+++ title = “Metrics” weight = 2 +++

Background

Metrics are measures of used to evaluate the performance of a system at run time. Quantitative assessment can be used to evaluate the performance of a system and to give relevant opinions on system optimization or business strategy. Apache ShardingSphere aims to build a distributed database solution. For the database,it analyzes its running status,connection data,transaction number,throughput and other relevant indicators. It is particularly important to provide visual advice and help for database scheduling,data smooth migration,sharding-database,sharding-table and other policies.

Plan

Apache ShardingSphere follows the Metrics standard, which defines a pluggable SPI standard that does not store, collect, or display Metrics information, It is only responsible for embedding Metrics in the program. Currently, the default implementation scheme is: Prometheus client API burial point, through which the service side passes HTTP protocol to periodically grab Metrics data.

Metrics indicators

Four types of metrics are currently defined.

• Counter : A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart.

• Gauge : A gauge is a metric that represents a single numerical value that can arbitrarily go up and down.

• Histogram : A histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.

• Summary : Similar to a histogram, a summary samples observations (usually things like request durations and response sizes). While it also provides a total count of observations and a sum of all observed values, it calculates configurable quantiles over a sliding time window.

name	type	labelName	description
request_total	Counter		Collect all request of ShardingSphere-Proxy
sql_statement_count	Counter	sql_type	Collect all the types of SQL , example (SELECT,UPDATE,INSERT...)
channel_count	Gauge		Collect all the connection number of ShardingSphere-Proxy
requests_latency_histogram_millis	Histogram		Collect all the request latency time(ms)
sharding_datasource	Counter	datasource	Collect all the sql sharding datasource
sharding_table	Counter	table	Collect all the sql sharding table
transaction	Counter	status	Collect all the sql transaction

Use

Add the following configuration to the server.yaml file of ShardingSphere-Proxy:

metrics:
   name: prometheus # The specified type is Prometheus..
   host:  127.0.0.1 # Specify host and, if empty, get the default of ShardingSphere-Proxy
   port:  9190  # Specify the Prometheus server fetching metrics port
props:
  proxy.metrics.enabled: ture  # true for on and false for off

Users set up the Prometheus service by themselves, adding the following configuration in the prometheus.yml file:

scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'shardingSphere-proxy'
    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.
    static_configs:
    - targets: ['localhost:9190']

Dashboard

It is recommended to use Granfana. Users can customize the query to personalize the panel panel. Later we will provide the default panel panel configuration.