SQL Editor overview
The SQL Editor is where you run queries on your dataset and get results. The main components of the SQL Editor are highlighted below:

Database explorer
Database explorer panel is used to explore your database objects, which includes namespaces, tables, views, and their columns (even complex columns), and partitions.
To view database objects, expand a database. Each object in the database explorer has a corresponding options menu .
The options menu lets you:
- Place the query
SELECT * FROM database.table LIMIT 100;
(tables and views only) - Place the query
DESC EXTENDED database.table;
(tables and views only) - Copy of object name
Copy

Worksheets
The worksheet is a document that stores all SQL statements.
Welcome worksheet - This worksheet was created for you when you first started SQL Editor. When you make changes to a worksheet it will save automatically after a delay of 5 seconds.
In the Worksheet panel, you can:
- Open a worksheet in the SQL editor
- Rename a worksheet
- Duplicate a worksheet
- Delete a worksheet
- Search your set of worksheets by name

Querying data
Before running a query you must select a running Lakehouse and Database.
To select (or change) the Running lakehouse for a worksheet, click the Select Lakehouse
dropdown in the upper-right corner of the query editor.
To select (or change) the current database for a worksheet, click the Select Database
dropdown in the upper-right corner of the query editor.
Write query
As you enter your script in the query editor, the autocomplete feature suggests:
- Query syntax keywords such as SQL functions or aliases.
- Values that match table or column names within a schema.
IOMETE tracks table aliases and suggests them as autocomplete options. For example, if you execute a query using cities as c
or cities c
as an alias, the next time you type c
, the autocomplete feature suggests the alias as an option.
If you want to open autocomplete, use the given shortcut:
- ⌘+Space (Mac)
- Ctrl+Space (Windows)

Run query
Currently, you can run only a single query
Using the query editor, run a single query as follows:
- Click
Run
button - ⌘+Enter (Mac)
- Ctrl+Enter (Windows)
Query Result
Up to 10,000 rows can be displayed in the results.
The query result includes the following information:
- The duration of the query execution.
- The status of the query execution.
- The number of rows.
- Result table

Download or Share Results
To download your results as a .csv file, click the
button.To share your results as a link, click the
button to copy the link.Results as CHART
To show result as chart click the
button.
You can customize the chart using filtering options on the right side.
Using Sort and Filters
You can use column sorting and filtering. Hover over columns to view the filter icon and click. When clicking the filter icon, you can see available filters.


Query Histories
When you run a query, it is tracked as a new item in the SQL history. You can use the SQL history to go back to previous queries so that you can see query results and open queries in the active worksheet.

Query Variables
Use variables in your SQL queries by wrapping them in double curly braces, like {{id}}
.
It is necessary to declare a variable before using it. Specifying an expression for the initial value for the variable.
After declaring the variable, you can see it in autocomplete.

IOMETE AI Assistant
To open IOMETE AI Assistant click the
button.
You can easily paste the SQL code using the
button from the chat into our editor, and then run it.IOMETE SQL AI assistant can help users in many different ways, some of which are:
Helping write queries: It creates SQL queries for users who aren't familiar with SQL or want quicker query writing.
Fixing errors: It finds and fixes mistakes in SQL queries instantly, so users can write accurate queries.
Speeding up queries: It suggests ways to make SQL queries run faster and more efficiently.
Quick suggestions: It predicts and suggests SQL words, namespaces, tables and more as users type, cutting down on errors and speeding up writing.
Exploring data: It makes it easier to understand databases by showing how tables relate and what information they hold.