SQL editor

The SQL editor runs read-only ClickHouse SQL over your project’s data. Use it for questions the Logs filters can’t answer, such as cost per model or error rate per customer.

Run a query

1

Open the editor

Go to Observability › SQL editor. A new tab offers Start from a template: Cost by day, Top models, Error rate, and Traces overview. Pick one, or write your own.

2

Write the SQL

The Tables panel on the right lists every table and column. Click a column to insert it, or use Preview rows on a table. The editor also autocompletes tables, columns, and functions.

This query returns cost and latency per model for the last 7 days:

SELECT
    model,
    count(*) AS requests,
    round(sum(cost), 2) AS total_cost,
    round(avg(latency), 2) AS avg_latency
FROM logs
WHERE timestamp >= now() - INTERVAL 7 DAY
GROUP BY model
ORDER BY total_cost DESC
LIMIT 20

3

Run it

Click Run or press ⌘ Enter (Ctrl Enter on Windows and Linux). If the tab has several statements, it runs the one at the cursor. If you select text, it runs the selection.

The results show below the editor, with the row count, duration, and time. Click a column header to sort, or click Inspect row to read one row in full.

Always filter on the table’s time column, such as timestamp for logs. Queries without one scan more data and are more likely to time out.

Save and manage queries

Every tab is a saved query. Your SQL saves as you type or run, and the editor shows Saved when it’s done.

• New query: click the button after the last tab. New queries are named Untitled query.
• Rename: hover the open tab and click the pencil.
• Delete: click × on the tab, then confirm. This deletes the saved query for good.

Chart the results

When the result has a time column and a numeric column, click Chart to plot it. Click Add to dashboard to put the chart on a Metrics view.

This query produces the chart above:

SELECT
    toDate(timestamp) AS day,
    sum(cost) AS total_cost
FROM logs
WHERE timestamp >= now() - INTERVAL 14 DAY
GROUP BY day
ORDER BY day

Export results

Click Export, or press E, and choose Export as CSV or Export as JSONL. The export reruns your query in the background, so it isn’t limited to the rows on screen. When it’s done, download it from the dialog or from Settings › Exports.

Copy rows as TSV, in the same menu, copies the rows shown.

Tables

The Rollups group in the Tables panel has pre-aggregated tables for faster charts over long ranges: log_metrics, log_metrics_hourly, latency_quantiles_minute, latency_quantiles_hourly, and metadata_metrics.

Useful logs columns include model, provider_id, cost, latency, prompt_tokens, completion_tokens, status, customer_identifier, thread_identifier, and trace_unique_id. Read custom properties with metadata['key'].

More examples

Error rate by model, last 24 hours:

SELECT
    model,
    count(*) AS requests,
    round(countIf(status = 'failed') / count(*) * 100, 2) AS error_rate_pct
FROM logs
WHERE timestamp >= now() - INTERVAL 1 DAY
GROUP BY model
HAVING count(*) > 10
ORDER BY error_rate_pct DESC

Cost by a custom property, such as feature:

SELECT
    metadata['feature'] AS feature,
    count(*) AS requests,
    round(sum(cost), 2) AS total_cost
FROM logs
WHERE timestamp >= now() - INTERVAL 7 DAY
GROUP BY feature
ORDER BY total_cost DESC

Limits