{"uid":"cap_JaFDXknVAvxffX7WsblMi","slug":"pipeline-durations-analytics-exact-row-deduplication-trailing-mean-cc6b9bbe","name":"Pipeline Durations Analytics: Exact Row Deduplication + Trailing Mean Series","description":"Pipeline durations — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series for supplied pipeline durations records (run_seconds, processed_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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-045?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","run_seconds","processed_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"run_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","run_seconds":10,"dataset_group":"group-a","processed_rows":1},{"date":"2026-10-02","row_id":"row-2","run_seconds":20,"dataset_group":"group-b","processed_rows":2},{"date":"2026-10-03","row_id":"row-3","run_seconds":15,"dataset_group":"group-a","processed_rows":3},{"date":"2026-10-04","row_id":"row-4","run_seconds":30,"dataset_group":"group-b","processed_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_seconds","processed_rows"],"type":"string","default":"run_seconds"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_EL8jEpKuPzSR9tQeV2O5g","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":"Deduplicates supplied pipeline duration records and computes a trailing moving average series over run_seconds or processed_rows for up to 200 rows.","exampleAgentPrompt":"Can you deduplicate these pipeline run records and compute a trailing mean series with a window of 3 over run_seconds? I have 4 records: row-1 on 2026-10-01 for group-a with 10 run_seconds and 1 processed_row, row-2 on 2026-10-02 for group-b with 20 run_seconds and 2 processed_rows, row-3 on 2026-10-03 for group-a with 15 run_seconds and 3 processed_rows, and row-4 on 2026-10-04 for group-b with 30 run_seconds and 4 processed_rows.","exampleUseCases":[{"title":"Detect duplicate ETL job runs","prompt":"I have a list of up to 80 pipeline run records with row IDs, dates, group names, run_seconds, and processed_rows — can you deduplicate them exactly and then show me a trailing mean of run_seconds using a window of 5?"},{"title":"Smooth pipeline performance trend","prompt":"Here are 150 pipeline duration records across multiple dataset groups. Can you remove any exact duplicate rows and then compute a rolling average of processed_rows with a window of 10 so I can see the smoothed throughput trend?"},{"title":"Audit repeated pipeline entries","prompt":"My pipeline logging system sometimes emits duplicate entries. Can you take these 60 records and give me both a deduplication report and a trailing mean series over run_seconds with a window of 4?"}],"resultDescription":"Returns two reports: (1) an exact row deduplication report identifying and removing fully duplicate records from the supplied dataset, and (2) a trailing moving average series computed over the specified numeric field (run_seconds or processed_rows) using the given window size — both derived entirely from the supplied input rows with no external lookups.","failureModes":["Missing required fields (row_id, date, dataset_group) causes validation error","Fewer than 1 row or more than 200 rows triggers a request rejection","Window size larger than the number of rows may produce incomplete or empty trailing mean output","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Null values in the target numeric field may result in gaps in the trailing mean series"],"whenToPreferThis":"Choose this endpoint when you have pipeline duration records (with run_seconds and/or processed_rows) and need both exact duplicate removal and a trailing moving average trend in a single call for up to 200 rows. It is ideal for lightweight, self-contained ETL analytics without any external data enrichment or prediction. Prefer alternatives if you need grouped summaries, outlier detection, string normalization, or more than 2 analytical reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:51.351Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-exact-row-deduplication-trailing-mean-cc6b9bbe"}