clickhouseexporter

package module

v0.72.0 Latest Latest Go to latest Published: Feb 22, 2023 License: Apache-2.0 Imports: 20 Imported by: 5

README ¶

ClickHouse Exporter

Status
Stability	alpha
Supported pipeline types	traces, logs, metrics
Distributions	contrib

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.

User Cases

Use Grafana Clickhouse datasource or vertamedia-clickhouse-datasource to make dashboard. Support time-series graph, table and logs.
Analyze logs via powerful clickhouse SQL.

Logs

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;

Traces

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

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.

Performance Guide

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.

Configuration options

The following settings are required:

endpoint (no default): The ClickHouse server endpoint, support multi host, for example: tcp protocol tcp://ip1:port,ip2:port http protocol http://ip:port,ip2:port

The following settings can be optionally configured:

username (default = ): The authentication username.
password (default = ): The authentication password.
ttl_days (default = 0): The data time-to-live in days, 0 means no ttl.
database (default = otel): The database name.
connection_params (default = {}). Params is the extra connection parameters with map format. for example compression/dial_timeout.
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.
timeout (default = 5s): The timeout for every attempt to send data to the backend.
sending_queue
- queue_size (default = 5000): 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

Example

receivers:
  examplereceiver:
processors:
  batch:
    timeout: 5s
    send_batch_size: 100000
exporters:
  clickhouse:
    endpoint: tcp://127.0.0.1:9000
    database: otel
    ttl_days: 3
    logs_table: otel_logs
    traces_table: otel_traces
    metrics_table: 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 ]

Schema

Logs

CREATE TABLE otel_logs
(
    `Timestamp`      DateTime64(9) CODEC (Delta, ZSTD(1)),
    `TraceId`        String CODEC (ZSTD(1)),
    `SpanId`         String CODEC (ZSTD(1)),
    `TraceFlags`     UInt32 CODEC (ZSTD(1)),
    `SeverityText` LowCardinality(String) CODEC (ZSTD(1)),
    `SeverityNumber` Int32 CODEC (ZSTD(1)),
    `ServiceName` LowCardinality(String) CODEC (ZSTD(1)),
    `Body`           String CODEC (ZSTD(1)),
    `ResourceAttributes` Map(LowCardinality(String), String) CODEC (ZSTD(1)),
    `LogAttributes` Map(LowCardinality(String), String) CODEC (ZSTD(1)),
    INDEX idx_trace_id TraceId TYPE bloom_filter(0.001) GRANULARITY 1,
    INDEX idx_res_attr_key mapKeys(ResourceAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_res_attr_value mapValues(ResourceAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_log_attr_key mapKeys(LogAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_log_attr_value mapValues(LogAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_body Body TYPE tokenbf_v1(32768, 3, 0) GRANULARITY 1
)
    ENGINE = MergeTree
        PARTITION BY toDate(Timestamp)
        ORDER BY (ServiceName, SeverityText, toUnixTimestamp(Timestamp), TraceId)
        TTL toDateTime(Timestamp) + toIntervalDay(3)
        SETTINGS index_granularity = 8192, ttl_only_drop_parts = 1;

Traces

CREATE TABLE otel.otel_traces
(
    `Timestamp`     DateTime64(9) CODEC (Delta(8), ZSTD(1)),
    `TraceId`       String CODEC (ZSTD(1)),
    `SpanId`        String CODEC (ZSTD(1)),
    `ParentSpanId`  String CODEC (ZSTD(1)),
    `TraceState`    String CODEC (ZSTD(1)),
    `SpanName` LowCardinality(String) CODEC (ZSTD(1)),
    `SpanKind` LowCardinality(String) CODEC (ZSTD(1)),
    `ServiceName` LowCardinality(String) CODEC (ZSTD(1)),
    `ResourceAttributes` Map(LowCardinality(String), String) CODEC (ZSTD(1)),
    `SpanAttributes` Map(LowCardinality(String), String) CODEC (ZSTD(1)),
    `Duration`      Int64 CODEC (ZSTD(1)),
    `StatusCode` LowCardinality(String) CODEC (ZSTD(1)),
    `StatusMessage` String CODEC (ZSTD(1)),
    `Events` Nested (
        `Timestamp` DateTime64(9),
        `Name` LowCardinality(String),
        `Attributes` Map(LowCardinality(String), String)
        ) CODEC(ZSTD(1)),
    `Links` Nested (
        `TraceId` String,
        `SpanId` String,
        `TraceState` String,
        `Attributes` Map(LowCardinality(String), String)
    ) CODEC(ZSTD(1)),
    INDEX idx_trace_id TraceId TYPE bloom_filter(0.001) GRANULARITY 1,
    INDEX idx_res_attr_key mapKeys(ResourceAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_res_attr_value mapValues(ResourceAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_span_attr_key mapKeys(SpanAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_span_attr_value mapValues(SpanAttributes) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_duration Duration TYPE minmax GRANULARITY 1
)
    ENGINE = MergeTree
        PARTITION BY toDate(Timestamp)
        ORDER BY (ServiceName, SpanName, toUnixTimestamp(Timestamp), TraceId)
        TTL toDateTime(Timestamp) + toIntervalDay(3)
        SETTINGS index_granularity = 8192, ttl_only_drop_parts = 1;

CREATE TABLE otel_traces_trace_id_ts
(
    `TraceId` String CODEC (ZSTD(1)),
    `Start`   DateTime CODEC (ZSTD(1)),
    `End`     DateTime CODEC (ZSTD(1)),
    INDEX idx_trace_id TraceId TYPE bloom_filter(0.01) GRANULARITY 1
)
    ENGINE = MergeTree
        ORDER BY (TraceId, toUnixTimestamp(Start))
        TTL toDateTime(Start) + toIntervalDay(3)
        SETTINGS index_granularity = 8192;

CREATE MATERIALIZED VIEW otel.otel_traces_trace_id_ts_mv TO otel.otel_traces_trace_id_ts
AS
SELECT TraceId,
       min(toDateTime(Timestamp)) AS Start,
       max(toDateTime(Timestamp)) AS End
FROM otel.otel_traces
WHERE TraceId != ''
GROUP BY TraceId;

Metrics

Gauge

CREATE TABLE IF NOT EXISTS otel.otel_metrics_gauge (
    ResourceAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ResourceSchemaUrl String CODEC(ZSTD(1)),
    ScopeName String CODEC(ZSTD(1)),
    ScopeVersion String CODEC(ZSTD(1)),
    ScopeAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ScopeDroppedAttrCount UInt32 CODEC(ZSTD(1)),
    ScopeSchemaUrl String CODEC(ZSTD(1)),
    MetricName String CODEC(ZSTD(1)),
    MetricDescription String CODEC(ZSTD(1)),
    MetricUnit String CODEC(ZSTD(1)),
    Attributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    StartTimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
    TimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
    Value Float64 CODEC(ZSTD(1)),
    Flags UInt32 CODEC(ZSTD(1)),
    Exemplars Nested (
		FilteredAttributes Map(LowCardinality(String), String),
		TimeUnix DateTime64(9),
		Value Float64,
		SpanId String,
		TraceId String
    ) CODEC(ZSTD(1))
) ENGINE MergeTree()
TTL toDateTime(TimeUnix) + toIntervalDay(3)
PARTITION BY toDate(TimeUnix)
ORDER BY (MetricName, Attributes, toUnixTimestamp64Nano(TimeUnix))
SETTINGS index_granularity=8192, ttl_only_drop_parts = 1;

Sum

CREATE TABLE IF NOT EXISTS otel.otel_metrics_sum (
    ResourceAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ResourceSchemaUrl String CODEC(ZSTD(1)),
    ScopeName String CODEC(ZSTD(1)),
    ScopeVersion String CODEC(ZSTD(1)),
    ScopeAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ScopeDroppedAttrCount UInt32 CODEC(ZSTD(1)),
    ScopeSchemaUrl String CODEC(ZSTD(1)),
    MetricName String CODEC(ZSTD(1)),
    MetricDescription String CODEC(ZSTD(1)),
    MetricUnit String CODEC(ZSTD(1)),
    Attributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
	StartTimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
	TimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
	Value Float64 CODEC(ZSTD(1)),
	Flags UInt32  CODEC(ZSTD(1)),
    Exemplars Nested (
		FilteredAttributes Map(LowCardinality(String), String),
		TimeUnix DateTime64(9),
		Value Float64,
		SpanId String,
		TraceId String
    ) CODEC(ZSTD(1)),
    AggTemp Int32 CODEC(ZSTD(1)),
	IsMonotonic Boolean CODEC(Delta, ZSTD(1))
) ENGINE MergeTree()
TTL toDateTime(TimeUnix) + toIntervalDay(3)
PARTITION BY toDate(TimeUnix)
ORDER BY (MetricName, Attributes, toUnixTimestamp64Nano(TimeUnix))
SETTINGS index_granularity=8192, ttl_only_drop_parts = 1;

Histogram

CREATE TABLE IF NOT EXISTS otel.otel_metrics_histogram (
    ResourceAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ResourceSchemaUrl String CODEC(ZSTD(1)),
    ScopeName String CODEC(ZSTD(1)),
    ScopeVersion String CODEC(ZSTD(1)),
    ScopeAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ScopeDroppedAttrCount UInt32 CODEC(ZSTD(1)),
    ScopeSchemaUrl String CODEC(ZSTD(1)),
    MetricName String CODEC(ZSTD(1)),
    MetricDescription String CODEC(ZSTD(1)),
    MetricUnit String CODEC(ZSTD(1)),
    Attributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
	StartTimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
	TimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
    Count Int64 CODEC(Delta, ZSTD(1)),
    Sum Float64 CODEC(ZSTD(1)),
    BucketCounts Array(UInt64) CODEC(ZSTD(1)),
    ExplicitBounds Array(Float64) CODEC(ZSTD(1)),
	Exemplars Nested (
		FilteredAttributes Map(LowCardinality(String), String),
		TimeUnix DateTime64(9),
		Value Float64,
		SpanId String,
		TraceId String
    ) CODEC(ZSTD(1)),
    Flags UInt32 CODEC(ZSTD(1)),
    Min Float64 CODEC(ZSTD(1)),
    Max Float64 CODEC(ZSTD(1))
) ENGINE MergeTree()
TTL toDateTime(TimeUnix) + toIntervalDay(3)
PARTITION BY toDate(TimeUnix)
ORDER BY (MetricName, Attributes, toUnixTimestamp64Nano(TimeUnix))
SETTINGS index_granularity=8192, ttl_only_drop_parts = 1;

Exponential histogram

CREATE TABLE IF NOT EXISTS otel.otel_metrics_exponential_histogram (
    ResourceAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ResourceSchemaUrl String CODEC(ZSTD(1)),
    ScopeName String CODEC(ZSTD(1)),
    ScopeVersion String CODEC(ZSTD(1)),
    ScopeAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ScopeDroppedAttrCount UInt32 CODEC(ZSTD(1)),
    ScopeSchemaUrl String CODEC(ZSTD(1)),
    MetricName String CODEC(ZSTD(1)),
    MetricDescription String CODEC(ZSTD(1)),
    MetricUnit String CODEC(ZSTD(1)),
    Attributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
	StartTimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
	TimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
    Count Int64 CODEC(Delta, ZSTD(1)),
    Sum Float64 CODEC(ZSTD(1)),
    Scale Int32 CODEC(ZSTD(1)),
    ZeroCount UInt64 CODEC(ZSTD(1)),
	PositiveOffset Int32 CODEC(ZSTD(1)),
	PositiveBucketCounts Array(UInt64) CODEC(ZSTD(1)),
	NegativeOffset Int32 CODEC(ZSTD(1)),
	NegativeBucketCounts Array(UInt64) CODEC(ZSTD(1)),
	Exemplars Nested (
		FilteredAttributes Map(LowCardinality(String), String),
		TimeUnix DateTime64(9),
		Value Float64,
		SpanId String,
		TraceId String
    ) CODEC(ZSTD(1)),
    Flags UInt32  CODEC(ZSTD(1)),
    Min Float64 CODEC(ZSTD(1)),
    Max Float64 CODEC(ZSTD(1))
) ENGINE MergeTree()
TTL toDateTime(TimeUnix) + toIntervalDay(3)
PARTITION BY toDate(TimeUnix)
ORDER BY (MetricName, Attributes, toUnixTimestamp64Nano(TimeUnix))
SETTINGS index_granularity=8192, ttl_only_drop_parts = 1;

Summary

CREATE TABLE IF NOT EXISTS otel.otel_metrics_summary (
    ResourceAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ResourceSchemaUrl String CODEC(ZSTD(1)),
    ScopeName String CODEC(ZSTD(1)),
    ScopeVersion String CODEC(ZSTD(1)),
    ScopeAttributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
    ScopeDroppedAttrCount UInt32 CODEC(ZSTD(1)),
    ScopeSchemaUrl String CODEC(ZSTD(1)),
    MetricName String CODEC(ZSTD(1)),
    MetricDescription String CODEC(ZSTD(1)),
    MetricUnit String CODEC(ZSTD(1)),
    Attributes Map(LowCardinality(String), String) CODEC(ZSTD(1)),
	StartTimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
	TimeUnix DateTime64(9) CODEC(Delta, ZSTD(1)),
    Count UInt64 CODEC(Delta, ZSTD(1)),
    Sum Float64 CODEC(ZSTD(1)),
    ValueAtQuantiles Nested(
		Quantile Float64,
		Value Float64
	) CODEC(ZSTD(1)),
    Flags UInt32  CODEC(ZSTD(1))
) ENGINE MergeTree()
TTL toDateTime(TimeUnix) + toIntervalDay(3)
PARTITION BY toDate(TimeUnix)
ORDER BY (MetricName, Attributes, toUnixTimestamp64Nano(TimeUnix))
SETTINGS index_granularity=8192, ttl_only_drop_parts = 1;

Documentation ¶

Index ¶

func NewFactory() exporter.Factory
type Config
- func (cfg *Config) Validate() (err error)
type QueueSettings

Constants ¶

This section is empty.

Variables ¶

This section is empty.

Functions ¶

func NewFactory ¶

func NewFactory() exporter.Factory

NewFactory creates a factory for Elastic exporter.

Types ¶

type Config ¶

type Config struct {
	exporterhelper.TimeoutSettings `mapstructure:",squash"`
	exporterhelper.RetrySettings   `mapstructure:"retry_on_failure"`
	// QueueSettings is a subset of exporterhelper.QueueSettings,
	// because only QueueSize is user-settable.
	QueueSettings QueueSettings `mapstructure:"sending_queue"`

	// Endpoint is the clickhouse server endpoint.
	// TCP endpoint: tcp://ip1:port,ip2:port
	// HTTP endpoint: http://ip:port,ip2:port
	Endpoint string `mapstructure:"endpoint"`
	// Username is the authentication username.
	Username string `mapstructure:"username"`
	// Username is the authentication password.
	Password string `mapstructure:"password"`
	// Database is the database name to export.
	Database string `mapstructure:"database"`
	// ConnectionParams is the extra connection parameters with map format. for example compression/dial_timeout
	ConnectionParams map[string]string `mapstructure:"connection_params"`
	// LogsTableName is the table name for logs. default is `otel_logs`.
	LogsTableName string `mapstructure:"logs_table_name"`
	// TracesTableName is the table name for logs. default is `otel_traces`.
	TracesTableName string `mapstructure:"traces_table_name"`
	// MetricsTableName is the table name for metrics. default is `otel_metrics`.
	MetricsTableName string `mapstructure:"metrics_table_name"`
	// TTLDays is The data time-to-live in days, 0 means no ttl.
	TTLDays uint `mapstructure:"ttl_days"`
}

Config defines configuration for Elastic exporter.

func (*Config) Validate ¶

func (cfg *Config) Validate() (err error)

Validate the clickhouse server configuration.

type QueueSettings ¶

type QueueSettings struct {
	// QueueSize set the length of the sending queue
	QueueSize int `mapstructure:"queue_size"`
}

QueueSettings is a subset of exporterhelper.QueueSettings.

Source Files ¶

View all Source files

Directories ¶

Path	Synopsis
internal

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