6.17. federated_query-nyc_taxi-trino-iceberg¶

Documents the scenario's paired Jupyter (notebook.ipynb) and Zeppelin (notebook.zpln) implementations. Both notebooks implement the same Trino queries through different clients.

1. Section map¶

Subsection	Trino SQL (Zeppelin)	Python client (Jupyter)
2.1 Setup	✓	✓
2.2 Read	✓	✓
2.3 Transform	✓	✓
2.4 Write	✓	✓
2.5 Verify	✓	✓

2. Walkthrough¶

2.1 Setup¶

Trino SQL (Zeppelin):

-- %trino is pre-bound to the Atlas Trino coordinator (catalog: lakehouse)

Python client (Jupyter):

from trino.dbapi import connect

cur = connect(host='trino', port=8080, user='atlas', catalog='lakehouse').cursor()
def q(sql):
    cur.execute(sql)
    return cur.fetchall()

2.2 Read¶

Trino SQL (Zeppelin):

SELECT * FROM lakehouse.bronze.nyc_taxi_trips LIMIT 10

Python client (Jupyter):

q('SELECT * FROM lakehouse.bronze.nyc_taxi_trips LIMIT 10')

2.3 Transform¶

Trino SQL (Zeppelin):

SELECT trip_date, count(*) AS trips, avg(fare_amount) AS avg_fare
FROM lakehouse.bronze.nyc_taxi_trips
GROUP BY trip_date ORDER BY trip_date

Python client (Jupyter):

q('SELECT trip_date, count(*) AS trips, avg(fare_amount) AS avg_fare '
  'FROM lakehouse.bronze.nyc_taxi_trips GROUP BY trip_date ORDER BY trip_date')

2.4 Write¶

Trino SQL (Zeppelin):

CREATE TABLE IF NOT EXISTS lakehouse.gold.nyc_taxi_daily_trino AS
SELECT trip_date, count(*) AS trips, avg(fare_amount) AS avg_fare
FROM lakehouse.bronze.nyc_taxi_trips GROUP BY trip_date

Python client (Jupyter):

q('CREATE TABLE IF NOT EXISTS lakehouse.gold.nyc_taxi_daily_trino AS '
  'SELECT trip_date, count(*) AS trips, avg(fare_amount) AS avg_fare '
  'FROM lakehouse.bronze.nyc_taxi_trips GROUP BY trip_date')

2.5 Verify¶

Trino SQL (Zeppelin):

SELECT count(*) FROM lakehouse.gold.nyc_taxi_daily_trino

Python client (Jupyter):

q('SELECT count(*) FROM lakehouse.gold.nyc_taxi_daily_trino')

3. Trino query equivalence¶

Both notebooks share the same numbered sections and issue equivalent Trino SQL. The Zeppelin notebook uses %trino; Jupyter uses the Python DB-API client. These two scenarios are execution-gated but are not included in the 17 Scala/PySpark parity pairs.

4. How to run¶

Open the scenario's zeppelin/notebook.zpln on the Atlas Zeppelin UI or jupyter/notebook.ipynb on JupyterHub, then run all paragraphs/cells top to bottom.