version: "1.0.0" name: aidp-snowflake description: Read Snowflake from an AIDP notebook through the AIDP aidataplatform Spark format handler. Use when the user mentions Snowflake, Snowflake warehouse, Basic authentication, KeyPair authentication, private.key.file, or private.key.content. Snowflake writes are not supported in AIDP 4.0. allowed-tools: Read, Write, Edit, Bash

aidp-snowflake — read Snowflake via AIDP aidataplatform

Use the built-in AIDP Snowflake connector (type=SNOWFLAKE). It supports Basic and KeyPair authentication, direct ingestion reads, external-catalog reads, and SQL pushdown. Do not generate write code for Snowflake in the 4.0 release.

When to use

• Read from a Snowflake warehouse in an AIDP notebook.
• Mentioned: "Snowflake", "warehouse", "private.key.file", or "KeyPair".

When NOT to use

• For a generic JDBC-only source that has no dedicated connector → `aidp-jdbc-custom`.
• For a Snowflake write request, explain that the 4.0 AIDP Snowflake connector is read-only.

Basic authentication read

import os
from oracle_ai_data_platform_connectors.aidataplatform import (
    AIDP_FORMAT, aidataplatform_options,
)
opts = aidataplatform_options(
    type="SNOWFLAKE",
    host=os.environ["SNOWFLAKE_HOST"],
    port=443,
    database_name=os.environ["SNOWFLAKE_DATABASE"],
    user=os.environ["SNOWFLAKE_USER"],
    password=os.environ["SNOWFLAKE_PASSWORD"],
    schema=os.environ["SNOWFLAKE_SCHEMA"],
    table=os.environ["SNOWFLAKE_TABLE"],
    extra={
        "authentication.method": "Basic",
        "warehouse": os.environ["SNOWFLAKE_WAREHOUSE"],
        "role": os.environ.get("SNOWFLAKE_ROLE", ""),
    },
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(5)

Key-pair authentication read

Set one of private.key.file or private.key.content. Use private.key.pass.phrase only for an encrypted key.

opts = aidataplatform_options(
    type="SNOWFLAKE",
    host=os.environ["SNOWFLAKE_HOST"],
    port=443,
    database_name=os.environ["SNOWFLAKE_DATABASE"],
    user=os.environ["SNOWFLAKE_USER"],
    schema=os.environ["SNOWFLAKE_SCHEMA"],
    table=os.environ["SNOWFLAKE_TABLE"],
    extra={
        "authentication.method": "KeyPair",
        "warehouse": os.environ["SNOWFLAKE_WAREHOUSE"],
        "role": os.environ.get("SNOWFLAKE_ROLE", ""),
        "private.key.file": os.environ["SNOWFLAKE_PRIVATE_KEY_FILE"],
        "private.key.pass.phrase": os.environ.get("SNOWFLAKE_PRIVATE_KEY_PASSPHRASE", ""),
    },
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(5)

To supply the key inline, replace private.key.file with private.key.content; never hard-code a private key in a notebook.

External-catalog read

Create the Snowflake external catalog in Master Catalogs first. You can then use a three-part table name or reuse its connection with catalog.id.

catalog_df = spark.table("<CATALOG_NAME>.<SCHEMA>.<TABLE_NAME>")
catalog_df.show(5)
catalog_id_df = (spark.read.format(AIDP_FORMAT)
    .option("catalog.id", "<CATALOG_ID>")
    .option("schema", "<SCHEMA>")
    .option("table", "<TABLE_NAME>")
    .load())
catalog_id_df.show(5)

Pushdown SQL

Use pushdown.sql to execute a source query in Snowflake.

pushdown_df = (spark.read.format(AIDP_FORMAT)
    .options(**opts)
    .option("pushdown.sql", "SELECT * FROM <SCHEMA>.<TABLE_NAME> LIMIT 10")
    .load())
pushdown_df.show(5)

Gotchas

• Read-only in 4.0. Do not use df.write, saveAsTable, insertInto, or write.mode with Snowflake.
• Authentication values are case-sensitive. Use Basic or KeyPair.
• Warehouse is required. Set warehouse for both authentication modes; role is optional.
• Network reachability. The AIDP cluster needs outbound HTTPS access to the Snowflake account endpoint.

References

• Official sample: Snowflake notebook