Skip to content

Fix class names in the codebase, cgroup, metrics and Kafka docs #9156

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
reiabreu merged 1 commit into from
Oct 3, 2026
+10 −10
Merged

Fix class names in the codebase, cgroup, metrics and Kafka docs #9156

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/Structure-of-the-codebase.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@ Here's a summary of the purpose of the main Java packages:

[org.apache.storm.daemon.Acker]({{page.git-blob-base}}/storm-client/src/jvm/org/apache/storm/daemon/Acker.java): Implementation of the "acker" bolt, which is a key part of how Storm guarantees data processing.

[org.apache.storm.daemon.DrpcServer]({{page.git-blob-base}}/storm-webapp/src/jvm/org/apache/storm/daemon/DrpcServer.java): Implementation of the DRPC server for use with DRPC topologies.
[org.apache.storm.daemon.drpc.DRPCServer]({{page.git-blob-base}}/storm-webapp/src/main/java/org/apache/storm/daemon/drpc/DRPCServer.java): Implementation of the DRPC server for use with DRPC topologies.

[org.apache.storm.event]({{page.git-blob-base}}/storm-server/src/jvm/org/apache/storm/event): Implements a simple asynchronous function executor. Used in various places in Nimbus and Supervisor to make functions execute in serial to avoid any race conditions.

Expand Down
12 changes: 6 additions & 6 deletions docs/cgroups_in_storm.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,13 +84,13 @@ CGroups can be used in conjunction with the Resource Aware Scheduler. CGroups w

CGroups not only can limit the amount of resources a worker has access to, but it can also help monitor the resource consumption of a worker. There are several metrics enabled by default that will check if the worker is a part of a CGroup and report corresponding metrics.

## CGroupCPU
## CGroupCpu

org.apache.storm.metrics2.cgroup.CGroupCPU reports metrics similar to org.apache.storm.metrics.sigar.CPUMetric, but for everything within the CGroup. It reports both user and system CPU usage in ms.
org.apache.storm.metrics2.cgroup.CGroupCpu reports metrics similar to org.apache.storm.metrics.sigar.CPUMetric, but for everything within the CGroup. It reports both user and system CPU usage in ms.

```
"CGroupCPU.user-ms": number
"CGroupCPU.sys-ms": number
"CGroupCpu.user-ms": number
"CGroupCpu.sys-ms": number
```

CGroup reports these as CLK_TCK counts, and not milliseconds so the accuracy is determined by what CLK_TCK is set to. On most systems it is 100 times a second so at most the accuracy is 10 ms.
Expand Down Expand Up @@ -142,8 +142,8 @@ These metrics can be very helpful in debugging what has happened or is happening

### CPU

CPU guarantees under storm are soft. It means that a worker can ea sly go over their guarantee if there is free CPU available. To detect that your worker is using more CPU then it requested you can sum up the values in CGroupCPU and compare them to CGroupCpuGuarantee.
If CGroupCPU is consistently higher then or equal to CGroupCpuGuarantee you probably want to look at requesting more CPU as your worker may be starved for CPU if more load is placed on the cluster. Being equal to CGroupCpuGuarantee means your worker may already
CPU guarantees under storm are soft. It means that a worker can ea sly go over their guarantee if there is free CPU available. To detect that your worker is using more CPU then it requested you can sum up the values in CGroupCpu and compare them to CGroupCpuGuarantee.
If CGroupCpu is consistently higher then or equal to CGroupCpuGuarantee you probably want to look at requesting more CPU as your worker may be starved for CPU if more load is placed on the cluster. Being equal to CGroupCpuGuarantee means your worker may already
be throttled. If the used CPU is much smaller than CGroupCpuGuarantee then you are probably wasting resources and may want to reduce your CPU ask.

If you do have high CPU you probably also want to check out the GC metrics and/or the GC log for your worker. Memory pressure on the heap can result in increased CPU as garbage collection happens.
Expand Down
2 changes: 1 addition & 1 deletion docs/metrics_v2.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -118,7 +118,7 @@ is determined by the `report.period` and `report.period.units` parameters.

Reporters can also be configured with an optional filter that determines which metrics get reported. Storm includes the
`org.apache.storm.metrics2.filters.RegexFilter` filter which uses a regular expression to determine which metrics get
reported. Custom filters can be created by implementing the `org.apache.storm.metrics2.filters.StormMetricFilter`
reported. Custom filters can be created by implementing the `org.apache.storm.metrics2.filters.StormMetricsFilter`
interface:

```java
Expand Down
4 changes: 2 additions & 2 deletions docs/storm-kafka-client.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,8 @@ Apache Kafka versions 0.10.1.0 onwards. Please be aware that [KAFKA-7044](https:

## Writing to Kafka as part of your topology
You can create an instance of org.apache.storm.kafka.bolt.KafkaBolt and attach it as a component to your topology or if you
are using trident you can use org.apache.storm.kafka.trident.TridentState, org.apache.storm.kafka.trident.TridentStateFactory and
org.apache.storm.kafka.trident.TridentKafkaUpdater.
are using trident you can use org.apache.storm.kafka.trident.TridentKafkaState, org.apache.storm.kafka.trident.TridentKafkaStateFactory and
org.apache.storm.kafka.trident.TridentKafkaStateUpdater.

You need to provide implementations for the following 2 interfaces

Expand Down
Loading