smtwilio commented on code in PR #19811:
URL: https://github.com/apache/hudi/pull/19811#discussion_r3961930340


##########
hudi-utilities/src/main/java/org/apache/hudi/utilities/streamer/HoodieMultiTableStreamer.java:
##########
@@ -461,28 +484,194 @@ private static String resetTarget(Config configuration, 
String database, String
 
   /**
    * Creates actual HoodieDeltaStreamer objects for every table/topic and does 
incremental sync.
+   *
+   * <p>In continuous mode each table's sync blocks until it is shut down, so 
the tables are synced concurrently.
+   * Otherwise the tables are synced sequentially, one after another.
    */
   public void sync() {
+    try {
+      if (continuousMode) {
+        syncContinuously();
+      } else {
+        syncSequentially();
+      }
+    } finally {
+      log.info("Ingestion was successful for topics: {}", successTables);
+      if (!failedTables.isEmpty()) {
+        log.info("Ingestion failed for topics: {}", failedTables);
+      }
+    }
+  }
+
+  private void syncSequentially() {
     for (TableExecutionContext context : tableExecutionContexts) {
       HoodieStreamer streamer = null;
       try {
         streamer = new HoodieStreamer(context.getConfig(), jssc, 
Option.ofNullable(context.getProperties()));
         streamer.sync();
         successTables.add(Helpers.getTableWithDatabase(context));
-        streamer.shutdownGracefully();
       } catch (Exception e) {
         log.error("error while running MultiTableDeltaStreamer for table: {}", 
context.getTableName(), e);
         failedTables.add(Helpers.getTableWithDatabase(context));
       } finally {
         if (streamer != null) {
-          streamer.shutdownGracefully();
+          shutdownQuietly(streamer, context);
         }
       }
     }
+  }
+
+  /**
+   * Syncs all tables concurrently, one thread per table. Used for continuous 
mode where each table's sync blocks
+   * indefinitely.
+   *
+   * <p>When {@code --fail-fast-on-continuous} is enabled, the first table 
failure fails the whole job. The sibling
+   * streamers are shut down and a {@link HoodieException} is thrown so the 
caller can exit with a non-zero status.
+   * Otherwise, every table is synced independently and a single failure does 
not affect the others.
+   */
+  private void syncContinuously() {
+    if (tableExecutionContexts.isEmpty()) {
+      return;
+    }
+    // Streamer instances are registered from worker threads, so a thread-safe 
list is required.
+    final List<HoodieStreamer> streamerInstances = new 
CopyOnWriteArrayList<>();
+    // Set once fail fast trips, so tasks that register their streamer 
afterwards stop before starting the sync.
+    final AtomicBoolean shutdownRequested = new AtomicBoolean(false);
+    final ExecutorService executor = 
Executors.newFixedThreadPool(tableExecutionContexts.size(),
+        new CustomizedThreadFactory("multi-table-streamer", true));
+    boolean terminated = false;
+    try {
+      final List<CompletableFuture<Void>> tableFutures = 
tableExecutionContexts.stream()
+          .map(context -> CompletableFuture.runAsync(
+              () -> runTableSync(context, streamerInstances, 
shutdownRequested), executor))
+          .collect(Collectors.toList());
+
+      if (failFastOnContinuousMode) {
+        log.info("Fail fast enabled in continuous mode. The whole job fails on 
any single table failure");
+        awaitFailFast(tableFutures, streamerInstances, shutdownRequested);
+      } else {
+        CompletableFuture.allOf(tableFutures.toArray(new 
CompletableFuture[0])).join();
+      }
+    } finally {
+      // Wait for every worker thread to finish (including its finally 
cleanup) before returning, so sync() does not
+      // return while a table is still writing and main() then stops the 
shared Spark context under it.
+      terminated = shutdownExecutor(executor);
+    }
+    // If the workers never terminated, ingestion may still be running. Fail 
loudly instead of returning as if the
+    // cleanup succeeded, so the caller does not silently proceed to Spark 
teardown with live writers.
+    if (!terminated) {
+      throw new HoodieException("Timed out shutting down table ingestion 
workers in continuous mode");
+    }
+  }
+
+  /**
+   * Syncs one table on the calling worker thread. Rethrows only under fail 
fast; otherwise the failure is recorded
+   * in {@link #failedTables} and the sibling tables carry on.
+   */
+  private void runTableSync(TableExecutionContext context, 
List<HoodieStreamer> streamerInstances, AtomicBoolean shutdownRequested) {
+    HoodieStreamer streamer = null;
+    try {
+      streamer = new HoodieStreamer(context.getConfig(), jssc, 
Option.ofNullable(context.getProperties()));
+      streamerInstances.add(streamer);
+      // Register before checking the flag so a concurrent shutdownStreamers() 
always sees this streamer.
+      if (shutdownRequested.get()) {
+        return;
+      }
+      streamer.sync();
+      // A streamer registered just before fail fast tripped can reach here 
without ever ingesting.
+      // shutdown() call will be a no-op because its ingestion service hadn't 
started yet.
+      // Don't count that as a success.
+      if (!shutdownRequested.get()) {
+        successTables.add(Helpers.getTableWithDatabase(context));
+      }
+    } catch (Exception e) {
+      String table = Helpers.getTableWithDatabase(context);
+      log.error("error while running MultiTableDeltaStreamer for table: {}", 
table, e);
+      failedTables.add(table);
+      if (failFastOnContinuousMode) {
+        // Name the table so the thrown exception identifies the culprit, not 
the siblings torn down after it.
+        throw new HoodieException("Table sync failed in continuous mode for 
table: " + table, e);

Review Comment:
   Good call, the test `testFailFastOnContinuousThrowsWhenATableFails` now 
captures the exception and does the assertion.



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