{"uid":"cap_Rj88yvyG_ZU2FKSv_6yfO","slug":"transformation-throughput-analytics-numeric-row-ordering-adjacent-row-07e2845f","name":"Transformation Throughput Analytics — Numeric Row Ordering + Adjacent Row Changes","description":"Transformation throughput — Numeric row ordering + Adjacent row changes: Numeric row ordering + Adjacent row changes 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-116?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"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"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_SchuA4oan7x-H728gKO80","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes transformation throughput records by computing numeric row ordering and adjacent row changes for processed_rows or duration_seconds fields across up to 200 rows.","exampleAgentPrompt":"I have a list of ETL pipeline runs with dates, dataset groups, processed_rows, and duration_seconds — can you rank them numerically by processed_rows and also show me the adjacent row-to-row changes between consecutive entries? I have about 20 rows across two groups.","exampleUseCases":[{"title":"Ranking ETL jobs by throughput","prompt":"Here are my last 30 daily ETL job records with processed_rows and duration_seconds — can you rank them numerically by processed_rows so I can see which runs handled the most data?"},{"title":"Detecting pipeline slowdowns via adjacent deltas","prompt":"I have 50 transformation job records across multiple dataset groups. Can you compute the adjacent row changes in duration_seconds so I can spot where processing time jumped significantly between consecutive runs?"},{"title":"Comparing consecutive batch runs across groups","prompt":"I've got 100 rows of transformation throughput data for group-a and group-b with daily dates, processed_rows, and duration_seconds. Run both reports — numeric ordering and adjacent row changes — on the processed_rows field so I can see the ranking and the step-by-step differences."}],"resultDescription":"Returns two analytical reports: (1) numeric row ordering — rows ranked by the selected field (processed_rows or duration_seconds), and (2) adjacent row changes — differences between each consecutive row for the selected field, enabling trend and delta analysis across the supplied transformation throughput records.","failureModes":["Exceeding 200 rows causes rejection","Missing required fields (row_id, date, processed_rows, duration_seconds) cause validation errors","Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure","Null values in the selected field may affect ordering and delta computation","Invalid field enum value (not processed_rows or duration_seconds) causes error","Empty rows array is rejected","Payment not included or insufficient USDC causes 402 response"],"whenToPreferThis":"Choose this endpoint when you need both a ranked ordering and consecutive-row delta analysis on transformation throughput data (processed_rows or duration_seconds) for up to 200 records in a single cost-efficient call. It is ideal for data engineers monitoring ETL pipeline performance trends without needing live lookups, predictions, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:50.617Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-numeric-row-ordering-adjacent-row-07e2845f"}