# Data Ingestion Batches — Exact Row Deduplication + Keyed Dataset Comparison > Data Ingestion Batches — Exact Row Deduplication + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18). Performs exact row deduplication and keyed dataset comparison on two supplied data ingestion batch datasets (received_rows, accepted_rows) of up to 200 rows each, returning two independent analytical reports. ## Facts - Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-053?utm_source=zero.xyz - Price: $0.01/call - Payment: x402 - Status: unknown - Last checked: 2026-10-18 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/data-ingestion-batches-exact-row-deduplication-keyed-dataset-comparison-4356ac89 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tnGSW27-txjVw_Mh6QxR3 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 data-ingestion-batches-exact-row-deduplication-keyed-dataset-comparison-4356ac89 -d '' ``` Example prompt: I have two versions of my data ingestion batch — the original and a revised one — each with up to 50 rows tagged with row_id, dataset_group, date, received_rows, and accepted_rows. Can you run exact row deduplication on the primary set and then compare both datasets by key to find what changed? ## When to prefer this Choose this endpoint when you need to locally analyze data ingestion batch records for exact duplicates and cross-dataset key-based differences without any external data lookups or live system access. It is ideal for ETL pipeline audits, data quality checks, and reconciliation tasks where you have two structured batch datasets with row_id, dataset_group, date, received_rows, and accepted_rows fields. Prefer it over general-purpose analytics when you need both a deduplication report and a keyed comparison report in a single low-cost call ($0.01 USDC) on up to 200 rows. ## Known failure modes - Input array exceeds 200 rows — request rejected - Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation error - Invalid date format not matching YYYY-MM-DD pattern — schema validation failure - row_id empty or exceeds 80 characters — field validation error - Numeric values out of allowed range (±1,000,000,000,000) — schema rejection - Empty rows array (minItems: 1 not met) — validation error - Payment of 0.01 USDC not received — 402 payment required response ## How this service works Data ingestion batches — Exact row deduplication + Keyed dataset comparison: Exact row deduplication + Keyed dataset comparison for supplied data ingestion batches records (received_rows, accepted_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows. ## Output Returns two independent analytical reports: (1) an exact row deduplication report identifying duplicate records in the primary dataset, and (2) a keyed dataset comparison report highlighting row-level differences between the two supplied datasets based on row_id keys, covering received_rows and accepted_rows fields. No external lookups or predictions are made — all analysis is performed locally on the supplied data. ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "rows": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "received_rows", "accepted_rows" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "accepted_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "received_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": false }, "default": [ { "date": "2026-10-01", "row_id": "row-1", "accepted_rows": 1, "dataset_group": "group-a", "received_rows": 10 }, { "date": "2026-10-02", "row_id": "row-2", "accepted_rows": 2, "dataset_group": "group-b", "received_rows": 20 }, { "date": "2026-10-03", "row_id": "row-3", "accepted_rows": 3, "dataset_group": "group-a", "received_rows": 15 }, { "date": "2026-10-04", "row_id": "row-4", "accepted_rows": 4, "dataset_group": "group-b", "received_rows": 30 } ], "maxItems": 200, "minItems": 1 }, "other": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "received_rows", "accepted_rows" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "accepted_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "received_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": false }, "de … (truncated) ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-exact-row-deduplication-keyed-dataset-comparison-4356ac89/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)