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Detector catalog / SQL plans
PLAN
Unpruned partitioned scan
A filtered scan with no partition filter reads every partition of the table.
- 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-introducedagainst 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": "unprunedScan"
}
}Response
{
"count": 1,
"detectors": [
{
"type": "unprunedScan",
"name": "unpruned partitioned scan",
"tag": "PLAN",
"tagSharedWith": [
"duplicatePlanSubtree",
"smallFiles",
"overBroadcast",
"underBroadcast",
"pythonUdf",
"nestedLoopJoin",
"mergeRewrite",
"joinKeyCast"
],
"family": "plan",
"pitch": "A filtered scan with no partition filter reads every partition of the table.",
"region": "action",
"scope": "sql",
"fixEffort": "code",
"thresholdSummary": "a filtered scan of a partitioned table with no partition filter that read at least 2 partitions and 1 GiB",
"detectors": [
{
"detector": "unprunedScan",
"version": 1,
"thresholds": {
"minBytesRead": 1073741824,
"minPartitionsRead": 2
}
}
],
"pages": {
"catalog": "docs/detectors/unprunedScan.html",
"guide": "docs/user-guide/understanding-findings.html#plan"
},
"tuning": {
"kind": "chapter",
"anchor": "#table-formats",
"path": "docs/tuning-reference/table-formats.html#table-formats"
},
"gate": null
}
]
}get_finding_documentation call
{
"tool": "get_finding_documentation",
"arguments": {
"type": "unprunedScan"
}
}Its response, with each Markdown body replaced by its length
{
"type": "unprunedScan",
"name": "Unpruned Partitioned Scan",
"detectionDoc": {
"tag": "PLAN",
"title": "Plan advisor",
"content": "<7876 characters of Markdown>"
},
"tuningDoc": {
"anchor": "#table-formats",
"title": "Table Formats",
"content": "<10919 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 unprunedScan --format md# Detectors (1)
## SQL plans
| Tag | Type | Scope | Fix | Gate | What it finds |
| --- | --- | --- | --- | --- | --- |
| PLAN | `unprunedScan` | sql | code | | A filtered scan with no partition filter reads every partition of the table. |
Report only this finding type for a run with --type:
sparkforensics-analyze <event-log> --type unprunedScan --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 filtered scan of a partitioned table with no partition filter that read at least 2 partitions and 1 GiB.
unprunedScan version 1
| Threshold | Default |
|---|---|
minBytesRead | 1073741824 |
minPartitionsRead | 2 |
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
- This finding is covered in a general tuning chapter: Spark tuning reference.
- Findings guide: PLAN in Understanding findings.
- Shares the PLAN tag with: duplicate plan subtree, small files, oversized broadcast join, missed broadcast join, row-at-a-time Python UDF, nested loop join, MERGE rewrite, cast on a join key.