Aidp Migration

作者 oracle-samples90b42d6c24d4無授權條款收錄於 2026年10月8日更新於 2026年10月8日

Guide a migration of notebooks/jobs from another platform (e.g. Databricks) into AIDP. Use when the user wants to port Databricks notebooks/jobs to AIDP, move workloads onto the AIDP lakehouse, or plan a migration. Orchestration-only — it composes the other self-contained aidp-* skills; it adds no new API surface.

僅含說明DevOps & Cloud
AI 產生的概覽

引導將 Databricks 等平台的筆記本與作業遷移至 AIDP,需人工確認。

功能
依序編排 AIDP 遷移:盤點來源筆記本、作業、資料表與程式庫,落地資料,移植筆記本,重建作業 DAG 與排程,然後驗證並切換。它組合其他 aidp-* 技能,不新增 API 介面。此技能僅負責編排,並明確不承諾批次自動轉換。
適用情境
當使用者想將 Databricks 筆記本或作業移植到 AIDP、把工作負載搬到 AIDP 湖倉,或規劃這類遷移時使用。
執行需求
透過代理執行,需要 OCI CLI 存取權以使用 oci raw-request 呼叫控制平面,並使用隨附的 scripts/aidp_sql.py 輔助指令碼執行互動式 Spark-SQL 與儲存格執行;另依賴所組合的 aidp-* 技能與參考文件。不需要 MCP 伺服器。此技能本身未附帶指令碼。

aidp-migration — guided migration into AIDP

Plan and execute a migration of notebooks/jobs onto AIDP by composing the other skills. Adds no new API surface — it sequences ingestion, notebooks, pipelines, and validation. Like every skill in this plugin it is self-contained: control-plane ops run via oci raw-request and interactive Spark-SQL/cell execution runs via the bundled scripts/aidp_sql.py. No MCP server or ai-data-engineer-agent repo is required.

When to use

  • "Migrate these Databricks notebooks/jobs to AIDP", "move this workload onto AIDP", "plan a migration".

Workflow

  1. Inventory the source assets (notebooks, jobs/schedules, tables, libraries) — list what must move.
  2. Land data: ingest source tables/files (aidp-ingest-file-to-table; external sources via the spark-connectors plugin + aidp-federate).
  3. Port notebooks: recreate notebooks in the workspace (aidp-notebooks / aidp-workspace-files), adapting platform-specifics (paths, compute:/// defaultFS caveats, cluster/session APIs, Delta vs other formats). Validate cells run with the bundled helper (python "$PLUGIN_DIR/scripts/aidp_sql.py" … --code …).
  4. Recreate jobs: build the task DAG + schedule (aidp-pipelines), heeding the clusterName-UUID pitfall and NOTEBOOK_TASK/dependsOn shape.
  5. Validate: profile + quality-check migrated tables (aidp-profiling-tables, aidp-data-quality); compare row counts/aggregates against the source; dry-run the job and inspect output.
  6. Cut over: only after validation; keep the source as fallback until confirmed.

Engines (inherited from the composed skills)

  • Control-plane (workspaces, catalogs, tables, clusters, jobs, files) → oci raw-request against the AIDP REST API — see references/oci-raw-request.md and references/no-mcp-rest-map.md.
  • Interactive Spark-SQL / cell execution (validate ported cells, compare counts/aggregates) → python "$PLUGIN_DIR/scripts/aidp_sql.py" --region <r> --datalake <OCID> --workspace <ws> --cluster <key> --code <…>.

Notes

  • Common AIDP gotchas to apply during porting: compute:/// defaultFS (executors can't write the driver FS; size APIs return 0 — measure via oci://), manifest commit semantics for external tables, and the clusterName-UUID pitfall when wiring jobs.
  • Keep scope to AIDP-native migration. OAC and OCI networking are out of scope.
  • This is a guided, human-confirmed process — no bulk automated conversion claims.

References

  • composes aidp-ingest-file-to-table, aidp-notebooks, aidp-workspace-files, aidp-pipelines, aidp-profiling-tables, aidp-data-quality, aidp-federate
  • references/oci-raw-request.md · references/no-mcp-rest-map.md · scripts/aidp_sql.py

來源與署名

來源:oracle-samples/oracle-aidp-samples位於ai/claude-code-plugins/oracle-ai-data-platform-workbench-engineer-agent/skills/aidp-migration提交90b42d6

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