Elasticsearch團隊自研的TimeStream時序引擎增強外掛程式,支援使用PromQL查詢Elasticsearch資料,無縫對接Prometheus+Grafana。本文介紹如何基於Elasticsearch TimeStream使用Prometheus整合介面。
背景資訊
TimeStream是Elasticsearch團隊自研,並結合Elastic社區時序類產品特性共建的時序引擎。Elasticsearch提供的TimeStream時序增強功能外掛程式,最佳化了Elasticsearch在儲存指標資料方面的DSL(Domain-Specific Language)查詢複雜且慢以及儲存成本過高等問題。詳細資料請參見TimeStream時序增強引擎介紹。
前提條件
已建立Elasticsearch執行個體,且執行個體版本為通用商業版7.16及以上、核心版本為1.7.0及以上,或者執行個體版本為通用商業版7.10、核心版本為1.8.0及以上。具體操作請參見建立Elasticsearch執行個體。
Prometheus API說明
Prometheus API除了可以訪問通過Prometheus Remote Write方式寫入的資料,也可以訪問任意TimeStream索引。
Prometheus API支援去掉返回的指標和維度前尾碼關鍵字。如果使用預設的資料模型,指標首碼metric.會被去掉,維度首碼label.會被去掉。
{
"labels": {
"instance": "127.0.0.1:9114",
"job": "elasticsearch"
},
"metrics": {
"up": 0.0,
"scrape_samples_post_metric_relabeling": 0.0,
"scrape_samples_scraped": 0.0,
"scrape_duration_seconds": 4.45999E-4,
"scrape_series_added": 0.0
},
"@timestamp": "1655717638795"
}{
"status" : "success",
"data" : [
"__name__",
"instance",
"job"
]
}
{
"status" : "success",
"data" : {
"scrape_samples_post_metric_relabeling" : [
{
"type" : "gauge",
"help" : "",
"unit" : ""
}
],
"scrape_samples_scraped" : [
{
"type" : "gauge",
"help" : "",
"unit" : ""
}
],
"scrape_duration_seconds" : [
{
"type" : "gauge",
"help" : "",
"unit" : ""
}
],
"scrape_series_added" : [
{
"type" : "gauge",
"help" : "",
"unit" : ""
}
],
"up" : [
{
"type" : "gauge",
"help" : "",
"unit" : ""
}
]
}
}PUT _time_stream/{name}
{
"time_stream": {
"labels_fields": "@labels.*_l",
"metrics_fields": "@metrics.*_m",
"label_prefix": "@labels.",
"label_suffix": "_l",
"metric_prefix": "@metrics.",
"metric_suffix": "_m"
}
}RemoteWrite介面
API
POST /_time_stream/prom_write/{index}
---PB data---使用說明
remote_write:
- url: "http://127.0.0.1:9200/_time_stream/prom_write/prom_index"
basic_auth:
username: elastic
password: xxxxPrometheus通過Remote Write寫入資料到TimeStream索引,只支援預設的時序資料模型,即維度首碼是label.,指標首碼是metric.。
Instant Query介面
API
GET /_time_stream/prom/{index}/query
POST /_time_stream/prom/{index}/query使用說明
Prometheus Instant Query介面,詳細資料請參見Prometheus instant queries。
Range Query介面
API
GET /_time_stream/prom/{index}/query_range
POST /_time_stream/prom/{index}/query_range使用說明
Prometheus Range Query介面,詳細資料請參見Prometheus range queries。
Series Metadata介面
API
GET /_time_stream/prom/{index}/series
POST /_time_stream/prom/{index}/series使用說明
Prometheus查詢時間軸的介面,詳細資料請參見Prometheus finding series by label matchers。
Labels Metadata介面
API
GET /_time_stream/prom/{index}/labels
POST /_time_stream/prom/{index}/labels使用說明
Prometheus查詢維度(label)列表的介面,詳細資料請參見Prometheus getting label names。
Label Values Metadata介面
API
GET /_time_stream/prom/{index}/label/<label_name>/values使用說明
Prometheus查詢維度對應values列表的介面,詳細資料請參見Prometheus querying label values。
Metric Metadata介面
API
GET /_time_stream/prom/{index}/metadata使用說明
Prometheus查詢指標(Metrics)列表的介面,詳細資料請參見Prometheus querying metric metadata。
TimeStream PromQL支援情況
運算式支援情況
| 運算式 | 類型 | 是否支援 | 說明 |
| powOp | binaryOperator | 是 | 冪乘 |
| unaryOp | binaryOperator | 是 | 正、負 |
| multOp | binaryOperator | 是 | 乘、除、模數 |
| addOp | binaryOperator | 是 | 加、減 |
| compareOp | binaryOperator | 是 | 比較(==,>=, >, <=, <, !=) |
| andUnlessOp | binaryOperator | 是 | 集合運算(and、or、unless) |
| orOp | binaryOperator | 是 | 集合運算(or) |
| function | vector | 是 | 函數 |
| aggregation | vector | 是 | 彙總運算 |
| instantSelector | vector | 是 | 瞬時選取器 |
| matrixSelector | vector | 是 | 向量選取器 |
| offset | vector | 是 | 位移量 |
| literal | vector | 是 | 常量 |
| labelMatcher | vector | 是 | 標籤匹配 |
| grouping | group | 否 | group彙總,包括on、ignoring、group_left、group_right |
Aggregation operator支援情況
| Aggregation operator | 是否支援 |
| sum(calculate sum over dimensions) | 是 |
| min(select minimum over dimensions) | 是 |
| max(select maximum over dimensions) | 是 |
| avg(calculate the average over dimensions) | 是 |
| group(all values in the resulting vector are 1) | 否 |
| stddev(calculate population standard deviation over dimensions) | 否 |
| stdvar(calculate population standard variance over dimensions) | 否 |
| count(count number of elements in the vector) | 是 |
| count_values(count number of elements with the same value) | 是 |
| bottomk(smallest k elements by sample value) | 是 |
| topk(largest k elements by sample value) | 是 |
| quantile(calculate φ-quantile (0 ≤ φ ≤ 1) over dimensions) | 是 |
Function支援情況
| Function | 是否支援 |
| abs(v instant-vector) | 是 |
| absent(v instant-vector) | 否 |
| absent_over_time(v range-vector) | 否 |
| ceil(v instant-vector) | 是 |
| changes(v range-vector) | 否 |
| clamp(v instant-vector, min scalar, max scalar) | 是 |
| clamp_max(v instant-vector, max scalar) | 是 |
| clamp_min(v instant-vector, min scalar) | 是 |
| day_of_month(v=vector(time()) instant-vector) | 是 |
| day_of_week(v=vector(time()) instant-vector) | 是 |
| days_in_month(v=vector(time()) instant-vector) | 否 |
| delta(v range-vector) | 是 |
| deriv(v range-vector) | 否 |
| exp(v instant-vector) | 是 |
| floor(v instant-vector) | 是 |
| histogram_quantile(φ scalar, b instant-vector) | 否 |
| holt_winters(v range-vector, sf scalar, tf scalar) | 否 |
| hour(v=vector(time()) instant-vector) | 是 |
| idelta(v range-vector) | 是 |
| increase(v range-vector) | 是 |
| irate(v range-vector) | 是 |
| label_join(v instant-vector, dst_label string, separator string, src_label_1 string, src_label_2 string, ...) | 否 |
| label_replace(v instant-vector, dst_label string, replacement string, src_label string, regex string) | 否 |
| ln(v instant-vector) | 是 |
| log2(v instant-vector) | 否 |
| log10(v instant-vector) | 是 |
| minute(v=vector(time()) instant-vector) | 是 |
| month(v=vector(time()) instant-vector) | 是 |
| predict_linear(v range-vector, t scalar) | 否 |
| rate(v range-vector) | 是 |
| resets(v range-vector) | 否 |
| round(v instant-vector, to_nearest=1 scalar) | 否 |
| scalar(v instant-vector) | 否 |
| sgn(v instant-vector) | 是 |
| sort(v instant-vector) | 否 |
| sort_desc() | 否 |
| sqrt(v instant-vector) | 是 |
| time() | 否 |
| timestamp(v instant-vector) | 是 |
| vector(s scalar) | 否 |
| year(v=vector(time()) instant-vector) | 是 |
| avg_over_time(range-vector) | 是 |
| min_over_time(range-vector) | 是 |
| max_over_time(range-vector) | 是 |
| sum_over_time(range-vector) | 是 |
| count_over_time(range-vector) | 是 |
| quantile_over_time(scalar, range-vector) | 是 |
| stddev_over_time(range-vector) | 否 |
| stdvar_over_time(range-vector) | 否 |
| last_over_time(range-vector) | 是 |
| present_over_time(range-vector) | 否 |
| acos(v instant-vector) | 是 |
| acosh(v instant-vector) | 是 |
| asin(v instant-vector) | 是 |
| asinh(v instant-vector) | 否 |
| atan(v instant-vector) | 是 |
| atanh(v instant-vector) | 否 |
| cos(v instant-vector) | 是 |
| cosh(v instant-vector) | 是 |
| sin(v instant-vector) | 是 |
| sinh(v instant-vector) | 是 |
| tan(v instant-vector) | 是 |
| tanh(v instant-vector) | 是 |
| deg(v instant-vector) | 是 |
| pi() | 是 |
| rad(v instant-vector) | 是 |