VTTablet runs a cooperative throttling service. This service probes the shard's MySQL topology and observes health, measure by replication lag, or by another metric delivered by custom query, on servers. The throttler is derived from GitHub's freno.

Why throttler: maintaining shard health via low replication lag #

Vitess uses MySQL with asynchronous or semi-synchronous replication. In these modes, each shard has a primary instance that applies changes and logs them to the binary log. The replicas for that shard will get binary log entries from the primary, potentially acknowledge them (if semi-synchronous replication is enabled), and apply them. A running replica normally applies the entries as soon as possible, unless it is stopped or configured to delay. However, if the replica is busy, then it may not have the resources to apply events in a timely fashion, and can therefore start lagging. For example, if the replica is serving traffic, it may lack the necessary disk I/O or CPU to avoid lagging behind the primary.

Maintaining low replication lag is important in production for two reasons:

• A lagging replica may not be representative of the data on the primary. Reads from the replica reflect data that is not consistent with the data on the primary. This is noticeable on web services following read-after-write from the replica, and this can produce results not reflecting the write.
• An up-to-date replica makes for a good failover experience. If all replicas are lagging, then a failover process must choose between waiting for a replica to catch up or losing data.

Some common database operations include mass writes to the database, including the following:

• Online schema migrations duplicating entire tables
• Mass population of columns, such as populating the new column with derived values following an ADD COLUMN migration
• Purging of old data
• Purging of tables as part of safe table DROP operation

Other operations include mass reads from the database:

• An ETL reading content of entire tables
• VReplication scanning an entire keyspace data and binary logs

These operations can easily incur replication lag. However, these operations are typically not time-limited. It is possible to rate-limit them to reduce database load.

This is where a throttler becomes useful. A throttler can detect when replication lag is low, a cluster is healthy, and operations can proceed. It can also detect when replication lag is high and advise applications to withhold the next operation.

Applications are expected to break down their tasks into small sub-tasks. For example, instead of deleting 1,000,000 rows, an application should only delete 50 at a time. Between these sub-tasks, the application should check in with the throttler.

The throttler is only intended for use with operations such as the above mass write/read cases. It should not be used for ongoing, normal OLTP queries.

Throttler overview #

Each vttablet runs an internal throttler service, and provides API endpoints to the throttler. Each tablet, including the primary, measures its own "self" health, discussed later.

Cluster health: #

In addition, the primary tablet is responsible for the overall health of the cluster/shard:

• The throttler confirms it is still the primary tablet for its shard.
• Every 10sec, the throttler uses the topology server to refresh the shard's tablets list.
• The throttler probes all REPLICA tablets for their replication lag. This is done by querying the _vt.heartbeat table.
  • The throttler begins in dormant probe mode. As long as no application or client is actually looking for metrics, it probes the servers at multi-second intervals.
  • When applications check for throttle advice, the throttler begins probing servers in subsecond intervals. It reverts to dormant probe mode if no requests are made in the duration of 1min.
• The throttler aggregates the last probed values from all relevant tablets. This is the cluster's metric.

The cluster's metric is only as accurate as the following metrics:

• The probe interval
• The heartbeat injection interval
• The aggregation interval

The error margin equals approximately the sum of the above values, plus additional overhead. The defaults for these intervals are as follows:

• Probe interval: 100ms
• Aggregation interval: 100ms
• Heartbeat interval: 250ms

The user may override the heartbeat interval by sending -heartbeat_interval flag to vttablet.

Thus, the aggregated interval can be off, by default, by some 500ms. This makes it inaccurate for evaluations that require high resolution lag evaluation. This resolution is sufficient for throttling purposes.

Self health #

Each tablet runs a local health check against its backend database, again in the form of evaluating replication lag from _vt.heartbeat. Intervals are identical to the cluster health interval illustrated above.

Response codes #

The throttler allows clients and applications to check for throttle advice. The check is an HTTP request, HEAD method, or GET method. Throttler returns one of the following HTTP response codes as an answer:

• 200 (OK): The application may write to the data store. This is the desired response.
• 404 (Not Found): The check contains an unknown metric name. This can take place immediately upon startup or immediately after failover, and should resolve within 10 seconds.
• 417 (Expectation Failed): The requesting application is explicitly forbidden to write. The throttler does not implement this at this time.
• 429 (Too Many Requests): Do not write. A normal, expected state indicating there is replication lag. This is the hint for applications or clients to withhold writes.
• 500 (Internal Server Error): An internal error has occurred. Do not write.

Normally, apps will see either 200 or 429. An app should only ever proceed to write to the database when it receives a 200 response code.

The throttler chooses the response by comparing the replication lag with a pre-defined threshold. If the lag is lower than the threshold, response can be 200 (OK). If the lag is higher than the threshold, the response would be 429 (Too Many Requests).

The throttler only collects and evaluates lag on a set of predefined tablet types. By default, this tablet type set is REPLICA. See Configuration.

When the throttler sees no relevant replicas in the shard, it allows writes by responding with HTTP 200 OK.

Custom metrics & queries #

The default behavior is to measure replication lag and throttle based on that lag. Vitess allows the user to use custom metrics and thresholds for throttling.

Vitess only supports gauges for custom metrics: the user may define a query which returns a gauge value, an absolute metric by which Vitess can throttle. See #Configuration, below.

App management #

It is possible for the throttler to respond differently -- to some extent -- to different clients, or apps. When a client asks for the throttler's advice, it may identify itself by any arbitrary name, which the throttler terms the app. For example, vreplication workflows identify by the name "vreplication", and Online DDL operations use "online-ddl", etc.

It is possible to restrict the throttler's response to one or more apps. For example, it's possible to completely throttle "vreplication" while still responding HTTP 200 to other apps. This is typically used to give way or precedence to one or two apps, or otherwise to further reduce the incoming load from a specific app.

It is not possible to give an app more way than the throttler's standard behavior. That is, if the throttler is set to throttler at 5s replication lag, it is not possible to respond wih HTTP 200 to a specific app with replication lag at 7s.

Vitess has a granular breakdown for its own throttler apps. Generally, the user should not change throttling configuration for internal apps. However, some of the apps are user-facing or user-initiated, and it makes sense for the user to restrict them. These apps include:

• online-ddl: affecting all schema migrations of all strategies.
• vreplication: all VReplication operations, for example: MoveTables, Reshard, Online DDL via vitess/online strategy.
• vplayer: the VPlayer component of VReplication, which tails, processes and applies events from the bianry logs.
• vcopier: the VCopier component of VReplication, which copies over the mass of table rows from source to target tables.

Configuration #

v16 is backwards compliant with v15 and still default to the v15 configuration. We illustrate both configurations so that you understand how to transition from one to the other.

v17 and forward #

In v17, throttler configuration is found in the local topology server. There is one configuration per keyspace. All shards and all tablets in all cells have the same throttler configuration: they are all enabled or disabled, and all share the same threshold or custom query. Since configuration is stored outside the tablet, it survives tablet restarts.

v16 introduced a new opt-in vttablet flag, --throttler-config-via-topo. In v16 this flag defaulted false. In v17 this flag now defaults true. With --throttler-config-via-topo set, the tablet will look for configuration in the topology server, and will watch and apply any changes made there.

When the flag --throttler-config-via-topo is set (and it is set by default), the following flags are ignored even if specified. These flags are scheduled to be removed in v18and v19:

• --enable_lag_throttler
• --throttle_threshold
• --throttle_metrics_query
• --throttle_metrics_threshold
• --throttle_check_as_check_self

Updating the throttler config is done via vtctlclient or vtctldclient. For example:

$ vtctlclient -- UpdateThrottlerConfig --enable --threshold 3.0 commerce
$ vtctldclient UpdateThrottlerConfig --disable commerce

See vtctl UpdateThrottlerConfig.

If you are still using the v15 flags, we recommend that you transition to the new throttler configuration scheme: first populate topo with a new throttler configuration via UpdateThrottlerConfig. At the very least, set a --threshold. You likely also want to --enable. Then, reconfigure vttablets with --throttler-config-via-topo, and restart them.

v16 and before #

In earlier versions, the throttler is configured per tablet. Each tablet can have throttler enabled/disabled independently, or have different thresholds.

v17 still supports the per-tablet configuration if you specify --throttler-config-via-topo=false, but this will be removed in v18.

• The throttler is disabled by default. Use the vttablet option --enable-lag-throttler to enable the throttler. When the throttler is disabled, it still serves /throttler/check and /throttler/check-self API endpoints, and responds with HTTP 200 OK to all requests. When the throttler is enabled, it implicitly also runs heartbeat injections.
• Use the vttablet flag --throttle_threshold to set a lag threshold value. The default threshold is 1sec and is set upon tablet startup. For example, to set a half-second lag threshold, use the flag --throttle_threshold=0.5s.
• To set the tablet types that the throttler queries for lag, use the vttablet flag --throttle_tablet_types="replica,rdonly". The default tablet type is replica; this type is always implicitly included in the tablet types list. You may add any other tablet type. Any type not specified is ignored by the throttler.
• To override the default lag evaluation, and measure a different metric, use --throttle_metrics_query. The query must be either of these forms:
  • SHOW GLOBAL STATUS LIKE '<metric>'
  • SHOW GLOBAL VARIABLES LIKE '<metric>'
  • SELECT <single-column> FROM ..., expecting single column, single row result
• To override the throttle threshold, use --throttle_metrics_threshold. Floating point values are accepted.
• Use --throttle_check_as_check_self to implicitly reroute any /throttler/check call into /throttler/check-self. This makes sense when the user supplies a custom query, and where the user wishes to throttle writes to the cluster based on the primary tablet's health, rather than the overall health of the cluster.

An example for custom query & threshold setup, using the MySQL metrics Threads_running (number of threads actively executing a query at a given time) on the primary, might look like:

$ vttablet
  --throttle_metrics_query "show global status like 'threads_running'"
  --throttle_metrics_threshold 150
  --throttle_check_as_check_self

Heartbeat configuration #

The throttler requires heartbeat to be enabled via vttablet flags. We recommend enabling heartbeats via --heartbeat_on_demand_duration in conjunction with --heartbeat_interval as follows:

• --heartbeat_interval indicates how frequently heartbeats are injected. The interval should over-sample the --throttle_threshold by a factor of 2 to 4. Examples:
  • If --throttle_threshold (replication lag) is 1s, use --heartbeat_interval 250ms.
  • If --throttle_threshold is 5s, use an interval of 1s or 2s.
• --heartbeat_on_demand_duration ensures heartbeats are only injected when needed (e.g. during active VReplication workflows such as MoveTables or Online DDL). Heartbeats are written to the binary logs, and can therefore bloat them. If this is a concern, configure for example: --heartbeat_on_demand_duration 5s. This setting means: any throttler request starts a 5s lease of heartbeat writes. In normal times, heartbeats are not written. Once a throttle check is requested (e.g. by a running migration), the throttler asks the tablet to start a 5s lease of heartbeats. that first check is likely to return a non-OK code, because heartbeats were stale. However, subsequent checks will soon pick up on the newly injected heartbeats. Checks made while the lease is held, further extend the lease time. In the scenario of a running migration, we can expect heartbeats to begin as soon as the migration begins, and terminate 5s (in our example) after the migration completes. A recommended value is a multiple of --throttle_threshold. If --throttle_threshold is 1s, reasonable values would be 5s to 60s.

Alternatively, you may choose to enable heartbeats unconditionally via --heartbeat_enable, again in conjunction with --heartbeat_interval <duration>.

API & usage #

Applications use these API endpoints:

Checks #

• /throttler/check?app=<app-name>, for apps that wish to write mass amounts of data to a shard, and wish to maintain the overall health of the shard. This check is only applicable on the PRIMARY tablet.
• /throttler/check-self, for apps that wish to perform some operation (e.g. a massive read) on a specific tablet and only wish to maintain the health of that tablet. This check is applicable on all tablets.

Examples: #

• gh-ost uses this throttler endpoint: /throttler/check?app=gh-ost&p=low
• A data backfill application will identify as such, and use normal priority: /throttler/check?app=my_backfill (priority not indicated in URL therefore assumed to be normal)
• An app reading a massive amount of data directly from a replica tablet will use /throttler/check-self?app=my_data_reader

A HEAD request is sufficient. A GET request also provides a JSON output. For example:

• {"StatusCode":200,"Value":0.207709,"Threshold":1,"Message":""}
• {"StatusCode":429,"Value":3.494452,"Threshold":1,"Message":"Threshold exceeded"}
• {"StatusCode":404,"Value":0,"Threshold":0,"Message":"No such metric"}

In the first two above examples we can see that the tablet is configured to throttle at 1sec

Instructions #

• /throttler/throttle-app?app=<name>&duration=<duration>[&ratio=<ratio>][&p=low]: instructs the throttler to begin throttling requests from given app.
  • A mandatory duration value auto expires the throttling after indicated time. You may specify these units: s (seconds), m (minutes), h (hours) or combinations. Example values: 90s, 30m, 1h, 1h30m, etc.
  • An optional ratio value indicates the throttling intensity, ranging from 0 (no throttling at all) to 1.0 (the default, full throttle). With a value of 0.3, for example, 3 out of 10, on average, checks by the app, are flat out denied, regardless of present metrics and threshold. The remaining 7 out of 10 checks, will get a response that is based on the actual metrics and threshold (thereby, thay may be approved, or they may be rejected).
  • Applications may also declare themselves to be low priority via ?p=low param. Managed online schema migrations (gh-ost, pt-online-schema-change) do so, as does the table purge process.
• /throttler/unthrottle-app?app=<name>: instructs the throttler to stop throttling for the given app. This removes any previous throttling instruction for the app. the throttler still reserves the right to throttle the app based on cluster status.

Examples: #

• /throttler/throttle-app?app=vreplication&duration=2h rejects all requests made by vreplication for the next 2 hours, after which the app is unthrottled.
• /throttler/throttle-app?app=vreplication&duration=2h&ratio=0.25 rejects on average 1 out of 4 requests made by vreplication for the next 2 hours, after which the app is unthrottled.

$ curl -s 'http://localhost:15000/throttler/throttle-app?app=test&ratio=0.25'

Information #

• /throttler/status endpoint. This is useful for monitoring and management purposes.
• /throttler/throttled-apps endpoint, listing all apps for which there's a throttling instruction

Vitess also accepts the SQL syntax:

• SHOW VITESS_THROTTLER STATUS: returns the status for all primary tables in the keyspace. See MySQL Query Extensions.

Example: Healthy primary tablet #

The following command gets throttler status on a primary tablet hosted on tablet1, serving on port 15100.

$ curl -s 'http://tablet1:15100/throttler/status' | jq .

This API call returns the following JSON object:

{
  "Keyspace": "commerce",
  "Shard": "80-c0",
  "IsLeader": true,
  "IsOpen": true,
  "IsDormant": false,
  "Query": "select unix_timestamp(now(6))-max(ts/1000000000) as replication_lag from _vt.heartbeat",
  "Threshold": 1,
  "AggregatedMetrics": {
    "mysql/self": {
      "Value": 0.749837
    },
    "mysql/shard": {
      "Value": 0.749887
    }
  },
  "MetricsHealth": {
    "mysql/self": {
      "LastHealthyAt": "2021-01-24T19:03:19.141933727+02:00",
      "SecondsSinceLastHealthy": 0
    },
    "mysql/shard": {
      "LastHealthyAt": "2021-01-24T19:03:19.141974429+02:00",
      "SecondsSinceLastHealthy": 0
    }
  }
}

The primary tablet serves two types of metrics:

• mysql/shard: an aggregated lag on relevant replicas in this shard. This is the metric to check when writing massive amounts of data to this server.
• mysql/self: the health of the specific primary MySQL server backed by this tablet.

"IsLeader": true indicates this tablet is active, is the primary, and is running probes. "IsDormant": false, means that an application has recently issued a check, and the throttler is probing for lag at high frequency.

Example: replica tablet #

The following command gets throttler status on a replica tablet hosted on tablet2, serving on port 15100.

$ curl -s 'http://tablet2:15100/throttler/status' | jq .

This API call returns the following JSON object:

{
  "Keyspace": "commerce",
  "Shard": "80-c0",
  "IsLeader": false,
  "IsOpen": true,
  "IsDormant": false,
  "Query": "select unix_timestamp(now(6))-max(ts/1000000000) as replication_lag from _vt.heartbeat",
  "Threshold": 1,
  "AggregatedMetrics": {
    "mysql/self": {
      "Value": 0.346409
    }
  },
  "MetricsHealth": {
    "mysql/self": {
      "LastHealthyAt": "2021-01-24T19:04:25.038290475+02:00",
      "SecondsSinceLastHealthy": 0
    }
  }
}

The replica tablet only presents mysql/self metric (measurement of its own backend MySQL's lag). It does not serve checks for the shard in general.

Example: throttled-apps #

$ curl -s 'http://127.0.0.1:15100/throttler/throttled-apps'

[
  {
    "AppName": "always-throttled-app",
    "ExpireAt": "2032-05-08T11:33:19.683767744Z",
    "Ratio": 1
  }
]

Resources #

• freno project page
• Mitigating replication lag and reducing read load with freno, a GitHub Engineering blog post