ET1’s Joiner Node

by | Sep 15, 2025 | App Documentation

On your magic quest to join data? We call it the Joiner node.

A simple joining solution that helps people join data at a row level.

In ET1, Joiner is focused on “keeping it simple” and will aim to automatically infers your joins.

ET1 assumes.

Inferring a join means it assumes you prepared the data prior. Like, Id = Id..

Without preparing the data stream prior, the assumptions may fail. Use this to your power, and save time by letting ET1’s Joiner Node assume the correct column for you.

Hint; make it easier by preparing your column headers before using the Joiner Node by using the Column Renamer Node. This will help you save time while using ET1.

How to use Joiner in ET1

  • Connect table1
  • Connect table2
  • Pick type inner join or left* join

Right join is possible by swapping which table you connect to the Joiner node first. This order of operation is considered, and by adjusting what connects to this node first – you’re able to right join. You’re simple using the left join and the understanding of what you just read.

Type: The style of join. Today, we only have inner and left join.

Append Fields with ET1’s Joiner

Using ET1’s Joiner Node

The Joiner Node is the tool for joining data at a row-level, it removes complexities when joining data, and these row-level relationships are likely the ‘key’ we need to use the ET1’s Joiner Node.

Goal, join our data to see if we need more inventory.

Problem, the data is broken into many different tables.

Use case: Purchase data and inventory data can be joined, lets break it down.

Purchase data csv.

ID,Date,Product,Quantity,Price,Total
1,2024-01-01,Widget A,10,15.50,155.00
2,2024-01-02,Gadget B,5,25.00,125.00
3,2024-01-03,Tool C,8,12.75,102.00
4,2024-01-04,Device D,3,45.20,135.60
5,2024-01-05,Accessory E,15,8.99,134.85
6,2024-01-06,Widget A,7,15.50,108.50
7,2024-01-07,Gadget B,12,25.00,300.00
8,2024-01-08,Tool C,6,12.75,76.50
9,2024-01-09,Device D,9,45.20,406.80
10,2024-01-10,Accessory E,20,8.99,179.80

Inventory data csv.

ID,Product,Quantity,Location,Supplier,Last_Updated,Unit_Cost,Min_Stock
1,Widget A,93,Warehouse A,Supplier X,2024-01-01,15.50,50
2,Gadget B,20,Warehouse B,Supplier Y,2024-01-02,25.00,25
3,Tool C,122,Warehouse A,Supplier X,2024-01-03,12.75,40
4,Device D,4,Warehouse C,Supplier Z,2024-01-04,45.20,15
5,Accessory E,300,Warehouse B,Supplier Y,2024-01-05,8.99,100
6,Widget A,120,Warehouse A,Supplier X,2024-01-06,15.50,50
7,Gadget B,60,Warehouse B,Supplier Y,2024-01-07,25.00,25
8,Tool C,180,Warehouse A,Supplier X,2024-01-08,12.75,40
9,Device D,30,Warehouse C,Supplier Z,2024-01-09,45.20,15
10,Accessory E,250,Warehouse B,Supplier Y,2024-01-10,8.99,100

In this example we need to aggregate our data (Aggregation Node) and group by in ET1.

While analyzing this request, I found the data has duplicate entries on the column Product. Product has a relationship between tables. However we need the tables to be grouped, or we will be creating a many-to-many join.

Here’s how our Inventory data will look after we group by Quantity, and rename our header to Inventory. 

Product,Inventory
Widget A,213
Gadget B,80
Tool C,302
Device D,34
Accessory E,550

A quick overview of our entire process in ET1, joining two tables together, and understanding inventory levels VS what was sold.

A close up view of the Joiner Node, setup in this process captured above.

Thanks for learning more about ET1 and know if you have any questions… Please contact us. We would love to hear about your use cases.

Return to ET1 Overview to learn more.