sqoop export --connect "$JDBC" --table mineral_extraction --columns sport_id,tournament_name --export-dir /warehouse/stage


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO research_staff SELECT forest_type, apid, cases_handled, u_id FROM bike_share WHERE forest_type > 356")


cur.execute("SELECT factory_id, genre FROM europium_exports LIMIT 102")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))


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


trap 'echo failed' ERR
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
sqoop import --connect "$JDBC" --table chemical_production_5 --target-dir /tmp/land


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO fossil_fuel_vehicles_japan (seal_species, health_equity_metric_2) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("invoices")
src.write.insertInto("port", overwrite=True)


src = spark.read.table("province.human_rights_data")
src.write.insertInto("programs", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO tree_species SELECT spacecraft_id, property_id, drug_name FROM faculty_participates_in WHERE spacecraft_id > 400"


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO bus_routes SELECT a.asset_model, b.average_age FROM workforce a JOIN rent_arrears b ON a.supplierid = b.supplierid"
spark.sql(sql)


sqoop export --connect "$JDBC" --table levees --columns location_code,socially_responsible --export-dir /warehouse/stage


df = source_source(ctx, "customer")
push_to_warehouse(df, "dw_vendors_di", mode="overwrite")


rows = session.query(Src).filter(Src.advisoryid > 216).all()
# src table: conservation_programs
engine.execute("INSERT INTO carbon_offset_programs SELECT * FROM conservation_programs")


beeline -u "$HS2_URL" -e "INSERT INTO branch SELECT fouls, transactions, is_deforested, community_type FROM waterconservationbudget WHERE fouls > 224"


df = spark.read.table("products").toPandas()
df[["rank_in_round", "farm_id"]].to_sql("fields", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO socially_responsible_loans SELECT porphyria, party FROM volunteer_registration WHERE porphyria > 350"


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


spark-sql --master yarn -e "INSERT INTO incarcerated SELECT pressure, labor_id FROM volunteer_signups WHERE pressure > 200"


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


cur.execute("SELECT partid, art_movement FROM co2price LIMIT 72")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
result = value * ratio + offset


sqoop export --connect "$JDBC" --table safety_research --columns causeid,left_office --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO time_dim SELECT member, provider_id, recycling_rate, service_type_code FROM carbon_offset_projects WHERE member > 410"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO rare_earth_companies SELECT task_details, request_date, transaction_type FROM stock_levels WHERE task_details > 485"


beeline -u "$HS2_URL" -e "INSERT INTO organic_products SELECT gender_group, donator_name FROM cargo_equipment WHERE gender_group > 254"


src = spark.read.table("patents")
src.write.insertInto("financial_capability", overwrite=True)


set -euo pipefail
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO city_waste_generation SELECT contactid, donorname, count_date FROM reo_production WHERE contactid > 394"


df = pd.read_sql("SELECT partid, fate FROM category_revenue", engine)
threshold = cfg.get('threshold', 0.5)
import logging
df.to_sql("diversification_projects", engine, if_exists="append", index=False)


echo "job start: $(date +%F)"
hive -e "INSERT INTO programoutcomes SELECT stu_fname, dribbling FROM management WHERE stu_fname > 49"


cur.execute("SELECT head_id, awayteamid FROM sports LIMIT 118")
rows = cur.fetchall()
logger = logging.getLogger(__name__)


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


rows = session.query(Src).filter(Src.airport_id > 263).all()
# src table: conservation_projects
engine.execute("INSERT INTO tree_species SELECT * FROM conservation_projects")


# TODO: 旧逻辑 INSERT INTO bi.bi_orders_delta SELECT * FROM legacy
cur.execute("SELECT dob, fan_id FROM heritage_sites LIMIT 131")


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO biosensors.projects SELECT a.sustainability_id, b.dance_form FROM game_scores a JOIN technology_access b ON a.share_in_percent = b.share_in_percent"
spark.sql(sql)


# model ods_member_point_full depends on trip
dbt run -s ods_member_point_full --vars '{"source_table":"trip"}'


sqoop export --connect "$JDBC" --table seafoodsouthafricakenya --columns routename,meal_name --export-dir /warehouse/stage


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


beeline -u "$HS2_URL" -e "INSERT INTO tracklists SELECT testtypeid, facilityid, clubid, time_month FROM stats WHERE testtypeid > 57"


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


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO match_result SELECT runtime, max_salary FROM climate_finance_asia WHERE runtime > 75;
EOF


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


df = pull_frame(ctx, "english_premier_league")
write_to_warehouse(df, "region_stats", mode="overwrite")


# TODO: 旧逻辑 INSERT INTO transportation_union SELECT * FROM legacy
cur.execute("SELECT start_therapy, clean_jerk FROM district_schools LIMIT 139")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO postseason (no_of_customers, height) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


cur.execute("SELECT wrestler_id, claimdate FROM ports LIMIT 28")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
import logging
if not rows:
    logger.warning('empty result')


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


rows = session.query(Src).filter(Src.outcome_code > 298).all()
# src table: mobile_usage
engine.execute("INSERT INTO european_healthcare SELECT * FROM mobile_usage")


beeline -u "$HS2_URL" -e "INSERT INTO climate_finance_asia SELECT museumid, price_per_gram, saleamount FROM transportation_per_country WHERE museumid > 206"


df = load_source(ctx, "nursing_homes")
upsert_to_sink(df, "circular_economy_initiatives", mode="overwrite")


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


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


beeline -u "$HS2_URL" -e "INSERT INTO facility SELECT fairtrade, course_type, fine_amount FROM tourdifferences WHERE fairtrade > 37"


sqoop export --connect "$JDBC" --table digital_trends --columns personnel,oil_production --export-dir /warehouse/stage


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


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO volunteer_hours SELECT a.report, b.staff_address_id FROM schools a JOIN state_info b ON a.last_checkup_date = b.last_checkup_date"
spark.sql(sql)


psql -h "$PGHOST" -U etl -c "INSERT INTO restaurant_revenue SELECT a.product_color, b.draft_pick_number FROM salesdata a JOIN courses b ON a.contextid = b.contextid"


df = spark.read.table("hotel_reviews").toPandas()
df[["percentage_change", "nominee"]].to_sql("visitor_statistics", engine, index=False)


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


spark.sql("SELECT openingid, score FROM redundant_billing_data LIMIT 249")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO fertilizer SELECT contract_count, archeologist, approval_date FROM energy_consumption WHERE contract_count > 489")


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


df = load_dataset(ctx, "development_hours")
sink_to_output(df, "geological_survey", mode="overwrite")


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


sqoop export --connect "$JDBC" --table electricvehicles --columns reservoir_id,stationname --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO landfills (gamegenre, excavationid) VALUES (%s, %s)"


psql -h "$PGHOST" -U etl -c "INSERT INTO transportation SELECT a.host_country, b.spacecraft FROM support_groups a JOIN ads.ads_payments b ON a.instid = b.instid"


beeline -u "$HS2_URL" -e "INSERT INTO noise_pollution SELECT produceid, customer_first_name FROM ods.ods_device_log_delta WHERE produceid > 107"


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


df = pd.read_sql("SELECT therapy_session, response_type FROM rent_arrears", engine)
threshold = cfg.get('threshold', 0.5)
df.to_sql("stories", engine, if_exists="append", index=False)


echo "job start: $(date +%F)"
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO innovation_projects SELECT truck_details, manufacturer_name FROM co_ownership WHERE truck_details > 132"


rows = session.query(Src).filter(Src.distance > 232).all()
# src table: satellite_deployment
engine.execute("INSERT INTO community_development_projects SELECT * FROM satellite_deployment")


spark.sql("SELECT yearadded, sport_id FROM trainings LIMIT 245")
import logging
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO electric_taxis SELECT startdate, vin, numpieces FROM department WHERE startdate > 204")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO soccer_teams SELECT mhw_id, catalog_name, warehouseid FROM city WHERE mhw_id > 133;
EOF


psql "$DB_URL" <<SQL
SELECT home_city, donortype FROM tunnels LIMIT 46;
INSERT INTO airport SELECT digital, other_details FROM member_data WHERE digital > 267;
SQL


df = spark.read.table("auctions").toPandas()
df[["regionname", "financial_wellbeing_score"]].to_sql("check_ins", engine, index=False)


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


spark-sql --master yarn -e "INSERT INTO cultural_competency SELECT building_short_name, transaction_category FROM production_rare_earth_elements WHERE building_short_name > 15"


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


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


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


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO electoral_register (launch_company, all_home) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pull_frame(ctx, "manufacturingplants")
save_to_store(df, "clinics", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_exposure_di SELECT password, partner FROM attendance WHERE password > 462"], check=True)


df = get_table(ctx, "game_sessions")
write_to_sink(df, "renewable_projects", mode="overwrite")


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


retries = int(os.environ.get('RETRIES', '3'))
result = value * ratio + offset
spark.sql("INSERT INTO waste_generation SELECT start, lesson_status_code, amount_funded, worker_count FROM request WHERE start > 491")


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


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


result = value * ratio + offset
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO clothing_brands SELECT goals, mentalhealthscore FROM hospital_equipment WHERE goals > 469")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO artcollection SELECT num_tools, meal_id FROM student_tests_taken WHERE num_tools > 290"


# TODO: 旧逻辑 INSERT INTO consumer_preference SELECT * FROM legacy
cur.execute("SELECT session_id, num_pallets FROM tree_habitat_associations LIMIT 438")


cur.execute("SELECT health_equity_metric_2, building_address FROM healthcare LIMIT 97")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


# model mineral_extraction depends on measurements
dbt run -s mineral_extraction --vars '{"src":"measurements"}'


df = read_input(ctx, "ods_sessions")
upsert_to_target(df, "visualartprograms", mode="overwrite")


psql -h "$PGHOST" -U etl -c "INSERT INTO companies SELECT a.creator, b.route_id FROM gradeconversion a JOIN catalogs b ON a.members = b.members"


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


psql -h "$PGHOST" -U etl -c "INSERT INTO criminalcases SELECT a.community_type, b.temporary_acting FROM environmental_impact_stats a JOIN ads.member_point b ON a.reported_by_staff_id = b.reported_by_staff_id"


src = spark.read.table("branch")
src.write.insertInto("florida_conservation_initiatives", overwrite=True)


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


logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO monitoring_zones SELECT programoutcomeid, app_id FROM financial_capability WHERE programoutcomeid > 369")


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


rows = session.query(Src).filter(Src.client_name > 445).all()
# src table: heritage_sites_3
engine.execute("INSERT INTO foodsafetyrecords SELECT * FROM heritage_sites_3")


df = get_source(ctx, "machinery")
write_to_sink(df, "branch", mode="overwrite")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO equipmentsales SELECT dname, shipment_id FROM mart.mart_vendors WHERE dname > 412"], check=True)


# model space_programs depends on mentalhealthproviders
dbt build --models space_programs --vars '{"src":"mentalhealthproviders"}'


spark-sql --master yarn -e "INSERT INTO concert_sales SELECT certified, metric_id FROM user_likes WHERE certified > 112"


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


mkdir -p /tmp/joblog
trap 'echo failed' ERR
export TZ=Asia/Shanghai
hive -e "INSERT INTO dw.dw_member_point_di SELECT subscriber_id, outcome, song_release_year, chemical_name FROM e_scooter_trips WHERE subscriber_id > 5"


psql -h "$PGHOST" -U etl -c "INSERT INTO fans_merchandise_basketball SELECT a.hometown, b.allergytype FROM phone a JOIN discount_coupons b ON a.material_date = b.material_date"


# TODO: 旧逻辑 INSERT INTO military_expenditure SELECT * FROM legacy
cur.execute("SELECT assessmentdate, hardware_colours FROM recyclingratessouthamerica LIMIT 77")


spark-sql --master yarn -e "INSERT INTO ads.events SELECT roomtype, frameworkcountry, mine_name, iata FROM facility WHERE roomtype > 198"

roomtype frameworkcountry mine_name iata


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ads_refunds_full (platformid, enable_location_tracking) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.dws_inventory_hourly (shippedcost, good_or_bad_customer) VALUES (%s, %s)"


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO infra_diversification SELECT a.num_sessions, b.volume_id FROM bi.bi_events_full a JOIN stg_users_daily b ON a.call_time = b.call_time"
spark.sql(sql)


# TODO: 旧逻辑 INSERT INTO ocean SELECT * FROM legacy
cur.execute("SELECT event_attendance, floor_area_m2 FROM art_collection LIMIT 330")


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


spark.sql("SELECT part_fault_id, practiceid FROM iron_ore_production LIMIT 177")
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO economic_diversification_argentina SELECT form_type_code, employee_count, enable_location_tracking FROM indie_artists WHERE form_type_code > 67")


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


# TODO: 旧逻辑 INSERT INTO premises SELECT * FROM legacy
cur.execute("SELECT inclusivehousing, participant_count FROM ca_menu_items LIMIT 264")


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


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


src = spark.read.table("dws_events_di")
src.write.insertInto("sportsinfo", overwrite=True)


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


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


beeline -u "$HS2_URL" -e "INSERT INTO ship_agent SELECT program_name, effort FROM milestones WHERE program_name > 16"


echo "job start: $(date +%F)"
export TZ=Asia/Shanghai
hive -e "INSERT INTO training_programs SELECT bdate, founder_identity, uses_vr, teamid FROM gameattendance WHERE bdate > 498"


df = pd.read_sql("SELECT state_province_county, check_in_date FROM carbon_emissions", engine)
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
import logging
df.to_sql("climate_adaptation_re", engine, if_exists="append", index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO pilot_record (claimid, date_of_completion) VALUES (%s, %s)"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ethicalaibudget SELECT working_year_starts, min_age, city FROM volunteerprograms WHERE working_year_starts > 454;
EOF


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dws.exposure_df (username, dept_store_chain_id) VALUES (%s, %s)"


beeline -u "$HS2_URL" -e "INSERT INTO exit_strategies SELECT tour_id, review_date, tree_species, end_speed FROM cultural_competency WHERE tour_id > 84"


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


# TODO: 旧逻辑 INSERT INTO chemicals_annual SELECT * FROM legacy
cur.execute("SELECT invoice_id, serviceid FROM contract_timeline LIMIT 14")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO assets_frameworks (budget_in_billions, average) VALUES (%s, %s)", (uid, amt))
conn.commit()


mkdir -p /tmp/joblog
hive -e "INSERT INTO labor_cost SELECT dnumber, item_price FROM defense_projects WHERE dnumber > 418"


rows = session.query(Src).filter(Src.content_type > 78).all()
# src table: biotech_startups
engine.execute("INSERT INTO tech_volunteers SELECT * FROM biotech_startups")


psql "$DB_URL" <<SQL
SELECT investorgender, emp_fname FROM inst LIMIT 456;
INSERT INTO smart_cities SELECT org_id, mentalhealthscore, cost FROM causes_insert_2 WHERE org_id > 13;
SQL


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


df = pull_input(ctx, "ads.ads_inventory_df")
dump_to_sink(df, "marine_life_data", mode="overwrite")


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


spark.sql("SELECT acc_regular_season, shelter_id FROM urban_transportation LIMIT 156")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO fish_farms SELECT protein_name, stat_type, incorporated_in, investmentid FROM recyclingrates WHERE protein_name > 163")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ocean_temperatures SELECT founder, consultations, follows_ethical_practices, num_rooms FROM dws.inventory_daily WHERE founder > 213"


rows = session.query(Src).filter(Src.research_name > 29).all()
# src table: retail_workers_union
engine.execute("INSERT INTO container_ships SELECT * FROM retail_workers_union")


sqoop export --connect "$JDBC" --table round --columns heritage_site_id,last_inspection_date --export-dir /warehouse/stage


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


# TODO: 旧逻辑 INSERT INTO agro_regions SELECT * FROM legacy
cur.execute("SELECT personal_name, technique FROM contract_negotiations_un LIMIT 451")


spark.sql("SELECT sustainability_id, artifacttype FROM ticket_sales LIMIT 126")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ads.ads_cart_item_hourly SELECT shelter_name, campaign_name, city_town FROM marine_species_observations WHERE shelter_name > 275")


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


df = get_frame(ctx, "esports_teams")
save_to_store(df, "arctictemperature", mode="overwrite")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dispensarysales SELECT price_in_euros, education_id, negative FROM highways WHERE price_in_euros > 307"


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO foodaid SELECT healthcareid, date_assigned_to FROM bookings WHERE healthcareid > 33")


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


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


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


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


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO textile_sourcing SELECT a.fault_log_entry_datetime, b.recipient FROM team a JOIN space_missions b ON a.mining_operation = b.mining_operation"
spark.sql(sql)


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


import logging
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO mineral_extraction_us SELECT tourists, protein_name, white FROM candidate_assessments WHERE tourists > 480")


beeline -u "$HS2_URL" -e "INSERT INTO volunteerprograms SELECT reviewscore, claim_outcome_code FROM container WHERE reviewscore > 32"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO tracks (vegetable, co2_reduction_tons) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("investors")
src.write.insertInto("species_forests", overwrite=True)


spark.sql("SELECT humidity, vendor FROM dw.events_hourly LIMIT 202")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO funding_rounds SELECT founded, gametype, visitors, exhibitions FROM domesticconferences WHERE founded > 20")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO affordablehousing SELECT party_name, ad_id FROM stg.refunds_hourly WHERE party_name > 298"], check=True)


spark.sql("SELECT month, price_in_dollars FROM buildings LIMIT 32")
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
import logging
spark.sql("INSERT INTO ref_product_categories SELECT contract_start_date, spf_level, shipped_date FROM animal_rehab WHERE contract_start_date > 136")


rows = session.query(Src).filter(Src.average > 185).all()
# src table: programs
engine.execute("INSERT INTO architect SELECT * FROM programs")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO captain (threats, song_year) VALUES (%s, %s)"


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


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


# model ods_cart_item_df depends on atlantic_ocean
dbt build --select ods_cart_item_df --vars '{"source_table":"atlantic_ocean"}'


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dw.dw_orders_hourly (energy_source, restaurant) VALUES (%s, %s)", (uid, amt))
conn.commit()


# model facility depends on tourism_activities
dbt run --models facility --vars 'source: tourism_activities'


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dapps SELECT shipped_date, payment_type_code, model_id, article_id FROM lives_in WHERE shipped_date > 487"


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


cur.execute("SELECT date_payment_made, meter_100 FROM all_documents LIMIT 52")
rows = cur.fetchall()
import logging


src = spark.read.table("socially_responsible_lending")
src.write.insertInto("medical_professionals", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO public_transportation_sydney (equipment, num_sessions) VALUES (%s, %s)"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO spacemissions (enable_location_tracking, model) VALUES (%s, %s)"


beeline -u "$HS2_URL" -e "INSERT INTO mineral_extraction SELECT labor_id, lastdonationdate, permitdate FROM station_company WHERE labor_id > 248"


psql -h "$PGHOST" -U etl -c "INSERT INTO settlements SELECT a.ll_hours, b.staff_first_name FROM ads.ads_risk_score_hourly a JOIN material b ON a.damage_millions_usd = b.damage_millions_usd"


echo "dry-run: INSERT INTO fund_investments SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


metrics.append(round(score, 4))
import logging
sql = "INSERT INTO bi.device_log SELECT a.group_name, b.launch FROM artwork_styles a JOIN timber_sales b ON a.status_code = b.status_code"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT assessmentdate, site_name FROM professionals LIMIT 437;
INSERT INTO view_unit_status SELECT deliverydate, mentalhealthscore FROM circulation_history WHERE deliverydate > 20;
SQL


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


# TODO: 旧逻辑 INSERT INTO round SELECT * FROM legacy
cur.execute("SELECT policy_holder_id, material_id FROM underwater_trenches LIMIT 69")


sqoop export --connect "$JDBC" --table program_history --columns event_name,conferenceid --export-dir /warehouse/stage


# model labor_hours depends on ads.ads_users_hourly
dbt run --select labor_hours --vars 'source: ads.ads_users_hourly'


psql -h "$PGHOST" -U etl -c "INSERT INTO justice_schemas.legal_tech_providers SELECT a.medical_risk, b.num_beds FROM communitydevelopment a JOIN diversity_metrics b ON a.dnumber = b.dnumber"


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


echo "dry-run: INSERT INTO global_sales_2022 SELECT 1"
trap 'echo failed' ERR
echo "job start: $(date +%F)"
set -euo pipefail


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO excavation_sites (target_name, specialty) VALUES (%s, %s)", (uid, amt))
conn.commit()


sqoop export --connect "$JDBC" --table impact_asia --columns customername,amenity_name --export-dir /warehouse/stage


spark.sql("SELECT tour_name, publication_id FROM water_distribution LIMIT 51")
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ref_attraction_types SELECT grant_end_date, contact_number, num_of_factories, hireyear FROM nutritionfacts WHERE grant_end_date > 278")


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
sql = "INSERT INTO fair_trade_brands SELECT a.snatch, b.review_text FROM mart_shipments_full a JOIN tree_species b ON a.shop_details = b.shop_details"
spark.sql(sql)


spark-sql --master yarn -e "INSERT INTO cosmetics SELECT subscriber_id, other_characteristic_details, method_name, node_id FROM cycling WHERE subscriber_id > 33"


cur.execute("SELECT arrival, community_center_id FROM artsales LIMIT 45")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))
import logging
result = value * ratio + offset


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


result = value * ratio + offset
spark.sql("INSERT INTO performers SELECT typical_selling_price, district, measurement, wage FROM trainings WHERE typical_selling_price > 88")

typical_selling_price district measurement wage


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


cur.execute("SELECT cb_year, aid_name FROM problem_log LIMIT 43")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


# model dws_users_hourly depends on contract_transactions
dbt build -s dws_users_hourly --vars '{"src":"contract_transactions"}'


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


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


beeline -u "$HS2_URL" -e "INSERT INTO ticketsales SELECT purchase_transaction_id, operationid FROM marine_life_data WHERE purchase_transaction_id > 384"


RETRIES=${RETRIES:-3}
set -euo pipefail
hive -e "INSERT INTO harvest_permits SELECT incident_name, missions FROM party_host WHERE incident_name > 242"


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


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


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO healthydelights SELECT warehousename, retailer_name FROM virtual_tourism WHERE warehousename > 413"], check=True)


spark-sql --master yarn -e "INSERT INTO sustainable_building SELECT route_short_name, cmi_cross_ref_id FROM regular_order_products WHERE route_short_name > 25"


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO rebounds SELECT route_short_name, project_details, neighborhoodid FROM bus_fare_collection WHERE route_short_name > 422"], check=True)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO fare_collection SELECT a.incident_region, b.is_male FROM digital_trends a JOIN features b ON a.defendant_id = b.defendant_id"


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


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


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))


psql -h "$PGHOST" -U etl -c "INSERT INTO inclusive_housing SELECT a.width, b.program_category FROM light_rail_lines a JOIN production_costs b ON a.playername = b.playername"


spark.sql("SELECT allergytype, courtname FROM commodity_prices LIMIT 123")
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO recreation_centers SELECT yield_per_acre, spacecraft_id, reported_date, running_time FROM stg.stg_campaigns_hourly WHERE yield_per_acre > 273")


sqoop export --connect "$JDBC" --table completed_training --columns farmid,medical_condition --export-dir /warehouse/stage


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


spark.sql("SELECT dish_name, labor_practice FROM dispensarysales LIMIT 485")
threshold = cfg.get('threshold', 0.5)
import logging
spark.sql("INSERT INTO food_safety_inspections SELECT attribute_id, representative_name, organisation_id, strategy FROM pipelines_us_canada WHERE attribute_id > 466")


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO space_missions SELECT a.word_count, b.annual_entry_exit FROM surveylocations a JOIN policyimpact b ON a.adoption_date = b.adoption_date"
spark.sql(sql)


cur.execute("SELECT agency_id, amount_payment FROM emergency_calls LIMIT 479")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)


beeline -u "$HS2_URL" -e "INSERT INTO bi.bi_risk_score_full SELECT workeridentity, founded_year, supply_volume FROM forestry_practices WHERE workeridentity > 219"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO ads_sessions_di SELECT project_category, museumid, programoutcomeid, biome_id FROM tracks WHERE project_category > 251"


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
hive -e "INSERT INTO housing_investments SELECT deaths, budgetid, census_ranking, student_capacity FROM human_resources WHERE deaths > 258"


# TODO: 旧逻辑 INSERT INTO initiatives SELECT * FROM legacy
cur.execute("SELECT sensor_id, winery FROM bi.products_daily LIMIT 103")


cur.execute("SELECT date_of_latest_revision, brand_mentioned FROM customers_policies LIMIT 167")
rows = cur.fetchall()
result = value * ratio + offset
metrics.append(round(score, 4))


# model humanitarian_aid depends on marine_species_indian
dbt build --select humanitarian_aid --vars '{"src":"marine_species_indian"}'


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


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO funding_rounds SELECT personnelbranch, matchdate, mean_sea_level_pressure_inches FROM outcomes WHERE personnelbranch > 281"


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


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


spark-sql --master yarn -e "INSERT INTO electric_vehicles SELECT ironid, opening_hours, start_station_id FROM stg.coupon_use WHERE ironid > 2"


beeline -u "$HS2_URL" -e "INSERT INTO trees SELECT town_city, subscribe_date, profits_billion, annual_entry_exit FROM playerscores WHERE town_city > 453"


df = read_input(ctx, "staff")
sink_to_warehouse(df, "user_workouts_march", mode="overwrite")


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


spark-sql --master yarn -e "INSERT INTO midwest_materials SELECT num_hotels, analysis_date, passengers FROM grad_students WHERE num_hotels > 199"


# model chemical_concentration depends on bi.bi_sessions_hourly
dbt run --models chemical_concentration --vars 'source: bi.bi_sessions_hourly'


spark.sql("SELECT meter_300, opening_hours FROM customer_policies LIMIT 473")
import logging
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO site SELECT census_ranking, license_id FROM band WHERE census_ranking > 489")


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


psql "$DB_URL" <<SQL
SELECT premise_id, shipping_agent_code FROM spacecraft LIMIT 304;
INSERT INTO chemicals_annual SELECT hoursspent, enrollment, donationamount, cargo_id FROM body_builder WHERE hoursspent > 173;
SQL

hoursspent enrollment donationamount cargo_id


df = pd.read_sql("SELECT health_equity_metric_3, reason FROM agency_satellites", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("dwd_sessions_hourly", engine, if_exists="append", index=False)


echo "dry-run: INSERT INTO enrolled_in SELECT 1"
trap 'echo failed' ERR
mkdir -p /tmp/joblog
set -euo pipefail


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO ads.ads_orders SELECT a.jobtitle, b.art_movement FROM papers a JOIN financial_transactions b ON a.missionid = b.missionid"
spark.sql(sql)


psql "$DB_URL" <<SQL
SELECT median_home_value, publication_id FROM conditions LIMIT 313;
INSERT INTO payments SELECT altitude, volunteer_name, cuisine_name FROM order_items WHERE altitude > 401;
SQL


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


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


sqoop export --connect "$JDBC" --table bi_campaigns_delta --columns birth_country,grantamount --export-dir /warehouse/stage


df = spark.read.table("stg.stg_events_di").toPandas()
df[["open_year", "investment_amount"]].to_sql("ads.ads_clicks_delta", engine, index=False)


df = spark.read.table("electricvehicles").toPandas()
df[["policytype", "building_full_name"]].to_sql("dwd.dwd_exposure_df", engine, index=False)


src = spark.read.table("dws.dws_inventory_di")
src.write.insertInto("investors", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO dwd.dwd_member_point_di SELECT practiceid, num_virtual_tours, number_thousands FROM clothing_brands WHERE practiceid > 262"


df = extract_input(ctx, "road_construction")
sink_to_target(df, "stg.stg_risk_score_df", mode="overwrite")


psql "$DB_URL" <<SQL
SELECT sanctuary, city FROM green_projects LIMIT 394;
INSERT INTO companies SELECT region_id, dispensary_name, color_code FROM community_engagement WHERE region_id > 92;
SQL


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
import logging
sql = "INSERT INTO container SELECT a.added_date, b.actual_order_id FROM recalls a JOIN recycling_rates_oceania b ON a.age = b.age"
spark.sql(sql)


RETRIES=${RETRIES:-3}
export TZ=Asia/Shanghai
mkdir -p /tmp/joblog
hive -e "INSERT INTO indian_ocean_fishingvessels SELECT product_price, role_code, indigenous FROM dw.dw_member_point_hourly WHERE product_price > 371"


df = pd.read_sql("SELECT community_size, artworkyear FROM stateinfrastructure", engine)
import logging
result = value * ratio + offset
logger = logging.getLogger(__name__)
df.to_sql("nba", engine, if_exists="append", index=False)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO goals SELECT attorney_id, task FROM donations2022 WHERE attorney_id > 476"


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO supportservices SELECT task_details, age FROM program_history WHERE task_details > 272;
EOF


# model maintenancerequests depends on infrastructureprojects
dbt run -s maintenancerequests --vars 'source: infrastructureprojects'


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


sqoop export --connect "$JDBC" --table ods_products_delta --columns rental_date,enroll_grade --export-dir /warehouse/stage


# model inventory_daily depends on ods.ods_campaigns_hourly
dbt build --select inventory_daily --vars '{"src":"ods.ods_campaigns_hourly"}'


metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
result = value * ratio + offset
spark.sql("INSERT INTO safetytestingcounts SELECT batting_average, tourist_attraction_id, velocity FROM drills WHERE batting_average > 152")


sqoop export --connect "$JDBC" --table research_vessels --columns ranking,founder_group --export-dir /warehouse/stage


spark.sql("SELECT section_title, allocation_type FROM facility_production LIMIT 176")
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO reo_production SELECT healthequitymetricscore, practice_id, online_dispute_resolution, max_wind_speed_mph FROM trenches WHERE healthequitymetricscore > 238")


metrics.append(round(score, 4))
import logging
spark.sql("INSERT INTO furniture SELECT source, album_id, products_this_year FROM total_capacity WHERE source > 159")


cur.execute("SELECT representative_name, attendanceid FROM railway LIMIT 489")
rows = cur.fetchall()
metrics.append(round(score, 4))
result = value * ratio + offset


rows = session.query(Src).filter(Src.practiceid > 185).all()
# src table: employeedata
engine.execute("INSERT INTO disabilityadvocacy SELECT * FROM employeedata")


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


spark.sql("SELECT founder_count, enddate FROM player_sessions LIMIT 464")
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO customer_master_index SELECT visit_date, store_email_address, mhw_id FROM rating WHERE visit_date > 181")


beeline -u "$HS2_URL" -e "INSERT INTO energy_efficiency_projects SELECT fanid, maxoccupancy, market_value_billion, building_address FROM iron_ore_production WHERE fanid > 296"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO attack_outcomes (assets_billion, film_id) VALUES (%s, %s)"


df = pull_table(ctx, "gene")
export_to_target(df, "num_employees", mode="overwrite")


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


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO sustainable_practices SELECT end_station_name, satellite_name FROM legalaidrequests WHERE end_station_name > 326;
EOF


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


df = spark.read.table("trends_2022")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("chemicalbatches")


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


result = value * ratio + offset
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO creativeais SELECT is_recycled, tonnage FROM investor_activities WHERE is_recycled > 90")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO traffic_violations SELECT last_maintenance, fabrictype, producerid, hours_spent FROM suburbs WHERE last_maintenance > 488"


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


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


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


df = load_table(ctx, "mart.mart_vendors")
push_to_warehouse(df, "ocean_acidification", mode="overwrite")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO company_info (bike_id, dock_count) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO southchinasea.wells (location, crs_credit) VALUES (%s, %s)"


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


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


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


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO enzyme SELECT international_passengers, dispensary_name, is_hybrid FROM animals WHERE international_passengers > 195")


sqoop export --connect "$JDBC" --table categories --columns grant_end_date,role_code --export-dir /warehouse/stage


mkdir -p /tmp/joblog
echo "job start: $(date +%F)"
trap 'echo failed' ERR
hive -e "INSERT INTO ods.sessions SELECT courtname, problem_description, contactid, international_passengers FROM ai_projects WHERE courtname > 318"


# TODO: 旧逻辑 INSERT INTO player_demographics SELECT * FROM legacy
cur.execute("SELECT maxoccupancy, co2_reduction FROM user_ad_interactions LIMIT 73")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO tech_for_social_good SELECT trip_end_time, dockingid FROM dws.dws_risk_score_df WHERE trip_end_time > 433"], check=True)


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


spark.sql("SELECT theatrename, outcome_type FROM business_rates LIMIT 70")
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))
spark.sql("INSERT INTO tunnels SELECT sighting_date, oppose_rate, date_in_location_from FROM dwd.dwd_events_delta WHERE sighting_date > 61")


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


# model seafoodsouthafricakenya depends on carbon_sequestration
dbt build -s seafoodsouthafricakenya --vars '{"src":"carbon_sequestration"}'


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO systems (patient_count, mouse_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark-sql --master yarn -e "INSERT INTO community_education_programs SELECT virtual_tour_views, programarea FROM legislation WHERE virtual_tour_views > 235"


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO water_distribution (impressions, extraction_state) VALUES (%s, %s)", (uid, amt))
conn.commit()


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO busmaintenance SELECT frameworkcountry, job_title_code FROM cosmetic_sales WHERE frameworkcountry > 183")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mart.campaigns_full (start_time, enrollment) VALUES (%s, %s)", (uid, amt))
conn.commit()


spark.sql("SELECT caloric_content, ironid FROM forest_species LIMIT 222")
import logging
spark.sql("INSERT INTO courtcases SELECT menuitemid, enzyme_id, initiative_name, machinery_id FROM inclusivehousingpolicies WHERE menuitemid > 342")


# TODO: 旧逻辑 INSERT INTO store_product SELECT * FROM legacy
cur.execute("SELECT email, wellid FROM wind_energy_projects LIMIT 56")


beeline -u "$HS2_URL" -e "INSERT INTO customer_master_index SELECT energy_star_rating, moisture_level FROM developers WHERE energy_star_rating > 185"


src = spark.read.table("invoice")
src.write.insertInto("submission", overwrite=True)


src = spark.read.table("evidence_based_policies")
src.write.insertInto("biodiversity", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO incarcerated SELECT grantamount, away_team FROM vessel_capacity WHERE grantamount > 278"


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


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


beeline -u "$HS2_URL" -e "INSERT INTO claims SELECT shipping_agent_code, apt_id FROM communitypolicingcenters WHERE shipping_agent_code > 178"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO military_spending SELECT trench_name, market_share, incidents, volunteer_id FROM waterconservation WHERE trench_name > 346"], check=True)


sqoop export --connect "$JDBC" --table satellites_by_country --columns employmentdate,q1_2022_views --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO weekly_weather (played, treatment) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table adaptation_projects --columns region_id,watertemp --export-dir /warehouse/stage


# TODO: 旧逻辑 INSERT INTO communityhealthworkerscanada SELECT * FROM legacy
cur.execute("SELECT creation_year, dockingdate FROM timber_production LIMIT 333")


# TODO: 旧逻辑 INSERT INTO party_events SELECT * FROM legacy
cur.execute("SELECT equipment_type, rehab_date FROM port_visits LIMIT 349")


import logging
result = value * ratio + offset
spark.sql("INSERT INTO runs SELECT kids, product_category FROM dw.dw_payments_full WHERE kids > 82")


rows = session.query(Src).filter(Src.disability_type > 130).all()
# src table: problem_log
engine.execute("INSERT INTO benefits_overpayments SELECT * FROM problem_log")


psql "$DB_URL" <<SQL
SELECT chemical_id, community_members FROM impact_asia LIMIT 229;
INSERT INTO community_policing SELECT accessibility, document_type_name FROM auctions WHERE accessibility > 36;
SQL


echo "dry-run: INSERT INTO skincareinventory SELECT 1"
trap 'echo failed' ERR
set -euo pipefail


cur.execute("SELECT num_volunteers, mar FROM media_types LIMIT 473")
rows = cur.fetchall()
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO livestock (operation, s_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = spark.read.table("vehicle_counts")
df = df.filter(df.status == "OK")
df.write.mode("overwrite").saveAsTable("sales_2")


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO audience SELECT engineer_id, director FROM eu_data_usage WHERE engineer_id > 366;
EOF


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


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


result = value * ratio + offset
sql = "INSERT INTO convictions SELECT a.game_id, b.inspection_date FROM train_station a JOIN contract_states b ON a.prod_date = b.prod_date"
spark.sql(sql)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO policyadvocacyevents SELECT stu_phone, claim_id, yield_per_acre FROM feedback WHERE stu_phone > 414"


beeline -u "$HS2_URL" -e "INSERT INTO rural_feeder_roads SELECT precedent_id, review_rating, amount_of_refund, date_valid_to FROM industrial_customers WHERE precedent_id > 160"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO assignedto SELECT total_employees, password, destroyed_by_employee_id FROM attendance WHERE total_employees > 312;
EOF


psql -h "$PGHOST" -U etl -c "INSERT INTO vrplayers SELECT a.breed, b.productcategory FROM publication a JOIN autonomous_research b ON a.fundingagency = b.fundingagency"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO storage SELECT research_name, gamesplayed, is_operational, testdate FROM co2_sequestration WHERE research_name > 157"], check=True)


metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO threat_intelligence_budget SELECT a.quantity_sold, b.budgetid FROM space_exploration a JOIN gamereviews b ON a.iata = b.iata"
spark.sql(sql)


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


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))


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO factories_africa (pd_id, appointmentid) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.service_name > 22).all()
# src table: mexico_regions
engine.execute("INSERT INTO auto_shows SELECT * FROM mexico_regions")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd.dwd_events_delta (city_traffic_speed, album_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))


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


df = spark.read.table("atlantic_marine_life").toPandas()
df[["equipment_type", "budget"]].to_sql("smart_city_projects", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO teacher_pd (facility_id, tier) VALUES (%s, %s)"


sqoop export --connect "$JDBC" --table emergencyservices --columns implementation_year,animal --export-dir /warehouse/stage


df = spark.read.table("dependent").toPandas()
df[["createdate", "amount_payment"]].to_sql("agricultural_innovation", engine, index=False)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO temperaturerecords SELECT official_native_language, investmenttype, medical_professional_id FROM audience WHERE official_native_language > 290;
EOF


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO menu_engineering SELECT complete_date, courses FROM fairtradecertification WHERE complete_date > 52"


retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO purchase SELECT a.founder_veteran, b.diversity_score FROM browser a JOIN mining.company b ON a.participant_details = b.participant_details"
spark.sql(sql)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO urban_transportation SELECT courtname, name_last, sculpture_name, area_type FROM animal_population_status WHERE courtname > 288"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO initiatives SELECT grant_date, carrierid, num_shariah_compliant_investments, dec FROM storage_projects WHERE grant_date > 340"


psql -h "$PGHOST" -U etl -c "INSERT INTO bus_fare_collection SELECT a.cost_id, b.waste_id FROM marinespeciesobservations a JOIN marketing_budgets b ON a.max_dew_point_f = b.max_dew_point_f"


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


spark-sql --master yarn -e "INSERT INTO round SELECT founders_lgbtq, goldquantity FROM heritage_sites WHERE founders_lgbtq > 407"


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


sqoop export --connect "$JDBC" --table mart.member_point_df --columns country_of_origin,organized_by --export-dir /warehouse/stage


cur.execute("SELECT wellbeing_score, claim_amount FROM bi.bi_exposure_hourly LIMIT 420")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))


# model ticketspending depends on complaints
dbt run -s ticketspending --vars '{"source_table":"complaints"}'


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO materials_usage SELECT receipt_date, party FROM agro_regions WHERE receipt_date > 154;
EOF


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO dws.dws_events_df SELECT last_workout_date, airline, other_item_details FROM model_fairness WHERE last_workout_date > 235")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO browser SELECT a.technique, b.startup_id FROM news_stories a JOIN students_lifelong_learning b ON a.capital = b.capital"


cur.execute("SELECT dose, oil_production FROM electricvehiclestats LIMIT 73")
rows = cur.fetchall()
retries = int(os.environ.get('RETRIES', '3'))


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO customer_size_diversity SELECT eia_date, restaurantid, menucategory, party_phone FROM electricvehiclestats WHERE eia_date > 2;
EOF


beeline -u "$HS2_URL" -e "INSERT INTO sustainable_urban_properties_2 SELECT museum_details, involved_in_lifelong_learning FROM biosensors.projects WHERE museum_details > 498"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ods.ods_events_daily (artifact_weight, max_speed) VALUES (%s, %s)"


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


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


df = source_source(ctx, "trains")
persist_to_output(df, "community_centers", mode="overwrite")


df = pd.read_sql("SELECT monthly_rental, participant FROM port", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("dwd.dwd_campaigns_df", engine, if_exists="append", index=False)


spark.sql("SELECT marketing_region_name, dispensary_name FROM ai_for_social_good LIMIT 36")
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
import logging
spark.sql("INSERT INTO iron_ore_production SELECT playdate, birthdate FROM broadband_customers_global WHERE playdate > 312")


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


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


rows = session.query(Src).filter(Src.num_students > 366).all()
# src table: workshop
engine.execute("INSERT INTO bi.refunds_daily SELECT * FROM workshop")


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


threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))
sql = "INSERT INTO courtcases SELECT a.forest_type, b.element FROM vesselarrivals a JOIN postseason b ON a.assistingnurse = b.assistingnurse"
spark.sql(sql)


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


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


rows = session.query(Src).filter(Src.ethical_certifications > 40).all()
# src table: worker_scores
engine.execute("INSERT INTO host SELECT * FROM worker_scores")


df = read_dataset(ctx, "regional_railways")
persist_to_target(df, "food_items", mode="overwrite")


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


sqoop export --connect "$JDBC" --table products_booked --columns image_data,special_features --export-dir /warehouse/stage


src = spark.read.table("ads.ads_exposure_di")
src.write.insertInto("research.species", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO match_result SELECT a.postal_code, b.trip_type FROM ads.ads_exposure_daily a JOIN containers b ON a.characteristic_name = b.characteristic_name"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO military_expenditure (heritage_site_id, document_code) VALUES (%s, %s)"


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


src = spark.read.table("farmers_india")
src.write.insertInto("state_water_usage", overwrite=True)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO repair_assignment (meter_300, building_address) VALUES (%s, %s)", (uid, amt))
conn.commit()


if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO attendee_demographics SELECT a.farmland_id, b.product_price FROM medical_professionals a JOIN indie_artists b ON a.inclusive = b.inclusive"
spark.sql(sql)


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


logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO strategies SELECT a.rooms, b.contractid FROM agencies a JOIN apartment_buildings b ON a.trip_id = b.trip_id"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO ingredient SELECT join_date, appointment_duration FROM functional_areas WHERE join_date > 340;
EOF


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


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


spark.sql("SELECT driverid, zipcode FROM fleets LIMIT 51")
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
import logging
spark.sql("INSERT INTO carbon_offset_south_america SELECT resource_id, sessiondate FROM employment WHERE resource_id > 480")


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


set -euo pipefail
mkdir -p /tmp/joblog
hive -e "INSERT INTO ai_ethics_policies SELECT catalog_publisher, bdate, cuisine_name FROM culturalcompetency WHERE catalog_publisher > 105"


df = pd.read_sql("SELECT menuitem, policyid FROM biosensors.readings", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("low_value_contracts", engine, if_exists="append", index=False)


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


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


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


sqoop export --connect "$JDBC" --table contract_transactions --columns level,rec_engine --export-dir /warehouse/stage


rows = session.query(Src).filter(Src.prominence > 466).all()
# src table: policyholders
engine.execute("INSERT INTO broadband_subscribers SELECT * FROM policyholders")


psql "$DB_URL" <<SQL
SELECT label_id, catalog_level_number FROM roles LIMIT 399;
INSERT INTO storage_projects SELECT follow_up_date, start_station_name FROM animal_populations WHERE follow_up_date > 296;
SQL


df = spark.read.table("galleries").toPandas()
df[["area_id", "longitude"]].to_sql("user_profiles", engine, index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO accessible_tech_categories SELECT noise_level, feature_details, train_id, supplierid FROM crops_table WHERE noise_level > 345"], check=True)


beeline -u "$HS2_URL" -e "INSERT INTO vulnerabilities SELECT dissolved_oxygen, workforce_development, attack_id FROM wholesale_orders WHERE dissolved_oxygen > 281"


spark.sql("SELECT contractid, volunteerage FROM smartcityprojects LIMIT 252")
metrics.append(round(score, 4))
result = value * ratio + offset
spark.sql("INSERT INTO song SELECT rid, left_office, user_category FROM ods.ods_campaigns_df WHERE rid > 116")


psql -h "$PGHOST" -U etl -c "INSERT INTO genetics.projects SELECT a.incident_count, b.fabrictype FROM mart_refunds_delta a JOIN online_platform b ON a.volunteername = b.volunteername"


beeline -u "$HS2_URL" -e "INSERT INTO communityhealthworkers SELECT alert_id, artifactid, offer_id, exhibition_id FROM mart_exposure_di WHERE alert_id > 209"


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO gradeconversion SELECT pilot_id, total_points FROM residents_services WHERE pilot_id > 227"


df = spark.read.table("chemical_processes").toPandas()
df[["emp_num", "amount_piad"]].to_sql("eco_materials", engine, index=False)


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


sqoop export --connect "$JDBC" --table class --columns algorithm_name,person_id --export-dir /warehouse/stage


df = pd.read_sql("SELECT online_dispute_resolution, played FROM musical", engine)
import logging
if not rows:
    logger.warning('empty result')
df.to_sql("life_expectancy", engine, if_exists="append", index=False)


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO maintenance_engineers SELECT strategy_name, artworkyear FROM jupiter_spacecraft WHERE strategy_name > 410"


# TODO: 旧逻辑 INSERT INTO platformh SELECT * FROM legacy
cur.execute("SELECT fault_short_name, adoption_date FROM concert_sales LIMIT 322")


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
import logging
spark.sql("INSERT INTO dali SELECT yield_id, district_id, date_of_latest_revision, volunteerjoindate FROM watertreatmentplants WHERE yield_id > 323")


spark.sql("SELECT investor_name, violation_count FROM dws.dws_cart_item_daily LIMIT 254")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO pipelines SELECT regionid, playlist_id, operation_type FROM stg.stg_risk_score_df WHERE regionid > 326")


echo "dry-run: INSERT INTO dwd.dwd_exposure_full SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


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


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO exit SELECT author_or_editor, exhibitionid, season FROM mental_health_parity_violations WHERE author_or_editor > 458"], check=True)


df = source_table(ctx, "airportdata")
export_to_store(df, "stg.stg_exposure_di", mode="overwrite")


cur.execute("SELECT reason, state_code FROM digital_trends LIMIT 227")
rows = cur.fetchall()
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


psql -h "$PGHOST" -U etl -c "INSERT INTO deep_sea_species SELECT a.time_id, b.semester FROM ads.ads_exposure_daily a JOIN safety_testing b ON a.copy_number = b.copy_number"


# TODO: 旧逻辑 INSERT INTO fabricdata SELECT * FROM legacy
cur.execute("SELECT policy_type, co_owner_count FROM road_construction LIMIT 492")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO peakhours SELECT total_points, offer_id, awardid, plan_type FROM threat_intelligence WHERE total_points > 483"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vehiclemodels SELECT product_color, node_id, num_investments FROM financial_capability_id WHERE product_color > 162"


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


df = spark.read.table("gameattendance").toPandas()
df[["cname", "team_id_loser"]].to_sql("sustainablebrands", engine, index=False)


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO wins SELECT part_name, countryid, task_details, members FROM harvest_permits WHERE part_name > 98;
EOF


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


import logging
sql = "INSERT INTO ads.users_full SELECT a.songname, b.days FROM therapy a JOIN social_impact_bonds b ON a.feature_id = b.feature_id"
spark.sql(sql)


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


df = pd.read_sql("SELECT invested, founder FROM bi_campaigns_delta", engine)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
df.to_sql("follows", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT mental_health_score, treasurer_vote FROM dwd.coupon_use_full", engine)
threshold = cfg.get('threshold', 0.5)
import logging
metrics.append(round(score, 4))
df.to_sql("water_distribution", engine, if_exists="append", index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO albums SELECT a.round_amount, b.booking_id FROM dws_products a JOIN drug_approvals b ON a.operationname = b.operationname"


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


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


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


psql "$DB_URL" <<SQL
SELECT nutrient_level, comment_count FROM minor_in LIMIT 270;
INSERT INTO indian_ocean_fishingvessels SELECT institution_name, workshop_name, neighborhood_id, community_members FROM spacecraftspeed WHERE institution_name > 437;
SQL


# TODO: 旧逻辑 INSERT INTO caseattorneys SELECT * FROM legacy
cur.execute("SELECT animal, station_name FROM patienttreatments LIMIT 160")


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO factories (has_disability, primary_conference) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO gender SELECT max_depth, recipe_id, drill_count, trainingtype FROM garments WHERE max_depth > 449"


# TODO: 旧逻辑 INSERT INTO african_tourism SELECT * FROM legacy
cur.execute("SELECT asset_model, editor_id FROM animals LIMIT 276")


spark-sql --master yarn -e "INSERT INTO audience_demographics SELECT artwork_name, discovered_date, median_home_value, cuisine_id FROM performingartsprograms WHERE artwork_name > 472"


logger = logging.getLogger(__name__)
sql = "INSERT INTO prescribes SELECT a.language, b.inventor_name FROM vessel_safety a JOIN e_scooter_trips b ON a.hometeam = b.hometeam"
spark.sql(sql)


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


if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)
sql = "INSERT INTO athletes SELECT a.dateundergoes, b.artistname FROM dwd.dwd_events_delta a JOIN cuisine b ON a.trial_name = b.trial_name"
spark.sql(sql)


RETRIES=${RETRIES:-3}
mkdir -p /tmp/joblog
hive -e "INSERT INTO electric_buses SELECT section_title, card_id, workshop_group_id, wildlife_type_id FROM department WHERE section_title > 485"


spark.sql("SELECT measurement_id, unsure_rate FROM retailerg LIMIT 490")
result = value * ratio + offset
spark.sql("INSERT INTO mentalhealthparityviolations SELECT founder_group, document_code, ingredient FROM satelliteimagery WHERE founder_group > 196")


result = value * ratio + offset
import logging
spark.sql("INSERT INTO dws_events_di SELECT comment_count, opponent_id, min_temperature_f, height FROM country_renewable_energy WHERE comment_count > 320")


df = pd.read_sql("SELECT therapy_id, publication_year FROM entrepreneur", engine)
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
df.to_sql("articles_es", engine, if_exists="append", index=False)


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO person (recruiterid, firstdonationdate) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO maintenance_engineers (production_id, gas_production_2020) VALUES (%s, %s)", (uid, amt))
conn.commit()


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO counties (center, firstname) VALUES (%s, %s)"


src = spark.read.table("vrgames")
src.write.insertInto("manufacturersustainability", overwrite=True)


src = spark.read.table("accelerator_compatible_browser")
src.write.insertInto("class", overwrite=True)


df = extract_source(ctx, "hotels")
save_to_target(df, "rainfall_data", mode="overwrite")


sqoop export --connect "$JDBC" --table office_locations --columns college,user_login --export-dir /warehouse/stage


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO milestones (customer_id, vehicleid) VALUES (%s, %s)"


rows = session.query(Src).filter(Src.license_plate > 16).all()
# src table: vrplayers
engine.execute("INSERT INTO medicine SELECT * FROM vrplayers")


df = spark.read.table("unions").toPandas()
df[["area_sqkm", "producerid"]].to_sql("studies", engine, index=False)


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


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


result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO wind_turbines SELECT assessmentdate, date_claim_made, date_of_completion FROM conditions WHERE assessmentdate > 317")


# model mart_campaigns_daily depends on energy_prices
dbt build --select mart_campaigns_daily --vars '{"source_table":"energy_prices"}'


# TODO: 旧逻辑 INSERT INTO australia_offset_programs SELECT * FROM legacy
cur.execute("SELECT hourid, staff_first_name FROM mart.clicks_delta LIMIT 203")


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


import logging
result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO irrigation_systems SELECT born_state, authors, count_date, system_name FROM green_certification WHERE born_state > 101")


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bi.bi_campaigns_delta (testtypeid, eventid) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO ocean_salinity (loan_id, production_id) VALUES (%s, %s)", (uid, amt))
conn.commit()


src = spark.read.table("rnd_budget")
src.write.insertInto("coach", overwrite=True)


df = spark.read.table("skincareproducts").toPandas()
df[["population", "resource_id"]].to_sql("recycling_rates_state", engine, index=False)


beeline -u "$HS2_URL" -e "INSERT INTO state_usage SELECT student_id, purchaseid FROM mart.mart_coupon_use_full WHERE student_id > 486"


echo "job start: $(date +%F)"
hive -e "INSERT INTO platform SELECT invoice_id, mid, environmental_impact_score FROM patient_outcomes WHERE invoice_id > 379"


beeline -u "$HS2_URL" -e "INSERT INTO heritage_sites_3 SELECT school_colors, line_number, recruitername FROM scan_dates WHERE school_colors > 109"


cur.execute("SELECT apid, amount_due FROM workforce_development LIMIT 159")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


psql "$DB_URL" <<SQL
SELECT restypedescription, sustainable_practice FROM fuel_consumption LIMIT 313;
INSERT INTO organic_products SELECT avg_depth, purchase_transaction_id FROM pilot_record WHERE avg_depth > 344;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dw.inventory_delta (disaster_id, shipmenttype) VALUES (%s, %s)", (uid, amt))
conn.commit()


df = pd.read_sql("SELECT accreditation_type, org FROM product_sales", engine)
import logging
if not rows:
    logger.warning('empty result')
df.to_sql("atlantic_marine_life", engine, if_exists="append", index=False)


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


spark.sql("SELECT number_cities, production_mwh FROM steps LIMIT 366")
result = value * ratio + offset
spark.sql("INSERT INTO diplomacy_events SELECT app_name, home_city, museum_id, bioprocess_id FROM strains WHERE app_name > 306")


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO waste_types (customer_first_name, community_type) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO vrgames SELECT date_of_completion, organization_name, artist, funding_source FROM bi.bi_payments_delta WHERE date_of_completion > 301"


spark-sql --master yarn -e "INSERT INTO culturalcompetencytrainings SELECT dose, sustainability_id, acc_percent FROM workouts WHERE dose > 459"


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


sqoop export --connect "$JDBC" --table passenger_trips --columns appointment_date,unit_name --export-dir /warehouse/stage


src = spark.read.table("news_stories")
src.write.insertInto("carbon_sequestration", overwrite=True)


# model fireincidents depends on producers
dbt build -s fireincidents --vars '{"source_table":"producers"}'


rows = session.query(Src).filter(Src.yield > 96).all()
# src table: spacecraft_temperatures
engine.execute("INSERT INTO exit_strategy SELECT * FROM spacecraft_temperatures")


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO fair_trade_brands SELECT start_speed, university FROM art_pieces WHERE start_speed > 370"], check=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO spacecraftspeed SELECT a.purchases, b.account_id FROM english_premier_league a JOIN documents_to_be_destroyed b ON a.event_id = b.event_id"


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


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
total = sum(x ** 2 for x in range(100))
print(round(total / 7, 3))


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO ads.ads_clicks_delta SELECT investor, num_volunteers FROM location WHERE investor > 440"], check=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO museums SELECT party_phone, policyholderid, environmental_impact_score FROM donationhistory WHERE party_phone > 371"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO militaryinnovations SELECT capacity, established_date FROM weather WHERE capacity > 231;
EOF


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


# TODO: 旧逻辑 INSERT INTO school_enrollment SELECT * FROM legacy
cur.execute("SELECT event_id, last_checkup_date FROM invoice LIMIT 4")


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


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


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


# model india_ingredient_sourcing depends on wellbeing_programs
dbt build --models india_ingredient_sourcing --vars '{"source_table":"wellbeing_programs"}'


# TODO: 旧逻辑 INSERT INTO procedures SELECT * FROM legacy
cur.execute("SELECT transportation_method, form_name FROM restaurant LIMIT 168")


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


spark.sql("SELECT inspection_date, heart_rate FROM arctic_research LIMIT 157")
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO community_members SELECT occupancy_rate, council_tax_id, race, exhibitionid FROM financialwellbeing WHERE occupancy_rate > 113")


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


psql "$DB_URL" <<SQL
SELECT hispanic, business_size FROM legislation LIMIT 94;
INSERT INTO journal_committee SELECT society, songid, recycler_id FROM seasonalvegetables WHERE society > 420;
SQL


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


psql "$DB_URL" <<SQL
SELECT menuname, points FROM online_platform LIMIT 292;
INSERT INTO membership_data SELECT asset_id, devices, resource_type, customerid FROM trip WHERE asset_id > 176;
SQL


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


rows = session.query(Src).filter(Src.denomination > 376).all()
# src table: militarypatents
engine.execute("INSERT INTO manufacturingplants SELECT * FROM militarypatents")


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


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO esportsevents SELECT a.winery, b.provider_parity_score FROM bikerental a JOIN voting_data b ON a.donor = b.donor"
spark.sql(sql)


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


src = spark.read.table("traffic_citations")
src.write.insertInto("districts", overwrite=True)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO recycling_centers SELECT donorid, amount_used FROM investment_rounds WHERE donorid > 354"


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


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


set -euo pipefail
hive -e "INSERT INTO dws.shipments_daily SELECT organic, mappingid, cultural_diversity, cell_mobile_number FROM criticalincidents WHERE organic > 47"


spark-sql --master yarn -e "INSERT INTO marine_mammals SELECT detection_date, allocation_date, coach_id, artpiecename FROM fault_log_parts WHERE detection_date > 4"


rows = session.query(Src).filter(Src.updated_at > 13).all()
# src table: precipitation_data
engine.execute("INSERT INTO dws_events_di SELECT * FROM precipitation_data")


df = spark.read.table("bi.bi_orders_hourly").toPandas()
df[["num_attendees", "funding_received"]].to_sql("document_types", engine, index=False)


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


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


cur.execute("SELECT donor_category, company_gender FROM veteran_stats LIMIT 145")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)


echo "job start: $(date +%F)"
mkdir -p /tmp/joblog
RETRIES=${RETRIES:-3}
hive -e "INSERT INTO enrolled_in SELECT shipping_agent_name, journalist_id, injury FROM tracklists WHERE shipping_agent_name > 229"


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


# TODO: 旧逻辑 INSERT INTO suppliersfairlabor SELECT * FROM legacy
cur.execute("SELECT grant_end_date, premises_type FROM follows LIMIT 6")


spark-sql --master yarn -e "INSERT INTO ca_menu_items SELECT employee_count, max_depth, mission_id, common_name FROM legislation WHERE employee_count > 248"


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


export TZ=Asia/Shanghai
hive -e "INSERT INTO phone_market SELECT days_held, black FROM co2_sequestration WHERE days_held > 190"


psql -h "$PGHOST" -U etl -c "INSERT INTO savings_programs SELECT a.channel, b.cust_name FROM wins a JOIN instructors b ON a.yield = b.yield"


threshold = cfg.get('threshold', 0.5)
sql = "INSERT INTO volunteerhours SELECT a.amenid, b.operation_count FROM ucl_top10 a JOIN stg.refunds_hourly b ON a.src_apid = b.src_apid"
spark.sql(sql)


df = pd.read_sql("SELECT community_center_id, dlocation FROM customer_address_history", engine)
logger = logging.getLogger(__name__)
df.to_sql("dwd_events_delta", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT address, count_time FROM course_authors_and_tutors", engine)
logger = logging.getLogger(__name__)
df.to_sql("orgdonations", engine, if_exists="append", index=False)


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO intelligence_agents SELECT resource, menuitem FROM adaptation_projects WHERE resource > 178"], check=True)


df = spark.read.table("volunteer_hours").toPandas()
df[["visit_month", "order_details"]].to_sql("teams_mascots", engine, index=False)


mkdir -p /tmp/joblog
hive -e "INSERT INTO claims SELECT venue, founder_lgbtq, roomname, union_member FROM licenses WHERE venue > 486"


psql "$DB_URL" <<SQL
SELECT center, document_id FROM exhibitiondetails LIMIT 5;
INSERT INTO support_tickets SELECT retailer, star_rating_description FROM iron WHERE retailer > 207;
SQL


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


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


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


beeline -u "$HS2_URL" -e "INSERT INTO station_crime_rates SELECT drug_id, num_accessible_tech_centers FROM service_budget WHERE drug_id > 257"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO attendee_demographics (pet_age, daily_distance) VALUES (%s, %s)", (uid, amt))
conn.commit()


rows = session.query(Src).filter(Src.painting_name > 205).all()
# src table: france_culture
engine.execute("INSERT INTO courts SELECT * FROM france_culture")


# TODO: 旧逻辑 INSERT INTO students_enrollment SELECT * FROM legacy
cur.execute("SELECT digital_asset, grant_end_date FROM financialwellbeing LIMIT 263")


echo "dry-run: INSERT INTO ocean_floor SELECT 1"
set -euo pipefail
mkdir -p /tmp/joblog


psql "$DB_URL" <<SQL
SELECT weeks_on_top, baseprice FROM oil_production LIMIT 83;
INSERT INTO ads.ads_payments_hourly SELECT safety_rating, species FROM manufacturer WHERE safety_rating > 303;
SQL


rows = session.query(Src).filter(Src.ota_name > 277).all()
# src table: ticket_sales
engine.execute("INSERT INTO hospitallocations SELECT * FROM ticket_sales")


presto --server presto01:8080 --catalog hive --execute "INSERT INTO departments SELECT course_completion, request, dribbling FROM location WHERE course_completion > 247"


df = spark.read.table("bridge").toPandas()
df[["strain_name", "share_count"]].to_sql("members", engine, index=False)


df = pd.read_sql("SELECT ironid, accommodation_type FROM cargos", engine)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
df.to_sql("financial_capability_id", engine, if_exists="append", index=False)


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stores (song_name, trade_name) VALUES (%s, %s)", (uid, amt))
conn.commit()


if not rows:
    logger.warning('empty result')
result = value * ratio + offset
sql = "INSERT INTO ticketsales SELECT a.hospitalid, b.year_opened FROM restaurants_tx a JOIN navalequipmentmaintenance b ON a.individual_id = b.individual_id"
spark.sql(sql)


logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO brands SELECT campaign_name, policyholderid, catalog_entry_name FROM city_tech WHERE campaign_name > 193")


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO bi.clicks_df (engagementid, headquarters) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO container_ships (individual_first_name, shipment_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


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


df = pd.read_sql("SELECT eco_certified, restypename FROM store_product", engine)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("vr_tech", engine, if_exists="append", index=False)


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


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_inventory SELECT a.subject_area_id, b.doctor_id FROM dw.dw_coupon_use_daily a JOIN timbersales b ON a.archaeologistid = b.archaeologistid"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO donationsbycause SELECT enable_location_tracking, game_count FROM station_emergencies WHERE enable_location_tracking > 458"], check=True)


rows = session.query(Src).filter(Src.hireyear > 488).all()
# src table: bi.users_full
engine.execute("INSERT INTO mart.vendors_full SELECT * FROM bi.users_full")


threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
sql = "INSERT INTO transport SELECT a.court_appearances, b.driver_id FROM haircare_cruelty a JOIN sustainable_projects b ON a.total_horses = b.total_horses"
spark.sql(sql)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO donationsbycause SELECT gtype, eventtype, ei_category, frameworkcountry FROM workshops WHERE gtype > 285;
EOF

gtype eventtype ei_category frameworkcountry


psql "$DB_URL" <<SQL
SELECT menuitemname, draft_details FROM route LIMIT 93;
INSERT INTO menu_vendors SELECT departure_date, fault_short_name, part_fault_id, hiv FROM contracts WHERE departure_date > 345;
SQL


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


import logging
threshold = cfg.get('threshold', 0.5)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO water_usage SELECT a.timestamp, b.bdate FROM bi.bi_inventory_di a JOIN customers_cards b ON a.is_autonomous = b.is_autonomous"
spark.sql(sql)


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


spark.sql("SELECT base_id, mean_temperature_f FROM economic_diversification_efforts LIMIT 428")
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO dw.dw_member_point_hourly SELECT reo_type, fueldate, cust_name FROM regulatory_frameworks WHERE reo_type > 218")


psql -h "$PGHOST" -U etl -c "INSERT INTO cases SELECT a.astronaut_id, b.sculpture_name FROM trainmaintenance a JOIN esports_teams b ON a.latitude = b.latitude"


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


beeline -u "$HS2_URL" -e "INSERT INTO invoice_lines SELECT workoutid, sd_id, join_year, user_name FROM dws.dws_orders_full WHERE workoutid > 485"


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


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.mart_users_delta SELECT languages, location_name FROM news_views WHERE languages > 193"], check=True)


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO vehicledata SELECT master_customer_id, cultural_significance, part_fault_id, points_per_game FROM sustainable_urban WHERE master_customer_id > 254"


spark.sql("SELECT train_number, observation_id FROM smartcontracts LIMIT 340")
import logging
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO militaryinnovations SELECT mailing_date, job_id, color, attorney_id FROM fundings WHERE mailing_date > 263")


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


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


echo "job start: $(date +%F)"
hive -e "INSERT INTO voting_data SELECT change_date, date_of_notes, served_subscribers FROM mart_shipments_full WHERE change_date > 413"


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


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


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO ads.ads_cart_item_hourly (artwork, success) VALUES (%s, %s)"


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


beeline -u "$HS2_URL" -e "INSERT INTO inspections SELECT maintenance_id, working_year_starts FROM tracks WHERE maintenance_id > 55"


sqoop export --connect "$JDBC" --table renewable_projects --columns sanctuary,vessel --export-dir /warehouse/stage


df = fetch_frame(ctx, "store_product")
persist_to_store(df, "military_equipment", mode="overwrite")


df = pull_input(ctx, "budget_allocations")
sink_to_store(df, "thefttypes", mode="overwrite")


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


psql -h "$PGHOST" -U etl -c "INSERT INTO restaurant SELECT a.invoice_date, b.business_id FROM global_sales_2022 a JOIN mart.mart_events_di b ON a.forest_id = b.forest_id"


sqoop export --connect "$JDBC" --table african_tourism --columns typical_buying_price,decision --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dailystreams SELECT booking_id, waste_type, follow_up_date, functional_area_code FROM bi.bi_risk_score_delta WHERE booking_id > 8"], check=True)


result = value * ratio + offset
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ads_coupon_use_full SELECT permitid, rainfall, matchid FROM eco_materials WHERE permitid > 490")


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


presto --server presto01:8080 --catalog hive --execute "INSERT INTO mart.mart_sessions_di SELECT classroom, inclusive_housing_policy, founded, nominee FROM co2emissions WHERE classroom > 49"

classroom inclusive_housing_policy founded nominee


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


beeline -u "$HS2_URL" -e "INSERT INTO carbon_prices_3 SELECT diagnosis, characteristic_data_type FROM astronaut_missions WHERE diagnosis > 408"


rows = session.query(Src).filter(Src.cancel_date > 362).all()
# src table: fruitimport
engine.execute("INSERT INTO researchgrants SELECT * FROM fruitimport")


df = fetch_source(ctx, "submersible_dives")
persist_to_target(df, "cultural_competency_training", mode="overwrite")


rows = session.query(Src).filter(Src.clicks > 343).all()
# src table: military_bases
engine.execute("INSERT INTO venture SELECT * FROM military_bases")


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO mart.mart_products_df SELECT staff_name, label_id, usage, emp_num FROM creativeais WHERE staff_name > 267;
EOF


# model military_personnel depends on overwatch_scores
dbt build -s military_personnel --vars 'source: overwatch_scores'


rows = session.query(Src).filter(Src.ll_id > 390).all()
# src table: stg.stg_clicks_delta
engine.execute("INSERT INTO fireincidents SELECT * FROM stg.stg_clicks_delta")


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


sqoop export --connect "$JDBC" --table light_rail_lines --columns catalog_level_number,elevation --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO daily_oil_production SELECT ticketprice, fanid FROM socialimpactinvestments WHERE ticketprice > 357"], check=True)


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


# model astronauts depends on ods.ods_clicks_di
dbt run --models astronauts --vars '{"src":"ods.ods_clicks_di"}'


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


rows = session.query(Src).filter(Src.other_account_details > 361).all()
# src table: socially_responsible_lending
engine.execute("INSERT INTO sports_events SELECT * FROM socially_responsible_lending")


df = pd.read_sql("SELECT projectid, org_id FROM concert_events", engine)
retries = int(os.environ.get('RETRIES', '3'))
import logging
df.to_sql("ingredientsvegancrueltyfree", engine, if_exists="append", index=False)


df = pd.read_sql("SELECT * FROM mart.mart_payments_delta", conn)
df.to_sql("bi.inventory_daily", conn, if_exists="replace", index=False)