[SPARK-43364][SS][DOCS] Add docs for RocksDB state store memory management

### What changes were proposed in this pull request?
Add docs for RocksDB state store memory management

### Why are the changes needed?
Docs only change

### Does this PR introduce _any_ user-facing change?
N/A

### How was this patch tested?
N/A

Closes #41042 from anishshri-db/task/SPARK-43364.

Authored-by: Anish Shrigondekar <[email protected]>
Signed-off-by: Jungtaek Lim <[email protected]>

Author: anishshri-db

docs/structured-streaming-programming-guide.md

@@ -2360,8 +2360,35 @@ Here are the configs regarding to RocksDB instance of the state store provider:
     <td>The maximum number of MemTables in RocksDB, both active and immutable. Value of -1 means that RocksDB internal default values will be used</td>
     <td>-1</td>
   </tr>
+  <tr>
+    <td>spark.sql.streaming.stateStore.rocksdb.boundedMemoryUsage</td>
+    <td>Whether total memory usage for RocksDB state store instances on a single node is bounded.</td>
+    <td>false</td>
+  </tr>
+  <tr>
+    <td>spark.sql.streaming.stateStore.rocksdb.maxMemoryUsageMB</td>
+    <td>Total memory limit in MB for RocksDB state store instances on a single node.</td>
+    <td>500</td>
+  </tr>
+  <tr>
+    <td>spark.sql.streaming.stateStore.rocksdb.writeBufferCacheRatio</td>
+    <td>Total memory to be occupied by write buffers as a fraction of memory allocated across all RocksDB instances on a single node using maxMemoryUsageMB.</td>
+    <td>0.5</td>
+  </tr>
+  <tr>
+    <td>spark.sql.streaming.stateStore.rocksdb.highPriorityPoolRatio</td>
+    <td>Total memory to be occupied by blocks in high priority pool as a fraction of memory allocated across all RocksDB instances on a single node using maxMemoryUsageMB.</td>
+    <td>0.1</td>
+  </tr>
 </table>
 
+##### RocksDB State Store Memory Management
+RocksDB allocates memory for different objects such as memtables, block cache and filter/index blocks. If left unbounded, RocksDB memory usage across multiple instances could grow indefinitely and potentially cause OOM (out-of-memory) issues.
+RocksDB provides a way to limit the memory usage for all DB instances running on a single node by using the write buffer manager functionality.
+If you want to cap RocksDB memory usage in your Spark Structured Streaming deployment, this feature can be enabled by setting the `spark.sql.streaming.stateStore.rocksdb.boundedMemoryUsage` config to `true`.
+You can also determine the max allowed memory for RocksDB instances by setting the `spark.sql.streaming.stateStore.rocksdb.maxMemoryUsageMB` value to a static number or as a fraction of the physical memory available on the node.
+Limits for individual RocksDB instances can also be configured by setting `spark.sql.streaming.stateStore.rocksdb.writeBufferSizeMB` and `spark.sql.streaming.stateStore.rocksdb.maxWriteBufferNumber` to the required values. By default, RocksDB internal defaults are used for these settings.
+
 ##### Performance-aspect considerations
 
 1. You may want to disable the track of total number of rows to aim the better performance on RocksDB state store.