[hotfix][docs] fix some typos (#601)
diff --git a/docs/content/docs/custom-resource/autoscaler.md b/docs/content/docs/custom-resource/autoscaler.md
index b1bdb79..748f9dc 100644
--- a/docs/content/docs/custom-resource/autoscaler.md
+++ b/docs/content/docs/custom-resource/autoscaler.md
@@ -56,7 +56,7 @@
Depending on your environment and job characteristics there are a few very important configurations that will affect how well the autoscaler works.
-Key configuration areas
+Key configuration areas:
- Job and per operator max parallelism
- Stabilization and metrics collection intervals
- Target utilization and flexible boundaries
@@ -67,9 +67,9 @@
### Job and per operator max parallelism
When computing the scaled parallelism, the autoscaler always considers the max parallelism settings for each job vertex to ensure that it doesn't introduce unnecessary data skew.
-The computed parallelism will always be a divisor of the max_parallelism number.
+The computed parallelism will always be a divisor of the max parallelism number.
-To ensure flexible scaling it is therefore recommended to chose max parallelism settings that have a [lot of divisors](https://en.wikipedia.org/wiki/Highly_composite_number) instead of relying on the Flink provided defaults.
+To ensure flexible scaling it is therefore recommended to choose max parallelism settings that have a [lot of divisors](https://en.wikipedia.org/wiki/Highly_composite_number) instead of relying on the Flink provided defaults.
You can then use the `pipeline.max-parallelism` to configure this for your pipeline.
Some good numbers for max-parallelism are: 120, 180, 240, 360, 720 etc.
@@ -120,7 +120,6 @@
kubernetes.operator.job.autoscaler.target.utilization.boundary: "0.2"
kubernetes.operator.job.autoscaler.restart.time: 2m
kubernetes.operator.job.autoscaler.catch-up.duration: 5m
-
pipeline.max-parallelism: "720"
```
