Concatenate Multiple Tables

Combine data from multiple tables into a single result set using the readFile() function

Query

flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1@{ shape: doc, label: "Source or File" } result{{Result Set}} repo --> 1 1 --> result

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readFile("users_2024", "users_2025", "temp_users")

Introduction

The readFile() function can be used to read data from CSV files, lookup files and tables. When provided with multiple file or table names, it concatenates the data from all specified sources, combining them into a single result set.

In this example, the readFile() function is used to concatenate data from multiple lookup tables named users_2024, users_2025, and temp_users, combining all events into a single result set.

Example data in the lookup tables might look like this:

Table users_2024:

user_id	name	department	join_date
001	Alice Johnson	Engineering	2024-01-15
002	Bob Smith	Marketing	2024-03-22
003	Carol Davis	Sales	2024-06-10

Table users_2025:

user_id	name	department	join_date
004	David Wilson	Engineering	2025-01-08
005	Emma Brown	HR	2025-02-14
006	Frank Miller	Sales	2025-03-01

Table temp_users:

user_id	name	department	join_date
007	Grace Lee	Marketing	2025-07-20
008	Henry Taylor	Engineering	2025-08-15

Step-by-Step

Starting with the source repository events.
flowchart LR; %%{init: {"flowchart": {"defaultRenderer": "elk"}} }%% repo{{Events}} 1@{ shape: doc, label: "Source or File" } result{{Result Set}} repo --> 1 1 --> result style 1 fill:#ff0000,stroke-width:4px,stroke:#000;
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```
readFile("users_2024", "users_2025", "temp_users")
```
Reads and concatenates data from three lookup tables: users_2024, users_2025, and temp_users. The readFile() function processes each table in the order specified and combines all events into a single result set, with events from the first table appearing first, followed by events from subsequent tables.
Event Result set.

Summary and Results

The query is used to combine data from multiple lookup tables into a single unified event set by concatenating their contents.

This query is useful, for example, to merge historical data stored in separate yearly tables, combine data from different regional databases, or consolidate temporary and permanent datasets for comprehensive analysis.

Sample output from the incoming example data:

user_id	name	department	join_date
001	Alice Johnson	Engineering	2024-01-15
002	Bob Smith	Marketing	2024-03-22
003	Carol Davis	Sales	2024-06-10
004	David Wilson	Engineering	2025-01-08
005	Emma Brown	HR	2025-02-14
006	Frank Miller	Sales	2025-03-01
007	Grace Lee	Marketing	2025-07-20
008	Henry Taylor	Engineering	2025-08-15

Note that the tables could be different formats (field names and content), but typically the schemas would match which will make it easier to query and display in a widget.

The events appear in the output in the same order as the files are specified in the function call, with all events from the first table appearing before any events from the second table, and so on.

Examples Library