Merge pull request #516 from j3-signalroom/github_issue-515

Resolved #515.

java/app/src/main/java/kickstarter/AvroDataGeneratorApp.java

@@ -71,18 +71,30 @@ public static void main(String[] args) throws Exception {
 		// --- Create a blank Flink execution environment (a.k.a. the Flink job graph -- the DAG).
 		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(config);
 
-        // --- Enable checkpointing every 5000 milliseconds (5 seconds).
+        /*
+         * Enable checkpointing every 5000 milliseconds (5 seconds).  Note, consider the
+         * resource cost of checkpointing frequency, as short intervals can lead to higher
+         * I/O and CPU overhead.  Proper tuning of checkpoint intervals depends on the
+         * state size, latency requirements, and resource constraints.
+         */
         env.enableCheckpointing(5000);
 
         /*
-         * Set timeout to 60 seconds
-         * The maximum amount of time a checkpoint attempt can take before being discarded.
+         * Set checkpoint timeout to 60 seconds, which is the maximum amount of time a
+         * checkpoint attempt can take before being discarded.  Note, setting an appropriate
+         * checkpoint timeout helps maintain a balance between achieving exactly-once semantics
+         * and avoiding excessive delays that can impact real-time stream processing performance.
          */
         env.getCheckpointConfig().setCheckpointTimeout(60000);
 
         /*
          * Set the maximum number of concurrent checkpoints to 1 (i.e., only one checkpoint
-         * is created at a time).
+         * is created at a time).  Note, this is useful for limiting resource usage and
+         * ensuring checkpoints do not interfere with each other, but may impact throughput
+         * if checkpointing is slow.  Adjust this setting based on the nature of your job,
+         * the size of the state, and available resources. If your environment has enough
+         * resources and you want to ensure faster recovery, you could increase the limit
+         * to allow multiple concurrent checkpoints.
          */
         env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
 

java/app/src/main/java/kickstarter/JsonDataGeneratorApp.java

@@ -61,18 +61,30 @@ public static void main(String[] args) throws Exception {
 		// --- Create a blank Flink execution environment (a.k.a. the Flink job graph -- the DAG).
 		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
 
-        // --- Enable checkpointing every 5000 milliseconds (5 seconds).
+        /*
+         * Enable checkpointing every 5000 milliseconds (5 seconds).  Note, consider the
+         * resource cost of checkpointing frequency, as short intervals can lead to higher
+         * I/O and CPU overhead.  Proper tuning of checkpoint intervals depends on the
+         * state size, latency requirements, and resource constraints.
+         */
         env.enableCheckpointing(5000);
 
         /*
-         * Set timeout to 60 seconds
-         * The maximum amount of time a checkpoint attempt can take before being discarded.
+         * Set checkpoint timeout to 60 seconds, which is the maximum amount of time a
+         * checkpoint attempt can take before being discarded.  Note, setting an appropriate
+         * checkpoint timeout helps maintain a balance between achieving exactly-once semantics
+         * and avoiding excessive delays that can impact real-time stream processing performance.
          */
         env.getCheckpointConfig().setCheckpointTimeout(60000);
 
         /*
          * Set the maximum number of concurrent checkpoints to 1 (i.e., only one checkpoint
-         * is created at a time).
+         * is created at a time).  Note, this is useful for limiting resource usage and
+         * ensuring checkpoints do not interfere with each other, but may impact throughput
+         * if checkpointing is slow.  Adjust this setting based on the nature of your job,
+         * the size of the state, and available resources. If your environment has enough
+         * resources and you want to ensure faster recovery, you could increase the limit
+         * to allow multiple concurrent checkpoints.
          */
         env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);