---
title: DataPrime query
description: Write, format, and run DataPrime queries in Explore, convert Lucene queries, and work with raw, aggregated, and charted results.
url: https://coralogix.com/docs/user-guides/data_exploration/dataprime/
product: dataengine
feature: DataPrime Language
feature_id: dataprime-language
feature_identifier: dataengine/dataprime-language
last_updated: '2026-11-12'
---

# DataPrime query

**DataPrime** is the second query syntax in Explore, alongside **Builder**. Use it when you need the precision and flexibility of DataPrime's pipeline syntax for filtering, transforming, and aggregating log data at scale.

[![DataPrime mode](/docs/assets/images/dataprime-mode-d2517ffd5d0aa37ed80983f194bbe435.webp)](https://coralogix.com/docs/assets/images/dataprime-mode-d2517ffd5d0aa37ed80983f194bbe435.webp) *DataPrime mode*

## Switch to DataPrime

Switch to DataPrime from within Explore:

1. Open **Explore**.
2. In the query bar, toggle the syntax switch from **Builder** to **DataPrime**.

The search bar is replaced by the DataPrime query editor. The editor opens pre-populated with `source <dataset>` for the active dataset, or with a translated form of your current Lucene query. Your time range and dataset selection are preserved.

In DataPrime mode, **Run** and the clear (**X**) control sit inside the query field itself, at its bottom right, and move down with the field as your query grows past a single line. This reclaims the row that **Builder** mode uses for its clause chips. One consequence is that the chart show and hide toggle from that row isn't available in DataPrime mode: collapse or restore the chart from the chevron in its own header instead. See [Collapse the chart](https://coralogix.com/docs/user-guides/data_exploration/timeseries-chart.md#collapse-the-chart).

## Write a query

DataPrime uses a pipeline syntax: each step in the pipeline transforms or filters the data passed from the previous step. Start with a `source` statement, then chain operators with the `|` pipe character.

Example query. Filter for errors and group by subsystem:

```
source logs

| filter $m.severity == ERROR

| groupby $l.subsystemname aggregate count() as error_count

| orderby $d.error_count desc

| limit 5
```

This query:

1. Sources data from the `logs` dataset.
2. Filters to log entries where severity is `ERROR` (a Coralogix metadata enum, no quotes).
3. Groups the filtered logs by subsystem and counts them.
4. Orders results by error count, highest first. Reference the alias `error_count` as `$d.error_count`. It lives in the user-data namespace after the aggregation.
5. Limits results to the top 5 subsystems.

Spans use the same pipeline syntax with `source spans`. For example, top 5 services by average span duration:

```
source spans

| groupby $l.serviceName aggregate avg($m.duration) as avg_duration

| orderby $d.avg_duration desc

| limit 5
```

Use `$d` for user-data fields, `$m` for Coralogix metadata (severity, applicationname, subsystemname, timestamp, duration), and `$l` for user labels and OpenTelemetry semantic-convention attributes (serviceName, operationName, and so on). See the [DataPrime documentation](https://coralogix.com/docs/dataprime/introduction/welcome-to-the-dataprime-reference.md) for the full namespace reference.

### Format, copy, or reset the query

While the DataPrime editor holds a query, three actions appear at the bottom right of the query bar, next to **Run**:

* **Format query**: lays the query out with one pipeline stage per line, which makes long single-line queries easier to read. A `|` inside a string, a regex, or a comment is left alone, and a query that doesn't parse is left unchanged. Undo reverts the formatting in one step. You can also press **Shift + Option + F** (Mac) or **Shift + Alt + F** (Windows and Linux); see [Explore keyboard shortcuts](https://coralogix.com/docs/user-guides/data_exploration/keyboard-shortcuts.md).
* **Copy query**: copies the query text exactly as it appears in the editor.
* **Reset query**: clears the editor.

## Filter with the Fields panel

The [Fields panel](https://coralogix.com/docs/user-guides/data_exploration/fields.md#filter-in-dataprime-mode) works in DataPrime mode. Expand a field to see its values, then select values or field actions to filter, add columns, or group by. Your selections are written into the query as `filter` clauses at the start of the pipeline, and the panel stays in sync as you edit the query directly. Value counts and distributions work here too. A query that reads from more than one source, such as several datasets or teams, can't be filtered from the panel, though its value counts still load.

## Generate a query with Olly

In DataPrime mode, describe what you're looking for in plain language and let Olly write the query for you. The AI query prompt sits above the DataPrime editor.

[![Generate a DataPrime query with Olly](/docs/assets/images/dataprime-assistance-afa0d73ca652299fb999005b2814bb9c.webp)](https://coralogix.com/docs/assets/images/dataprime-assistance-afa0d73ca652299fb999005b2814bb9c.webp)

1. In DataPrime mode, enter your request in the prompt box (**Ask Olly to write a query…**).
2. Select **Generate query** or press Enter. Olly generates a DataPrime query for the dataset you've selected (logs, spans, or any other dataset you query in Explore) and places it in the editor.
3. Review and adjust the query, then run it. If your request implies a time range (for example, "errors in the last 3 hours") Olly sets the time picker to that window when you run the query.

To hide or show the prompt, open the query builder's actions menu and select **Hide Prompt AI** or **Show Prompt AI**.

Generating a query consumes AI units; writing DataPrime queries yourself is always free. For enablement, more examples, and limitations, see [DataPrime query assistance](https://coralogix.com/docs/user-guides/olly/dataprime-query-assistance.md).

## DataPrime cheat sheet

Explore includes a built-in DataPrime reference so you can look up syntax without leaving the query editor. When DataPrime is the active syntax, select the help icon in the query bar to open the cheat sheet in a panel beside the results. The help icon appears only in DataPrime mode.

[![DataPrime cheat sheet](/docs/assets/images/dp-helper-a3785af9bdacfc88b5878098aba19aea.webp)](https://coralogix.com/docs/assets/images/dp-helper-a3785af9bdacfc88b5878098aba19aea.webp)

Use the cheat sheet to:

* **Browse by section**: select a section from the outline dropdown to jump to it. The dropdown tracks the section you're reading as you scroll.
* **Search**: enter a term in the search box to highlight matches across the reference and move between them.
* **Copy an example**: hover over a code snippet and select the copy button, then paste the query into the editor.

Select the close button, or the help icon again, to hide the panel.

## Lucene to DataPrime

Switching from **Builder** to **DataPrime** seeds the editor with a translated form of your Lucene query when one exists, otherwise with `source <dataset>` for the active dataset. The translation is structural, not semantic. Review the result and adjust as needed.

DataPrime field references use a prefix notation: `$d` for log data fields, `$m` for metadata fields, and `$l` for user labels.

A confirmation dialog only appears when you leave a Builder-only context (Templates, Traces, Flows, or RED metrics). Its buttons are **Cancel**, **Open DataPrime in new tab**, and **Convert to DataPrime**. For a normal Logs tab in Lucene, the toggle switches without confirmation.

## Switch back to the query builder

If you switch from DataPrime back to **Builder** without editing the DataPrime expression, Explore restores your original Builder filters, **Grouped by**, and **Aggregation** as they were before the switch. Your Builder state remains intact.

If you edit the DataPrime expression and then switch back, Explore tries to translate it into Builder. Simple queries translate cleanly: a `source` on its own, or a `source` combined with `filter`, `group by`, and `aggregation` clauses. When the query translates, Explore converts it and opens the equivalent query in Builder, with no query loss.

If the query uses anything Builder can't represent (other operators or functions, more than one source, and so on), Explore can't translate it and opens a **Switch to Lucene** dialog with three options:

* **Discard and switch**: the red link at the left of the dialog. Switches the current tab to Builder on the dataset's default empty state, discarding the DataPrime query.
* **Go back**: the secondary button. Keeps you in DataPrime with your query intact.
* **Open Lucene in new tab**: the main button. Keeps the DataPrime query in the current tab and opens a fresh, empty Builder tab. It's unavailable once you have the maximum of 10 tabs open.

The saved Builder state lives in the current tab only. Refresh the page or open a new tab to clear it.

## Work with results

DataPrime results appear in a single **Results** tab below the query editor. The tab header shows the row count next to its name (for example, `Results 5`).

[![Results table](/docs/assets/images/resutls-table-6994f649ab9e3580b1192089700cc615.webp)](https://coralogix.com/docs/assets/images/resutls-table-6994f649ab9e3580b1192089700cc615.webp)

On the **spans** dataset, the [Highlights](https://coralogix.com/docs/user-guides/data_exploration/spans/highlights-tab.md) tab is the one Builder-mode view preserved when you switch to DataPrime, running a DataPrime query while on the Highlights tab keeps you on Highlights instead of dropping you to Results. The other spans views (Spans, Traces, Flows, RED metrics) collapse into the single Results tab.

### Raw results

Queries without a `groupby` operator return individual log records, one row per matching log. Each row is expandable in place; expand a row to inspect its fields. Use the column headers to sort by any column.

### Aggregated results

Queries with a `groupby` operator return one row per group. Columns include each grouping field and the aliased aggregation outputs, for example, `subsystemname` and `error_count` from the example above.

Aggregated rows don't expand. When a column holds an array or object, for example from `collect($d)`, hover the cell and select **Show full content** to read the whole value, then **Show less** to return to your row size.

[![A DataPrime groupby true collect($d) result: hovering the collected cell shows Copy content and Show full content, which grows the row to the whole value, with no Visualize as selector](/docs/assets/images/dataprime-full-content-eb451270584ce7332b39be939b48e7a6.webp)](https://coralogix.com/docs/assets/images/dataprime-full-content-eb451270584ce7332b39be939b48e7a6.webp)

### Results from multiple sources

When the `source` statement lists several datasets, or datasets from more than one team (with the `teamId` parameter), the Results tab returns their combined rows. Add `groupby teamId()` to get one row per team. See [Query across teams](https://coralogix.com/docs/user-guides/data_exploration/datasets.md#query-across-teams).

[![DataPrime Results tab for a query grouped by teamId(), showing one row per team with its count](data:image/webp;base64,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)](data:image/webp;base64,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)

## Chart visualizations

On a time-based dataset, DataPrime renders a count-over-time chart above the Results table for non-aggregation queries. The same time-series chart Builder shows. The chart plots the record count across your selected time range.

[![DataPrime source spans query with the Count Spans over time chart above the Results table, whose header has no Visualize as selector](/docs/assets/images/dataprime-chart-a93d87c12ceb8e3409a5d496515a14a2.webp)](https://coralogix.com/docs/assets/images/dataprime-chart-a93d87c12ceb8e3409a5d496515a14a2.webp)

Aggregation queries (those with a `groupby` or `aggregate` operator) return straight to the results table without the chart.

To show aggregated results as a chart instead of a table, use the **Visualize as** selector in the results header. The selector appears only when the results can be charted, so raw results and table-only results, such as `groupby true collect($d)`, don't show it.

## Related resources

* [DataPrime syntax reference](https://coralogix.com/docs/dataprime/introduction/welcome-to-the-dataprime-reference.md)
* [Filter with fields](https://coralogix.com/docs/user-guides/data_exploration/fields.md)
* [Query Builder](https://coralogix.com/docs/user-guides/data_exploration/query_builder.md)
* [Overview tab](https://coralogix.com/docs/user-guides/data_exploration/overview-tab.md)
* [Errors and warnings](https://coralogix.com/docs/user-guides/data_exploration/errors-and-warnings.md)

## Next steps

Plot DataPrime results over time with the [time-series chart](https://coralogix.com/docs/user-guides/data_exploration/timeseries-chart.md).