aidp-siebel — Oracle Siebel CRM via AIDP aidataplatform

When to use

• User wants to ingest Siebel CRM data (contacts, accounts, opportunities, service requests) into a Spark DataFrame from an AIDP notebook.
• User mentions: "Siebel", "Siebel CRM", "S_CONTACT", "S_ORG_EXT", "S_OPTY", Siebel base tables.

When NOT to use

• For Oracle Autonomous DB family (ALH/ADW/ATP) → aidp-alh.
• For Oracle PeopleSoft → aidp-peoplesoft.
• For generic Oracle DB → aidp-oracle-db.

Prerequisites in the AIDP notebook

1. Helpers on sys.path (run aidp-connectors-bootstrap first).
2. Env vars / OCI Vault secrets:
   • SIEBEL_HOST, SIEBEL_PORT (typically 1521)
   • SIEBEL_DATABASE_NAME (Oracle SID / service)
   • SIEBEL_USER, SIEBEL_PASSWORD
   • SIEBEL_SCHEMA (typically SIEBEL)
   • SIEBEL_TABLE (a Siebel base table, e.g. S_CONTACT, S_ORG_EXT)

Read

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

opts = aidataplatform_options(
    type="ORACLE_SIEBEL",
    host=os.environ["SIEBEL_HOST"],
    port=int(os.environ["SIEBEL_PORT"]),
    database_name=os.environ["SIEBEL_DATABASE_NAME"],
    user=os.environ["SIEBEL_USER"],
    password=os.environ["SIEBEL_PASSWORD"],
    schema=os.environ.get("SIEBEL_SCHEMA", "SIEBEL"),
    table=os.environ["SIEBEL_TABLE"],
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(10)

Pushdown SQL

Use pushdown.sql to run a complete source query — push joins, filters, and aggregations to the Siebel DB instead of pulling whole base tables into Spark.

opts = aidataplatform_options(
    type="ORACLE_SIEBEL",
    host=os.environ["SIEBEL_HOST"],
    port=int(os.environ["SIEBEL_PORT"]),
    database_name=os.environ["SIEBEL_DATABASE_NAME"],
    user=os.environ["SIEBEL_USER"],
    password=os.environ["SIEBEL_PASSWORD"],
    extra={
        "pushdown.sql": (
            "SELECT C.ROW_ID, C.LAST_NAME, C.FST_NAME, O.NAME AS ACCOUNT "
            "FROM SIEBEL.S_CONTACT C "
            "JOIN SIEBEL.S_ORG_EXT O ON C.PR_HELD_POSTN_ID = O.ROW_ID "
            "WHERE C.STATUS_CD = 'Active'"
        ),
    },
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(10)

Gotchas

• Connector is read-only. Siebel data should be written back through Siebel's EAI/REST channels, not Spark. The connector is intentionally one-way.
• Underlying Oracle DB. Siebel runs on Oracle DB; network reachability rules from aidp-oracle-db apply.
• SIEBEL schema owner. Standard Siebel install owns all base tables (S_*) under the SIEBEL schema. The connector user needs SELECT privs.
• Soft-delete columns. Siebel uses ROW_ID keys and LAST_UPD for incremental ingest. Filter with WHERE LAST_UPD > :since via pushdown.sql for delta loads.
• Audit columns. CREATED, CREATED_BY, LAST_UPD, LAST_UPD_BY are populated by triggers on every row — useful for change tracking.

References

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