[CELEBORN-1789][DOC] Document on Java Columnar Shuffle

### What changes were proposed in this pull request?
Introduction to Celeborn's Java Columnar Shuffle

### Why are the changes needed?
Introduction to Celeborn's Java Columnar Shuffle

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
CI

Closes #3010 from kerwin-zk/CELEBORN-1789.

Authored-by: xiyu.zk <xiyu.zk@alibaba-inc.com>
Signed-off-by: mingji <fengmingxiao.fmx@alibaba-inc.com>

docs/developers/java-columnar-shuffle.md

@@ -0,0 +1,56 @@
+---
+license: |
+  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
+
+      https://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.
+---
+
+# Introduction to Celeborn's Java Columnar Shuffle
+
+## Overview
+
+Celeborn presents a Java Columnar Shuffle designed to enhance performance and efficiency in SparkSQL and DataFrame operations. This innovative approach leverages a columnar format for shuffle operations, achieving a higher compression rate than traditional Row-based Shuffle methods. This improvement leads to significant savings in disk space usage during shuffle operations.
+
+## Benefits
+
+- **High Compression Rate**: By organizing data into a columnar format, this feature significantly increases the compression ratio, reducing the disk space required for Shuffle data. 
+However, enabling this optimization incurs overhead for row-to-column and column-to-row transformations. If disk space is a higher priority, it is recommended to enable this feature.
+If performance is a higher priority, it is advisable to weigh the trade-offs.
+
+## Configuration
+
+To leverage Celeborn's Java Columnar Shuffle, you need to apply a patch and configure certain settings in Spark 3.x. Follow the steps below for implementation:
+
+### Step 1: Apply this patch to obtain the schema information for shuffle
+
+1. Obtain the `https://github.com/apache/celeborn/tree/main/assets/spark-patch/Celeborn_Columnar_Shuffle_spark3.patch` file that contains the modifications needed for enabling Columnar Shuffle in Spark 3.x.
+2. Navigate to your Spark source directory.
+3. Apply the patch.
+
+### Step 2: Configure Celeborn Settings
+
+To enable Columnar Shuffle, adjust the following configurations in your Spark application:
+Open the Spark configuration file or set these parameters in your Spark application.
+Add the following configuration settings:
+
+```
+spark.celeborn.columnarShuffle.enabled true
+spark.celeborn.columnarShuffle.encoding.dictionary.enabled true
+```
+
+If you require further performance optimization, consider enabling code generation with:
+
+```
+spark.celeborn.columnarShuffle.codegen.enabled true
+```

mkdocs.yml

@@ -95,6 +95,7 @@ nav:
         - Overview: developers/client.md
         - LifecycleManager: developers/lifecyclemanager.md
         - ShuffleClient: developers/shuffleclient.md
+        - JavaColumnarShuffle: developers/java-columnar-shuffle.md
       - Configuration: developers/configuration.md
       - Fault Tolerant: developers/faulttolerant.md
       - Worker Exclusion: developers/workerexclusion.md