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[SPARK-49649][DOCS] Make docs/index.md up-to-date for 4.0.0 #48113

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[SPARK-49649][DOCS] Make docs/index.md up-to-date for 4.0.0 #48113

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[SPARK-49649][DOCS] Make `docs/index.md` up-to-date for 4.0.0
dongjoon-hyun Sep 13, 2024
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Update docs/index.md
dongjoon-hyun Sep 14, 2024
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14 changes: 8 additions & 6 deletions docs/index.md
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Expand Up @@ -34,9 +34,8 @@ source, visit [Building Spark](building-spark.html).

Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS), and it should run on any platform that runs a supported version of Java. This should include JVMs on x86_64 and ARM64. It's easy to run locally on one machine --- all you need is to have `java` installed on your system `PATH`, or the `JAVA_HOME` environment variable pointing to a Java installation.

Spark runs on Java 17/21, Scala 2.13, Python 3.8+, and R 3.5+.
When using the Scala API, it is necessary for applications to use the same version of Scala that Spark was compiled for.
For example, when using Scala 2.13, use Spark compiled for 2.13, and compile code/applications for Scala 2.13 as well.
Spark runs on Java 17/21, Scala 2.13, Python 3.9+, and R 3.5+ (Deprecated).
When using the Scala API, it is necessary for applications to use the same version of Scala that Spark was compiled for. Since Spark 4.0.0, it's Scala 2.13.
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@dongjoon-hyun dongjoon-hyun Sep 13, 2024

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We support only Scala 2.13.


# Running the Examples and Shell

Expand Down Expand Up @@ -110,7 +109,7 @@ options for deployment:
* [Spark Streaming](streaming-programming-guide.html): processing data streams using DStreams (old API)
* [MLlib](ml-guide.html): applying machine learning algorithms
* [GraphX](graphx-programming-guide.html): processing graphs
* [SparkR](sparkr.html): processing data with Spark in R
* [SparkR (Deprecated)](sparkr.html): processing data with Spark in R
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@dongjoon-hyun dongjoon-hyun Sep 13, 2024

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We deprecated SparkR.

* [PySpark](api/python/getting_started/index.html): processing data with Spark in Python
* [Spark SQL CLI](sql-distributed-sql-engine-spark-sql-cli.html): processing data with SQL on the command line

Expand All @@ -128,10 +127,13 @@ options for deployment:
* [Cluster Overview](cluster-overview.html): overview of concepts and components when running on a cluster
* [Submitting Applications](submitting-applications.html): packaging and deploying applications
* Deployment modes:
* [Amazon EC2](https://github.com/amplab/spark-ec2): scripts that let you launch a cluster on EC2 in about 5 minutes
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I moved this to the end of this list because the link is archived on 2017.

Screenshot 2024-09-13 at 15 59 26

* [Standalone Deploy Mode](spark-standalone.html): launch a standalone cluster quickly without a third-party cluster manager
* [YARN](running-on-yarn.html): deploy Spark on top of Hadoop NextGen (YARN)
* [Kubernetes](running-on-kubernetes.html): deploy Spark on top of Kubernetes
* [Kubernetes](running-on-kubernetes.html): deploy Spark apps on top of Kubernetes directly
* [Amazon EC2](https://github.com/amplab/spark-ec2): scripts that let you launch a cluster on EC2 in about 5 minutes
* [Spark Kubernetes Operator](https://github.com/apache/spark-kubernetes-operator):
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We support Spark Kubernetes Operator.

* [SparkApp](https://github.com/apache/spark-kubernetes-operator/blob/main/examples/pyspark-pi.yaml): deploy Spark apps on top of Kubernetes via [operator patterns](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/)
* [SparkCluster](https://github.com/apache/spark-kubernetes-operator/blob/main/examples/cluster-with-template.yaml): deploy Spark clusters on top of Kubernetes via [operator patterns](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/)

**Other Documents:**

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