Trabalho com agregadores e matrizes

Workflows often produce many items at once — several rows from a sheet, multiple emails, a list of orders. Sometimes you need to combine them into a single result, such as one summary email instead of dozens.

This is the job of an aggregator.

An array is simply an ordered list of values. In automation, a step that returns multiple items effectively hands you an array — for example a list of customer names.

Understanding arrays is key to controlling how collections flow through your workflow.

An aggregator takes the many items coming from an earlier step and merges them into one bundle. Instead of the workflow continuing once per item, it continues a single time with everything combined.

It is the opposite of an iterator, which splits one bundle into many items.

A common use is combining text. A text aggregator joins many values into one string, often separated by commas or new lines.

For example, ten task names become a single bulleted list you can drop into one notification.

Aggregators can also do math across items. A numeric aggregator can sum, average, count, or find the maximum of a field.

This lets a workflow calculate, say, total revenue from a list of orders in one step.

Many aggregators support a group by setting. Instead of one big bundle, items are grouped by a shared key — like grouping orders by customer or sales by region.

Grouping turns a flat list into meaningful, organized chunks.

An array aggregator bundles multiple items back into a single structured array, preserving each item's fields.

This is useful when a later step expects a list — for example sending many line items to one invoice.

A powerful pattern is iterate, then aggregate. You split a bundle into items with an iterator, process each one, then merge the results back with an aggregator.

This split-process-rejoin flow handles collections cleanly without manual steps.

When configuring an aggregator, you must pick the source module — the step whose output is being combined. Everything between that source and the aggregator is rolled into the bundle.

Choosing the wrong source leads to too few or too many items being merged.

Aggregators shine when you need to:

• Send one daily digest instead of many alerts
• Total or average values across records
• Build a single document from many rows
• Group data before reporting

Watch out for these pitfalls:

• Forgetting to set the source module correctly
• Aggregating empty results, which can produce blank output
• Combining items that should have stayed separate

Always test with sample data to confirm the bundle looks right.

Test your understanding of aggregators and arrays.

You learned to work with aggregators and arrays:

• Arrays are ordered lists of values flowing through a workflow
• Aggregators combine many items into one bundle
• Use text, numeric, and array aggregators for different needs
• Group items by a key and pair iterators with aggregators
• Always set the correct source and test with sample data

Aggregation lets your workflows summarize and organize collections with ease.