SparkForensics

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Detector catalog / SQL plans

PLAN

Nested loop join

A join with no usable key compares every row with every row and multiplies its output.

Outcome
SQL plans
Scope
Judged per SQL query
Usual fix
A change in the job code
CI gate
No budget flag: gate it with --fail-on-introduced against a baseline

An example finding

Where you see it

Dashboard

The PLAN tag marks it in the action region of the dashboard, among the widgets that rank a fix. How to read it in the findings guide.

Agent (MCP)

An assistant can read this entry with the list_detectors tool and its background with get_finding_documentation. The call and the response below come from a real run of the MCP server.

Call

{
  "tool": "list_detectors",
  "arguments": {
    "type": "nestedLoopJoin"
  }
}

Response

{
  "count": 1,
  "detectors": [
    {
      "type": "nestedLoopJoin",
      "name": "nested loop join",
      "tag": "PLAN",
      "tagSharedWith": [
        "duplicatePlanSubtree",
        "smallFiles",
        "overBroadcast",
        "underBroadcast",
        "pythonUdf",
        "mergeRewrite",
        "unprunedScan",
        "joinKeyCast"
      ],
      "family": "plan",
      "pitch": "A join with no usable key compares every row with every row and multiplies its output.",
      "region": "action",
      "scope": "sql",
      "fixEffort": "code",
      "thresholdSummary": "a nested-loop or cartesian join with over 1,000,000 output rows, at least 10x its larger input",
      "detectors": [
        {
          "detector": "nestedLoopJoin",
          "version": 1,
          "thresholds": {
            "minOutputRows": 1000000,
            "minExpansion": 10
          }
        }
      ],
      "pages": {
        "catalog": "docs/detectors/nestedLoopJoin.html",
        "guide": "docs/user-guide/understanding-findings.html#plan"
      },
      "tuning": {
        "kind": "chapter",
        "anchor": "#joins",
        "path": "docs/tuning-reference/joins.html#joins"
      },
      "gate": null
    }
  ]
}

get_finding_documentation call

{
  "tool": "get_finding_documentation",
  "arguments": {
    "type": "nestedLoopJoin"
  }
}

Its response, with each Markdown body replaced by its length

{
  "type": "nestedLoopJoin",
  "name": "Nested Loop Join",
  "detectionDoc": {
    "tag": "PLAN",
    "title": "Plan advisor",
    "content": "<7876 characters of Markdown>"
  },
  "tuningDoc": {
    "anchor": "#joins",
    "title": "Join Optimization",
    "content": "<12010 characters of Markdown>"
  }
}

CI (CLI)

List this entry from the command line. The output below is a real run of the command. Budgets and exit codes are in the CI guide. 

sparkforensics-analyze detectors --type nestedLoopJoin --format md
# Detectors (1)

## SQL plans

| Tag | Type | Scope | Fix | Gate | What it finds |
| --- | --- | --- | --- | --- | --- |
| PLAN | `nestedLoopJoin` | sql | code |  | A join with no usable key compares every row with every row and multiplies its output. |

Report only this finding type for a run with --type:

sparkforensics-analyze <event-log> --type nestedLoopJoin --impact critical,warning,info

It has no budget flag. Fail a build on a new one by comparing against a baseline with --fail-on-introduced.

Airflow

The operator has no budget parameter for it. Use fail_on_introduced with a baseline.

check_spark_job = SparkForensicsOperator(
    task_id="check_spark_job",
    log_source=...,
    backend=SubprocessAnalyzeHook(),
    baseline_log_source=...,
    fail_on_introduced="critical",
)

The operator works per run, and its summary counts findings per impact band. See the operator for its parameters.

How it is measured

Thresholds

A nested-loop or cartesian join with over 1,000,000 output rows, at least 10x its larger input.

nestedLoopJoin version 1

ThresholdDefault
minOutputRows1000000
minExpansion10

Each rule's impact bands and fixed fallbacks are in the threshold tables.

Override a default per run with --thresholds; see Tuning detector thresholds.

Docs