Update apache-spark-performance.md

Author: santhoshravindran7

articles/synapse-analytics/spark/apache-spark-performance.md

@@ -59,8 +59,10 @@ Spark operates by placing data in memory, so managing memory resources is a key
 * Prefer smaller data partitions and account for data size, types, and distribution in your partitioning strategy.
 * In Synapse Spark (Runtime 3.1 or higher) you get Kryo data serialization enabled by default [Kryo data serialization](https://github.com/EsotericSoftware/kryo).
 * You can customize the kryoserializer buffer size using Spark configuration based on your workload requirements
+
 `// Set the desired property`
 `spark.conf.set("spark.kryoserializer.buffer.max", "256m") `
+
 * Monitor and tune Spark configuration settings.
 
 For your reference, the Spark memory structure and some key executor memory parameters are shown in the next image.