This is an automated email from the ASF dual-hosted git repository. aljoscha pushed a commit to branch release-1.11 in repository https://gitbox.apache.org/repos/asf/flink.git
commit e526b8cdce0cbbadd23bc1f062a1d64399545cd1 Author: Aljoscha Krettek <[email protected]> AuthorDate: Mon Jun 22 17:25:11 2020 +0200 [minor] Rename "Flink Worker" to TaskManager in flink-architecture.md This makes it more in line with using JobManager for the other major component. --- docs/concepts/flink-architecture.md | 10 +++++----- docs/concepts/flink-architecture.zh.md | 10 +++++----- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/concepts/flink-architecture.md b/docs/concepts/flink-architecture.md index d4c36bc..2862752 100644 --- a/docs/concepts/flink-architecture.md +++ b/docs/concepts/flink-architecture.md @@ -40,7 +40,7 @@ main components interact to execute applications and recover from failures. ## Anatomy of a Flink Cluster -The Flink runtime consists of two types of processes: a _JobManager_ and one or more _Flink Workers_. +The Flink runtime consists of two types of processes: a _JobManager_ and one or more _TaskManagers_. <img src="{{ site.baseurl }}/fig/processes.svg" alt="The processes involved in executing a Flink dataflow" class="offset" width="70%" /> @@ -70,7 +70,7 @@ failures, among others. This process consists of three different components: The _ResourceManager_ is responsible for resource de-/allocation and provisioning in a Flink cluster — it manages **task slots**, which are the - unit of resource scheduling in a Flink cluster (see [Flink Workers](#flink-workers)). + unit of resource scheduling in a Flink cluster (see [TaskManagers](#taskmanagers)). Flink implements multiple ResourceManagers for different environments and resource providers such as YARN, Mesos, Kubernetes and standalone deployments. In a standalone setup, the ResourceManager can only distribute @@ -125,8 +125,8 @@ hence with five parallel threads. ## Task Slots and Resources Each worker (TaskManager) is a *JVM process*, and may execute one or more -subtasks in separate threads. To control how many tasks a worker accepts, a -worker has so called **task slots** (at least one). +subtasks in separate threads. To control how many tasks a TaskManager accepts, it +has so called **task slots** (at least one). Each *task slot* represents a fixed subset of resources of the TaskManager. A TaskManager with three slots, for example, will dedicate 1/3 of its managed @@ -196,7 +196,7 @@ isolation guarantees. Because all jobs are sharing the same cluster, there is some competition for cluster resources — like network bandwidth in the submit-job phase. One limitation of this shared setup is that if one TaskManager crashes, then all - jobs that have tasks running on this worker will fail; in a similar way, if + jobs that have tasks running on this TaskManager will fail; in a similar way, if some fatal error occurs on the JobManager, it will affect all jobs running in the cluster. diff --git a/docs/concepts/flink-architecture.zh.md b/docs/concepts/flink-architecture.zh.md index 54e4e53..c11bb4f 100644 --- a/docs/concepts/flink-architecture.zh.md +++ b/docs/concepts/flink-architecture.zh.md @@ -40,7 +40,7 @@ main components interact to execute applications and recover from failures. ## Anatomy of a Flink Cluster -The Flink runtime consists of two types of processes: a _JobManager_ and one or more _Flink Workers_. +The Flink runtime consists of two types of processes: a _JobManager_ and one or more _TaskManagers_. <img src="{{ site.baseurl }}/fig/processes.svg" alt="The processes involved in executing a Flink dataflow" class="offset" width="70%" /> @@ -70,7 +70,7 @@ failures, among others. This process consists of three different components: The _ResourceManager_ is responsible for resource de-/allocation and provisioning in a Flink cluster — it manages **task slots**, which are the - unit of resource scheduling in a Flink cluster (see [Flink Workers](#flink-workers)). + unit of resource scheduling in a Flink cluster (see [TaskManagers](#taskmanagers)). Flink implements multiple ResourceManagers for different environments and resource providers such as YARN, Mesos, Kubernetes and standalone deployments. In a standalone setup, the ResourceManager can only distribute @@ -125,8 +125,8 @@ hence with five parallel threads. ## Task Slots and Resources Each worker (TaskManager) is a *JVM process*, and may execute one or more -subtasks in separate threads. To control how many tasks a worker accepts, a -worker has so called **task slots** (at least one). +subtasks in separate threads. To control how many tasks a TaskManager accepts, it +has so called **task slots** (at least one). Each *task slot* represents a fixed subset of resources of the TaskManager. A TaskManager with three slots, for example, will dedicate 1/3 of its managed @@ -196,7 +196,7 @@ isolation guarantees. Because all jobs are sharing the same cluster, there is some competition for cluster resources — like network bandwidth in the submit-job phase. One limitation of this shared setup is that if one TaskManager crashes, then all - jobs that have tasks running on this worker will fail; in a similar way, if + jobs that have tasks running on this TaskManager will fail; in a similar way, if some fatal error occurs on the JobManager, it will affect all jobs running in the cluster.
