dapr
/
docs
mirror of https://github.com/dapr/docs.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'website' into mchmarny-binding-concept-link

This commit is contained in:
Aaron Crawfis 2020-12-10 10:54:16 -08:00 committed by GitHub
parent 4f0701780f 2f6faa1aab
commit aa82222a4e
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
daprdocs/content/en/developing-applications/building-blocks/actors/actors-background.md
View File

@ -54,7 +54,7 @@ To provide scalability and reliability, actors instances are distributed through
Actors are distributed across the instances of the actor service, and those instance are distributed across the nodes in a cluster. Each service instance contains a set of actors for a given actor type.
### Actor placement service
The Dapr actor runtime manages distribution scheme and key range settings for you. This is done by the actor `Placement` service. When a new instance of a service is created, the corresponding Dapr runtime register the actor types it can create and the `Placement` service calculates the partitioning across all the instances for a given actor type. This table of partition information for each actor type is updated and stored in each Dapr instance running in the environment and can change dynamically as new instance of actor services are created and destroyed. This is shown in the diagram below.
The Dapr actor runtime manages distribution scheme and key range settings for you. This is done by the actor `Placement` service. When a new instance of a service is created, the corresponding Dapr runtime registers the actor types it can create and the `Placement` service calculates the partitioning across all the instances for a given actor type. This table of partition information for each actor type is updated and stored in each Dapr instance running in the environment and can change dynamically as new instance of actor services are created and destroyed. This is shown in the diagram below.
<img src="/images/actors_background_placement_service_registration.png" width=600>
@ -67,11 +67,11 @@ When a client calls an actor with a particular id (for example, actor id 123), t
* By default, actors are randomly placed into pods resulting in uniform distribution.
* Because actors are randomly placed, it should be expected that actor operations always require network communication, including serialization and deserialization of method call data, incurring latency and overhead.
Note: The Dapr actor Placement service is only used for actor placement and therefore is not needed if your services are not using Dapr actors. The Placement service can run in all hosting environments for example, self hosted, Kubernetes
Note: The Dapr actor Placement service is only used for actor placement and therefore is not needed if your services are not using Dapr actors. The Placement service can run in all [hosting environments]({{< ref hosting >}}), including self-hosted and Kubernetes.
## Actor communication
You can interact with Dapr to invoke the actor method by calling HTTP/gRPC endpoint
You can interact with Dapr to invoke the actor method by calling HTTP/gRPC endpoint.
```bash
POST/GET/PUT/DELETE http://localhost:3500/v1.0/actors/<actorType>/<actorId>/<method/state/timers/reminders>

2
daprdocs/content/en/developing-applications/building-blocks/state-management/query-state-store/query-redis-store.md
View File

@ -6,7 +6,7 @@ weight: 2000
description: "Use Redis as a backend state store"
---
Dapr doesn't transform state values while saving and retrieving states. Dapr requires all state store implementations to abide by a certain key format scheme (see [Dapr state management spec]({{<ref state_api.md>}}). You can directly interact with the underlying store to manipulate the state data, such querying states, creating aggregated views and making backups.
Dapr doesn't transform state values while saving and retrieving states. Dapr requires all state store implementations to abide by a certain key format scheme (see [Dapr state management spec]({{<ref state_api.md>}}). You can directly interact with the underlying store to manipulate the state data, such as querying states, creating aggregated views and making backups.
>**NOTE:** The following examples uses Redis CLI against a Redis store using the default Dapr state store implementation.