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Clickhouse Queries

Overview​

Clickhouse is used for observability in LangDB. It provides high-performance analytics capabilities that allow us to track and analyze system behavior, performance metrics, and user activities across the platform.

Table Schemas​

Traces Table​

The following create query represents thetracestable that stores distributed tracing information of Langdb AI Gateway.

CREATE TABLE IF NOT EXISTS langdb.traces
(
    trace_id        UUID,
    span_id         UInt64,
    parent_span_id  UInt64,
    operation_name  LowCardinality(String),
    kind            String,
    start_time_us   UInt64,
    finish_time_us  UInt64,
    finish_date     Date,
    attribute       Map(String, String),
    tenant_id       Nullable(String),
    project_id      String,
    thread_id       String,
    tags            Map(String, String),
    parent_trace_id Nullable(UUID),
    run_id          Nullable(UUID)
)
ENGINE = MergeTree
ORDER BY (finish_date, finish_time_us, trace_id)
SETTINGS index_granularity = 8192;

-- Add bloom filter index for thread_id
ALTER TABLE langdb.traces ADD INDEX idx_thread_id thread_id TYPE bloom_filter GRANULARITY 4;

-- Add composite index for tenant_id, project_id, and operation_name
ALTER TABLE langdb.traces ADD INDEX idx_tenant_projec

Common Filters​

  • thread_id field with its dedicated bloom filter index allows for efficient filtering of traces based on specific execution threads.
  • The run_id field enables filtering and grouping traces by specific execution runs.