Row Limit

Row Limit is the parameter that restricts the maximum number of rows in the report output. It protects against overflowing the output sheet and speeds up execution.

Why a row limit is needed

• Sheet protection — Google Sheets has a limit of 10 million cells. Without a restriction, a report could exceed it
• Speed — fewer rows means faster execution and writing
• Relevance — often you only need the top N rows, sorted by a key metric

Step-by-step instructions

1. Set the limit

In the builder, go to the Data > Row Limit section. Enter a number or choose from the presets.

2. Available presets

• No limit — all rows (not recommended for large reports)
• 100 — for quick test runs
• 1,000 — the standard limit for most reports
• 10,000 — for detailed reports
• 100,000 — the maximum recommended limit for Google Sheets
• Custom — any number from 1 to 1,000,000

3. Account for sorting

The row limit is applied after sorting. This means that with Cost DESC and a limit of 100, you get the top 100 campaigns by spend, not 100 random rows.

4. Account for write mode

In Append mode, each new batch of data is appended at the end. The row limit restricts each individual batch, not the total sheet volume. In Replace mode, old data is deleted, and only the last batch (up to the row limit) remains in the sheet.

How to verify

• Run the report and check the number of rows in the output sheet (minus the header row)
• Compare against the set limit — the number of data rows should be <= the limit
• If the row count exactly matches the limit, data may have been truncated. Increase the limit to check

Important notes

• A limit of 0 means "no restriction"
• If there is less data than the limit, all available rows are output
• The row limit doesn't affect API requests to the source — data is still extracted in full and truncated at the output stage

Related articles

• Sorting — the limit is applied after sorting
• Filters — reducing the row count before the limit
• Write Modes — how the limit affects each mode
• Large Reports — working with large data volumes