Dataset Splitter: CSV, XLSX, JSON by rows or column

Cut a big CSV or Apify dataset into parts, by rows, column or size

For anyone whose file is too big for the next tool: Google Sheets stops at 10 million cells, a CRM import accepts 10,000 rows at a time, a colleague needs one file per country. Give this Actor an Apify dataset or a CSV / TSV / JSON / NDJSON file URL, choose how to cut it, and get one file (or dataset) per part, each with a download link. $0.10 per 1,000 rows processed (rounded up per run). Failed runs and the demo are free. No scraping, no API keys.

Sample output (150 rows split into parts of 50):

partIndex	key	rows	bytes	downloadUrl
1	iris-part-001.csv	50	1,740	https://api.apify.com/v2/key-value-stores/…/records/iris-part-001.csv?signature=…
2	iris-part-002.csv	50	1,751	…
3	iris-part-003.csv	50	1,760	…

Try it free: leave input empty and press Start. The demo splits a built-in 25-row sample CSV into parts of 10 rows (not charged, rows carry _demo: true).

Price example: a 25,000-row file costs 25 units = $2.50, whether you make 3 parts or 300. A 150-row file costs 1 unit = $0.10.

What it does

• Fixed rows per part: for example 10,000 rows per file for CRM imports or Google Sheets
• Fixed number of parts: split into N files of nearly equal size
• One part per column value: one file per country, status or customer, with a cap on the number of parts
• Approximate size per part: aim for files of about 5 MB (estimated from the output format, so allow some percent of difference)
• Random sample instead of splitting: n rows or a percentage, with a seed so the same sample can be drawn again (rows keep their original order)
• Output: CSV, JSON, NDJSON or XLSX files in the key-value store, and/or one new named dataset per part
• Reads an Apify dataset (pick it from your runs) or a public file URL; detects the format, the delimiter and the text encoding (UTF-8, Shift_JIS, Windows-1252)
• Keeps your data as it is: CSV values stay exactly as in the file (a ZIP code 00123 stays 00123); turn on detectNumbers if you want real numbers in XLSX or JSON. Every part repeats the header row. Text starting with =, +, -, @ is stored as plain text in XLSX, never as a formula

Input example

{
  "fileUrl": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv",
  "splitMode": "column",
  "column": "species",
  "outputFormat": "xlsx"
}

To split an Apify dataset use datasetId. Modes and their fields: rows (rowsPerPart), parts (partCount), column (column, maxParts), size (targetSizeMb), sample (sampleRows or samplePercent, seed).

Output

• Dataset: one summary row per part with partIndex, key (file name in the key-value store), value (the column value, for split by column), rows, bytes, format, downloadUrl and, when datasets are written, datasetName and datasetId. In sample mode the row also has the seed used. A failed run has one row with status: failed and a plain-language error.
• Key-value store: the part files, named <source>-part-001.csv, <source>-<value>.csv or <source>-sample.csv (change the start with fileName). downloadUrl is Apify's signed public link, so you can share a file without sharing your token.
• New datasets (option saveToDatasets): prefix-001, prefix-002, ... The default prefix is split- plus the run ID, so it is always new. Named datasets stay until you delete them; the run stops before writing if one of them already has items.
• STATS record: input rows, parts, bytes, 1,000-row units charged, notes and the sample seed.

{
  "partIndex": 1, "status": "ok", "key": "iris-part-001.csv", "value": null,
  "rows": 50, "bytes": 1740, "format": "csv",
  "downloadUrl": "https://api.apify.com/v2/key-value-stores/…/records/iris-part-001.csv?signature=…"
}

Limits (cannot be raised by input)

• 2,000,000 rows and 1,000 columns per run; 500 parts per run; 200 MB per source file
• A run that would break a limit fails before anything is written and is not charged; rows are never silently cut. Example: 1,000,000 rows at 1,000 rows per part would need 1,000 parts, so the run asks for at least 2,000 rows per part
• XLSX parts can have at most 1,048,575 rows (Excel's limit); use CSV or smaller parts. A warning is logged when a part is bigger than the Google Sheets limit of 10,000,000 cells
• Source URLs must be public http or https links. Addresses on internal networks (localhost, private ranges, cloud metadata) are blocked, also after redirects. XLSX and zip files are not read (convert them to CSV first)
• JSON input must be an array of objects (or an object with one such array); nested values are kept as JSON text in CSV and XLSX output and as nested JSON in JSON, NDJSON and datasets
• The whole source is held in memory. Rough guide per 1 GB of run memory: about 500,000 CSV rows or 350,000 JSON rows of a dozen short columns (fewer with wide rows). The default 2 GB covers about twice that; for more rows start the run with 4 GB or more memory

Pricing

Pay per event: $0.10 per 1,000 rows processed (event rows-1000). All rows read from the source count once, rounded up per run: 2,500 rows cost 3 units ($0.30), regardless of mode, number of parts or output format (a random sample is charged for the rows read, not for the sample size). Nothing is charged for a failed run or the demo. The charge is made after all parts are saved. Set a maximum charge per run to cap spend: if it is too low for the whole source, the run stops before splitting anything. On the Apify Free plan, the $5 of monthly platform credit covers about 50,000 rows a month — enough to try it on real data.

Use cases

• Cut a 600,000-row export into files of 10,000 rows for a CRM or e-mail tool import
• Keep a spreadsheet under Google Sheets' 10 million cell limit
• One Excel file per sales region, country or account manager
• Send a reproducible 5 percent test sample of a large dataset to a colleague or a model
• Break a large scraper dataset into 5 smaller datasets that can be processed in parallel

FAQ

Does the order of rows stay the same? Yes, in every mode (also in the sample). In the rows, parts and size modes the parts are consecutive blocks of the source. What happens to rows with an empty value in the split column? They go to a part named empty. How exact is the size mode? It estimates each row's size in the chosen format and fills parts up to the target. CSV, JSON and NDJSON are usually within a few percent; XLSX is compressed, so it is only a rough guide. Can I run it twice with the same dataset prefix? Not if the first run left items in those datasets. Pick a new prefix or delete the old datasets. Does it change my source? No. It only reads the file or dataset and writes new files. Is the file link private? Anyone holding the signed link can download that file; it gives no access to anything else in your account.

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