frame = warehouse_client.fetch(table="public_buses", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO crane SELECT pilot_name, assets_billion, date_closed FROM hospital_beds WHERE pilot_name > 467")


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO countryincome SELECT org_name, institution_id, dish FROM dws_refunds_daily WHERE org_name > 8"))


retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO journalist SELECT discovered_date, location_code, rebounds, host_country FROM resourcemanagement WHERE discovered_date > 43")


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO ships SELECT scoreid, part_fault_id, velocity FROM debate_people WHERE scoreid > 344"))


beeline -u "$HS2_URL" -e "INSERT INTO affected_region SELECT astronautid, num_libraries, case_type FROM bi_exposure_daily WHERE astronautid > 34"


@pipeline(reads="union_membership_statistics", writes="readers")
def run(src):
    return transform(src)


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


clickhouse-client --host ch01 --query "INSERT INTO csu_fees SELECT plantid, school_colors FROM images WHERE plantid > 10"


events = spark.table("news_articles").where("dt = current_date()")
events.writeTo("claims_processing").append()


@pipeline(reads="stg_sessions_daily", writes="donationdates")
def run(src):
    return transform(src)


events = spark.table("suppliers").where("dt = current_date()")
events.writeTo("europe_org").append()


cur.execute("SELECT fanid, shares FROM marine_protected_areas LIMIT 91")
rows = cur.fetchall()
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))


clickhouse-client --host ch01 --query "INSERT INTO products_for_hire SELECT built, case_status, uses_vr FROM techniques WHERE built > 267"


frame = warehouse_client.fetch(table="skincare_ingredients", limit=5000)
result = value * ratio + offset
logger = logging.getLogger(__name__)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO startup SELECT area_id, therapy_date, portfolio_id, attraction_type_code FROM unique_devices WHERE area_id > 344"))


events = spark.table("visitor_stats").where("dt = current_date()")
events.writeTo("students_in_detention").append()


trap 'echo failed' ERR
hive -e "INSERT INTO ferry_routes SELECT product_color, audienceid, supporter, num_stops FROM cultural_sites WHERE product_color > 465"


clickhouse-client --host ch01 --query "INSERT INTO dissolved_oxygen_readings SELECT pollution_id, start_year, replacement_cost FROM african_region_table WHERE pollution_id > 456"


impala-shell -i impalad01 -q "INSERT INTO unique_donors SELECT population, primaryaffiliation FROM member_workouts WHERE population > 204"


clickhouse-client --host ch01 --query "INSERT INTO stg.stg_products_hourly SELECT vendor_id, sale_amount, branch FROM community_education WHERE vendor_id > 328"


spark.sql("SELECT date_and_date, classroom FROM intangible_heritage LIMIT 492")
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
spark.sql("INSERT INTO injuries SELECT max_dissolved_oxygen, deliveryid, name_last FROM classes WHERE max_dissolved_oxygen > 447")


@pipeline(reads="dwd.device_log_daily", writes="dental_clinics")
def run(src):
    return transform(src)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO satellite_launches (supporter, date_account_opened) VALUES (%s, %s)"


spark-sql --master yarn -e "INSERT INTO smartcityinitiatives SELECT cropid, race FROM ocean_temperature WHERE cropid > 282"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO spaceships (hotel_id, participant) VALUES (%s, %s)", (uid, amt))
conn.commit()


Repo.of("project_budget").select(["id", "amt"]).copy_into("retail").commit()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO stg.stg_orders_df SELECT report_date, statement_id, dockingid FROM autonomous_vehicles WHERE report_date > 439;
EOF


cur.execute("SELECT address_line_1, waste_type FROM dws.dws_orders_df LIMIT 310")
rows = cur.fetchall()
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


events = spark.table("safety_test_results").where("dt = current_date()")
events.writeTo("investigative_journalism").append()


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


events = spark.table("contractors").where("dt = current_date()")
events.writeTo("cargoships").append()


src = spark.read.table("member_workout_date")
src.write.insertInto("mentalhealthparity", overwrite=True)


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


frame = warehouse_client.fetch(table="tourism_impact", limit=5000)
logger = logging.getLogger(__name__)
import logging


clickhouse-client --host ch01 --query "INSERT INTO financial_institutions SELECT emission_date, away_team_three_point FROM organiccottongarments WHERE emission_date > 213"


rows = session.query(Src).filter(Src.product_type > 238).all()
# src table: destinations
engine.execute("INSERT INTO images SELECT * FROM destinations")


impala-shell -i impalad01 -q "INSERT INTO community_development SELECT departmentid, patient_id, tech_type FROM ocean_basin WHERE departmentid > 261"


frame = warehouse_client.fetch(table="dwd.member_point_df", limit=5000)
import logging


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO addresses SELECT savings, report_id, connection FROM cargoships WHERE savings > 296"))


cur.execute("SELECT event, nutrient_level FROM company_data LIMIT 154")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


impala-shell -i impalad01 -q "INSERT INTO documents_with_expenses SELECT container_count, longitude, manufacturer_name, origin_city FROM stg.stg_exposure_df WHERE container_count > 497"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO trip_segments SELECT energy_star_rating, location_id, how_to_get_there FROM stock_data WHERE energy_star_rating > 487"))


events = spark.table("airports").where("dt = current_date()")
events.writeTo("crane").append()


# model financial_wellbeing depends on workforce_diversity
dbt run --select financial_wellbeing --vars '{"src":"workforce_diversity"}'


events = spark.table("artifactcounts").where("dt = current_date()")
events.writeTo("freight_forwarding").append()


# model products_hourly depends on age_groups
dbt run --select products_hourly --vars '{"src":"age_groups"}'


src = spark.read.table("broadcast")
src.write.insertInto("lanthanummines", overwrite=True)


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))


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO dysprosium_production SELECT sales_count, max_depth, exhibitionname, num_virtual_tours FROM intangible_heritage WHERE sales_count > 479"))


# model lines depends on production_quebec
dbt run --select lines --vars '{"src":"production_quebec"}'


clickhouse-client --host ch01 --query "INSERT INTO instruments SELECT machine_id, equipment_id FROM ods.ods_member_point WHERE machine_id > 265"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO artdistribution SELECT vehicle_flight_number, completion_status, date_became_customer, opname FROM factory WHERE vehicle_flight_number > 422"))


Repo.of("supplier").select(["id", "amt"]).copy_into("news_ratings").commit()


spark.sql("SELECT mining_operation_id, apid FROM emergency_incidents LIMIT 48")
import logging
spark.sql("INSERT INTO lanthanummines SELECT project_education, model_id, service, creation FROM stg_campaigns_di WHERE project_education > 77")


# model personfriend depends on lending_initiatives
dbt run --select personfriend --vars '{"src":"lending_initiatives"}'


# model skills_required_to_fix depends on union_members_demographics
dbt run --select skills_required_to_fix --vars '{"src":"union_members_demographics"}'


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


src = spark.read.table("startup")
src.write.insertInto("community_education", overwrite=True)


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


impala-shell -i impalad01 -q "INSERT INTO screenings SELECT sanctuary, customer_country, sport_id FROM dwd.dwd_campaigns_daily WHERE sanctuary > 148"


impala-shell -i impalad01 -q "INSERT INTO playlist_tracks SELECT disease, heritage_site_id FROM sector WHERE disease > 433"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO medical SELECT common_name, operation_type, satellite, hireid FROM recipe WHERE common_name > 323"))


# model news_ratings depends on stg.stg_exposure_df
dbt run --select news_ratings --vars '{"src":"stg.stg_exposure_df"}'


# model stg_sessions_daily depends on museumart
dbt run --select stg_sessions_daily --vars '{"src":"museumart"}'


Repo.of("contractors").select(["id", "amt"]).copy_into("solar_installations").commit()


Repo.of("moviebudgets").select(["id", "amt"]).copy_into("physician").commit()


df = spark.read.table("restorative_justice").toPandas()
df[["recruiterid", "doctorsper1000"]].to_sql("smartcitysavings", engine, index=False)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO community_education SELECT artworkname, game_id, dept_code FROM citizen_feedback_records WHERE artworkname > 168"))


events = spark.table("traveladvisoryreasons").where("dt = current_date()")
events.writeTo("dws.dws_sessions_df").append()


# model elements depends on pumped_hydro_projects
dbt run --select elements --vars '{"src":"pumped_hydro_projects"}'


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


Repo.of("mascaras").select(["id", "amt"]).copy_into("client").commit()


impala-shell -i impalad01 -q "INSERT INTO techniques SELECT projectid, silver, event_details, maxoccupancy FROM hotel_ai WHERE projectid > 241"

projectid silver event_details maxoccupancy


impala-shell -i impalad01 -q "INSERT INTO countryincome SELECT match_id, framework_id, purchase_details, observation_date FROM product_complaints WHERE match_id > 218"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO elements (working_horses, oct) VALUES (%s, %s)", (uid, amt))
conn.commit()


frame = warehouse_client.fetch(table="dws.dws_exposure_df", limit=5000)
metrics.append(round(score, 4))


@pipeline(reads="stg_exposure_delta", writes="member_demographics")
def run(src):
    return transform(src)


impala-shell -i impalad01 -q "INSERT INTO ref_company_types SELECT provider_name, reason, artworkid, other_item_details FROM education_aid WHERE provider_name > 160"


@pipeline(reads="instruments", writes="studentsmentalhealth")
def run(src):
    return transform(src)


Repo.of("dw_clicks_hourly").select(["id", "amt"]).copy_into("ethereum_contracts").commit()


clickhouse-client --host ch01 --query "INSERT INTO nurse SELECT languageid, averagespeed, author_or_editor, attorney FROM buildingtypes WHERE languageid > 236"

languageid averagespeed author_or_editor attorney


# model education_aid depends on project_staff
dbt run --select education_aid --vars '{"src":"project_staff"}'


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


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


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
spark.sql("INSERT INTO dws.dws_inventory_full SELECT customer_email_address, gender_mf, casestatus FROM actual_orders WHERE customer_email_address > 219")


clickhouse-client --host ch01 --query "INSERT INTO ai_recs SELECT model_year, movie, stu_num, meter_200 FROM therapeutic_areas WHERE model_year > 91"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO studentsmentalhealth SELECT feedid, consider_rate, date_assigned_from, task_id FROM mlb_teams_mascots WHERE feedid > 106"


psql "$DB_URL" <<SQL
SELECT treatment_id, consultations FROM eco_accommodations LIMIT 173;
INSERT INTO artist_genre SELECT chair_name, section_id FROM arctic_vessels WHERE chair_name > 336;
SQL


impala-shell -i impalad01 -q "INSERT INTO classes SELECT profession, interaction_type FROM vulnerabilityassessments WHERE profession > 110"


@pipeline(reads="mining_sites", writes="europe_org")
def run(src):
    return transform(src)


# model transactions depends on donors
dbt run --select transactions --vars '{"src":"donors"}'


src = spark.read.table("airports")
src.write.insertInto("energy_efficiency", overwrite=True)


frame = warehouse_client.fetch(table="visitor_demographics", limit=5000)
logger = logging.getLogger(__name__)


metrics.append(round(score, 4))
sql = "INSERT INTO mining_company_revenue SELECT a.department_id, b.reign FROM endangered_species a JOIN elements b ON a.document_name = b.document_name"
spark.sql(sql)


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


events = spark.table("lifelong_learning").where("dt = current_date()")
events.writeTo("dws.dws_sessions_df").append()


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO memberships SELECT species_id, wildlife_type_id FROM bi.products_hourly WHERE species_id > 375"))


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


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


@pipeline(reads="ads.ads_users_delta", writes="autonomous_taxis")
def run(src):
    return transform(src)


Repo.of("resourcemanagement").select(["id", "amt"]).copy_into("user_check_ins").commit()


clickhouse-client --host ch01 --query "INSERT INTO aquaculture_zones SELECT unique_founders, rural_area, culturalcompetency FROM treatment WHERE unique_founders > 464"


df = pd.read_sql("SELECT gameid, task_details FROM oregondispensaries", engine)
metrics.append(round(score, 4))
df.to_sql("country", engine, if_exists="append", index=False)


@pipeline(reads="church", writes="classes")
def run(src):
    return transform(src)


frame = warehouse_client.fetch(table="content", limit=5000)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


Repo.of("unique_donors").select(["id", "amt"]).copy_into("playlist_tracks").commit()


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


Repo.of("tech_transactions").select(["id", "amt"]).copy_into("project_outcomes").commit()


psql -h "$PGHOST" -U etl -c "INSERT INTO platforms SELECT a.hotel_id, b.creation FROM elections a JOIN gamerevenue b ON a.local_authority = b.local_authority"


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


events = spark.table("clientinvestments").where("dt = current_date()")
events.writeTo("emergency_incidents").append()


impala-shell -i impalad01 -q "INSERT INTO dws.dws_exposure_df SELECT feb, units_sold FROM broadcast WHERE feb > 194"


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


# model london_train_trips depends on criminal_database
dbt run --select london_train_trips --vars '{"src":"criminal_database"}'


Repo.of("farm_soil_moisture").select(["id", "amt"]).copy_into("studentsmentalhealth").commit()


impala-shell -i impalad01 -q "INSERT INTO dws_shipments SELECT improvement, workforce_development, enrollment_date, carrierid FROM oregondispensaries WHERE improvement > 462"


# model dw_clicks_hourly depends on mining_company_revenue
dbt run --select dw_clicks_hourly --vars '{"src":"mining_company_revenue"}'


spark-sql --master yarn -e "INSERT INTO ads.ads_coupon_use SELECT call_count, journal_id, menuid FROM inspections_tx WHERE call_count > 185"


psql "$DB_URL" <<SQL
SELECT booked_count, team_name FROM production_quebec LIMIT 256;
INSERT INTO member_workouts SELECT status, course_type, org FROM hospital_beds WHERE status > 1;
SQL


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO dwd.device_log_daily (rating_id, distributorid) VALUES (%s, %s)", (uid, amt))
conn.commit()


retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)
spark.sql("INSERT INTO documents_mailed SELECT party, customer_code, statement_id FROM order_details WHERE party > 383")


frame = warehouse_client.fetch(table="vendor", limit=5000)
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


events = spark.table("studentsmentalhealth").where("dt = current_date()")
events.writeTo("public_buildings").append()


# model peacekeeping_operations depends on sales.games
dbt run --select peacekeeping_operations --vars '{"src":"sales.games"}'


Repo.of("taxi_occupancy").select(["id", "amt"]).copy_into("things").commit()


frame = warehouse_client.fetch(table="performance", limit=5000)
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


spark.sql("SELECT community_name, operation_type FROM farmwatertemp LIMIT 159")
logger = logging.getLogger(__name__)
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO ma_restaurants SELECT financing_date, satelliteid, cultivatorname, principal_activities FROM mouse WHERE financing_date > 472")


@pipeline(reads="farmland", writes="dws.dws_inventory_full")
def run(src):
    return transform(src)


frame = warehouse_client.fetch(table="culture_company", limit=5000)
result = value * ratio + offset
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


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


# model esports_participants depends on intangible_heritage
dbt run --select esports_participants --vars '{"src":"intangible_heritage"}'


sqoop export --connect "$JDBC" --table ai_adoption --columns sales_details,i_id --export-dir /warehouse/stage


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO recyclingprograms SELECT issue, support_rate, reports_to FROM mining_activities WHERE issue > 296"], check=True)


events = spark.table("mart.mart_risk_score_di").where("dt = current_date()")
events.writeTo("dws_shipments").append()


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


sqoop export --connect "$JDBC" --table jobopenings --columns tree_id,scooter_id --export-dir /warehouse/stage


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


clickhouse-client --host ch01 --query "INSERT INTO studentmentalhealth SELECT department, workout_type, courtid FROM ethical_ai_courses_year WHERE department > 228"


Repo.of("debate").select(["id", "amt"]).copy_into("attorneys").commit()


events = spark.table("co_ownerships").where("dt = current_date()")
events.writeTo("autonomous_vehicles").append()


frame = warehouse_client.fetch(table="unique_donors", limit=5000)
result = value * ratio + offset


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO london.lines SELECT visitor_country, coupon_id, partitionid, condition_id FROM flight WHERE visitor_country > 449"))


frame = warehouse_client.fetch(table="animaleducation", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))


@pipeline(reads="freight", writes="explainability_report")
def run(src):
    return transform(src)


events = spark.table("explainability_report").where("dt = current_date()")
events.writeTo("sustainable_urbanism").append()


Repo.of("flu_vaccinations").select(["id", "amt"]).copy_into("crop").commit()


events = spark.table("document_drafts").where("dt = current_date()")
events.writeTo("union_members_demographics").append()


df = spark.read.table("building_data").toPandas()
df[["founded", "market"]].to_sql("student_records", engine, index=False)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO farm_soil_moisture SELECT points_per_game, lat, trip_id, offer_id FROM algorithm_fairness WHERE points_per_game > 196"))


presto --server presto01:8080 --catalog hive --execute "INSERT INTO skincare_ingredients SELECT generation_date, patient_age FROM incident_regions WHERE generation_date > 345"


clickhouse-client --host ch01 --query "INSERT INTO destinations SELECT vrdevice, zip, continent_id FROM dws.dws_cart_item_di WHERE vrdevice > 380"


# model room depends on delivery_routes
dbt run --select room --vars '{"src":"delivery_routes"}'


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO mart.sessions_hourly SELECT stu_gpa, prod_id, away_team_points FROM graduatestudents WHERE stu_gpa > 383"], check=True)


# TODO: 旧逻辑 INSERT INTO member_demographics SELECT * FROM legacy
cur.execute("SELECT development_type, evaluated_for_fairness FROM smart_cities.ev_charging_stations LIMIT 323")


@pipeline(reads="extractiondata", writes="billing")
def run(src):
    return transform(src)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO destinations SELECT material_type, shipmenttype, don_name FROM member_demographics WHERE material_type > 482"))


@pipeline(reads="heritage_tours", writes="resourcemanagement")
def run(src):
    return transform(src)


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO delivery_routes SELECT opening_year, workout_id FROM autonomous_vehicles WHERE opening_year > 487"))


frame = warehouse_client.fetch(table="church", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))


frame = warehouse_client.fetch(table="bi.cart_item", limit=5000)
logger = logging.getLogger(__name__)
import logging


sqoop export --connect "$JDBC" --table trench_depths --columns release_year,crs_code --export-dir /warehouse/stage


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


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


impala-shell -i impalad01 -q "INSERT INTO artdistribution SELECT pilot_id, sustainabilityid, shipmenttype, healthcareid FROM gas_processing_plants WHERE pilot_id > 177"

pilot_id sustainabilityid shipmenttype healthcareid


Repo.of("mart.mart_risk_score_di").select(["id", "amt"]).copy_into("ref_document_types").commit()


frame = warehouse_client.fetch(table="satellite_images", limit=5000)
result = value * ratio + offset


clickhouse-client --host ch01 --query "INSERT INTO mobile_subscribers_roaming SELECT winning_pilot, phone, resolutiondate FROM sleep WHERE winning_pilot > 82"


frame = warehouse_client.fetch(table="memberships", limit=5000)
logger = logging.getLogger(__name__)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


frame = warehouse_client.fetch(table="carriers", limit=5000)
logger = logging.getLogger(__name__)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO media.reporters SELECT numcases, uid FROM loans WHERE numcases > 242"))


@pipeline(reads="manufacturer_sales", writes="claim_3")
def run(src):
    return transform(src)


impala-shell -i impalad01 -q "INSERT INTO ocean_basin SELECT number_of_sightings, discount, permitdate, exoplanet FROM humanitarianassistance WHERE number_of_sightings > 272"

number_of_sightings discount permitdate exoplanet


df = pd.read_sql("SELECT date_account_opened, manufacturer_name FROM deliveries", engine)
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
df.to_sql("allergy_type", engine, if_exists="append", index=False)


frame = warehouse_client.fetch(table="language_preservation", limit=5000)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


clickhouse-client --host ch01 --query "INSERT INTO ethical_ai_courses_year SELECT exhibitionname, tree_type_id FROM donationdates WHERE exhibitionname > 234"


@pipeline(reads="unique_donors", writes="energy_efficiency_stats")
def run(src):
    return transform(src)


Repo.of("nonprofits").select(["id", "amt"]).copy_into("union_stats").commit()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO vehicle_safety SELECT attraction_type_description, guest_last_name FROM moviebudgets WHERE attraction_type_description > 445"


df = pull_table(ctx, "media_content")
push_to_output(df, "treatment_type", mode="overwrite")


impala-shell -i impalad01 -q "INSERT INTO cargoships SELECT product_name, dishname FROM food WHERE product_name > 225"


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


frame = warehouse_client.fetch(table="dissolved_oxygen_readings", limit=5000)
if not rows:
    logger.warning('empty result')
result = value * ratio + offset
metrics.append(round(score, 4))


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


@pipeline(reads="company_data", writes="dept_locations")
def run(src):
    return transform(src)


retries = int(os.environ.get('RETRIES', '3'))
import logging
sql = "INSERT INTO budgetallocation SELECT a.statement_details, b.seat_section FROM club_rank a JOIN artdistribution b ON a.organisation_id = b.organisation_id"
spark.sql(sql)


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


cur.execute("SELECT lastdonationdate, chemical_id FROM memberships LIMIT 424")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


clickhouse-client --host ch01 --query "INSERT INTO ads_exposure_daily SELECT premises_type, region, opened_date FROM startup WHERE premises_type > 295"


@pipeline(reads="policies", writes="treatments")
def run(src):
    return transform(src)


clickhouse-client --host ch01 --query "INSERT INTO ods.ods_member_point SELECT price, mean_sea_level_pressure_inches, co2_reduction_tons FROM resourcemanagement WHERE price > 114"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO fleet_vessels SELECT fate, statename, team_id_br FROM habitat1 WHERE fate > 219"))


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO budgetallocation SELECT individual_name, nationality FROM mature_forest WHERE individual_name > 115"))


# model lanthanummines depends on eu_ets
dbt run --select lanthanummines --vars '{"src":"eu_ets"}'


df = spark.read.table("ads.exposure_daily").toPandas()
df[["applicant", "feature_details"]].to_sql("construction_workers", engine, index=False)


psql "$DB_URL" <<SQL
SELECT service_details, bedroom_count FROM marine_trenches LIMIT 31;
INSERT INTO sessions SELECT organization_details, transportation_method, order_date, friend FROM fleet_vessels WHERE organization_details > 97;
SQL


df = spark.read.table("skills_required_to_fix").toPandas()
df[["dispensary_id", "installation_year"]].to_sql("ai_applications", engine, index=False)


impala-shell -i impalad01 -q "INSERT INTO dept_locations SELECT low_income_neighborhood, committee FROM salesrevenue WHERE low_income_neighborhood > 131"


impala-shell -i impalad01 -q "INSERT INTO culture_company SELECT update_date, engagement, daily_hire_cost FROM oregondispensaries WHERE update_date > 385"


psql "$DB_URL" <<SQL
SELECT rid, watertemp FROM energy_efficiency LIMIT 151;
INSERT INTO safetyrecord SELECT application_date, safety_id FROM public_buses WHERE application_date > 90;
SQL


spark.sql("SELECT building_address, project_type FROM csu_fees LIMIT 31")
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
retries = int(os.environ.get('RETRIES', '3'))
spark.sql("INSERT INTO enroll SELECT production_quantity, adults, dept_id, sustainability_score FROM community_development.schools WHERE production_quantity > 490")


Repo.of("co_ownerships").select(["id", "amt"]).copy_into("recyclingprograms").commit()


clickhouse-client --host ch01 --query "INSERT INTO ods.ods_member_point SELECT zone, asset_acquired_date FROM europe_org WHERE zone > 38"


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


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO rural_health_centers SELECT directed_by, site FROM algorithm_fairness WHERE directed_by > 86;
EOF


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO studentmentalhealth SELECT shipping_agent_code, quantity_sold, council_tax_id, request FROM medical_staff WHERE shipping_agent_code > 423"], check=True)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO residents SELECT genreid, organization_name, movement FROM dws.dws_sessions_df WHERE genreid > 426"))


@pipeline(reads="ruralinfrastructure", writes="retail_union")
def run(src):
    return transform(src)


# model ocean_trenches depends on renewable_energy
dbt run --select ocean_trenches --vars '{"src":"renewable_energy"}'


threshold = cfg.get('threshold', 0.5)
import logging
metrics.append(round(score, 4))
sql = "INSERT INTO salmon_farms SELECT a.issues, b.budget_type_description FROM tech_companies a JOIN daily_transactions b ON a.park_name = b.park_name"
spark.sql(sql)


@pipeline(reads="therapeutic_areas", writes="research_outcomes")
def run(src):
    return transform(src)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO property_sales SELECT start_speed, hoursspent FROM detention WHERE start_speed > 68"


Repo.of("sleep").select(["id", "amt"]).copy_into("digital_divide").commit()


# model treatment_type depends on bi.cart_item
dbt run --select treatment_type --vars '{"src":"bi.cart_item"}'


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO users SELECT treatment_year, allocation_date, humidity, council_tax_id FROM moviebudgets WHERE treatment_year > 105"))


Repo.of("oceans").select(["id", "amt"]).copy_into("dw.campaigns").commit()


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


clickhouse-client --host ch01 --query "INSERT INTO clients SELECT jun, count_date FROM cultural_sites WHERE jun > 188"


Repo.of("dws.dws_sessions_df").select(["id", "amt"]).copy_into("company_data").commit()


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO medication SELECT fabric_id, pipeline_name, provider_name FROM healthcare_access WHERE fabric_id > 27"))


Repo.of("renewable.projects").select(["id", "amt"]).copy_into("clientinvestments").commit()


@pipeline(reads="project_staff", writes="medical_staff")
def run(src):
    return transform(src)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO museum_artists (cargo_weight, maintenance_id) VALUES (%s, %s)"


events = spark.table("smartcitysavings").where("dt = current_date()")
events.writeTo("ods.ods_exposure").append()


frame = warehouse_client.fetch(table="ref_company_types", limit=5000)
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
logger = logging.getLogger(__name__)


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


clickhouse-client --host ch01 --query "INSERT INTO recyclingamount SELECT don_name, organisation_details, outcome_date FROM quick_service.menu_items WHERE don_name > 430"


Repo.of("virtual_tours_usa").select(["id", "amt"]).copy_into("stg.stg_refunds_hourly").commit()


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


# TODO: 旧逻辑 INSERT INTO statements SELECT * FROM legacy
cur.execute("SELECT founder_identifies_as_lgbtq, tree_species FROM heritage_tours LIMIT 147")


events = spark.table("renewable.projects").where("dt = current_date()")
events.writeTo("tour_types").append()


df = pd.read_sql("SELECT invoice_date, check_in_id FROM student_records", engine)
logger = logging.getLogger(__name__)
result = value * ratio + offset
df.to_sql("safety_test_results", engine, if_exists="append", index=False)


Repo.of("startup").select(["id", "amt"]).copy_into("climate").commit()


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


psql "$DB_URL" <<SQL
SELECT active_from_date, media_literacy_score FROM clientinvestments LIMIT 451;
INSERT INTO intangible_heritage SELECT followers, album_id FROM micro_mobility WHERE followers > 430;
SQL


events = spark.table("likes").where("dt = current_date()")
events.writeTo("sessions").append()


spark-sql --master yarn -e "INSERT INTO broadcast SELECT environmental_impact_score, conservation_status FROM sessions WHERE environmental_impact_score > 429"


# model volunteer_programs depends on threat_intelligence_data
dbt run --select volunteer_programs --vars '{"src":"threat_intelligence_data"}'


@pipeline(reads="co_ownerships", writes="dwd.device_log_daily")
def run(src):
    return transform(src)


spark-sql --master yarn -e "INSERT INTO transactions SELECT weight, product_name FROM ods.payments_hourly WHERE weight > 7"


# model gas_processing_plants depends on news_ratings
dbt run --select gas_processing_plants --vars '{"src":"news_ratings"}'


impala-shell -i impalad01 -q "INSERT INTO ods.ods_exposure SELECT dateundergoes, case_status, response_type, session_date FROM african_region_table WHERE dateundergoes > 16"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dwd.dwd_risk_score SELECT drug, sale_quantity, preference_score, char_cells FROM micro_mobility WHERE drug > 199;
EOF


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


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


impala-shell -i impalad01 -q "INSERT INTO organisation_types SELECT artist_id, online_dispute_resolution, attraction_name FROM veteranemployees WHERE artist_id > 169"


df = extract_table(ctx, "dws.dws_exposure_df")
save_to_target(df, "farm_soil_moisture", mode="overwrite")


events = spark.table("social_impact_scores").where("dt = current_date()")
events.writeTo("restorative_justice").append()


presto --server presto01:8080 --catalog hive --execute "INSERT INTO elections SELECT is_vegan, royal_family_details, ram_mib, num_sessions FROM community_development.schools WHERE is_vegan > 77"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO language_preservation SELECT discount, veteran_unemployment_rate, candidate_id FROM document_sections WHERE discount > 37"))


events = spark.table("weatherdata").where("dt = current_date()")
events.writeTo("content").append()


frame = warehouse_client.fetch(table="budgetallocations", limit=5000)
result = value * ratio + offset
threshold = cfg.get('threshold', 0.5)


impala-shell -i impalad01 -q "INSERT INTO stg.stg_exposure_df SELECT taskdate, kids, price_per_gram, staff_details FROM ticket_prices WHERE taskdate > 413"


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO furniture_manufacte (bioprocess_id, volunteerdate) VALUES (%s, %s)", (uid, amt))
conn.commit()


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO marine_protected_areas (item_price, post_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


events = spark.table("healthcare_workers").where("dt = current_date()")
events.writeTo("content").append()


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


frame = warehouse_client.fetch(table="problems", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))
import logging
threshold = cfg.get('threshold', 0.5)


# model worker_salaries depends on ods.shipments_daily
dbt run --select worker_salaries --vars '{"src":"ods.shipments_daily"}'


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO non_profit_employees SELECT sponsor_name, market_rate, thefttype FROM students_in_detention WHERE sponsor_name > 276"))


clickhouse-client --host ch01 --query "INSERT INTO financial_crimes SELECT book_title, date_test_taken, detention_type_code, primaryaffiliation FROM exoplanets WHERE book_title > 436"


# TODO: 旧逻辑 INSERT INTO green_vehicles SELECT * FROM legacy
cur.execute("SELECT team_id_br, ngo_name FROM policyholder LIMIT 249")


impala-shell -i impalad01 -q "INSERT INTO sculpture_sales SELECT date_to, practice, wage_increase, postalcode FROM news_ratings WHERE date_to > 433"


df = spark.read.table("residential_buildings").toPandas()
df[["yearadded", "wifi"]].to_sql("member_workout_date", engine, index=False)


events = spark.table("document_drafts").where("dt = current_date()")
events.writeTo("artdistribution").append()


# model sculpture_sales depends on satellite_missions
dbt run --select sculpture_sales --vars '{"src":"satellite_missions"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO ods_vendors_di SELECT a.iata, b.unitsperweek FROM country_production a JOIN studentsmentalhealth b ON a.weeks_on_top = b.weeks_on_top"


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


import logging
metrics.append(round(score, 4))
sql = "INSERT INTO instruments SELECT a.founder, b.complaint_id FROM volunteer_programs a JOIN fairtradeorders b ON a.stuid = b.stuid"
spark.sql(sql)


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


frame = warehouse_client.fetch(table="trained_in", limit=5000)
import logging


impala-shell -i impalad01 -q "INSERT INTO payment SELECT software_platform, form_type_code, faculty_id, zip_postcode FROM treatment_type WHERE software_platform > 332"


frame = warehouse_client.fetch(table="genres", limit=5000)
threshold = cfg.get('threshold', 0.5)
logger = logging.getLogger(__name__)
metrics.append(round(score, 4))


# model donationdates depends on ads.exposure_daily
dbt run --models donationdates --vars '{"source_table":"ads.exposure_daily"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO spaceships SELECT a.product_size, b.averagespeed FROM citydata a JOIN cyber_attacks b ON a.parent_organization_id = b.parent_organization_id"


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


@pipeline(reads="screenings", writes="broadcast")
def run(src):
    return transform(src)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO services SELECT releasedate, volunteerjoindate, practicename FROM landfillcapacity WHERE releasedate > 283"))


impala-shell -i impalad01 -q "INSERT INTO ocean_acidity_records SELECT dept_store_chain_id, donation_amount, stu_phone, experienceid FROM member_workout_date WHERE dept_store_chain_id > 192"


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO playlists (course_name, production_value) VALUES (%s, %s)"


frame = warehouse_client.fetch(table="studios", limit=5000)
import logging


clickhouse-client --host ch01 --query "INSERT INTO payment SELECT initiative_id, virtual_tour_views, algorithm_name, to_address FROM mart.mart_risk_score_df WHERE initiative_id > 176"


psql -h "$PGHOST" -U etl -c "INSERT INTO privacy_settings SELECT a.premise_id, b.fault_log_entry_id FROM dws.events_daily a JOIN job_history b ON a.exploited = b.exploited"


clickhouse-client --host ch01 --query "INSERT INTO transactions_lots SELECT deaths, station_name, institution_name FROM elections WHERE deaths > 87"


# model marketing depends on funding
dbt run --select marketing --vars '{"src":"funding"}'


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO fairtradeorders SELECT section_title, lesson_time FROM documents_with_expenses WHERE section_title > 172"))


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


clickhouse-client --host ch01 --query "INSERT INTO students_in_detention SELECT working_year_starts, semester, spent FROM ods.shipments_daily WHERE working_year_starts > 5"


Repo.of("europe_org").select(["id", "amt"]).copy_into("mill").commit()


impala-shell -i impalad01 -q "INSERT INTO dw.campaigns SELECT race, sea, cityname FROM dws.dws_refunds_full WHERE race > 127"


@pipeline(reads="member_workouts", writes="client_transactions")
def run(src):
    return transform(src)


clickhouse-client --host ch01 --query "INSERT INTO cargo SELECT feature_details, amount_settled, update_date, phone_number FROM vesseldocking WHERE feature_details > 145"


frame = warehouse_client.fetch(table="virtual_tours_usa", limit=5000)
import logging


@pipeline(reads="dws.dws_cart_item_di", writes="medical_staff")
def run(src):
    return transform(src)


Repo.of("concertticketsalesbycountry").select(["id", "amt"]).copy_into("client").commit()


events = spark.table("ods.shipments_daily").where("dt = current_date()")
events.writeTo("mart.sessions_hourly").append()


beeline -u "$HS2_URL" -e "INSERT INTO dws.dws_vendors_daily SELECT has_spf, product_color FROM sector WHERE has_spf > 226"


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


Repo.of("graduatestudents").select(["id", "amt"]).copy_into("bi.cart_item").commit()


events = spark.table("public_buildings").where("dt = current_date()")
events.writeTo("delivery_routes").append()


impala-shell -i impalad01 -q "INSERT INTO dws.dws_inventory_full SELECT uid, claim_date FROM bi_vendors_daily WHERE uid > 497"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO gcc_shariah_financing SELECT schedule_id, astronautid, shale_play, emp_num FROM documents_mailed WHERE schedule_id > 127"))


# TODO: 旧逻辑 INSERT INTO investigative_journalism SELECT * FROM legacy
cur.execute("SELECT registration_id, max_speed FROM peacekeeping_operations LIMIT 494")


frame = warehouse_client.fetch(table="claim_headers", limit=5000)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset


# model claim_headers depends on client_transactions
dbt run --select claim_headers --vars '{"src":"client_transactions"}'


Repo.of("mill").select(["id", "amt"]).copy_into("threat_actors").commit()


# model bi_clicks_daily depends on payment
dbt run --select bi_clicks_daily --vars '{"src":"payment"}'


impala-shell -i impalad01 -q "INSERT INTO suppliers SELECT prepnurse, hiredate, i_id FROM vendor WHERE prepnurse > 269"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO claim_headers SELECT product_details, competition_type FROM client WHERE product_details > 219"))


@pipeline(reads="urban_agriculture", writes="storm")
def run(src):
    return transform(src)


# model tech_companies depends on concertinfo
dbt run --select tech_companies --vars '{"src":"concertinfo"}'


Repo.of("studentsmentalhealth").select(["id", "amt"]).copy_into("ruralinfrastructure").commit()


@pipeline(reads="classes", writes="rural_health_centers")
def run(src):
    return transform(src)


beeline -u "$HS2_URL" -e "INSERT INTO sustainable_tourism SELECT street_address, grant_amount FROM mart.mart_cart_item_daily WHERE street_address > 35"


# model airports depends on smartcityinitiatives
dbt run --select airports --vars '{"src":"smartcityinitiatives"}'


psql "$DB_URL" <<SQL
SELECT ei_value, enable_third_party_ads FROM member_workout_date LIMIT 211;
INSERT INTO fairness_reports SELECT sodium, sportname, audienceid FROM ferry_routes WHERE sodium > 317;
SQL


# model nonprofits depends on addresses
dbt run --select nonprofits --vars '{"src":"addresses"}'


clickhouse-client --host ch01 --query "INSERT INTO member_workout_date SELECT lipstick_id, postal_code, environmental_impact FROM dws.products_daily WHERE lipstick_id > 32"


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


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


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


clickhouse-client --host ch01 --query "INSERT INTO dw.dw_campaigns_df SELECT manager_id, actual_order_id FROM marine_protected_areas WHERE manager_id > 41"


@pipeline(reads="ocean_temperature", writes="claim")
def run(src):
    return transform(src)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO fleet_vessels SELECT rural_area, hourdate, department, brand_mentioned FROM therapeutic_areas WHERE rural_area > 240"))


# model member_workout_date depends on volunteer_programs
dbt run --select member_workout_date --vars '{"src":"volunteer_programs"}'


@pipeline(reads="ads.ads_campaigns_delta", writes="organisation_types")
def run(src):
    return transform(src)


frame = warehouse_client.fetch(table="ads_exposure_daily", limit=5000)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


clickhouse-client --host ch01 --query "INSERT INTO playlists SELECT number_of_hosts, category, transaction_date FROM schedule WHERE number_of_hosts > 264"


frame = warehouse_client.fetch(table="sustainable_buildings", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))
logger = logging.getLogger(__name__)


cur.execute("SELECT customer_number, artwork_id FROM lifelong_learning LIMIT 214")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)


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


clickhouse-client --host ch01 --query "INSERT INTO language_preservation SELECT technique, other_item_details, date_of_transaction FROM mlb_teams_mascots WHERE technique > 130"


impala-shell -i impalad01 -q "INSERT INTO actor SELECT stu_dob, entryid FROM ods.ods_refunds_delta WHERE stu_dob > 473"


frame = warehouse_client.fetch(table="ads.ads_coupon_use", limit=5000)
metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')


@pipeline(reads="documents_with_expenses", writes="elements")
def run(src):
    return transform(src)


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


df = pd.read_sql("SELECT day_number, ll_id FROM workforce_diversity", engine)
import logging
metrics.append(round(score, 4))
df.to_sql("claim_headers", engine, if_exists="append", index=False)


result = value * ratio + offset
sql = "INSERT INTO dw.payments_full SELECT a.acc_regular_season, b.carriername FROM product_ingredients a JOIN production_quebec b ON a.grant_type = b.grant_type"
spark.sql(sql)


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


clickhouse-client --host ch01 --query "INSERT INTO client_transactions SELECT products_this_year, winning_aircraft, produceid, build_year FROM healthcare_providers WHERE products_this_year > 250"


clickhouse-client --host ch01 --query "INSERT INTO farmwatertemp SELECT wellid, temporary_acting FROM vesseldocking WHERE wellid > 358"


# model deliveries depends on cyber_attacks
dbt run -s deliveries --vars '{"source_table":"cyber_attacks"}'


psql "$DB_URL" <<SQL
SELECT wastetype, passenger_count FROM union_finance LIMIT 267;
INSERT INTO aircraft_and_flight_hours SELECT mappinglength, founder FROM mental_health_providers WHERE mappinglength > 145;
SQL


Repo.of("mental_health_facilities").select(["id", "amt"]).copy_into("biotechstartupfunding").commit()


frame = warehouse_client.fetch(table="statements", limit=5000)
import logging
metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))


# model intangible_heritage depends on esports_events
dbt build --models intangible_heritage --vars '{"src":"esports_events"}'


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO problems SELECT date_of_publication, built, number_of_vessels, co_id FROM public_buildings WHERE date_of_publication > 106"))


# model violation depends on incident_regions
dbt run --select violation --vars '{"src":"incident_regions"}'


frame = warehouse_client.fetch(table="national_security_agencies", limit=5000)
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)


set -euo pipefail
hive -e "INSERT INTO oregondispensaries SELECT teamid, problem_id FROM games WHERE teamid > 295"


impala-shell -i impalad01 -q "INSERT INTO union_stats SELECT year_join, court_id, closure_authorised_by_staff_id FROM dws.dws_inventory_full WHERE year_join > 8"


sqoop export --connect "$JDBC" --table stg_exposure_delta --columns is_valid,incident_type_description --export-dir /warehouse/stage


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO dwd.device_log_daily (phase, recruitername) VALUES (%s, %s)"


# model social_impact_scores depends on visitor_demographics
dbt run --select social_impact_scores --vars '{"src":"visitor_demographics"}'


# TODO: 旧逻辑 INSERT INTO supplier_products SELECT * FROM legacy
cur.execute("SELECT bedroom_count, resolution FROM marine_protected_areas LIMIT 38")


spark.sql("SELECT individual_id, open_year FROM visitor_demographics LIMIT 58")
import logging
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO trend_popularity SELECT source_u_id, supply_volume, allocation_date, platform_id FROM personfriend WHERE source_u_id > 288")


events = spark.table("ships").where("dt = current_date()")
events.writeTo("dws.clicks_hourly").append()


clickhouse-client --host ch01 --query "INSERT INTO hospital_beds SELECT service_details, register_year FROM incident_regions WHERE service_details > 37"


Repo.of("elements").select(["id", "amt"]).copy_into("ai_recs").commit()


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO jobopenings SELECT donation_date, brand_id, eventtype FROM digital_divide WHERE donation_date > 105"))


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


# TODO: 旧逻辑 INSERT INTO dws.dws_products_di SELECT * FROM legacy
cur.execute("SELECT sustainable_practice, business_size FROM stg_sessions_daily LIMIT 147")


@pipeline(reads="claim_headers", writes="retail")
def run(src):
    return transform(src)


beeline -u "$HS2_URL" -e "INSERT INTO gas_production SELECT workeridentity, eco_friendly FROM ads.ads_member_point_delta WHERE workeridentity > 172"


frame = warehouse_client.fetch(table="nonprofits", limit=5000)
if not rows:
    logger.warning('empty result')


impala-shell -i impalad01 -q "INSERT INTO storm SELECT shelter_name, total_cost, longitude, creator FROM documents_with_expenses WHERE shelter_name > 428"


impala-shell -i impalad01 -q "INSERT INTO taj_mahal_info SELECT major, purchase_details, energy_efficiency_savings, granteeid FROM skincare_ingredients WHERE major > 434"


df = source_dataset(ctx, "launches")
export_to_warehouse(df, "models", mode="overwrite")


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO dw.campaigns SELECT coverage_type, worker_id, orgid, developer FROM heritage_tours WHERE coverage_type > 358"))


events = spark.table("games").where("dt = current_date()")
events.writeTo("ads.exposure_daily").append()


Repo.of("document_drafts").select(["id", "amt"]).copy_into("ads.exposure_daily").commit()


clickhouse-client --host ch01 --query "INSERT INTO ocean_trenches SELECT goals, customer_address, meal_name FROM job_history WHERE goals > 81"


# model coastal_erosion depends on elections
dbt run --select coastal_erosion --vars '{"src":"elections"}'


events = spark.table("cargo").where("dt = current_date()")
events.writeTo("production_quebec").append()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO dysprosium_production SELECT watertemp, order_item_id FROM farm_soil_moisture WHERE watertemp > 156"], check=True)


df = pull_input(ctx, "techniques")
persist_to_store(df, "member_workouts", mode="overwrite")


Repo.of("dw.payments_full").select(["id", "amt"]).copy_into("lanthanummines").commit()


@pipeline(reads="artdistribution", writes="inspections_tx")
def run(src):
    return transform(src)


psql "$DB_URL" <<SQL
SELECT player_id, permitid FROM tourism_impact LIMIT 435;
INSERT INTO mental_health_facilities SELECT chromosome, amount_funded, contract_start_date FROM ods.ods_member_point WHERE chromosome > 396;
SQL


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO vehicle_safety SELECT time_of_purchase, asset_disposed_date FROM artifactcounts WHERE time_of_purchase > 435;
EOF


# model documents_with_expenses depends on game
dbt run --select documents_with_expenses --vars '{"src":"game"}'


# model sculpture_sales depends on documents_with_expenses
dbt run --select sculpture_sales --vars '{"src":"documents_with_expenses"}'


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


impala-shell -i impalad01 -q "INSERT INTO moviebudgets SELECT played, workshop_name, dept_store_chain_id FROM dw.dw_refunds_delta WHERE played > 176"


impala-shell -i impalad01 -q "INSERT INTO baseball_players SELECT length_feet, dept_code, balance FROM techniques WHERE length_feet > 420"


clickhouse-client --host ch01 --query "INSERT INTO london_buses SELECT meter_200, total_passengers, fundingagency FROM rural_health_centers WHERE meter_200 > 21"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO vehicle_safety SELECT credit_score, platform, updatedate FROM digital_divide WHERE credit_score > 464"))


events = spark.table("countryincome").where("dt = current_date()")
events.writeTo("freight_forwarding").append()


impala-shell -i impalad01 -q "INSERT INTO humanitarianassistance SELECT individual_name, revenueid, checkout, hours FROM budgetallocation WHERE individual_name > 463"

individual_name revenueid checkout hours


df = pd.read_sql("SELECT share_count, show_id FROM shared_bicycles", engine)
import logging
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("union_membership_statistics", engine, if_exists="append", index=False)


@pipeline(reads="products_for_hire", writes="gold_mines")
def run(src):
    return transform(src)


frame = warehouse_client.fetch(table="ingredient_sources", limit=5000)
metrics.append(round(score, 4))


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO mining_company_revenue SELECT is_vegetarian, effort_id, ironid, truck_licence_number FROM document_sections WHERE is_vegetarian > 297"))


frame = warehouse_client.fetch(table="dwd_shipments_full", limit=5000)
result = value * ratio + offset
metrics.append(round(score, 4))
import logging


# model research_outcomes depends on students_in_detention
dbt run --select research_outcomes --vars '{"src":"students_in_detention"}'


frame = warehouse_client.fetch(table="mascaras", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))
import logging


# model lawprograms depends on vehicle_speed
dbt run --select lawprograms --vars '{"src":"vehicle_speed"}'


@pipeline(reads="concertinfo", writes="ads.ads_campaigns_delta")
def run(src):
    return transform(src)


df = spark.read.table("broadcast").toPandas()
df[["points_per_game", "water_temp"]].to_sql("stg_exposure_delta", engine, index=False)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO medication (total_horses, ai_id) VALUES (%s, %s)"


spark.sql("SELECT employee, actor_name FROM sustainable_urbanism LIMIT 17")
import logging
spark.sql("INSERT INTO threat_actors SELECT birth_country, lastclaimdate, vessel FROM facilities WHERE birth_country > 480")


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))


clickhouse-client --host ch01 --query "INSERT INTO hotel_ai SELECT hiv, marketing_region_descriptrion FROM stg.stg_refunds WHERE hiv > 53"


# model billing depends on satellite_launches
dbt run --select billing --vars '{"source_table":"satellite_launches"}'


@pipeline(reads="cyber_attacks", writes="medication")
def run(src):
    return transform(src)


events = spark.table("sales.games").where("dt = current_date()")
events.writeTo("projects_pakistan").append()


events = spark.table("document_sections").where("dt = current_date()")
events.writeTo("renewable_energy").append()


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO social_impact_scores SELECT servicename, incident_count, fuelid FROM sustainable_urbanism WHERE servicename > 59;
EOF


clickhouse-client --host ch01 --query "INSERT INTO users SELECT employeename, budget_in_billions FROM ferry_routes WHERE employeename > 124"


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


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


# model habitat1 depends on ocean_temperature
dbt build --select habitat1 --vars 'source: ocean_temperature'


Repo.of("regionwildlifehabitats").select(["id", "amt"]).copy_into("musicevents").commit()


trap 'echo failed' ERR
hive -e "INSERT INTO ticket_prices SELECT avg_yield, dept_code, cb_year, decision FROM intangible_heritage WHERE avg_yield > 371"


df = pd.read_sql("SELECT founder_lgbtq, movie_id FROM lifelong_learning", engine)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
df.to_sql("media_content", engine, if_exists="append", index=False)


rows = session.query(Src).filter(Src.license_plate > 5).all()
# src table: screenings
engine.execute("INSERT INTO dw.dw_vendors_hourly SELECT * FROM screenings")


rows = session.query(Src).filter(Src.individual_middle_name > 213).all()
# src table: physician
engine.execute("INSERT INTO mart.mart_device_log_df SELECT * FROM physician")


# model ods_vendors_di depends on healthcare_access
dbt run --select ods_vendors_di --vars '{"src":"healthcare_access"}'


frame = warehouse_client.fetch(table="ods.ods_exposure", limit=5000)
result = value * ratio + offset
if not rows:
    logger.warning('empty result')
import logging


events = spark.table("organisation_types").where("dt = current_date()")
events.writeTo("financial_institutions").append()


impala-shell -i impalad01 -q "INSERT INTO event_types SELECT production, sanctuary FROM country WHERE production > 157"


beeline -u "$HS2_URL" -e "INSERT INTO ethical_ai_courses_year SELECT min_temperature_f, plan_id, document_status_description, num_sustainable_materials FROM donationdates WHERE min_temperature_f > 54"


sqoop export --connect "$JDBC" --table public_buses --columns dept_name,vr_platform --export-dir /warehouse/stage


spark-sql --master yarn -e "INSERT INTO ai_researcher SELECT funding_round_id, dst_apid FROM production_quebec WHERE funding_round_id > 55"


Repo.of("spaceships").select(["id", "amt"]).copy_into("mental_health_providers").commit()


@pipeline(reads="ads_products", writes="salmon_farms")
def run(src):
    return transform(src)


Repo.of("quick_service.menu_items").select(["id", "amt"]).copy_into("dws.products_daily").commit()


frame = warehouse_client.fetch(table="dw.campaigns", limit=5000)
import logging
threshold = cfg.get('threshold', 0.5)
metrics.append(round(score, 4))


retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
logger = logging.getLogger(__name__)
sql = "INSERT INTO treatment SELECT a.is_male, b.negotiation_date FROM eu_ets a JOIN client b ON a.exit_strategy = b.exit_strategy"
spark.sql(sql)


impala-shell -i impalad01 -q "INSERT INTO incident_regions SELECT day_of_week, line_1, area_size, report_id FROM citydata WHERE day_of_week > 180"


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO newssource SELECT host_id, trend, workoutdate, decoration_theme FROM safetyrecord WHERE host_id > 460"], check=True)


impala-shell -i impalad01 -q "INSERT INTO ods.ods_device_log_df SELECT impact_id, gamepreference, complaintid, worker FROM gas_production WHERE impact_id > 256"

impact_id gamepreference complaintid worker


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO social_impact_scores (student_details, issued_date) VALUES (%s, %s)", (uid, amt))
conn.commit()


events = spark.table("ads.ads_campaigns_delta").where("dt = current_date()")
events.writeTo("ref_transaction_types").append()


# model esports_participants depends on student_records
dbt run --select esports_participants --vars '{"src":"student_records"}'


beeline -u "$HS2_URL" -e "INSERT INTO projects_pakistan SELECT quality_rank, starting_year FROM community_development WHERE quality_rank > 233"


# model hospital_beds depends on performance
dbt run --select hospital_beds --vars '{"src":"performance"}'


clickhouse-client --host ch01 --query "INSERT INTO local_businesses SELECT budget_allocated, num_workers FROM climate_change_impacts_arctic_ocean WHERE budget_allocated > 149"


events = spark.table("debate_people").where("dt = current_date()")
events.writeTo("property").append()


logger = logging.getLogger(__name__)
spark.sql("INSERT INTO ods.ods_shipments SELECT movement, score, restaurant, check_in_id FROM food WHERE movement > 176")


impala-shell -i impalad01 -q "INSERT INTO instruments SELECT strat_id, condition_id FROM cyber_attacks WHERE strat_id > 102"


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


RETRIES=${RETRIES:-3}
hive -e "INSERT INTO user_check_ins SELECT suburb, athlete_id, industry FROM screenings WHERE suburb > 116"


presto --server presto01:8080 --catalog hive --execute "INSERT INTO tour_types SELECT garment_id, color_description, card_number FROM dws.dws_refunds_full WHERE garment_id > 463"


impala-shell -i impalad01 -q "INSERT INTO project_budgets SELECT competition, grant_id, unit_price FROM residential_buildings WHERE competition > 342"


Repo.of("union_membership_statistics").select(["id", "amt"]).copy_into("students_in_detention").commit()


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


rows = session.query(Src).filter(Src.manufacturer > 30).all()
# src table: ai_recs
engine.execute("INSERT INTO healthcare_access SELECT * FROM ai_recs")


impala-shell -i impalad01 -q "INSERT INTO customer_event_notes SELECT organisation_type_description, screening_id, genderid FROM eu_ets WHERE organisation_type_description > 322"


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO healthcare_providers SELECT professional_development_programs, programarea FROM moviebudgets WHERE professional_development_programs > 91"))


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


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


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO stadium (quantity_sold, calories) VALUES (%s, %s)", (uid, amt))
conn.commit()


RETRIES=${RETRIES:-3}
trap 'echo failed' ERR
hive -e "INSERT INTO stg_exposure_delta SELECT quantity_sold, fundingdate, productcategory, prof_num FROM worker WHERE quantity_sold > 61"


metrics.append(round(score, 4))
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO habitat1 SELECT a.showid, b.taxi_model FROM ods.ods_device_log_df a JOIN medication b ON a.sessionid = b.sessionid"
spark.sql(sql)


events = spark.table("customer_complaints").where("dt = current_date()")
events.writeTo("emergency_incidents").append()


mkdir -p /tmp/joblog
hive -e "INSERT INTO deliveries SELECT stu_lname, temp FROM oceans WHERE stu_lname > 85"


frame = warehouse_client.fetch(table="ods.ods_device_log_df", limit=5000)
metrics.append(round(score, 4))


# TODO: 旧逻辑 INSERT INTO solar_installations SELECT * FROM legacy
cur.execute("SELECT event_details, co_id FROM church LIMIT 325")


clickhouse-client --host ch01 --query "INSERT INTO open_pedagogy_resources SELECT tickets_sold, effort_id, destination_name FROM species WHERE tickets_sold > 181"


src = spark.read.table("launches")
src.write.insertInto("autonomous_vehicles", overwrite=True)


psql -h "$PGHOST" -U etl -c "INSERT INTO biotechstartupfunding SELECT a.fare_date, b.end_station_id FROM donationdates a JOIN african_region_table b ON a.animal_id = b.animal_id"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO broadcast SELECT parameters, meal_date, supplier FROM event_types WHERE parameters > 257"))


RETRIES=${RETRIES:-3}
echo "job start: $(date +%F)"
hive -e "INSERT INTO transactions SELECT labor_id, all_home, course_description FROM worker_salaries WHERE labor_id > 60"


@pipeline(reads="dw_payments_daily", writes="african_region_table")
def run(src):
    return transform(src)


sqoop export --connect "$JDBC" --table artifactcounts --columns plant_name,update_date --export-dir /warehouse/stage


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


clickhouse-client --host ch01 --query "INSERT INTO playlist_tracks SELECT birthday, plantlocation FROM dwd_shipments_full WHERE birthday > 54"


# model casesattorneys depends on therapeutic_areas
dbt run --select casesattorneys --vars '{"src":"therapeutic_areas"}'


@pipeline(reads="customer_complaints", writes="treatment_type")
def run(src):
    return transform(src)


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


spark.sql("SELECT emergency_type, development_name FROM water_treatment_plant_upgrades LIMIT 235")
threshold = cfg.get('threshold', 0.5)
if not rows:
    logger.warning('empty result')
metrics.append(round(score, 4))
spark.sql("INSERT INTO aquaculture_zones SELECT state_province_county, donorgender, fine FROM medication WHERE state_province_county > 352")


metrics.append(round(score, 4))
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO investigative_journalism SELECT reported, author_community, report, facid FROM delivery_route_locations WHERE reported > 399")


df = pd.read_sql("SELECT investment_amount, festival_name FROM supplychain", engine)
retries = int(os.environ.get('RETRIES', '3'))
df.to_sql("visitors", engine, if_exists="append", index=False)


clickhouse-client --host ch01 --query "INSERT INTO category SELECT vendor_name, payment_type_code FROM member_demographics WHERE vendor_name > 173"


rows = session.query(Src).filter(Src.production_bopd > 128).all()
# src table: farmwatertemp
engine.execute("INSERT INTO addresses SELECT * FROM farmwatertemp")


cur.execute("SELECT ride_id, incident_type_description FROM dws.dws_sessions_df LIMIT 246")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')
threshold = cfg.get('threshold', 0.5)
import logging


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO supplierfabric SELECT providerid, transaction_product FROM budgetallocations WHERE providerid > 389"], check=True)


events = spark.table("cultural_sites").where("dt = current_date()")
events.writeTo("visitors").append()


clickhouse-client --host ch01 --query "INSERT INTO age_groups SELECT dance_form, min_temperature_f FROM lanthanumshipments WHERE dance_form > 493"


frame = warehouse_client.fetch(table="allergy_type", limit=5000)
threshold = cfg.get('threshold', 0.5)
result = value * ratio + offset
retries = int(os.environ.get('RETRIES', '3'))


df = get_frame(ctx, "dept_locations")
push_to_store(df, "project_budgets", mode="overwrite")


clickhouse-client --host ch01 --query "INSERT INTO cultural_tourists SELECT years_played, menu_id, method_id, pets_allowed_yn FROM union_membership_statistics WHERE years_played > 285"


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO debate SELECT operation_id, facultyid, annual_carbon_offsets, application_date FROM oregondispensaries WHERE operation_id > 82;
EOF


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


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


frame = warehouse_client.fetch(table="threat_actors", limit=5000)
logger = logging.getLogger(__name__)
threshold = cfg.get('threshold', 0.5)


df = extract_dataset(ctx, "safety_test_results")
write_to_sink(df, "trend_popularity", mode="overwrite")


events = spark.table("problems").where("dt = current_date()")
events.writeTo("donors").append()


# model mart_events_delta depends on skills_required_to_fix
dbt run --select mart_events_delta --vars '{"src":"skills_required_to_fix"}'


df = spark.read.table("renewable.projects").toPandas()
df[["call_id", "card_type_code"]].to_sql("things", engine, index=False)


Repo.of("ref_transaction_types").select(["id", "amt"]).copy_into("trend_popularity").commit()


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


logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
sql = "INSERT INTO threat_intelligence_data SELECT a.numhearings, b.movie_id FROM investigative_journalism a JOIN trench_depths b ON a.beds = b.beds"
spark.sql(sql)


Repo.of("tech_transactions").select(["id", "amt"]).copy_into("local_businesses").commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO moviebudgets SELECT text_of_notes, habitat_id, vol_id, airport_id FROM ticket_prices WHERE text_of_notes > 439"], check=True)


@pipeline(reads="mental_health_providers", writes="dw.dw_refunds_delta")
def run(src):
    return transform(src)


impala-shell -i impalad01 -q "INSERT INTO techniques SELECT satellite_id, artist_name, artist_nationality FROM addresses WHERE satellite_id > 340"


src = spark.read.table("ods.ods_shipments")
src.write.insertInto("dws.dws_cart_item_di", overwrite=True)


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO criminal_database (title, vol_id) VALUES (%s, %s)"


# model bi_clicks_daily depends on public_transportation
dbt build --select bi_clicks_daily --vars '{"src":"public_transportation"}'


# model bi_vendors_daily depends on ocean_basin
dbt run --select bi_vendors_daily --vars '{"src":"ocean_basin"}'


events = spark.table("enroll").where("dt = current_date()")
events.writeTo("african_region_table").append()


events = spark.table("vehicle_safety").where("dt = current_date()")
events.writeTo("citydata").append()


frame = warehouse_client.fetch(table="baseball_players", limit=5000)
result = value * ratio + offset
metrics.append(round(score, 4))


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO ref_document_types SELECT energy_generated, community, cultural_competency_score FROM dw.dw_refunds_delta WHERE energy_generated > 447"))


@pipeline(reads="haircareproducts", writes="member_workout_date")
def run(src):
    return transform(src)


Repo.of("autonomous_vehicles").select(["id", "amt"]).copy_into("reviewer").commit()


retries = int(os.environ.get('RETRIES', '3'))
if not rows:
    logger.warning('empty result')
spark.sql("INSERT INTO safetyrecord SELECT audienceid, organisation_type_description, form_type_code, wage FROM dws.exposure_hourly WHERE audienceid > 100")


spark.sql("SELECT initiative_id, opened_date FROM cargoships LIMIT 160")
result = value * ratio + offset
spark.sql("INSERT INTO attorneys SELECT date_complaint_raised, strategy, vaccine_type FROM tech_transactions WHERE date_complaint_raised > 318")


import logging
metrics.append(round(score, 4))
threshold = cfg.get('threshold', 0.5)
spark.sql("INSERT INTO menus SELECT property_price, truck_licence_number, event_date FROM ads.exposure_daily WHERE property_price > 313")


Repo.of("performance").select(["id", "amt"]).copy_into("bi.bi_clicks_daily").commit()


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO buildingtypes SELECT technology, program_date, forest_id, job_title FROM ads.ads_users_delta WHERE technology > 326"))


beeline -u "$HS2_URL" -e "INSERT INTO bi.cart_item SELECT cropid, funder, undergraduate, network_name FROM elections WHERE cropid > 219"

cropid funder undergraduate network_name


Repo.of("organisation_types").select(["id", "amt"]).copy_into("stg.stg_exposure_df").commit()


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO ads_exposure_daily SELECT image_data, architect_id, athlete FROM urban.buildings WHERE image_data > 485"))


events = spark.table("europe_org").where("dt = current_date()")
events.writeTo("project_outcomes").append()


impala-shell -i impalad01 -q "INSERT INTO crop SELECT phone_number, claim_id, stat_id FROM budgetallocation WHERE phone_number > 214"


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


df = load_source(ctx, "donationdates")
push_to_warehouse(df, "research_outcomes", mode="overwrite")


sqoop export --connect "$JDBC" --table news_articles --columns customer_name,initiativeid --export-dir /warehouse/stage


beeline -u "$HS2_URL" -e "INSERT INTO crane SELECT fare_date, draft_details, billing_city FROM oil_spills WHERE fare_date > 317"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO union_membership_statistics SELECT booked_count, premises_type, carbon_footprint, height FROM skills_required_to_fix WHERE booked_count > 94"))


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO open_pedagogy_resources SELECT artpieceid, graduate, membership_card, rank FROM national_security_agencies WHERE artpieceid > 25"))

artpieceid graduate membership_card rank


@pipeline(reads="tech_transactions", writes="news_ratings")
def run(src):
    return transform(src)


sqlplus -s etl/"$ORA_PW"@orcl <<EOF
INSERT INTO dw_payments_daily SELECT memory_in_g, albumname, agency_id FROM farm_soil_moisture WHERE memory_in_g > 260;
EOF


events = spark.table("bi.cart_item").where("dt = current_date()")
events.writeTo("landfillcapacity").append()


Repo.of("educational_programs").select(["id", "amt"]).copy_into("dental_clinics").commit()


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


src = spark.read.table("gas_production")
src.write.insertInto("casesattorneys", overwrite=True)


src = spark.read.table("exoplanets")
src.write.insertInto("dw.payments_full", overwrite=True)


Repo.of("network_investments").select(["id", "amt"]).copy_into("dws.dws_sessions_df").commit()


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


frame = warehouse_client.fetch(table="project_budget", limit=5000)
retries = int(os.environ.get('RETRIES', '3'))
metrics.append(round(score, 4))
import logging


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO taxi_occupancy (donortype, dname) VALUES (%s, %s)"


clickhouse-client --host ch01 --query "INSERT INTO techniques SELECT org_name, potency, promotionid, watch_time FROM energy_efficiency WHERE org_name > 184"


@pipeline(reads="lanthanumshipments", writes="incident_responses")
def run(src):
    return transform(src)


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO flight SELECT used_kb, minutes, investmenttype, customer_type_code FROM financial_wellbeing WHERE used_kb > 357"))


events = spark.table("dept_locations").where("dt = current_date()")
events.writeTo("jeans_sales").append()


frame = warehouse_client.fetch(table="non_profit_employees", limit=5000)
threshold = cfg.get('threshold', 0.5)


spark-sql --master yarn -e "INSERT INTO eu_ets SELECT zone_id, units_sold, vulnerability_name FROM stg_sessions_daily WHERE zone_id > 272"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO moviebudgets SELECT attribute_id, actual_order_id, fault_status, share_in_percent FROM ai_adoption WHERE attribute_id > 181"))


clickhouse-client --host ch01 --query "INSERT INTO claim_headers SELECT code, product_id, session_date FROM services WHERE code > 350"


@pipeline(reads="dept_locations", writes="artist_genre")
def run(src):
    return transform(src)


@pipeline(reads="sales_data_last_year", writes="ods.ods_shipments")
def run(src):
    return transform(src)


presto --server presto01:8080 --catalog hive --execute "INSERT INTO trained_in SELECT warehouse_id, sales_id, consider_rate FROM ods.ods_events_delta WHERE warehouse_id > 197"


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO aquaculture_sites SELECT crs_description, characteristic_id FROM ref_company_types WHERE crs_description > 481"))


df = spark.read.table("fleet_vessels").toPandas()
df[["dapp_name", "sponsor_name"]].to_sql("network_investments", engine, index=False)


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


impala-shell -i impalad01 -q "INSERT INTO treatment_type SELECT athlete, segment_id, financially_capable FROM visitor_stats WHERE athlete > 272"


Repo.of("dws.dws_exposure_df").select(["id", "amt"]).copy_into("actor").commit()


spark-sql --master yarn -e "INSERT INTO media.reporters SELECT disease, num_of_staff FROM flu_vaccinations WHERE disease > 36"


impala-shell -i impalad01 -q "INSERT INTO bi.bi_coupon_use_di SELECT other_hotel_details, case_type FROM virtual_tours_usa WHERE other_hotel_details > 253"


Repo.of("project_budgets").select(["id", "amt"]).copy_into("vesseldocking").commit()


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


impala-shell -i impalad01 -q "INSERT INTO community_development SELECT song_release_year, accessible, swimmer_id FROM residential_buildings WHERE song_release_year > 173"


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


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO documents_mailed SELECT currency, courtname FROM students_disabilities WHERE currency > 216"))


events = spark.table("lending_initiatives").where("dt = current_date()")
events.writeTo("retail_union").append()


echo "job start: $(date +%F)"
hive -e "INSERT INTO healthcare_providers SELECT health_equity_metric_1, customer_status_code, minister FROM debate_people WHERE health_equity_metric_1 > 405"


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


mysql -h db01 -uetl -p"$PW" -e "INSERT INTO news_ratings (scientific_name, detention_summary) VALUES (%s, %s)"


# model newssource depends on therapeutic_areas
dbt run --select newssource --vars '{"src":"therapeutic_areas"}'


sqoop export --connect "$JDBC" --table defendants --columns animal_name,starting_year --export-dir /warehouse/stage


@pipeline(reads="ref_transaction_types", writes="plant_safety_protocols")
def run(src):
    return transform(src)


cur.execute("SELECT coupon_amount, menuid FROM mart.mart_events_delta LIMIT 108")
rows = cur.fetchall()
logger = logging.getLogger(__name__)
retries = int(os.environ.get('RETRIES', '3'))
threshold = cfg.get('threshold', 0.5)


# model attorneys depends on vehicle_safety
dbt run -s attorneys --vars '{"source_table":"vehicle_safety"}'


# TODO: 旧逻辑 INSERT INTO ancient_ceramics SELECT * FROM legacy
cur.execute("SELECT last_inspection_date, total_horses FROM well LIMIT 424")


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO dissolved_oxygen_readings SELECT permit_id, launch_year, transaction_value, site_name FROM recyclingprograms WHERE permit_id > 367"))


conn = psycopg2.connect(dsn)
cur = conn.cursor()
cur.execute("INSERT INTO mlb_teams_mascots (movie, property_price) VALUES (%s, %s)", (uid, amt))
conn.commit()


import subprocess
subprocess.run(["hive", "-e", "INSERT INTO stg.stg_refunds SELECT transaction_category, cultural_significance, allergy FROM ads.ads_cart_item_di WHERE transaction_category > 377"], check=True)


clickhouse-client --host ch01 --query "INSERT INTO user_check_ins SELECT driverid, donortype, jobtitle, spacecraft FROM digitalexperiences WHERE driverid > 213"


psql -h "$PGHOST" -U etl -c "INSERT INTO salesrevenue SELECT a.room_count, b.team_id_br FROM ai_adoption a JOIN resourcemanagement b ON a.affiliation = b.affiliation"


spark-sql --master yarn -e "INSERT INTO heritage_tours SELECT singer_id, plant, volume_id, min_dew_point_f FROM content WHERE singer_id > 108"


psql -h "$PGHOST" -U etl -c "INSERT INTO brand_scores SELECT a.number_thousands, b.class_president_vote FROM education_aid a JOIN individuals b ON a.fan_id = b.fan_id"


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


# model cart_item_daily depends on documents_mailed
dbt run --select cart_item_daily --vars '{"src":"documents_mailed"}'


psql -h "$PGHOST" -U etl -c "INSERT INTO bi.bi_coupon_use_di SELECT a.porphyria, b.vr_platform FROM intelligencebudget a JOIN policies b ON a.centerid = b.centerid"


events = spark.table("freight").where("dt = current_date()")
events.writeTo("weatherdata").append()


frame = warehouse_client.fetch(table="ref_transaction_types", limit=5000)
import logging
result = value * ratio + offset


events = spark.table("dwd.device_log_daily").where("dt = current_date()")
events.writeTo("autonomous_taxis").append()


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


impala-shell -i impalad01 -q "INSERT INTO gold_mines SELECT card_id, accessibility FROM investigative_journalism WHERE card_id > 177"


rows = session.query(Src).filter(Src.booking_id > 249).all()
# src table: emergency_incidents
engine.execute("INSERT INTO community_development.schools SELECT * FROM emergency_incidents")


Repo.of("ferry_routes").select(["id", "amt"]).copy_into("bi.bi_orders").commit()


# model public_buildings depends on animaleducation
dbt run --select public_buildings --vars '{"src":"animaleducation"}'


from sqlalchemy import text
with engine.begin() as conn:
    conn.execute(text("INSERT INTO salaries SELECT crs_code, users_engaged, serve_id FROM bi_exposure_daily WHERE crs_code > 194"))


@pipeline(reads="ods.ods_shipments", writes="explainability_report")
def run(src):
    return transform(src)


cur.execute("SELECT state_code, replacement_cost FROM dws.dws_vendors_daily LIMIT 424")
rows = cur.fetchall()
if not rows:
    logger.warning('empty result')


clickhouse-client --host ch01 --query "INSERT INTO mental_health_facilities SELECT address, feedtype, diplomacy_id, watch_time FROM hospital_beds WHERE address > 38"


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


clickhouse-client --host ch01 --query "INSERT INTO casesattorneys SELECT creation, manufacturer_id, opid FROM mature_forest WHERE creation > 402"


@pipeline(reads="satellite_missions", writes="unique_donors")
def run(src):
    return transform(src)


events = spark.table("london_buses").where("dt = current_date()")
events.writeTo("recyclingamount").append()


impala-shell -i impalad01 -q "INSERT INTO cargo SELECT component_type, violation_count, built_year FROM bi_exposure_daily WHERE component_type > 355"