aidp-sqlserver — Microsoft SQL Server via AIDP aidataplatform

When to use

• Read or write a Microsoft SQL Server from an AIDP notebook.
• Mentioned: "SQL Server", "MSSQL", "TDS".

When NOT to use

• For Postgres → aidp-postgresql.
• For MySQL → aidp-mysql.
• For Azure SQL Database → aidp-azuresql.

Read

import os
from oracle_ai_data_platform_connectors.aidataplatform import (
    AIDP_FORMAT, aidataplatform_options,
)

opts = aidataplatform_options(
    type="SQLSERVER",
    host=os.environ["MSSQL_HOST"],
    port=int(os.environ.get("MSSQL_PORT", "1433")),
    user=os.environ["MSSQL_USER"],
    password=os.environ["MSSQL_PASSWORD"],
    schema=os.environ.get("MSSQL_SCHEMA", "dbo"),
    table=os.environ["MSSQL_TABLE"],
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(5)

Write

opts = aidataplatform_options(
    type="SQLSERVER",
    host=os.environ["MSSQL_HOST"],
    port=int(os.environ.get("MSSQL_PORT", "1433")),
    database_name=os.environ["MSSQL_DATABASE"],   # required on write
    user=os.environ["MSSQL_USER"],
    password=os.environ["MSSQL_PASSWORD"],
    schema=os.environ.get("MSSQL_SCHEMA", "dbo"),
    table=os.environ["MSSQL_TARGET_TABLE"],
    extra={"write.mode": "CREATE"},
)
df.write.format(AIDP_FORMAT).options(**opts).save()

Gotchas

• database.name is required on write but not strictly on read. If a read fails with "object not found", supply database_name= too — some SQL Server installs require it for the connector to disambiguate.
• Schema vs database: SQL Server has both. schema here is the SQL-Server schema (typically dbo); database.name is the catalog (e.g. master, AdventureWorks).
• TDS port 1433 by default. Azure SQL Database exposes port 1433 over public TLS; AIDP must reach it via its egress route.

References

• Helper: scripts/oracle_ai_data_platform_connectors/aidataplatform.py
• Official sample: oracle-samples/oracle-aidp-samples → data-engineering/ingestion/Read_Write_External_Ecosystem_Connectors.ipynb