[flink] branch release-1.13 updated: [hotfix][docs] Replace local failover with partial failover

[tr...@apache.org]

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trohrmann pushed a commit to branch release-1.13
in repository https://gitbox.apache.org/repos/asf/flink.git


The following commit(s) were added to refs/heads/release-1.13 by this push:
     new d434625  [hotfix][docs] Replace local failover with partial failover
d434625 is described below

commit d43462599d13941a67ffe31987afc4c6649cc3fa
Author: Till Rohrmann <tr...@apache.org>
AuthorDate: Thu May 6 10:03:51 2021 +0200

    [hotfix][docs] Replace local failover with partial failover
---
 docs/content.zh/docs/deployment/elastic_scaling.md | 2 +-
 docs/content/docs/deployment/elastic_scaling.md    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/content.zh/docs/deployment/elastic_scaling.md b/docs/content.zh/docs/deployment/elastic_scaling.md
index 14a0e24..8a06749 100644
--- a/docs/content.zh/docs/deployment/elastic_scaling.md
+++ b/docs/content.zh/docs/deployment/elastic_scaling.md
@@ -146,7 +146,7 @@ The behavior of Adaptive Scheduler is configured by [all configuration options c
 
 - **Streaming jobs only**: The first version of Adaptive Scheduler runs with streaming jobs only. When submitting a batch job, we will automatically fall back to the default scheduler.
 - **No support for [local recovery]({{< ref "docs/ops/state/large_state_tuning">}}#task-local-recovery)**: Local recovery is a feature that schedules tasks to machines so that the state on that machine gets re-used if possible. The lack of this feature means that Adaptive Scheduler will always need to download the entire state from the checkpoint storage.
-- **No support for local failover**: Local failover means that the scheduler is able to restart parts ("regions" in Flink's internals) of a failed job, instead of the entire job. This limitation impacts only recovery time of embarrassingly parallel jobs: Flink's default scheduler can restart failed parts, while Adaptive Scheduler will restart the entire job.
+- **No support for partial failover**: Partial failover means that the scheduler is able to restart parts ("regions" in Flink's internals) of a failed job, instead of the entire job. This limitation impacts only recovery time of embarrassingly parallel jobs: Flink's default scheduler can restart failed parts, while Adaptive Scheduler will restart the entire job.
 - **Limited integration with Flink's Web UI**: Adaptive Scheduler allows that a job's parallelism can change over its lifetime. The web UI only shows the current parallelism the job.
 - **Limited Job metrics**: With the exception of `numRestarts` all [availability]({{< ref "docs/ops/metrics" >}}#availability) and [checkpointing]({{< ref "docs/ops/metrics" >}}#checkpointing) metrics with the `Job` scope are not working correctly.
 - **Unused slots**: If the max parallelism for slot sharing groups is not equal, slots offered to Adaptive Scheduler might be unused.
diff --git a/docs/content/docs/deployment/elastic_scaling.md b/docs/content/docs/deployment/elastic_scaling.md
index 14a0e24..8a06749 100644
--- a/docs/content/docs/deployment/elastic_scaling.md
+++ b/docs/content/docs/deployment/elastic_scaling.md
@@ -146,7 +146,7 @@ The behavior of Adaptive Scheduler is configured by [all configuration options c
 
 - **Streaming jobs only**: The first version of Adaptive Scheduler runs with streaming jobs only. When submitting a batch job, we will automatically fall back to the default scheduler.
 - **No support for [local recovery]({{< ref "docs/ops/state/large_state_tuning">}}#task-local-recovery)**: Local recovery is a feature that schedules tasks to machines so that the state on that machine gets re-used if possible. The lack of this feature means that Adaptive Scheduler will always need to download the entire state from the checkpoint storage.
-- **No support for local failover**: Local failover means that the scheduler is able to restart parts ("regions" in Flink's internals) of a failed job, instead of the entire job. This limitation impacts only recovery time of embarrassingly parallel jobs: Flink's default scheduler can restart failed parts, while Adaptive Scheduler will restart the entire job.
+- **No support for partial failover**: Partial failover means that the scheduler is able to restart parts ("regions" in Flink's internals) of a failed job, instead of the entire job. This limitation impacts only recovery time of embarrassingly parallel jobs: Flink's default scheduler can restart failed parts, while Adaptive Scheduler will restart the entire job.
 - **Limited integration with Flink's Web UI**: Adaptive Scheduler allows that a job's parallelism can change over its lifetime. The web UI only shows the current parallelism the job.
 - **Limited Job metrics**: With the exception of `numRestarts` all [availability]({{< ref "docs/ops/metrics" >}}#availability) and [checkpointing]({{< ref "docs/ops/metrics" >}}#checkpointing) metrics with the `Job` scope are not working correctly.
 - **Unused slots**: If the max parallelism for slot sharing groups is not equal, slots offered to Adaptive Scheduler might be unused.