review 2

src/java/org/apache/cassandra/db/compression/CompressionDictionaryScheduler.java

@@ -195,7 +195,7 @@ public void run()
                            cancelManualTraining();
                            if (throwable != null)
                            {
-                               logger.error("Manual dictionary training failed for {}.{}", keyspaceName, tableName, throwable);
+                               logger.error("Manual dictionary training failed for {}.{}: {}", keyspaceName, tableName, throwable.getMessage());
                            }
                            else
                            {

src/java/org/apache/cassandra/tools/NodeProbe.java

@@ -2753,7 +2753,7 @@ public long getCompressionDictionaryTrainingTotalSampleSize(String keyspace, Str
     private CompressionDictionaryManagerMBean getDictionaryManagerProxy(String keyspace, String table) throws IOException
     {
         // Construct table-specific MBean name
-        String mbeanName = "org.apache.cassandra.db.compression:type=CompressionDictionaryManager,keyspace=" + keyspace + ",table=" + table;
+        String mbeanName = CompressionDictionaryManagerMBean.MBEAN_NAME + ",keyspace=" + keyspace + ",table=" + table;
         try
         {
             ObjectName objectName = new ObjectName(mbeanName);

src/java/org/apache/cassandra/tools/nodetool/TrainCompressionDictionary.java

@@ -26,7 +26,10 @@
 
 import org.apache.cassandra.db.compression.ICompressionDictionaryTrainer.TrainingStatus;
 import org.apache.cassandra.db.compression.ManualTrainingOptions;
+import org.apache.cassandra.io.util.FileUtils;
 import org.apache.cassandra.tools.NodeProbe;
+import org.apache.cassandra.tools.nodetool.formatter.TableBuilder;
+import org.apache.cassandra.utils.Clock;
 import picocli.CommandLine.Command;
 import picocli.CommandLine.Option;
 import picocli.CommandLine.Parameters;
@@ -42,7 +45,7 @@ public class TrainCompressionDictionary extends AbstractCommand
     private String table;
 
     @Option(names = {"-d", "--max-sampling-duration"},
-    description = "Maximum time to collect samples before training dictionary (default: 600 seconds)")
+    description = "Maximum time to collect samples before training dictionary, in seconds. (default: 600)")
     private int maxSamplingDurationSeconds = 600;
 
     @Option(names = {"-r", "--sampling-rate"},
@@ -116,9 +119,9 @@ public void execute(NodeProbe probe)
                         "writing to new SSTable, you might consider running nodetool 'flush' along " +
                         "with this command to have chunk available for sampling)");
             long maxWaitMillis = TimeUnit.SECONDS.toMillis(maxSamplingDurationSeconds + 300); // Add 5 minutes for training
-            long startTime = System.currentTimeMillis();
+            long startTime = Clock.Global.currentTimeMillis();
 
-            while (System.currentTimeMillis() - startTime < maxWaitMillis)
+            while (Clock.Global.currentTimeMillis() - startTime < maxWaitMillis)
             {
                 String statusStr = probe.getCompressionDictionaryTrainingStatus(keyspace, table);
                 TrainingStatus status = TrainingStatus.valueOf(statusStr);
@@ -136,7 +139,7 @@ else if (TrainingStatus.FAILED == status)
                 // Display meaningful statistics
                 long sampleCount = probe.getCompressionDictionaryTrainingSampleCount(keyspace, table);
                 long totalSampleSize = probe.getCompressionDictionaryTrainingTotalSampleSize(keyspace, table);
-                long elapsedSeconds = (System.currentTimeMillis() - startTime) / 1000;
+                long elapsedSeconds = (Clock.Global.currentTimeMillis() - startTime) / 1000;
                 double sampleSizeMB = totalSampleSize / (1024.0 * 1024.0);
 
                 out.printf("\rStatus: %s | Samples: %d | Size: %.2f MiB | Elapsed: %ds",
@@ -172,44 +175,46 @@ private void showTrainingStatus(NodeProbe probe)
         }
 
         TrainingStatus status = TrainingStatus.valueOf(statusStr);
+
         switch (status)
         {
             case NOT_STARTED:
-                out.printf("Trainer is not running for %s.%s%n", keyspace, table);
-                break;
             case SAMPLING:
-                out.printf("Trainer is collecting sample data for %s.%s%n", keyspace, table);
-                showStatistics(probe, out);
-                break;
             case TRAINING:
-                out.printf("Training is in progress for %s.%s%n", keyspace, table);
-                showStatistics(probe, out);
-                break;
             case COMPLETED:
-                out.printf("Training is completed for %s.%s%n", keyspace, table);
+                showStatistics(probe, out, status);
                 break;
             case FAILED:
-                err.printf("Training failed for %s.%s%n", keyspace, table);
+                showStatistics(probe, err, status);
                 break;
             default:
                 err.printf("Encountered unexpected training status for %s.%s: %s%n", keyspace, table, status);
         }
     }
 
-    private void showStatistics(NodeProbe probe, PrintStream out)
+    private void showStatistics(NodeProbe probe, PrintStream out, TrainingStatus status)
     {
         try
         {
-            long sampleCount = probe.getCompressionDictionaryTrainingSampleCount(keyspace, table);
-            long totalSampleSize = probe.getCompressionDictionaryTrainingTotalSampleSize(keyspace, table);
-            double sampleSizeMB = totalSampleSize / (1024.0 * 1024.0);
+            TableBuilder tableBuilder = new TableBuilder();
+            tableBuilder.add("keyspace", keyspace);
+            tableBuilder.add("table", table);
+            tableBuilder.add("status", status.name());
+
+            if (status == TrainingStatus.SAMPLING || status == TrainingStatus.TRAINING)
+            {
+                long sampleCount = probe.getCompressionDictionaryTrainingSampleCount(keyspace, table);
+                long totalSampleSize = probe.getCompressionDictionaryTrainingTotalSampleSize(keyspace, table);
+
+                tableBuilder.add("samples collected", String.format("%d", sampleCount));
+                tableBuilder.add("total sample size", FileUtils.stringifyFileSize(totalSampleSize));
+            }
 
-            out.printf("  Samples collected: %d%n", sampleCount);
-            out.printf("  Total sample size: %.2f MiB%n", sampleSizeMB);
+            tableBuilder.printTo(out);
         }
         catch (Exception e)
         {
-            out.printf("  Unable to retrieve training statistics: %s%n", e.getMessage());
+            out.printf("Unable to retrieve training statistics: %s%n", e.getMessage());
         }
     }
 }