This is an automated email from the ASF dual-hosted git repository.
dongjoon pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/spark-kubernetes-operator.git
The following commit(s) were added to refs/heads/main by this push:
new 736d256 [SPARK-52292] Use `super-linter` for markdown files
736d256 is described below
commit 736d256a86d79d6b087f03ef2ff76250b47efe10
Author: Dongjoon Hyun <[email protected]>
AuthorDate: Sat May 24 09:30:21 2025 -0700
[SPARK-52292] Use `super-linter` for markdown files
### What changes were proposed in this pull request?
This PR aims to apply `super-linter` for markdown files.
### Why are the changes needed?
For consistency.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs with the newly added `super-linter` test.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #224 from dongjoon-hyun/SPARK-52292.
Authored-by: Dongjoon Hyun <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
---
.github/workflows/build_and_test.yml | 8 ++++++
.markdownlint.yaml | 18 ++++++++++++++
.markdownlintignore | 18 ++++++++++++++
README.md | 37 +++++++++++++--------------
docs/architecture.md | 38 ++++++++++++++--------------
docs/configuration.md | 34 ++++++++++++-------------
docs/operations.md | 12 +++++----
docs/spark_custom_resources.md | 48 +++++++++++++++---------------------
8 files changed, 126 insertions(+), 87 deletions(-)
diff --git a/.github/workflows/build_and_test.yml
b/.github/workflows/build_and_test.yml
index ee9f474..de95b82 100644
--- a/.github/workflows/build_and_test.yml
+++ b/.github/workflows/build_and_test.yml
@@ -147,6 +147,14 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
+ with:
+ fetch-depth: 0
+ - name: Super-Linter
+ uses:
super-linter/super-linter@12150456a73e248bdc94d0794898f94e23127c88
+ env:
+ DEFAULT_BRANCH: main
+ VALIDATE_MARKDOWN: true
+ GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Set up JDK 17
uses: actions/setup-java@v4
with:
diff --git a/.markdownlint.yaml b/.markdownlint.yaml
new file mode 100644
index 0000000..11c7a48
--- /dev/null
+++ b/.markdownlint.yaml
@@ -0,0 +1,18 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+MD013: false
diff --git a/.markdownlintignore b/.markdownlintignore
new file mode 100644
index 0000000..8169fbb
--- /dev/null
+++ b/.markdownlintignore
@@ -0,0 +1,18 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+docs/config_properties.md
diff --git a/README.md b/README.md
index d2af819..b998b38 100644
--- a/README.md
+++ b/README.md
@@ -12,13 +12,14 @@ aims to extend K8s resource manager to manage Apache Spark
applications via
## Install Helm Chart
Apache Spark provides a Helm Chart.
+
- <https://apache.github.io/spark-kubernetes-operator/>
-
<https://artifacthub.io/packages/helm/spark-kubernetes-operator/spark-kubernetes-operator/>
-```
-$ helm repo add spark-kubernetes-operator
https://apache.github.io/spark-kubernetes-operator
-$ helm repo update
-$ helm install spark-kubernetes-operator
spark-kubernetes-operator/spark-kubernetes-operator
+```bash
+helm repo add spark-kubernetes-operator
https://apache.github.io/spark-kubernetes-operator
+helm repo update
+helm install spark-kubernetes-operator
spark-kubernetes-operator/spark-kubernetes-operator
```
## Building Spark K8s Operator
@@ -27,25 +28,25 @@ Spark K8s Operator is built using Gradle.
To build, run:
```bash
-$ ./gradlew build -x test
+./gradlew build -x test
```
## Running Tests
```bash
-$ ./gradlew build
+./gradlew build
```
## Build Docker Image
```bash
-$ ./gradlew buildDockerImage
+./gradlew buildDockerImage
```
-## Install Helm Chart
+## Install Helm Chart from the source code
```bash
-$ helm install spark -f build-tools/helm/spark-kubernetes-operator/values.yaml
build-tools/helm/spark-kubernetes-operator/
+helm install spark -f build-tools/helm/spark-kubernetes-operator/values.yaml
build-tools/helm/spark-kubernetes-operator/
```
## Run Spark Pi App
@@ -97,14 +98,14 @@ sparkcluster.spark.apache.org "prod" deleted
## Run Spark Pi App on Apache YuniKorn scheduler
-If you have not yet done so, follow [YuniKorn
docs](https://yunikorn.apache.org/docs/#install) to install the latest version:
+If you have not yet done so, follow [YuniKorn
docs](https://yunikorn.apache.org/docs/#install) to install the latest version:
```bash
-$ helm repo add yunikorn https://apache.github.io/yunikorn-release
+helm repo add yunikorn https://apache.github.io/yunikorn-release
-$ helm repo update
+helm repo update
-$ helm install yunikorn yunikorn/yunikorn --namespace yunikorn --version 1.6.3
--create-namespace --set embedAdmissionController=false
+helm install yunikorn yunikorn/yunikorn --namespace yunikorn --version 1.6.3
--create-namespace --set embedAdmissionController=false
```
Submit a Spark app to YuniKorn enabled cluster:
@@ -134,7 +135,7 @@ sparkapplication.spark.apache.org "pi-on-yunikorn" deleted
Check the existing Spark applications and clusters. If exists, delete them.
-```
+```bash
$ kubectl get sparkapp
No resources found in default namespace.
@@ -144,12 +145,12 @@ No resources found in default namespace.
Remove HelmChart and CRDs.
-```
-$ helm uninstall spark-kubernetes-operator
+```bash
+helm uninstall spark-kubernetes-operator
-$ kubectl delete crd sparkapplications.spark.apache.org
+kubectl delete crd sparkapplications.spark.apache.org
-$ kubectl delete crd sparkclusters.spark.apache.org
+kubectl delete crd sparkclusters.spark.apache.org
```
## Contributing
diff --git a/docs/architecture.md b/docs/architecture.md
index 0539355..040db9f 100644
--- a/docs/architecture.md
+++ b/docs/architecture.md
@@ -23,10 +23,10 @@ under the License.
deployment lifecycle of Spark applications and clusters. The Operator can be
installed on Kubernetes
cluster(s) using Helm. In most production environments it is typically
deployed in a designated
namespace and controls Spark workload in one or more managed namespaces.
-Spark Operator enables user to describe Spark application(s) or cluster(s) as
-[Custom
Resources](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/).
+Spark Operator enables user to describe Spark application(s) or cluster(s) as
+[Custom
Resources](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/).
-The Operator continuously tracks events related to the Spark custom resources
in its reconciliation
+The Operator continuously tracks events related to the Spark custom resources
in its reconciliation
loops:
For SparkApplications:
@@ -43,39 +43,39 @@ For SparkClusters:
* Operator releases all Spark-cluster owned resources to cluster upon failure
The Operator is built with the [Java Operator
SDK](https://javaoperatorsdk.io/) for
-launching Spark deployments and submitting jobs under the hood. It also uses
+launching Spark deployments and submitting jobs under the hood. It also uses
[fabric8](https://fabric8.io/) client to interact with Kubernetes API Server.
## Application State Transition
-[<img
src="resources/application_state_machine.png">](resources/application_state_machine.png)
+[](resources/application_state_machine.png)
* Spark applications are expected to run from submitted to succeeded before
releasing resources
* User may configure the app CR to time-out after given threshold of time if
it cannot reach healthy
- state after given threshold. The timeout can be configured for different
lifecycle stages,
+ state after given threshold. The timeout can be configured for different
lifecycle stages,
when driver starting and when requesting executor pods. To update the
default threshold,
- configure `.spec.applicationTolerations.applicationTimeoutConfig` for the
application.
-* K8s resources created for an application would be deleted as the final stage
of the application
+ configure `.spec.applicationTolerations.applicationTimeoutConfig` for the
application.
+* K8s resources created for an application would be deleted as the final stage
of the application
lifecycle by default. This is to ensure resource quota release for completed
applications.
-* It is also possible to retain the created k8s resources for debug or audit
purpose. To do so,
- user may set `.spec.applicationTolerations.resourceRetainPolicy` to
`OnFailure` to retain
- resources upon application failure, or set to `Always` to retain resources
regardless of
+* It is also possible to retain the created k8s resources for debug or audit
purpose. To do so,
+ user may set `.spec.applicationTolerations.resourceRetainPolicy` to
`OnFailure` to retain
+ resources upon application failure, or set to `Always` to retain resources
regardless of
application final state.
- - This controls the behavior of k8s resources created by Operator for the
application, including
- driver pod, config map, service, and PVC(if enabled). This does not
apply to resources created
+ * This controls the behavior of k8s resources created by Operator for the
application, including
+ driver pod, config map, service, and PVC(if enabled). This does not
apply to resources created
by driver (for example, executor pods). User may configure SparkConf to
- include `spark.kubernetes.executor.deleteOnTermination` for executor
retention. Please refer
+ include `spark.kubernetes.executor.deleteOnTermination` for executor
retention. Please refer
[Spark
docs](https://spark.apache.org/docs/latest/running-on-kubernetes.html) for
details.
- - The created k8s resources have `ownerReference` to their related
`SparkApplication` custom
+ * The created k8s resources have `ownerReference` to their related
`SparkApplication` custom
resource, such that they could be garbage collected when the
`SparkApplication` is deleted.
- - Please be advised that k8s resources would not be retained if the
application is configured to
- restart. This is to avoid resource quota usage increase unexpectedly or
resource conflicts
+ * Please be advised that k8s resources would not be retained if the
application is configured to
+ restart. This is to avoid resource quota usage increase unexpectedly or
resource conflicts
among multiple attempts.
## Cluster State Transition
-[<img
src="resources/cluster_state_machine.png">](resources/application_state_machine.png)
+[](resources/application_state_machine.png)
* Spark clusters are expected to be always running after submitted.
-* Similar to Spark applications, K8s resources created for a cluster would be
deleted as the final
+* Similar to Spark applications, K8s resources created for a cluster would be
deleted as the final
stage of the cluster lifecycle by default.
diff --git a/docs/configuration.md b/docs/configuration.md
index bafd3c5..d13a82c 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -29,20 +29,20 @@ Spark Operator supports different ways to configure the
behavior:
files](../build-tools/helm/spark-kubernetes-operator/values.yaml).
* **System Properties** : when provided as system properties (e.g. via -D
options to the
operator JVM), it overrides the values provided in property file.
-* **Hot property loading** : when enabled, a
- [configmap](https://kubernetes.io/docs/concepts/configuration/configmap/)
would be created with
- the operator in the same namespace. Operator can monitor updates performed
on the configmap. Hot
+* **Hot property loading** : when enabled, a
+ [configmap](https://kubernetes.io/docs/concepts/configuration/configmap/)
would be created with
+ the operator in the same namespace. Operator can monitor updates performed
on the configmap. Hot
properties reloading takes higher precedence comparing with default
properties override.
- - An example use case: operator use hot properties to figure the list of
namespace(s) to
+ * An example use case: operator use hot properties to figure the list of
namespace(s) to
operate Spark applications. The hot properties config map can be updated
and
maintained by user or additional microservice to tune the operator
behavior without
rebooting it.
- - Please be advised that not all properties can be hot-loaded and honored
at runtime.
+ * Please be advised that not all properties can be hot-loaded and honored at
runtime.
Refer the list of [supported properties](./config_properties.md) for
more details.
To enable hot properties loading, update the **helm chart values file** with
-```
+```yaml
operatorConfiguration:
spark-operator.properties: |+
spark.operator.dynamic.config.enabled=true
@@ -60,18 +60,18 @@ the [Dropwizard Metrics
Library](https://metrics.dropwizard.io/4.2.25/). Note th
does not have Spark UI, MetricsServlet
and PrometheusServlet from org.apache.spark.metrics.sink package are not
supported. If you are
interested in Prometheus metrics exporting, please take a look at below
-section [Forward Metrics to Prometheus](#Forward-Metrics-to-Prometheus)
+section [Forward Metrics to Prometheus](#forward-metrics-to-prometheus)
### JVM Metrics
Spark Operator collects JVM metrics
via [Codahale JVM
Metrics](https://javadoc.io/doc/com.codahale.metrics/metrics-jvm/latest/index.html)
-- BufferPoolMetricSet
-- FileDescriptorRatioGauge
-- GarbageCollectorMetricSet
-- MemoryUsageGaugeSet
-- ThreadStatesGaugeSet
+* BufferPoolMetricSet
+* FileDescriptorRatioGauge
+* GarbageCollectorMetricSet
+* MemoryUsageGaugeSet
+* ThreadStatesGaugeSet
### Kubernetes Client Metrics
@@ -81,15 +81,15 @@ via [Codahale JVM
Metrics](https://javadoc.io/doc/com.codahale.metrics/metrics-j
| kubernetes.client.http.response | Meter |
Tracking the rates of HTTP response from the Kubernetes API Server
|
| kubernetes.client.http.response.failed | Meter |
Tracking the rates of HTTP requests which have no response from the Kubernetes
API Server |
| kubernetes.client.http.response.latency.nanos | Histograms |
Measures the statistical distribution of HTTP response latency from the
Kubernetes API Server |
-| kubernetes.client.http.response.<ResponseCode> | Meter |
Tracking the rates of HTTP response based on response code from the Kubernetes
API Server |
-| kubernetes.client.http.request.<RequestMethod> | Meter |
Tracking the rates of HTTP request based type of method to the Kubernetes API
Server |
+| kubernetes.client.http.response.`ResponseCode` | Meter |
Tracking the rates of HTTP response based on response code from the Kubernetes
API Server |
+| kubernetes.client.http.request.`RequestMethod` | Meter |
Tracking the rates of HTTP request based type of method to the Kubernetes API
Server |
| kubernetes.client.http.response.1xx | Meter |
Tracking the rates of HTTP Code 1xx responses (informational) received from the
Kubernetes API Server per response code. |
| kubernetes.client.http.response.2xx | Meter |
Tracking the rates of HTTP Code 2xx responses (success) received from the
Kubernetes API Server per response code. |
| kubernetes.client.http.response.3xx | Meter |
Tracking the rates of HTTP Code 3xx responses (redirection) received from the
Kubernetes API Server per response code. |
| kubernetes.client.http.response.4xx | Meter |
Tracking the rates of HTTP Code 4xx responses (client error) received from the
Kubernetes API Server per response code. |
| kubernetes.client.http.response.5xx | Meter |
Tracking the rates of HTTP Code 5xx responses (server error) received from the
Kubernetes API Server per response code. |
-| kubernetes.client.<ResourceName>.<Method> | Meter |
Tracking the rates of HTTP request for a combination of one Kubernetes resource
and one http method |
-| kubernetes.client.<NamespaceName>.<ResourceName>.<Method> | Meter |
Tracking the rates of HTTP request for a combination of one namespace-scoped
Kubernetes resource and one http method |
+| kubernetes.client.`ResourceName`.`Method` | Meter |
Tracking the rates of HTTP request for a combination of one Kubernetes resource
and one http method |
+| kubernetes.client.`NamespaceName`.`ResourceName`.`Method` | Meter |
Tracking the rates of HTTP request for a combination of one namespace-scoped
Kubernetes resource and one http method |
### Forward Metrics to Prometheus
@@ -141,4 +141,4 @@ kubectl port-forward --address 0.0.0.0
pod/prometheus-server-654bc74fc9-8hgkb 8
open your browser with address `localhost:8080`. Click on Status Targets tab,
you should be able
to find target as below.
-[<img src="resources/prometheus.png">](resources/prometheus.png)
+[](resources/prometheus.png)
diff --git a/docs/operations.md b/docs/operations.md
index 80fba14..f16fa4a 100644
--- a/docs/operations.md
+++ b/docs/operations.md
@@ -17,15 +17,17 @@ specific language governing permissions and limitations
under the License.
-->
-### Compatibility
+# Operations
+
+## Compatibility
- Java 17, 21 and 24
- Kubernetes version compatibility:
- + k8s version >= 1.30 is recommended. Operator attempts to be API
compatible as possible, but
+ - k8s version >= 1.30 is recommended. Operator attempts to be API compatible
as possible, but
patch support will not be performed on k8s versions that reached EOL.
- Spark versions 3.5 or above.
-### Spark Application Namespaces
+## Spark Application Namespaces
By default, Spark applications are created in the same namespace as the
operator deployment.
You many also configure the chart deployment to add necessary RBAC resources
for
@@ -38,7 +40,7 @@ in `values.yaml`) for the Helm chart.
To override single parameters you can use `--set`, for example:
-```
+```bash
helm install --set image.repository=<my_registory>/spark-kubernetes-operator \
-f build-tools/helm/spark-kubernetes-operator/values.yaml \
build-tools/helm/spark-kubernetes-operator/
@@ -47,7 +49,7 @@ helm install --set
image.repository=<my_registory>/spark-kubernetes-operator \
You can also provide multiple custom values file by using the `-f` flag, the
latest takes
higher precedence:
-```
+```bash
helm install spark-kubernetes-operator \
-f build-tools/helm/spark-kubernetes-operator/values.yaml \
-f my_values.yaml \
diff --git a/docs/spark_custom_resources.md b/docs/spark_custom_resources.md
index 62f1ff6..9e34dbe 100644
--- a/docs/spark_custom_resources.md
+++ b/docs/spark_custom_resources.md
@@ -17,21 +17,21 @@ specific language governing permissions and limitations
under the License.
-->
-## Spark Operator API
+# Spark Operator API
-The core user facing API of the Spark Kubernetes Operator is the
`SparkApplication` and
-`SparkCluster` Custom Resources Definition (CRD). Spark custom resource
extends
+The core user facing API of the Spark Kubernetes Operator is the
`SparkApplication` and
+`SparkCluster` Custom Resources Definition (CRD). Spark custom resource extends
standard k8s API, defines Spark Application spec and tracks status.
Once the Spark Operator is installed and running in your Kubernetes
environment, it will
-continuously watch SparkApplication(s) and SparkCluster(s) submitted, via k8s
API client or
+continuously watch SparkApplication(s) and SparkCluster(s) submitted, via k8s
API client or
kubectl by the user, orchestrate secondary resources (pods, configmaps .etc).
Please check out the [quickstart](../README.md) as well for installing
operator.
## SparkApplication
-SparkApplication can be defined in YAML format. User may configure the
application entrypoint
+SparkApplication can be defined in YAML format. User may configure the
application entrypoint
and configurations. Let's start with the [Spark-Pi
example](../examples/pi.yaml):
```yaml
@@ -59,7 +59,7 @@ spec:
After application is submitted, Operator will add status information to your
application based on
the observed state:
-```
+```bash
kubectl get sparkapp pi -o yaml
```
@@ -101,8 +101,8 @@ refer [Spark
doc](https://spark.apache.org/docs/latest/running-on-kubernetes.htm
## Enable Additional Ingress for Driver
Operator may create
[Ingress](https://kubernetes.io/docs/concepts/services-networking/ingress/) for
-Spark driver of running applications on demand. For example, to expose Spark
UI - which is by
-default enabled on driver port 4040, you may configure
+Spark driver of running applications on demand. For example, to expose Spark
UI - which is by
+default enabled on driver port 4040, you may configure
```yaml
spec:
@@ -132,16 +132,16 @@ spec:
number: 80
```
-Spark Operator by default would populate the `.spec.selector` field of the
created Service to match
+Spark Operator by default would populate the `.spec.selector` field of the
created Service to match
the driver labels. If `.ingressSpec.rules` is not provided, Spark Operator
would also populate one
-default rule backed by the associated Service. It's recommended to always
provide the ingress spec
-to make sure it's compatible with your
+default rule backed by the associated Service. It's recommended to always
provide the ingress spec
+to make sure it's compatible with your
[IngressController](https://kubernetes.io/docs/concepts/services-networking/ingress-controllers/).
## Create and Mount ConfigMap
-It is possible to ask operator to create configmap so they can be used by
driver and/or executor
-pods on the fly. `configMapSpecs` allows you to specify the desired metadata
and data as string
+It is possible to ask operator to create configmap so they can be used by
driver and/or executor
+pods on the fly. `configMapSpecs` allows you to specify the desired metadata
and data as string
literals for the configmap(s) to be created.
```yaml
@@ -155,9 +155,9 @@ spec:
Like other app-specific resources, the created configmap has owner reference
to Spark driver and
therefore shares the same lifecycle and garbage collection mechanism with the
associated app.
-This feature can be used to create lightweight override config files for given
Spark app. For
+This feature can be used to create lightweight override config files for given
Spark app. For
example, below snippet would create and mount a configmap with metrics
property file, then use it
-in SparkConf:
+in SparkConf:
```yaml
spec:
@@ -201,17 +201,11 @@ with non-zero code), Spark Operator introduces a few
different failure state for
app status monitoring at high level, and for ease of setting up different
handlers if users
are creating / managing SparkApplications with external microservices or
workflow engines.
-
Spark Operator recognizes "infrastructure failure" in the best effort way. It
is possible to
configure different restart policy on general failure(s) vs. on potential
infrastructure
failure(s). For example, you may configure the app to restart only upon
infrastructure
-failures. If Spark application fails as a result of
-
-```
-DriverStartTimedOut
-ExecutorsStartTimedOut
-SchedulingFailure
-```
+failures. If Spark application fails as a result of `DriverStartTimedOut`,
+`ExecutorsStartTimedOut`, `SchedulingFailure`.
It is more likely that the app failed as a result of infrastructure reason(s),
including
scenarios like driver or executors cannot be scheduled or cannot initialize in
configured
@@ -242,9 +236,8 @@ restartConfig:
### Timeouts
-It's possible to configure applications to be proactively terminated and
resubmitted in particular
-cases to avoid resource deadlock.
-
+It's possible to configure applications to be proactively terminated and
resubmitted in particular
+cases to avoid resource deadlock.
| Field
| Type | Default Value | Descritpion
|
|-----------------------------------------------------------------------------------------|---------|---------------|--------------------------------------------------------------------------------------------------------------------|
@@ -254,7 +247,6 @@ cases to avoid resource deadlock.
|
.spec.applicationTolerations.applicationTimeoutConfig.driverReadyTimeoutMillis
| integer | 300000 | Time to wait for driver reaches ready
state. |
|
.spec.applicationTolerations.applicationTimeoutConfig.terminationRequeuePeriodMillis
| integer | 2000 | Back-off time when releasing resource need to
be re-attempted for application. |
-
### Instance Config
Instance Config helps operator to decide whether an application is running
healthy. When
@@ -318,5 +310,5 @@ worker instances would be deployed as
[StatefulSets](https://kubernetes.io/docs/
and exposed via k8s
[service(s)](https://kubernetes.io/docs/concepts/services-networking/service/).
Like Pod Template Support for Applications, it's also possible to submit
template(s) for the Spark
-instances for `SparkCluster` to configure spec that's not supported via
SparkConf. It's worth notice
+instances for `SparkCluster` to configure spec that's not supported via
SparkConf. It's worth notice
that Spark may overwrite certain fields.
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