Dataset Deduplicate & Merge (Fuzzy) avatar

Dataset Deduplicate & Merge (Fuzzy)

Pricing

from $10.00 / 1,000 1,000 items processeds

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Dataset Deduplicate & Merge (Fuzzy)

Dataset Deduplicate & Merge (Fuzzy)

Merge multiple Apify datasets or CSV/JSON/XLSX files and remove duplicates with normalised or fuzzy matching. Only-new mode returns just items you have not seen before.

Pricing

from $10.00 / 1,000 1,000 items processeds

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Larchrow

Larchrow

Maintained by Community

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8 days ago

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EN · Merge any number of Apify datasets (plus JSON/CSV URLs) and remove duplicates that simple exact-match dedupers miss:

  • Normalisers per field: url (drops www, trailing slash, utm_/gclid/fbclid tracking params, sorts query), phone (E.164, German 0-prefix → +49), email (case, Gmail dots and +tags), company (drops GmbH, UG, AG, KG, Ltd, LLC, Inc … and punctuation), text (case, accents, whitespace), exact.
  • Fuzzy merge of near-identical names (typos, missing letters) with a safety rule: values that differ by a real word – e.g. Hospital Rijeka vs Hospital Osijek, NL Nord vs NL Süd – are never merged.
  • Merge strategies: keep first, keep last, fill empty fields from duplicates, or fill and union list fields. Every output item gets __dupes (how many records were merged) and __source.
  • Only-new mode: remembers keys across runs, so a scheduled scraper + this actor outputs only records you have never seen.
  • Streaming reads in 10k pages, works with datasets you own (no extra permissions needed). Stats in the key-value store record STATS.

Pricing: pay per event, per 1,000 input items processed. No charge for empty runs.

DE · Führt beliebig viele Apify-Datasets (und JSON/CSV-URLs) zusammen und entfernt Duplikate, die einfache Exakt-Vergleiche übersehen: URL-, Telefon-, E-Mail- und Firmennamen-Normalisierung (GmbH & Co. KG, UG, AG …), unscharfer Abgleich mit Schutzregel gegen Fehlzusammenführungen, vier Merge-Strategien und ein „nur neue“-Modus für Monitoring.

Hinweis: Das Tool verarbeitet nur Daten, die du selbst einbringst. Für personenbezogene Daten in deinen Datasets bist du Verantwortlicher im Sinne der DSGVO.

Example input:

{"datasetIds":["<run-1-dataset>","<run-2-dataset>"],"fields":["website:url"],"fuzzyField":"name:company","mergeStrategy":"fill"}

New (merged from dataset-tools): XLSX/JSONL input, mergeStrategy: most-complete (keeps the duplicate with the most filled fields), renameFields, fieldsToKeep, fieldsToDrop, requiredFields. Neu: XLSX/JSONL-Eingabe, Strategie „most-complete“ (vollständigster Eintrag), Felder umbenennen/auswählen/entfernen, Pflichtfelder.