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aidp-federate

Skill

Federate across multiple data sources in one AIDP Spark session — read from several connectors (Oracle ADB/ExaCS, Fusion, Snowflake, S3, lakehouse tables, …) and join them in a single notebook. Use when the user wants to combine/join data from more than one source, blend an external system with the

0Databases

Install

git clone https://github.com/oracle-samples/oracle-aidp-samples.git ~/.claude/skills/aidp-federate

What is aidp-federate?

Federate across multiple data sources in one AIDP Spark session — read from several connectors (Oracle ADB/ExaCS, Fusion, Snowflake, S3, lakehouse tables, …) and join them in a single notebook. Use when the user wants to combine/join data from more than one source, blend an external system with the lakehouse, or do cross-source analysis. Composes the spark-connectors plugin; does not duplicate connectors.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~102 tokens of context used while enabled, before you invoke anything

Documentation

README · ~2 min read

aidp-federate — cross-source federation in one Spark session

Blend multiple sources by reading each into one Spark session and joining them — a signature differentiator (competitor agents degrade on foreign tables or need an external orchestrator + manual key-joins). Execution is via the bundled scripts/aidp_sql.py helper (no MCP, no AIDP_SESSION required).

When to use

  • "Join data from and ", "combine Fusion + the lakehouse", "blend Snowflake with store_sales", any cross-source analysis.
  • Also the entry point for a SINGLE external source ("a notebook that connects to Fusion / EPM / ADB / …"): the connection recipe still comes from the spark-connectors plugin's aidp-<source> skill (step 1) — this skill just adds the join. Never hand-roll the source connection. (Check the spark-connectors plugin is

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