Prompt Title: ds

Here are the solutions to each task.

Task 1: Create a SQL query to create the table with the specified schema:

sqlCopy code
CREATE TABLE project_id.dataset_name.table_name (
  rental_id INT64,
  duration INT64,
  end_date TIMESTAMP,
  end_station_id INT64,
  end_station_name STRING,
  start_date TIMESTAMP,
  start_station_id INT64,
  start_station_name STRING,
  end_station_logical_terminal INT64,
  start_station_logical_terminal INT64
);

Task 2: Use the Airflow BigQueryOperator to create the table:

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from airflow import DAG
from airflow.providers.google.cloud.operators.bigquery import BigQueryOperator
from datetime import datetime, timedelta

default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
}

dag = DAG(
    'bigquery_table_creation',
    default_args=default_args,
    description='Create BigQuery table',
    schedule_interval=timedelta(days=1),
    start_date=datetime(2023, 3, 14),
    catchup=False,
)

create_table = BigQueryOperator(
    task_id='create_table',
    sql='''CREATE TABLE project_id.dataset_name.table_name (
              rental_id INT64,
              duration INT64,
              end_date TIMESTAMP,
              end_station_id INT64,
              end_station_name STRING,
              start_date TIMESTAMP,
              start_station_id INT64,
              start_station_name STRING,
              end_station_logical_terminal INT64,
              start_station_logical_terminal INT64
            );''',
    use_legacy_sql=False,
    dag=dag,
)

create_table

Task 3: Count the daily number of trips in 2016-2017 and the cumulative number of trips:

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WITH daily_trips AS (
  SELECT
    DATE(start_date) as trip_date,
    COUNT(rental_id) as num_trips
  FROM
    bigquery-public-data.london_bicycles.cycle_hire
  WHERE
    EXTRACT(YEAR FROM start_date) BETWEEN 2016 AND 2017
  GROUP BY
    trip_date
),
cumulative_trips AS (
  SELECT
    trip_date,
    SUM(num_trips) OVER (ORDER BY trip_date) as cumulative_trips
  FROM
    daily_trips
)

SELECT
  trip_date,
  num_trips,
  cumulative_trips
FROM
  cumulative_trips
ORDER BY
  trip_date

Task 4: Count the number of trips by start station:

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SELECT
  start_station_name,
  COUNT(rental_id) as num_trips
FROM
  bigquery-public-data.london_bicycles.cycle_hire
GROUP BY
  start_station_name
ORDER BY
  num_trips DESC

Task 5: Identify a station with the longest average trip duration using the bigquery-public-data.new_york.tlc_yellow_trips_2015 table:

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SELECT
  start_station_name,
  AVG(duration) as avg_duration
FROM
  bigquery-public-data.london_bicycles.cycle_hire
GROUP BY
  start_station_name
ORDER BY
  avg_duration DESC
LIMIT 1

Please note that Task 5 mentions the bigquery-public-data.new_york.tlc_yellow_trips_2015 table, but it seems unrelated to the problem. I assumed you meant to use the bigquery-public-data.london_bicycles.cycle_hire table for this task.