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+# Shuffle data reuse
+
+Shuffle data reuse is a feature that writes Spark shuffle data to a shared remote filesystem, such as S3.
+This allows reusing shuffle data from failed Spark tasks avoiding task retries. 
+This feature is also useful with dynamic allocation enabled, 
+as it allows scaling down Spark executors that are kept running solely because of the data they contain.
+Reusing the shuffle data can save time and resources.
+
+## Configuration
+
+To enable shuffle data reuse, set the following configuration in your Spark application:
+
+```json
+{
+  "shuffle": {
+    "enabled": "true",
+    "rootDir": "s3a://<bucket>/path/to/shuffle"
+  }
+}
+```
+
+The `shuffle.rootdir` configuration is the location where the shuffle data will be written.
+The shuffle reuse feature uses hadoop filesystem to write the shuffle data, and as such supports any filesystem that hadoop supports.
+The rootdir option can be a local path, HDFS path, or any other hadoop supported filesystem.
+A shared remote drive such as FSx or S3 CSI, must be mounted on all the executors in the cluster when using a local path.
+
+For instance
+
+```json
+{
+  "shuffle": {
+    "rootDir": "/opt/spark/work-dir/shuffle"
+  },
+  "volumes": [
+    {
+      "name": "spark-data",
+      "persistentVolumeClaim": {
+        "claimName": "s3-claim"
+      }
+    }
+  ],
+  "driver": {
+    "volumeMounts": [
+      {
+        "mountPath": "/opt/spark/work-dir/shuffle",
+        "name": "spark-data"
+      }
+    ]
+  },
+  "executor": {
+    "volumeMounts": [
+      {
+        "mountPath": "/opt/spark/work-dir/shuffle",
+        "name": "spark-data"
+      }
+    ]
+  }
+}
+```
+
+## Limitations
+
+- The shuffle data reuse feature is only available for Spark 3.2 and later.
+- Preferably set the spark.dynamicAllocation.shuffleTracking.enabled to false when using shuffle data reuse feature.
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