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Documentation Index

Fetch the complete documentation index at: https://parabola.io/docs/llms.txt

Use this file to discover all available pages before exploring further.

Input/output

This step takes two tables as its input and shows you how they overlap. It will help you answer a question like, “Which rows from Table 1 do or do not exist in Table 2?”

Input 1

Table 1 shows products in our first store with three columns: ‘Variant ID’, ‘Name’, and ‘Sales Price’.
Input table 1 listing Store 1 products with Variant ID, Name, and Sales Price columns

Input 2

Table 2 shows products in our second store with two columns: ‘Variant ID’ and ‘Name’.
Input table 2 listing Store 2 products with Variant ID and Name columns

Output

Let’s say we want to find which products from Store 1 are also sold in Store 2. The step will immediately tell us this as its output. Below we can see that there are three products sold in both stores. Since ‘Store 1’ was our primary table in the step, it’s showing us the complete rows from that table.
Output table showing the three Store 1 products that also appear in Store 2

Default settings

When you first connect your two inputs into this step, you’ll see that your first input is treated as the primary table, and that rows have been matched by the lead column. By default, the step will keep rows where any of the rules are true.
Default settings panel showing Input 1 set as the primary table with rows matched on the lead column

Custom settings

First, make sure the step is configured to use the correct primary table, in this case, ‘Input 1’. Then, determine how the rules should be honored. If you are setting multiple rules, the step can be structured so that ‘any’ rule counts as a match or ‘all’ rules must be met to be considered a match.
Custom settings panel showing the primary table selector and the 'any' versus 'all' rule logic toggle
Now we’re ready to configure the rules for how the step should identify matches. Each rule compares tables according to values in specified columns. First, select the relevant column from each table. Then, choose one of three options in the match type:
Match rule with column selectors and the match type dropdown showing Exact match, Match ignoring case, and Approximate match options
‘Exact match’ will look for an exact match, including casing. ‘Match ignoring case’ will allow for differences in capitalization. ‘Approximate match’ will look for a fuzzy match. If you choose ‘Approximate match’, you can adjust the confidence percentage. The higher the percentage, the closer to an exact match this step will attempt to make. For comparison, 100% confidence is equivalent to searching for an exact match.
Approximate match settings with a confidence percentage slider for fuzzy matching
To add another rule, click ’+ Or, another match’ below your first rule.
Last modified on May 18, 2026