# Transformation Throughput — Exact Row Deduplication + Trailing Mean Series

> Transformation Throughput — Exact Row Deduplication + Trailing Mean Series 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 transformation throughput records exactly and computes trailing mean series for processed_rows or duration_seconds fields across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-045?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-trailing-mean-series-63806d0b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_K4I4HsGPjy7mkr1p04k6c

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-trailing-mean-series-63806d0b -d '<json body>'
```

Example prompt: Can you deduplicate my transformation throughput records and compute a trailing mean series with a window of 3 for processed_rows? Here are my rows: row-1 on 2026-10-01 in group-a with 100 processed rows and 5 seconds, row-2 on 2026-10-02 in group-b with 200 rows and 10 seconds, and row-3 on 2026-10-03 in group-a with 100 rows and 5 seconds.

## When to prefer this

Choose this endpoint when you need both exact row-level deduplication and a trailing/rolling mean time series computed together in a single API call on transformation throughput data (processed_rows, duration_seconds). It is ideal for data engineers who want to clean pipeline run logs and simultaneously analyze throughput trends without writing custom code. Prefer this over general analytics platforms when you need a lightweight, pay-per-call solution for up to 200 records.

## Known failure modes

- Input array is empty or missing — returns validation error
- More than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field enum value not one of processed_rows or duration_seconds — validation error
- Window value outside range 2–200 — schema rejection
- All rows are unique — deduplication report returns empty duplicate set

## How this service works

Transformation throughput — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series 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: (1) an exact row deduplication report identifying and removing fully duplicate records from the supplied transformation throughput rows, and (2) a trailing mean series computed over the specified numeric field (processed_rows or duration_seconds) using the given rolling window size — all derived locally from the 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-exact-row-deduplication-trailing-mean-series-63806d0b/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)