liubing 64981805a5 marshal | 11 месяцев назад | |
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.. | ||
example | 1 год назад | |
internal | 1 год назад | |
testdata | 1 год назад | |
Makefile | 2 лет назад | |
README.md | 1 год назад | |
config.go | 1 год назад | |
config_test.go | 1 год назад | |
exporter_logs.go | 1 год назад | |
exporter_logs_test.go | 1 год назад | |
exporter_metrics.go | 1 год назад | |
exporter_metrics_test.go | 1 год назад | |
exporter_traces.go | 11 месяцев назад | |
exporter_traces_test.go | 1 год назад | |
factory.go | 1 год назад | |
factory_test.go | 1 год назад | |
go.mod | 1 год назад | |
go.sum | 1 год назад | |
metadata.yaml | 1 год назад |
Status | |
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Stability | alpha: traces, metrics, logs |
Distributions | contrib |
Issues | |
Code Owners | @hanjm, @dmitryax, @Frapschen |
This exporter supports sending OpenTelemetry data to ClickHouse.
ClickHouse is an open-source, high performance columnar OLAP database management system for real-time analytics using SQL. Throughput can be measured in rows per second or megabytes per second. If the data is placed in the page cache, a query that is not too complex is processed on modern hardware at a speed of approximately 2-10 GB/s of uncompressed data on a single server. If 10 bytes of columns are extracted, the speed is expected to be around 100-200 million rows per second.
Note: Always add batch-processor to collector pipeline, as ClickHouse document says:
We recommend inserting data in packets of at least 1000 rows, or no more than a single request per second. When inserting to a MergeTree table from a tab-separated dump, the insertion speed can be from 50 to 200 MB/s.
Use Grafana Clickhouse datasource or vertamedia-clickhouse-datasource to make dashboard. Support time-series graph, table and logs.
Analyze logs via powerful clickhouse SQL.
Get log severity count time series.
SELECT toDateTime(toStartOfInterval(Timestamp, INTERVAL 60 second)) as time, SeverityText, count() as count
FROM otel_logs
WHERE time >= NOW() - INTERVAL 1 HOUR
GROUP BY SeverityText, time
ORDER BY time;
Find any log.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with specific service.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE ServiceName = 'clickhouse-exporter'
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with specific attribute.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE LogAttributes['container_name'] = '/example_flog_1'
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with body contain string token.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE hasToken(Body, 'http')
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with body contain string.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE Body like '%http%'
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with body regexp match string.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE match(Body, 'http')
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find log with body json extract.
SELECT Timestamp as log_time, Body
FROM otel_logs
WHERE JSONExtractFloat(Body, 'bytes') > 1000
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find spans with specific attribute.
SELECT Timestamp as log_time,
TraceId,
SpanId,
ParentSpanId,
SpanName,
SpanKind,
ServiceName,
Duration,
StatusCode,
StatusMessage,
toString(SpanAttributes),
toString(ResourceAttributes),
toString(Events.Name),
toString(Links.TraceId)
FROM otel_traces
WHERE ServiceName = 'clickhouse-exporter'
AND SpanAttributes['peer.service'] = 'tracegen-server'
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find traces with traceID (using time primary index and TraceID skip index).
WITH
'391dae938234560b16bb63f51501cb6f' as trace_id,
(SELECT min(Start) FROM otel_traces_trace_id_ts WHERE TraceId = trace_id) as start,
(SELECT max(End) + 1 FROM otel_traces_trace_id_ts WHERE TraceId = trace_id) as end
SELECT Timestamp as log_time,
TraceId,
SpanId,
ParentSpanId,
SpanName,
SpanKind,
ServiceName,
Duration,
StatusCode,
StatusMessage,
toString(SpanAttributes),
toString(ResourceAttributes),
toString(Events.Name),
toString(Links.TraceId)
FROM otel_traces
WHERE TraceId = trace_id
AND Timestamp >= start
AND Timestamp <= end
Limit 100;
Find spans is error.
SELECT Timestamp as log_time,
TraceId,
SpanId,
ParentSpanId,
SpanName,
SpanKind,
ServiceName,
Duration,
StatusCode,
StatusMessage,
toString(SpanAttributes),
toString(ResourceAttributes),
toString(Events.Name),
toString(Links.TraceId)
FROM otel_traces
WHERE ServiceName = 'clickhouse-exporter'
AND StatusCode = 'STATUS_CODE_ERROR'
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Find slow spans.
SELECT Timestamp as log_time,
TraceId,
SpanId,
ParentSpanId,
SpanName,
SpanKind,
ServiceName,
Duration,
StatusCode,
StatusMessage,
toString(SpanAttributes),
toString(ResourceAttributes),
toString(Events.Name),
toString(Links.TraceId)
FROM otel_traces
WHERE ServiceName = 'clickhouse-exporter'
AND Duration > 1 * 1e9
AND Timestamp >= NOW() - INTERVAL 1 HOUR
Limit 100;
Metrics data is stored in different clickhouse tables depending on their types. The tables will have a suffix to distinguish which type of metrics data is stored.
Metrics Type | Metrics Table |
---|---|
sum | _sum |
gauge | _gauge |
histogram | _histogram |
exponential histogram | _exponential_histogram |
summary | _summary |
Before you make a metrics query, you need to know the type of metric you wish to use. If your metrics come from Prometheus(or someone else uses OpenMetrics protocol), you also need to know the compatibility between Prometheus(OpenMetrics) and OTLP Metrics.
Find a sum metrics with name
select TimeUnix,MetricName,Attributes,Value from otel_metrics_sum
where MetricName='calls_total' limit 100
Find a sum metrics with name, attribute.
select TimeUnix,MetricName,Attributes,Value from otel_metrics_sum
where MetricName='calls_total' and Attributes['service_name']='featureflagservice'
limit 100
The OTLP Metrics define two type value for one datapoint, clickhouse only use one value of float64 to store them.
A single ClickHouse instance with 32 CPU cores and 128 GB RAM can handle around 20 TB (20 Billion) logs per day, the data compression ratio is 7 ~ 11, the compressed data store in disk is 1.8 TB ~ 2.85 TB, add more clickhouse node to cluster can increase linearly.
The otel-collector with otlp receiver/batch processor/clickhouse tcp exporter
can process
around 40k/s logs entry per CPU cores, add more collector node can increase linearly.
The following settings are required:
endpoint
(no default): The ClickHouse server address, support multi host with port, for example:
tcp://addr1:port,tcp://addr2:port
or TLS tcp://addr1:port,addr2:port?secure=true
http://addr1:port,addr2:port
or https https://addr1:port,addr2:port
clickhouse://addr1:port,addr2:port
or TLS clickhouse://addr1:port,addr2:port?secure=true
Many other ClickHouse specific options can be configured through query parameters e.g. addr?dial_timeout=5s&compress=lz4
. For a full list of options see the ClickHouse driver documentation
Connection options:
username
(default = ): The authentication username.password
(default = ): The authentication password.ttl_days
(default = 0): Deprecated: Use 'ttl' instead. The data time-to-live in days, 0 means no ttl.ttl
(default = 0): The data time-to-live example 30m, 48h. Also, 0 means no ttl.database
(default = otel): The database name.connection_params
(default = {}). Params is the extra connection parameters with map format.ClickHouse tables:
logs_table_name
(default = otel_logs): The table name for logs.traces_table_name
(default = otel_traces): The table name for traces.metrics_table_name
(default = otel_metrics): The table name for metrics.Processing:
timeout
(default = 5s): The timeout for every attempt to send data to the backend.sending_queue
queue_size
(default = 1000): Maximum number of batches kept in memory before dropping data.retry_on_failure
enabled
(default = true)initial_interval
(default = 5s): The Time to wait after the first failure before retrying; ignored if enabled
is false
max_interval
(default = 30s): The upper bound on backoff; ignored if enabled
is false
max_elapsed_time
(default = 300s): The maximum amount of time spent trying to send a batch; ignored if enabled
is false
The exporter supports TLS. To enable TLS, you need to specify the secure=true
query parameter in the endpoint
URL or
use the https
scheme.
This example shows how to configure the exporter to send data to a ClickHouse server. It uses the native protocol without TLS. The exporter will create the database and tables if they don't exist. The data is stored for 72 hours (3 days).
receivers:
examplereceiver:
processors:
batch:
timeout: 5s
send_batch_size: 100000
exporters:
clickhouse:
endpoint: tcp://127.0.0.1:9000?dial_timeout=10s&compress=lz4
database: otel
ttl: 72h
logs_table_name: otel_logs
traces_table_name: otel_traces
metrics_table_name: otel_metrics
timeout: 5s
retry_on_failure:
enabled: true
initial_interval: 5s
max_interval: 30s
max_elapsed_time: 300s
service:
pipelines:
logs:
receivers: [ examplereceiver ]
processors: [ batch ]
exporters: [ clickhouse ]