211 lines
9.2 KiB
Markdown
211 lines
9.2 KiB
Markdown
---
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stage: none
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group: unassigned
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info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments
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---
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# Redis guidelines
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## Redis instances
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GitLab uses [Redis](https://redis.io) for the following distinct purposes:
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- Caching (mostly via `Rails.cache`).
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- As a job processing queue with [Sidekiq](sidekiq/index.md).
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- To manage the shared application state.
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- To store CI trace chunks.
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- As a Pub/Sub queue backend for ActionCable.
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- Rate limiting state storage.
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- Sessions.
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In most environments (including the GDK), all of these point to the same
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Redis instance.
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On GitLab.com, we use [separate Redis instances](../administration/redis/replication_and_failover.md#running-multiple-redis-clusters).
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See the [Redis SRE guide](https://gitlab.com/gitlab-com/runbooks/-/blob/master/docs/redis/redis-survival-guide-for-sres.md)
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for more details on our setup.
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Every application process is configured to use the same Redis servers, so they
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can be used for inter-process communication in cases where [PostgreSQL](sql.md)
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is less appropriate. For example, transient state or data that is written much
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more often than it is read.
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If [Geo](geo.md) is enabled, each Geo node gets its own, independent Redis
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database.
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We have [development documentation on adding a new Redis instance](redis/new_redis_instance.md).
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## Key naming
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Redis is a flat namespace with no hierarchy, which means we must pay attention
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to key names to avoid collisions. Typically we use colon-separated elements to
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provide a semblance of structure at application level. An example might be
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`projects:1:somekey`.
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Although we split our Redis usage by purpose into distinct categories, and
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those may map to separate Redis servers in a Highly Available
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configuration like GitLab.com, the default Omnibus and GDK setups share
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a single Redis server. This means that keys should **always** be
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globally unique across all categories.
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It is usually better to use immutable identifiers - project ID rather than
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full path, for instance - in Redis key names. If full path is used, the key
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stops being consulted if the project is renamed. If the contents of the key are
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invalidated by a name change, it is better to include a hook that expires
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the entry, instead of relying on the key changing.
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### Multi-key commands
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We don't use Redis Cluster, but support for it is tracked in [this issue](https://gitlab.com/gitlab-org/gitlab/-/issues/118820).
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This imposes an additional constraint on naming: where GitLab is performing
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operations that require several keys to be held on the same Redis server - for
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instance, diffing two sets held in Redis - the keys should ensure that by
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enclosing the changeable parts in curly braces.
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For example:
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```plaintext
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project:{1}:set_a
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project:{1}:set_b
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project:{2}:set_c
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```
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`set_a` and `set_b` are guaranteed to be held on the same Redis server, while `set_c` is not.
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Currently, we validate this in the development and test environments
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with the [`RedisClusterValidator`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/instrumentation/redis_cluster_validator.rb),
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which is enabled for the `cache` and `shared_state`
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[Redis instances](https://docs.gitlab.com/omnibus/settings/redis.html#running-with-multiple-redis-instances)..
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## Redis in structured logging
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For GitLab Team Members: There are <i class="fa fa-youtube-play youtube" aria-hidden="true"></i>
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[basic](https://www.youtube.com/watch?v=Uhdj19Dc6vU) and
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<i class="fa fa-youtube-play youtube" aria-hidden="true"></i> [advanced](https://youtu.be/jw1Wv2IJxzs)
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videos that show how you can work with the Redis
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structured logging fields on GitLab.com.
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Our [structured logging](logging.md#use-structured-json-logging) for web
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requests and Sidekiq jobs contains fields for the duration, call count,
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bytes written, and bytes read per Redis instance, along with a total for
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all Redis instances. For a particular request, this might look like:
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| Field | Value |
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| --- | --- |
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| `json.queue_duration_s` | 0.01 |
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| `json.redis_cache_calls` | 1 |
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| `json.redis_cache_duration_s` | 0 |
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| `json.redis_cache_read_bytes` | 109 |
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| `json.redis_cache_write_bytes` | 49 |
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| `json.redis_calls` | 2 |
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| `json.redis_duration_s` | 0.001 |
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| `json.redis_read_bytes` | 111 |
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| `json.redis_shared_state_calls` | 1 |
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| `json.redis_shared_state_duration_s` | 0 |
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| `json.redis_shared_state_read_bytes` | 2 |
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| `json.redis_shared_state_write_bytes` | 206 |
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| `json.redis_write_bytes` | 255 |
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As all of these fields are indexed, it is then straightforward to
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investigate Redis usage in production. For instance, to find the
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requests that read the most data from the cache, we can just sort by
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`redis_cache_read_bytes` in descending order.
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### The slow log
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NOTE:
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There is a [video showing how to see the slow log](https://youtu.be/BBI68QuYRH8) (GitLab internal)
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on GitLab.com
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<!-- vale gitlab.Substitutions = NO -->
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On GitLab.com, entries from the [Redis slow log](https://redis.io/commands/slowlog/) are available in the
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`pubsub-redis-inf-gprd*` index with the [`redis.slowlog` tag](https://log.gprd.gitlab.net/app/kibana#/discover?_g=(filters:!(),refreshInterval:(pause:!t,value:0),time:(from:now-1d,to:now))&_a=(columns:!(json.type,json.command,json.exec_time_s),filters:!(('$state':(store:appState),meta:(alias:!n,disabled:!f,index:AWSQX_Vf93rHTYrsexmk,key:json.tag,negate:!f,params:(query:redis.slowlog),type:phrase),query:(match:(json.tag:(query:redis.slowlog,type:phrase))))),index:AWSQX_Vf93rHTYrsexmk)).
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This shows commands that have taken a long time and may be a performance
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concern.
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<!-- vale gitlab.Substitutions = YES -->
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The
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[`fluent-plugin-redis-slowlog`](https://gitlab.com/gitlab-org/fluent-plugin-redis-slowlog)
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project is responsible for taking the `slowlog` entries from Redis and
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passing to Fluentd (and ultimately Elasticsearch).
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## Analyzing the entire keyspace
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The [Redis Keyspace Analyzer](https://gitlab.com/gitlab-com/gl-infra/redis-keyspace-analyzer)
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project contains tools for dumping the full key list and memory usage of a Redis
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instance, and then analyzing those lists while eliminating potentially sensitive
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data from the results. It can be used to find the most frequent key patterns, or
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those that use the most memory.
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Currently this is not run automatically for the GitLab.com Redis instances, but
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is run manually on an as-needed basis.
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## Utility classes
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We have some extra classes to help with specific use cases. These are
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mostly for fine-grained control of Redis usage, so they wouldn't be used
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in combination with the `Rails.cache` wrapper: we'd either use
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`Rails.cache` or these classes and literal Redis commands.
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We prefer using `Rails.cache` so we can reap the benefits of future
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optimizations done to Rails. Ruby objects are
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[marshalled](https://github.com/rails/rails/blob/v6.0.3.1/activesupport/lib/active_support/cache/redis_cache_store.rb#L447)
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when written to Redis, so we must pay attention to store neither huge objects,
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nor untrusted user input.
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Typically we would only use these classes when at least one of the
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following is true:
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1. We want to manipulate data on a non-cache Redis instance.
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1. `Rails.cache` does not support the operations we want to perform.
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### `Gitlab::Redis::{Cache,SharedState,Queues}`
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These classes wrap the Redis instances (using
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[`Gitlab::Redis::Wrapper`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/redis/wrapper.rb))
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to make it convenient to work with them directly. The typical use is to
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call `.with` on the class, which takes a block that yields the Redis
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connection. For example:
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```ruby
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# Get the value of `key` from the shared state (persistent) Redis
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Gitlab::Redis::SharedState.with { |redis| redis.get(key) }
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# Check if `value` is a member of the set `key`
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Gitlab::Redis::Cache.with { |redis| redis.sismember(key, value) }
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```
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### `Gitlab::Redis::Boolean`
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In Redis, every value is a string.
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[`Gitlab::Redis::Boolean`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/redis/boolean.rb)
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makes sure that booleans are encoded and decoded consistently.
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### `Gitlab::Redis::HLL`
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The Redis [`PFCOUNT`](https://redis.io/commands/pfcount/),
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[`PFADD`](https://redis.io/commands/pfadd/), and
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[`PFMERGE`](https://redis.io/commands/pfmerge/) commands operate on
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HyperLogLogs, a data structure that allows estimating the number of unique
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elements with low memory usage. (In addition to the `PFCOUNT` documentation,
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Thoughtbot's article on [HyperLogLogs in Redis](https://thoughtbot.com/blog/hyperloglogs-in-redis)
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provides a good background here.)
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[`Gitlab::Redis::HLL`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/redis/hll.rb)
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provides a convenient interface for adding and counting values in HyperLogLogs.
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### `Gitlab::SetCache`
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For cases where we need to efficiently check the whether an item is in a group
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of items, we can use a Redis set.
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[`Gitlab::SetCache`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/set_cache.rb)
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provides an `#include?` method that uses the
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[`SISMEMBER`](https://redis.io/commands/sismember/) command, as well as `#read`
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to fetch all entries in the set.
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This is used by the
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[`RepositorySetCache`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/repository_set_cache.rb)
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to provide a convenient way to use sets to cache repository data like branch
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names.
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