# Transformation Throughput — Exact Row Deduplication + Numeric Interval Filter

> Transformation Throughput — Exact Row Deduplication + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Deduplicates exact rows and filters by a numeric interval on transformation throughput records (processed_rows, duration_seconds) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-043?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-exact-row-deduplication-numeric-interval-0f294a9d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_FTbKDoSDoTfpL6Br-Z6gu

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability transformation-throughput-exact-row-deduplication-numeric-interval-0f294a9d -d '<json body>'
```

Example prompt: Deduplicate my transformation throughput records and then filter them to only keep rows where processed_rows is between 10 and 500 — here's my dataset of up to 200 rows with row_id, dataset_group, date, processed_rows, and duration_seconds fields.

## When to prefer this

Choose this endpoint when you need both exact row deduplication and a numeric interval filter applied to transformation throughput data (processed_rows or duration_seconds) in a single call, without needing live lookups, ML predictions, or external integrations. Ideal for data engineering pipelines that need lightweight, local analytical cleaning on batches up to 200 rows at very low cost.

## Known failure modes

- Exceeding 200 rows causes rejection
- Invalid date format (not YYYY-MM-DD) causes validation error
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes schema error
- minimum greater than maximum may return empty interval filter results
- Numeric values outside ±1,000,000,000,000 boundary are rejected
- Empty rows array causes rejection

## How this service works

Transformation throughput — Exact row deduplication + Numeric interval filter: Exact row deduplication + Numeric interval filter for supplied transformation throughput records (processed_rows, duration_seconds). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two analytical reports per call: one showing the result of exact row deduplication (rows with all fields identical removed), and one showing the subset of rows where the specified numeric field (processed_rows or duration_seconds) falls within the provided minimum and maximum bounds. Reports are generated locally from supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "processed_rows",
     "duration_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "processed_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "duration_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "processed_rows": 10,
     "duration_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "processed_rows": 20,
     "duration_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "processed_rows": 15,
     "duration_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "processed_rows": 30,
     "duration_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "processed_rows",
    "duration_seconds"
   ],
   "type": "string",
   "default": "processed_rows"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-exact-row-deduplication-numeric-interval-0f294a9d/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)