ZettaPark Quick Start
This guide helps you complete installation, establish a session, query data, and write to a table — the full workflow — in under 10 minutes.
Prerequisites
Python 3.10 or higher
An existing Singdata Lakehouse account with the following connection details ready: instance name, workspace name, username, and password
Installation
pip install clickzetta_zettapark_python
💡 Tip : In Jupyter Notebook, use !pip install clickzetta_zettapark_python.
Establishing a Session
A session is the entry point for all operations. It connects to a specified Lakehouse instance and workspace.
from clickzetta.zettapark.session import Session
session = Session.builder.configs({
"username": "your_username",
"password": "your_password",
"service": "cn-shanghai-alicloud.api.singdata.com",
"instance": "your_instance",
"workspace": "your_workspace",
"schema": "public",
"vcluster": "default"
}).create()
Verify the connection:
session.sql("SHOW SCHEMAS").show(3)
+-----------------+
| schema_name|
+-----------------+
| bronze|
| cat_litter|
|clickzetta_doc_kb|
+-----------------+
Querying Data
Create a DataFrame from an existing table and apply filters:
from clickzetta.zettapark import functions as F
df = session.table("your_table")
df.filter(F.col("amount") > 100).select("id", "amount", "region").show(5)
You can also execute SQL directly:
df = session.sql("SELECT region, SUM(amount) AS total FROM your_table GROUP BY region")
df.show()
💡 Tip : show() triggers execution and prints the results; collect() returns a list of Row objects; to_pandas() returns a pandas DataFrame.
Writing to a Table
Write Python data to a Lakehouse table:
from clickzetta.zettapark.types import IntegerType, StringType, StructType, StructField
schema = StructType([
StructField("id", IntegerType()),
StructField("name", StringType()),
StructField("amount", IntegerType()),
])
df = session.create_dataframe(
[[1, "Alice", 200], [2, "Bob", 150], [3, "Carol", 300]],
schema=schema
)
df.write.save_as_table("my_first_table", mode="overwrite")
Verify the write result:
session.table("my_first_table").show()
+---+-----+------+
| id| name|amount|
+---+-----+------+
| 1|Alice| 200|
| 2| Bob| 150|
| 3|Carol| 300|
+---+-----+------+
Closing a Session
session.close()
Next Steps
