aidp-snowflake

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