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SQLAlchemy Driver

IOMETE lakehouse endpoints are compatible with py-hive-iomete driver

Usage​

info

For a quick start, you can use the samples repository: https://github.com/iomete/py-hive-iomete-samples

DB-API​

Install the following dependency

pip install py-hive-iomete==1.1.0

DB-API sample​

from pyhive import hive

connection = hive.connect(
    host="<cluster_id>.iomete.cloud",
    workspace_id="<workspace_id>",
    lakehouse="<lakehouse_cluster_name>",
    database="default",
    username="<username>",
    password="<password>"
)

cursor = connection.cursor()
cursor.execute("SELECT * FROM my_awesome_data LIMIT 10")

print(cursor.fetchone())
print(cursor.fetchall())

DB-API (asynchronous) sample​

from pyhive import hive
from TCLIService.ttypes import TOperationState

connection = hive.connect(
    host="<cluster_id>.iomete.cloud",
    workspace_id="<workspace_id>",
    lakehouse="<lakehouse_cluster_name>",
    database="default",
    username="<username>",
    password="<password>"
)

cursor = connection.cursor()

cursor.execute("SELECT * FROM my_awesome_data LIMIT 10", async_=True)

status = cursor.poll().operationState

while status in (TOperationState.INITIALIZED_STATE, TOperationState.RUNNING_STATE):
    logs = cursor.fetch_logs()
    for message in logs:
        print(message)

    # If needed, an asynchronous query can be cancelled at any time with:
    # cursor.cancel()

    status = cursor.poll().operationState

print(cursor.fetchall())

SQLAlchemy​

Install SQLAlchemy extra package

pip install "py-hive-iomete[sqlalchemy]"
from sqlalchemy.engine import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.schema import *

engine = create_engine(
    'iomete://<username>:<personal_access_token>@<cluster_id>.iomete.cloud/<database>?workspace_id=<workspace_id>&lakehouse=<lakehouse_cluster_name>')

# Alternatively, "hive" driver could be used as well
# engine = create_engine(
#    'hive://<username>:<personal_access_token>@<cluster_id>.iomete.cloud/<database>?workspace_id=<workspace_id>&lakehouse=<lakehouse_cluster_name>')

session = sessionmaker(bind=engine)()
records = session.query(Table('my_awesome_data', MetaData(bind=engine), autoload=True)) \
    .limit(10) \
    .all()
print(records)

You can find the configuration parameters from the lakehouse "Connection Details" tab from the IOMETE console