Monitoring ClickHouse Performance and Errors with Tracing

What is tracing?

Distributed tracingopen in new window allows to precisely pinpoint the problem in complex systems, especially those built using a microservices architecture.

Tracing allows to follow requests as they travel through distributed systems. You get a full context of what is different, what is broken, and which logs & errors are relevant.

What is OpenTelemetry?

OpenTelemetryopen in new window is an open source and vendor-neutral API for distributed tracingopen in new window (including logs and errors) and metricsopen in new window.

Otel specifies how to collect and export telemetry data in a vendor agnostic way. With OpenTelemetry, you can instrumentopen in new window your application once and then add or change vendors without changing the instrumentation, for example, many open source tracing toolsopen in new window already support OpenTelemetry.

chotel instrumentation

go-clickhouse supports tracing and metrics using OpenTelemetry API. OpenTelemetry is a vendor-neutral API for distributed traces and metrics. It specifies how to collect and send telemetry data to backend platforms. It means that you can instrument your application once and then add or change vendors (backends) as required.

go-clickhouse comes with an OpenTelemetry instrumentation called chotelopen in new window that is distributed as a separate module:

go get

To instrument go-clickhouse database, you need to add the hook provided by chotel:

import (

db := ch.Connect(ch.WithDatabase("test"))


Uptrace is an open-source APMopen in new window and a popular DataDog competitoropen in new window that supports distributed tracing, metrics, and logs. You can use it to monitor applications and set up automatic alerts to receive notifications via email, Slack, Telegram, and more.

You can install Uptraceopen in new window by downloading a DEB/RPM package or a pre-compiled binary.


Trace example

As expected, go-clickhouse creates spansopen in new window for processed queries and records any errors as they occur. Here is how the collected information is displayed at Uptrace UI:

clickhouse trace

You can find a runnable example at GitHubopen in new window.

ClickHouse spans

To trace the ClickHouse database, you can setup a materialized view to export spans from the system.opentelemetry_span_log tableopen in new window:

CREATE MATERIALIZED VIEW default.zipkin_spans
ENGINE = URL('<key><project_id>', 'JSONEachRow')
SETTINGS output_format_json_named_tuples_as_objects = 1,
    output_format_json_array_of_rows = 1 AS
    lower(hex(trace_id)) AS traceId,
    case when parent_span_id = 0 then '' else lower(hex(parent_span_id)) end AS parentId,
    lower(hex(span_id)) AS id,
    operation_name AS name,
    start_time_us AS timestamp,
    finish_time_us - start_time_us AS duration,
    cast(tuple('clickhouse'), 'Tuple(serviceName text)') AS localEndpoint,
    attribute AS tags
FROM system.opentelemetry_span_log

See ClickHouse documentationopen in new window for details.

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