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Batch Job Resources — Date by Category Pivot
x402
Batch Job Resources — Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).
Generates a date-by-category pivot table for batch job resource metrics (duration and memory) from up to 200 supplied records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Batch job resources - Date by category pivot: Date by category pivot for Batch job resources. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded date by category pivot report.
Output
A bounded descriptive analytics pivot report cross-tabulating the selected metric (duration_seconds or peak_memory_mb) by job category (rows) and date (columns), derived locally from the supplied records with no external enrichment or forecasting.
Example use cases
Daily memory usage breakdown by job
“I have 150 batch job records with peak_memory_mb readings for each run — can you pivot that data so I can see peak memory usage per job category across each date?”
Comparing job run times over a sprint
“We ran two job groups, 'etl-nightly' and 'report-gen', every day last week. Can you take these records and give me a pivot table of their duration_seconds by date so I can spot which days were slowest?”
Resource audit for infrastructure review
“I need a date-by-category pivot of our batch job resource metrics — about 80 rows covering three job types — using the duration_seconds field, so I can present a usage summary in our infrastructure review.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-batch-job-resources-pivot?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 batch job resource records and need a fast, local descriptive pivot table cross-tabulating either duration or memory usage by job category and date — without needing external data enrichment, forecasting, or validation. Ideal for operational dashboards, sprint reviews, or infrastructure audits where the data is already clean and structured.
Side effects
- More than 200 rows supplied — request exceeds maxItems limit
- Missing required fields (row_id, job, date, duration_seconds, peak_memory_mb) on any record
- Invalid date format (must match YYYY-MM-DD pattern)
- Invalid field enum value (must be 'duration_seconds' or 'peak_memory_mb')
- Empty rows array (minItems: 1 not met)
- Numeric values outside allowable range cause validation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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