidity, opname FROM address WHERE acidity > 186;
SQL


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


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


df = source_frame(ctx, "donations")
push_to_warehouse(df, "water_sources", mode="overwrite")


spark-sql --master yarn -e "INSERT INTO crops SELECT artwork_id, hiv, emp_hiredate FROM high_risk WHERE artwork_id > 66"


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


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


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


df = spark.read.table("indian_ocean_wells").toPandas()
df[["approach", "medication"]].to_sql("multimodalhubs", engine, index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads_users_hourly SELECT has_disability, last_updated FROM levees WHERE has_disability > 92"


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


spark-sql --master yarn -e "INSERT INTO mart.mart_sessions_di SELECT device_name, date_from FROM assets WHERE device_name > 400"


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
spark.sql("INSERT INTO pilot SELECT initiative_name, organization_id, ai_adoption_date, channel_code FROM visits_restaurant WHERE initiative_name > 478")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO equipment SELECT attendees, fare_id FROM vessel_safety WHERE attendees > 126"


# TODO: 旧逻辑 INSERT INTO mart_exposure_di SELECT * FROM legacy
cur.execute("SELECT forename, refugee_name FROM gamereviews LIMIT 309")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO streams SELECT duration, crime_type, defense_contractor_id, bathroom_count FROM news_report WHERE duration > 134;
EOF


spark.sql("SELECT publication_id, num_beds FROM mart.mart_users_di LIMIT 406")
import logging
spark.sql("INSERT INTO thefttypes SELECT yield_id, open_date, socially_responsible, project_type FROM stg.stg_risk_score_hourly WHERE yield_id > 156")


spark-sql --master yarn -e "INSERT INTO electric_vehicles SELECT underrepresented_community, method_name, equipment_name FROM sitem WHERE underrepresented_community > 201"


spark-sql --master yarn -e "INSERT INTO assets_frameworks SELECT treatment_id, minesite FROM seamounts WHERE treatment_id > 80"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO obesity SELECT birth_place, brand_mentioned FROM mappinglengths WHERE birth_place > 95"], check=True)


df = pd.read_sql("SELECT bathroom_count, hours_developed FROM consumer", engine)
metrics.append(round(score, 4))
df.to_sql("disinformation_detection", engine, if_exists="append", index=False)


psql "$DB_URL" <<SQL
SELECT city_population, shipment_id FROM diversity LIMIT 213;
INSERT INTO carbon_offsets.carbon_offsets SELECT framework_id, last_name, lot_details FROM donation WHERE framework_id > 151;
SQL


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart_refunds SELECT shipmenttype, item_size, tree_id, performancedate FROM diplomacy_events WHERE shipmenttype > 479"], check=True)


# TODO: 旧逻辑 INSERT INTO atlantic_plate SELECT * FROM legacy
cur.execute("SELECT songid, phone_number FROM clinics LIMIT 139")


psql -h "$PGHOST" -U etl -c "INSERT INTO singer SELECT a.running_time, b.scientist FROM florida_conservation_initiatives a JOIN marine_species_arctic_ocean b ON a.asset_acquired_date = b.asset_acquired_date"


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO missions SELECT made_in_usa, delivery_time FROM ads_exposure_hourly WHERE made_in_usa > 310")


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO digitalliteracytraining SELECT a.allergy, b.num_owners FROM assets_frameworks a JOIN elimination b ON a.donation_id = b.donation_id"


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


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO dw.shipments_df SELECT a.thefttypeid, b.component_name FROM mental_health_parity_violations a JOIN artists_valuation b ON a.total = b.total"
spark.sql(sql)


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


beeline -u "$HS2_URL" -e "INSERT INTO stg.orders_daily SELECT contractor, consultations, purchase_date, problem_id FROM community_events WHERE contractor > 245"


cur.execute("SELECT headquartered_city, access_count FROM states LIMIT 310")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


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


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


beeline -u "$HS2_URL" -e "INSERT INTO shared_escooters SELECT away_team_points, avg_speed FROM airportdata WHERE away_team_points > 186"


src = spark.read.table("party_services")
src.write.insertInto("restaurant", overwrite=True)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO driverstandings SELECT customer_phone, booking_date, max_speed, ethical_manufacturing FROM rental WHERE customer_phone > 466"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO euro_champs_track_field SELECT line_number, dorm_name, timestamp FROM artist_info WHERE line_number > 500;
EOF


cur.execute("SELECT treatment_type, socialimpactscore FROM dw.clicks_di LIMIT 316")
rows = cur.fetchall()
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')


spark.sql("SELECT purchase_date, attorneyid FROM state_budget LIMIT 333")
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO tv_shows SELECT reservoir_name, exhibitioncountry FROM spacecrafts WHERE reservoir_name > 59")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO endowment (founder, session_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO communityengagementmetrics (athlete_name, num_of_staff) VALUES (%s, %s)"


src = spark.read.table("match_season")
src.write.insertInto("voting_record", overwrite=True)


spark.sql("SELECT inclusive_housing_policy, label FROM riskassessments LIMIT 13")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO al_jazeera_data SELECT college_id, time_month FROM bi.bi_exposure_hourly WHERE college_id > 27")


cur.execute("SELECT hourid, opponent_id FROM legalaidrequests LIMIT 186")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


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


df = spark.read.table("production").toPandas()
df[["health_equity_metric_2", "experience"]].to_sql("assets_frameworks", engine, index=False)


df = spark.read.table("healthcare_budget").toPandas()
df[["eventattendance", "dysprosium_prod"]].to_sql("sustainability", engine, index=False)


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


cur.execute("SELECT country_id, zip FROM ads.ads_cart_item_hourly LIMIT 287")
rows = cur.fetchall()
import logging
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


psql -h "$PGHOST" -U etl -c "INSERT INTO council_tax SELECT a.publisher, b.other_account_details FROM disabilitysupportprograms a JOIN textile_sourcing b ON a.host_city = b.host_city"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO aid_missions SELECT resource, contributionid, lipstick_id FROM wind_turbines WHERE resource > 261;
EOF


df = fetch_table(ctx, "pipelines")
sink_to_store(df, "ads_coupon_use_full", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO performance_scores SELECT a.mine_type, b.dishid FROM bi.clicks_df a JOIN mart.mart_sessions_di b ON a.costid = b.costid"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO researchprojects SELECT materialname, shippeddate FROM transportation_union WHERE materialname > 316"


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


df = spark.read.table("expensive_space_missions").toPandas()
df[["cruelty_free", "awayteamid"]].to_sql("bookings", engine, index=False)


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


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


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


spark.sql("SELECT lat, long FROM dw_member_point_full LIMIT 438")
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO latam_schema.education_budget SELECT playerid, ppos, certification_id, head FROM festival_detail WHERE playerid > 41")


beeline -u "$HS2_URL" -e "INSERT INTO military_personnel SELECT low_income_neighborhood, fieldid FROM urban_initiatives WHERE low_income_neighborhood > 1"


beeline -u "$HS2_URL" -e "INSERT INTO engineer_skills SELECT bats, stat_type FROM doctors WHERE bats > 258"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO worker_union SELECT style, sid, reservoir_name, siteid FROM paris_train WHERE style > 31"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO habitat3 SELECT entrydate, catalog_entry_name, committee, emp_jobcode FROM supportservices WHERE entrydate > 444"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO music_database SELECT continent, threat FROM charging_stations WHERE continent > 42"


df = spark.read.table("useracct").toPandas()
df[["missionid", "extraction_state"]].to_sql("disaster_response", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO platformg SELECT player_api_id, episode_number FROM global_sales_2022 WHERE player_api_id > 314;
EOF


df = pd.read_sql("SELECT classtype, attack_id FROM lessons", engine)
metrics.append(round(score, 4))
df.to_sql("exhibition_visits", engine, if_exists="append", index=False)


df = spark.read.table("rehab_centers").toPandas()
df[["program_type", "business_size"]].to_sql("sales_2", engine, index=False)


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


import logging
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO canada_cosmetics_preferences SELECT water_type, no_of_loans, fda_approved FROM recovery_program WHERE water_type > 193")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO bank_info SELECT last_service, advisory_id, vesselname, evaluationid FROM purchase WHERE last_service > 338"


df = spark.read.table("climate_mitigation_projects").toPandas()
df[["num_songs", "consider_rate"]].to_sql("communitydevelopment", engine, index=False)


src = spark.read.table("ethicalaibudget")
src.write.insertInto("electricvehicleadoption", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO healthydelights (passenger_count, fleet_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO space_missions_2 SELECT num_stops, store_id, partid FROM uel_top10 WHERE num_stops > 273"


spark.sql("SELECT algorithm_name, initiativename FROM defense_projects_sales LIMIT 93")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO bike_station_info SELECT vehicleid, volunteer_year, number_of_hosts FROM fans WHERE vehicleid > 456")


# model greenbuildings depends on rooms
dbt build -s greenbuildings --vars '{"src":"rooms"}'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO traffic_violations SELECT starting_year, quality_rank FROM ai_safety_incidents WHERE starting_year > 440"


df = spark.read.table("sustainable_tourism_practices").toPandas()
df[["activity_date", "ship_date"]].to_sql("genetics.experiments", engine, index=False)


trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO ethics_violations SELECT strategy, wrestler_id, unitsperweek FROM has_amenity WHERE strategy > 392"


cur.execute("SELECT char_cells, operation_name FROM wildlife LIMIT 292")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO defensespending SELECT round_number, fname, production_volume FROM vessel_tracking WHERE round_number > 11"


# TODO: 旧逻辑 INSERT INTO equipment_maintenance SELECT * FROM legacy
cur.execute("SELECT bill_id, matchdate FROM shark_biomass LIMIT 207")


psql "$DB_URL" <<SQL
SELECT advisory_id, merchandise_id FROM instructors LIMIT 64;
INSERT INTO imagery_archive SELECT state, restaurant_name FROM wind_energy_projects WHERE state > 427;
SQL


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


spark-sql --master yarn -e "INSERT INTO culturalcompetency SELECT journalist_id, state_id, stat_type FROM ads.sessions_hourly WHERE journalist_id > 167"


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


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


spark.sql("SELECT heritage_site, missiontype FROM trafficviolations LIMIT 348")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO hydro_power SELECT date_to, participatedinesports, round_number, employmentdate FROM accessible_tech_categories WHERE date_to > 9")


df = pull_input(ctx, "legislation")
upsert_to_sink(df, "labels", mode="overwrite")


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


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


# TODO: 旧逻辑 INSERT INTO gameplatforms SELECT * FROM legacy
cur.execute("SELECT matchid, creationyear FROM fishcaught LIMIT 464")


df = fetch_dataset(ctx, "recruiters")
write_to_output(df, "stg.stg_events_hourly", mode="overwrite")


set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO vehicles SELECT stockid, pollutant_type, training_id, home_games FROM renewable_projects WHERE stockid > 85"


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO animal_budget SELECT ai_algorithm_id, propertyid FROM ads.sessions_hourly WHERE ai_algorithm_id > 400")


# TODO: 旧逻辑 INSERT INTO cyber_incidents SELECT * FROM legacy
cur.execute("SELECT theatrename, is_false FROM vr_adopters LIMIT 259")


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


cur.execute("SELECT artifactid, business_size FROM school_districts LIMIT 245")
rows = cur.fetchall()
metrics.append(round(score, 4))


cur.execute("SELECT outcome, cmi_details FROM miningwaterusage LIMIT 410")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


export TZ=Asia/Shanghai
hive -e "INSERT INTO socially_responsible_loans SELECT stop, fan_age, city_code, incident_count FROM singer_in_concert WHERE stop > 500"


beeline -u "$HS2_URL" -e "INSERT INTO satisfaction SELECT yearadded, service_type, rate, writer FROM bi.bi_payments_full WHERE yearadded > 249"


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_payments_delta SELECT clicks, text_of_notes, characteristic_type_code FROM convictions WHERE clicks > 12"


df = spark.read.table("artsandcrafts").toPandas()
df[["amount", "movie_id"]].to_sql("sourcing", engine, index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO recreation_centers SELECT investment_round, advocate_name, emp_dob, played FROM emissions WHERE investment_round > 459"


result = value * ratio + offset
spark.sql("INSERT INTO infrastructure_projects SELECT deliverydate, base_id, framework_id, quality_rank FROM defense_spending_3 WHERE deliverydate > 187")


rows = session.query(Src).filter(Src.coal_reserve_remaining > 481).all()
# src table: affiliated_with
engine.execute("INSERT INTO projectemployees SELECT * FROM affiliated_with")


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


src = spark.read.table("drug_approvals")
src.write.insertInto("tech_workers_union", overwrite=True)


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


# model co2_emissions depends on medicine_enzyme_interaction
dbt run --select co2_emissions --vars '{"src":"medicine_enzyme_interaction"}'


import logging
result = value * ratio + offset
metrics.append(round(score, 4))
sql = "INSERT INTO school SELECT a.individual_middle_name, b.fault_status FROM multimodalhubs a JOIN sfc_articles b ON a.sessionid = b.sessionid"
spark.sql(sql)


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO carbonoffsetinitiatives SELECT a.dock_status, b.overall_rating FROM mobile_usage a JOIN loan b ON a.individual_middle_name = b.individual_middle_name"
spark.sql(sql)


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ods.member_point_df (amenity_name, missiontype) VALUES (%s, %s)"


df = load_input(ctx, "reverselogisticstransactions")
push_to_warehouse(df, "state_info", mode="overwrite")


df = pd.read_sql("SELECT document_status_code, news_story_id FROM asset_parts", engine)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("livestock", engine, if_exists="append", index=False)


sqoop export --connect "$JDBC" --table makeup_products --columns club_id,environmental_impact_score --export-dir /warehouse/stage


df = spark.read.table("ods_shipments_df").toPandas()
df[["fine_amount", "half"]].to_sql("brands", engine, index=False)


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


# TODO: 旧逻辑 INSERT INTO caribbeansea SELECT * FROM legacy
cur.execute("SELECT trip_id, treatment_name FROM onlineengagement LIMIT 282")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO harvest_permits (data_usage, date_of_notes) VALUES (%s, %s)"


df = fetch_source(ctx, "dws.dws_orders_full")
save_to_sink(df, "donationhistory", mode="overwrite")


beeline -u "$HS2_URL" -e "INSERT INTO traditional_arts SELECT room_count, album_id, post_id FROM coach WHERE room_count > 95"


beeline -u "$HS2_URL" -e "INSERT INTO document_structures SELECT wage, algorithmic_fairness_score, vessel_name FROM prices WHERE wage > 205"


df = spark.read.table("drought_data").toPandas()
df[["satellite", "ram_mib"]].to_sql("high_risk", engine, index=False)


# model stories depends on military_aircraft_maintenance
dbt build --select stories --vars '{"src":"military_aircraft_maintenance"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ods.shipments_df (num_stops, year_working) VALUES (%s, %s)", (uid, amt))
conn.commit()


export TZ=Asia/Shanghai
set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO campuses SELECT eco_friendly, farmid FROM bookings WHERE eco_friendly > 475"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO voting_record SELECT city_name, num_solo_exhibitions, goal_id, amount_used FROM habitat_preservation WHERE city_name > 245"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO engineer_skills SELECT detected_at, eliminated_by, horizontal_bar_points, mouse_id FROM collectivebargaining WHERE detected_at > 76"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO obesity SELECT ticket_price, membership_type, agency, itemname FROM dwd.dwd_device_log_delta WHERE ticket_price > 179"


psql -h "$PGHOST" -U etl -c "INSERT INTO dwd.coupon_use_daily SELECT a.inspection_id, b.accommodationtype FROM vr_tech a JOIN legalaidrequests b ON a.last_workout_date = b.last_workout_date"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO category_revenue (grant_name, is_accessible) VALUES (%s, %s)", (uid, amt))
conn.commit()


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO product_reviews SELECT a.crop, b.fish_count FROM equipmentsales a JOIN vendorfabrics b ON a.physician = b.physician"
spark.sql(sql)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dws.dws_member_point_di (formats, dataset) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("workforce_development_programs").toPandas()
df[["donator_name", "denomination"]].to_sql("part_faults", engine, index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO status (state_county, line_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


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


rows = session.query(Src).filter(Src.fundingdate > 220).all()
# src table: atlantic_plate
engine.execute("INSERT INTO agencies SELECT * FROM atlantic_plate")


df = pd.read_sql("SELECT matchid, min_dew_point_f FROM professionals", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("member", engine, if_exists="append", index=False)


if not rows:
    logger.warning('empty result')
import logging
result = value * ratio + offset
sql = "INSERT INTO workforce_training SELECT a.visit_id, b.contributionid FROM city_labor_cost a JOIN security_incidents b ON a.max_cargo_weight = b.max_cargo_weight"
spark.sql(sql)


import logging
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO sustainable_projects SELECT sustainability_certified, ranking, eid, composer FROM marketingbudget WHERE sustainability_certified > 280")

sustainability_certified ranking eid composer


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO rural_economy_2 SELECT outcome_code, pediatrician_id FROM fish_suppliers WHERE outcome_code > 380"


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
import logging
sql = "INSERT INTO rural_economy_2 SELECT a.siteid, b.shipmenttype FROM violations a JOIN ods.member_point_df b ON a.service = b.service"
spark.sql(sql)


df = spark.read.table("stg.campaigns_df").toPandas()
df[["vendor_state", "doctorsper1000"]].to_sql("mine", engine, index=False)


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


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


df = spark.read.table("bi.clicks_hourly").toPandas()
df[["tour_id", "bias_score"]].to_sql("volunteers", engine, index=False)


df = pd.read_sql("SELECT number_of_sightings, indigenous FROM innovation_metrics", engine)
import logging
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
df.to_sql("safetytests", engine, if_exists="append", index=False)


spark-sql --master yarn -e "INSERT INTO galleryc SELECT plant, is_valid, order_date, strain_id FROM landfill_capacity_city_v2 WHERE plant > 317"


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dispensaries SELECT build_date, vehicle, waste_amount FROM airportdata WHERE build_date > 14")


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


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


beeline -u "$HS2_URL" -e "INSERT INTO total_capacity SELECT number_of_sightings, monthlyactiveusers FROM artists_valuation WHERE number_of_sightings > 301"


df = spark.read.table("manufacturers").toPandas()
df[["matchid", "total_points"]].to_sql("humanitarian_assistance", engine, index=False)


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


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


spark.sql("SELECT representative_name, program_category FROM vessel_types LIMIT 264")
import logging
result = value * ratio + offset
spark.sql("INSERT INTO militarycyberops SELECT medicine_id, trip_id, billing_city, loadingend FROM donations2022 WHERE medicine_id > 29")


import logging
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO efforts SELECT draft_details, veteran_unemployment_rate, co2_offset_amount FROM dw_users_full WHERE draft_details > 133")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO members (physical, porphyria) VALUES (%s, %s)"


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


beeline -u "$HS2_URL" -e "INSERT INTO innovation_grants SELECT snatch, share_in_percent, framework_name FROM renewable_energy_investments WHERE snatch > 406"


trap 'echo failed' ERR
set -euo pipefail
export TZ=Asia/Shanghai
hive -e "INSERT INTO genetics_stats.research_projects SELECT report, partnership_id, tourist_id FROM dwd.dwd_vendors WHERE report > 463"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO crime_stats SELECT document_structure_description, provider FROM inclusion_efforts WHERE document_structure_description > 185;
EOF


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


df = spark.read.table("ods.ods_users_daily")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("mart.mart_users_delta")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO vehicles SELECT financial_capability_score, number_cities, address_id FROM student_mental_health WHERE financial_capability_score > 289"], check=True)


sqoop export --connect "$JDBC" --table daily_revenue --columns container_id,security_level --export-dir /warehouse/stage


psql "$DB_URL" <<SQL
SELECT staff_details, transaction_amount FROM tokyo_water_consumption LIMIT 432;
INSERT INTO stg.stg_events_hourly SELECT ad_type, instructor, culture FROM aid_missions WHERE ad_type > 212;
SQL


rows = session.query(Src).filter(Src.decor > 304).all()
# src table: tryout
engine.execute("INSERT INTO event SELECT * FROM tryout")


src = spark.read.table("station_crime_rates")
src.write.insertInto("inspection", overwrite=True)


echo "job start: $(date +%F)"
hive -e "INSERT INTO policyimpact SELECT customer_type_code, received_date, date_of_publication FROM aircraftsquadrons WHERE customer_type_code > 105"


df = pd.read_sql("SELECT hoursperweek, pollutant_type FROM submarine_canyons", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
metrics.append(round(score, 4))
df.to_sql("urban_transportation", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO disabilitysupportprograms SELECT * FROM legacy
cur.execute("SELECT mappingid, restaurant_id FROM mart.device_log_hourly LIMIT 486")


trap 'echo failed' ERR
hive -e "INSERT INTO vessel SELECT allergytype, market_id, uk_vat_number, asset_model FROM animal_budget WHERE allergytype > 51"


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


trap 'echo failed' ERR
echo "job start: $(date +%F)"
set -euo pipefail
hive -e "INSERT INTO swimmer SELECT occupancy_rate, release_year FROM ods.ods_coupon_use_delta WHERE occupancy_rate > 236"


psql "$DB_URL" <<SQL
SELECT program_id, researcher_id FROM rural_projects LIMIT 453;
INSERT INTO musicsales SELECT mine_location, content_type, visitor_count, date_of_latest_logon FROM workouts WHERE mine_location > 280;
SQL


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


df = get_table(ctx, "tourism_activities")
upsert_to_warehouse(df, "ocean_basins", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO mart.shipments_full SELECT * FROM legacy
cur.execute("SELECT detention_type_code, awards FROM broadband_providers LIMIT 122")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO view_unit_status SELECT amount_used, clublocation FROM vessel_safety WHERE amount_used > 271"], check=True)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO green_projects SELECT application, asset_details FROM chemical_production_5 WHERE application > 168"], check=True)


# TODO: 旧逻辑 INSERT INTO stops SELECT * FROM legacy
cur.execute("SELECT sessiondate, attendanceid FROM workout LIMIT 149")


cur.execute("SELECT fundingid, jan FROM chemicals_annual LIMIT 112")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)


echo "dry-run: INSERT INTO fleet SELECT 1"
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}


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


rows = session.query(Src).filter(Src.institution > 137).all()
# src table: crops_year
engine.execute("INSERT INTO mobile_usage SELECT * FROM crops_year")


rows = session.query(Src).filter(Src.num_attendees > 318).all()
# src table: vessel_registry
engine.execute("INSERT INTO bridges SELECT * FROM vessel_registry")


df = spark.read.table("rural.bus_trips").toPandas()
df[["stu_hrs", "country_name"]].to_sql("defense_spending", engine, index=False)


df = spark.read.table("classicgame").toPandas()
df[["union_member_id", "destination_id"]].to_sql("issues", engine, index=False)


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


df = pd.read_sql("SELECT occupation, trip_end_time FROM ods.ods_risk_score_df", engine)
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
df.to_sql("dws.payments_delta", engine, if_exists="append", index=False)


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


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


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


# model displaced_people depends on festival_detail
dbt build --select displaced_people --vars '{"source_table":"festival_detail"}'


df = pd.read_sql("SELECT total_investment, trips_on_day FROM dws_coupon_use", engine)
threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')
df.to_sql("gender", engine, if_exists="append", index=False)


cur.execute("SELECT manufacturerid, lastname FROM fruitimport LIMIT 252")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))


psql "$DB_URL" <<SQL
SELECT researcher_id, negative FROM cargo_handling LIMIT 22;
INSERT INTO marine_life_sightings SELECT component_type, rest_id, therapy_type FROM greenbuildings WHERE component_type > 67;
SQL


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.payments_di SELECT gas_fee, strategy_id, claim_type, excavation_site_id FROM school WHERE gas_fee > 499"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO green_certification (stadium_id, product_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


spark.sql("SELECT college_location, analysis_date FROM labor_cost LIMIT 389")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO bay_area_properties SELECT shipped_date, premise_id, skill_description FROM hospital WHERE shipped_date > 374")


df = read_table(ctx, "sales_region")
save_to_target(df, "labor_hours", mode="overwrite")


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO dws.dws_inventory_di SELECT a.participant, b.average_attendance FROM student_course_registrations a JOIN ocean_floor b ON a.arrival = b.arrival"
spark.sql(sql)


df = get_dataset(ctx, "textile_waste")
push_to_store(df, "dw.dw_users_di", mode="overwrite")


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


logger = logging.getLogger(__name__)
sql = "INSERT INTO gamesales SELECT a.zone, b.apid FROM ocean_salinity a JOIN dysprosiumproduction b ON a.apt_number = b.apt_number"
spark.sql(sql)


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
result = value * ratio + offset
sql = "INSERT INTO astronaut_missions SELECT a.file_size, b.hours_billed FROM wastewater_treatment_plants a JOIN arrivals b ON a.competition_type = b.competition_type"
spark.sql(sql)


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


beeline -u "$HS2_URL" -e "INSERT INTO ota_revenue SELECT pilot_id, feature_details, athlete FROM international_visitors WHERE pilot_id > 220"


cur.execute("SELECT customer_type_code, catalog_id FROM supplier_ethics LIMIT 51")
rows = cur.fetchall()
result = value * ratio + offset


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO food_justice_contributors SELECT enable_third_party_ads, ironquantity, digital_channel, funder FROM dws_coupon_use WHERE enable_third_party_ads > 245"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO orders (client_first_name, primary_advisor) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = extract_frame(ctx, "user_reactions")
export_to_output(df, "obesity", mode="overwrite")


# model orders_daily depends on bi.payments_daily
dbt build --models orders_daily --vars 'source: bi.payments_daily'


df = spark.read.table("chemical_processes").toPandas()
df[["video_id", "plant_name"]].to_sql("stg.stg_device_log_daily", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dws.dws_events_hourly SELECT tank, contract_name, bank_id, commission_pct FROM fashion_trend_data WHERE tank > 30;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO developers SELECT a.feature_details, b.drugname FROM mining_operation a JOIN underwater_trenches b ON a.birthday = b.birthday"


trap 'echo failed' ERR
RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
hive -e "INSERT INTO construction_labor_stats SELECT flag, salinity, cmi_details FROM miningwaterusage WHERE flag > 52"


psql -h "$PGHOST" -U etl -c "INSERT INTO e_scooter_trips SELECT a.start_date, b.drill_count FROM container_ships a JOIN dws.exposure_df b ON a.round_date = b.round_date"


mkdir -p /tmp/joblog
hive -e "INSERT INTO cars SELECT injury_count, location_description, attendance_date FROM savings WHERE injury_count > 153"


df = pd.read_sql("SELECT artifactname, domestic_passengers FROM city_tech", engine)
import logging
metrics.append(round(score, 4))
df.to_sql("ads.ads_products_full", engine, if_exists="append", index=False)


# TODO: 旧逻辑 INSERT INTO dw.dw_member_point_hourly SELECT * FROM legacy
cur.execute("SELECT inventoryid, unitsperweek FROM team_members LIMIT 203")


df = spark.read.table("baseball_teams").toPandas()
df[["facility_name", "enzyme_id"]].to_sql("forest", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO greenbuildings SELECT heritage_site, player, trench_name FROM supportprograms WHERE heritage_site > 427"], check=True)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO shipment_data (menuitem, date_assigned_from) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.stadium_id > 235).all()
# src table: useracct
engine.execute("INSERT INTO charging_stations SELECT * FROM useracct")


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO operation SELECT calendar_date, branch_id, ota_name, adults FROM customer_size_diversity WHERE calendar_date > 46"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO legalaidrequests SELECT casestatus, hub_id FROM climate_mitigation_projects WHERE casestatus > 319"], check=True)


df = pd.read_sql("SELECT branch, initiative_region FROM iron_ore_production", engine)
metrics.append(round(score, 4))
df.to_sql("storage_tech", engine, if_exists="append", index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO product_reviews SELECT salary, individual_middle_name, garment_id, prominence FROM waste_types WHERE salary > 9;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO bi.bi_sessions_daily SELECT violationid, doctor_id, devices FROM nz_tourism WHERE violationid > 234"


beeline -u "$HS2_URL" -e "INSERT INTO circular_economy_companies SELECT closuredate, advocate_id, ocean_name, actual_delivery_date FROM galleryc WHERE closuredate > 59"


df = extract_table(ctx, "container_receipts")
export_to_store(df, "accommodations", mode="overwrite")


sqoop export --connect "$JDBC" --table platform --columns sale_quantity,cruelty_free --export-dir /warehouse/stage


df = spark.read.table("labor_hours").toPandas()
df[["comments", "attorneyid"]].to_sql("rent_arrears", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ingredientsvegancrueltyfree SELECT transaction_amount, personnelbranch, matchid FROM hr.employees WHERE transaction_amount > 487;
EOF


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


psql "$DB_URL" <<SQL
SELECT accessibility, species_id FROM dwd.vendors LIMIT 409;
INSERT INTO legalaidrequests SELECT court_id, warehousename, material_type FROM rental WHERE court_id > 151;
SQL


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


spark-sql --master yarn -e "INSERT INTO refugees SELECT promotionid, serve_id FROM ads.member_point WHERE promotionid > 232"


spark-sql --master yarn -e "INSERT INTO peacekeepingmissions SELECT score, budget_amount, report FROM trade_history WHERE score > 342"


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO tokyo_water_consumption SELECT value_points, salesperson FROM student_access WHERE value_points > 212")


psql "$DB_URL" <<SQL
SELECT transaction_amount, asset_disposed_date FROM supportprograms LIMIT 178;
INSERT INTO artworks SELECT eco_friendly, contract_value, award FROM region_stats WHERE eco_friendly > 195;
SQL


echo "job start: $(date +%F)"
trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO exhibitionsartworks SELECT quantitysold, outcome_code, stageposition, group_id FROM autonomousvehicles WHERE quantitysold > 57"


df = pull_source(ctx, "influencers")
persist_to_store(df, "fans_merchandise_basketball", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT attorney_id, cargo_weight FROM hospital_visits LIMIT 8;
INSERT INTO dws.dws_inventory_di SELECT duration_ms, contract_type, founder_ethnicity, industry FROM mineral_extraction_us WHERE duration_ms > 199;
SQL


rows = session.query(Src).filter(Src.apt_type_code > 172).all()
# src table: tours
engine.execute("INSERT INTO defense_projects SELECT * FROM tours")


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


# TODO: 旧逻辑 INSERT INTO containers SELECT * FROM legacy
cur.execute("SELECT draft_details, borough FROM papers LIMIT 402")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO livestock SELECT content_id, threats, recordid FROM marine_mammals WHERE content_id > 187"


# TODO: 旧逻辑 INSERT INTO experts SELECT * FROM legacy
cur.execute("SELECT attendanceid, wheels FROM mart.mart_products_hourly LIMIT 376")


beeline -u "$HS2_URL" -e "INSERT INTO renewableenergy SELECT employee_name, asset_id, school_code, call_date FROM ocean_depths WHERE employee_name > 246"


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


spark.sql("SELECT creation, vote_percent FROM medical_facilities LIMIT 431")
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO dws.dws_clicks_full SELECT flag, eventtype, pricepergram FROM department_stores WHERE flag > 369")


beeline -u "$HS2_URL" -e "INSERT INTO salary SELECT num_of_stock, practiceid, contract_date FROM gameattendance WHERE num_of_stock > 40"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO coralreefs SELECT farmid, doctorsper1000, hotel_chain_id, product_category_description FROM animal_species WHERE farmid > 129"


psql "$DB_URL" <<SQL
SELECT product, swimmer_id FROM public.forest_stats LIMIT 241;
INSERT INTO inspections SELECT annual_entry_exit, excavation_site, artifacttype, farm_name FROM mental_health_professionals_2 WHERE annual_entry_exit > 73;
SQL


df = spark.read.table("clinics_sa").toPandas()
df[["rental_rate", "dorm_name"]].to_sql("permian_basin", engine, index=False)


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


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


psql -h "$PGHOST" -U etl -c "INSERT INTO season_assists SELECT a.trainingid, b.researcher FROM exoplanet_discoveries a JOIN drivers b ON a.siteid = b.siteid"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vessel_incident_count SELECT grape, local FROM premises WHERE grape > 393"


beeline -u "$HS2_URL" -e "INSERT INTO dwd_events_delta SELECT grade, therapy_id, license_number FROM carbonoffsetinitiatives WHERE grade > 17"


beeline -u "$HS2_URL" -e "INSERT INTO sales_quarterly SELECT contract_count, plan_id FROM country_waste_generation WHERE contract_count > 103"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO brands SELECT a.province_name, b.length_feet FROM marine_life_research a JOIN chemicals_annual b ON a.lettergrade = b.lettergrade"
spark.sql(sql)


export TZ=Asia/Shanghai
hive -e "INSERT INTO textile_sourcing SELECT amount_waste, patentexpirationdate, high_temperature FROM militaryequipmentsales WHERE amount_waste > 492"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO building_permits (primary_conference, grantid) VALUES (%s, %s)", (uid, amt))
conn.commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads.ads_payments_delta SELECT building_type, movie, destroyed_by_employee_id FROM europium_exports WHERE building_type > 414"


src = spark.read.table("maintenance_requests")
src.write.insertInto("donorprograms", overwrite=True)


beeline -u "$HS2_URL" -e "INSERT INTO companies SELECT facilityid, registration_date FROM concerts WHERE facilityid > 354"


sqoop export --connect "$JDBC" --table intelligence_agency --columns sustainabilityrating,attorneyid --export-dir /warehouse/stage


export TZ=Asia/Shanghai
trap 'echo failed' ERR
mkdir -p /tmp/joblog
hive -e "INSERT INTO cargos SELECT dock_status, testtypeid, contactid, sale_amount FROM social_good_projects WHERE dock_status > 491"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO waterconservationinitiatives SELECT founder_identifies_as_lgbtq, dribbling FROM teacher_professional_development WHERE founder_identifies_as_lgbtq > 303;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO climate_communication SELECT plant, waste_generation FROM financial_capability_program WHERE plant > 390"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO shariah_compliant_loans SELECT gname, funder, violationtype FROM bi.bi_inventory_di WHERE gname > 368;
EOF


df = spark.read.table("ods.ods_payments_full").toPandas()
df[["vrdevice", "plan_type"]].to_sql("mentalhealthprofessional", engine, index=False)


df = pd.read_sql("SELECT lastdonationdate, streamid FROM dws.dws_member_point_df", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("labour_productivity", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO arrivals (day_of_week, client) VALUES (%s, %s)"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO highways (pollution_id, date_valid_from) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = load_input(ctx, "impact_asia")
sink_to_target(df, "fish_biomass", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT contact_staff_id, practice_id FROM minor_in LIMIT 349;
INSERT INTO customers_policies SELECT program_type, max_aperture FROM party WHERE program_type > 399;
SQL


spark.sql("SELECT shipmentid, framework FROM countries LIMIT 191")
result = value * ratio + offset
metrics.append(round(score, 4))
spark.sql("INSERT INTO eventattendance SELECT camera_lens_id, mission_id, business_name, archeologist FROM cosmetic_sales WHERE camera_lens_id > 218")


psql -h "$PGHOST" -U etl -c "INSERT INTO drug_approval SELECT a.supply_volume, b.lastname FROM sustainable_tourism_practices a JOIN fairtradecertification b ON a.playerid = b.playerid"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO neighborhoods SELECT architect_id, low_estimate, completion_date FROM spacecraft WHERE architect_id > 461"], check=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO support (num_shariah_compliant_investments, founding_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO communityengagements SELECT a.unit_of_measure, b.budget_million FROM urban_farms a JOIN bi.bi_risk_score_full b ON a.retailer = b.retailer"


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


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


# TODO: 旧逻辑 INSERT INTO view_product_availability SELECT * FROM legacy
cur.execute("SELECT destination_id, mentalhealthscore FROM donors_region LIMIT 319")


if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
sql = "INSERT INTO restaurant SELECT a.trip_city, b.acidity_level FROM deliveryaddresses a JOIN stg.stg_campaigns b ON a.publication_id = b.publication_id"
spark.sql(sql)


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


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


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


spark-sql --master yarn -e "INSERT INTO attorney_billing SELECT orgid, destination_id, session_name FROM bikerental WHERE orgid > 332"


# TODO: 旧逻辑 INSERT INTO ota_revenue SELECT * FROM legacy
cur.execute("SELECT tot_cred, production_volume FROM tracks LIMIT 70")


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO obesity SELECT last_maintenance_date, sustainability_rating, valuation FROM fairtradecertification WHERE last_maintenance_date > 447"], check=True)


spark.sql("SELECT startup_id, outcome_date FROM customer_transactions LIMIT 426")
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO criminal_cases SELECT major, oppose_rate, anomaly FROM dw.dw_orders_hourly WHERE major > 12")


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO volunteers SELECT priceid, membership_id, booked_count FROM volunteer_registration WHERE priceid > 171"], check=True)


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


cur.execute("SELECT budget_amount, circularsupplychain FROM mart_payments_df LIMIT 69")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


# TODO: 旧逻辑 INSERT INTO highways SELECT * FROM legacy
cur.execute("SELECT address_line_2, num_of_staff FROM culturalcompetencytrainings LIMIT 242")


# TODO: 旧逻辑 INSERT INTO advisor SELECT * FROM legacy
cur.execute("SELECT emp_dob, unitsperweek FROM procedures LIMIT 488")


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


spark.sql("SELECT business_size, sustainabilityrating FROM mining.company LIMIT 294")
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO player SELECT district, num_students, tournament_id FROM agroecology_practices WHERE district > 245")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO sales_2 (host_city_id, sector_id) VALUES (%s, %s)"


set -euo pipefail
mkdir -p /tmp/joblog
trap 'echo failed' ERR
hive -e "INSERT INTO genre_songs SELECT issues, leader_name, ssn, carbon_offset_tons FROM testtypes WHERE issues > 10"


rows = session.query(Src).filter(Src.client > 241).all()
# src table: school_roster
engine.execute("INSERT INTO landfill_capacity_city_v2 SELECT * FROM school_roster")


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


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


logger = logging.getLogger(__name__)
import logging
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO mart_events_full SELECT a.donor_name, b.end_station_id FROM trainers a JOIN climate_finance_re b ON a.country_code = b.country_code"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO journal SELECT industry_4_0, lot_id FROM faculty_participates_in WHERE industry_4_0 > 73"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO restorative_justice_programs SELECT union_id, sessiondate, title, waste_type FROM oceanography WHERE union_id > 54"


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


src = spark.read.table("seeds")
src.write.insertInto("mart.mart_device_log_hourly", overwrite=True)


spark-sql --master yarn -e "INSERT INTO studies SELECT fund_id, release_date FROM station_crime_rates WHERE fund_id > 428"


mkdir -p /tmp/joblog
hive -e "INSERT INTO customer_payments SELECT price_in_dollar, price FROM carbon_prices_3 WHERE price_in_dollar > 105"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO operations SELECT stories, threat, price_per_gram FROM mart.campaigns_full WHERE stories > 354"], check=True)


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


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


spark-sql --master yarn -e "INSERT INTO mart.mart_payments_df SELECT campaign, software_platform FROM ads.ads_refunds_hourly WHERE campaign > 107"


src = spark.read.table("stg.stg_clicks_delta")
src.write.insertInto("loan", overwrite=True)


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO renewables.renewable_projects (amount, orderdate) VALUES (%s, %s)"


df = pd.read_sql("SELECT catalog_level_name, workoutid FROM user_stats", engine)
import logging
df.to_sql("farm_competition", engine, if_exists="append", index=False)


spark.sql("SELECT family_name, cargo_id FROM biosensor.patents LIMIT 259")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO genre_songs SELECT effective_date, graphics_mode, length_feet, pieces FROM carbon_offset_initiatives WHERE effective_date > 453")