hudi-agent commented on code in PR #19811: URL: https://github.com/apache/hudi/pull/19811#discussion_r3964726865
########## hudi-utilities/src/test/java/org/apache/hudi/utilities/sources/ContinuousTestSource.java: ########## @@ -0,0 +1,156 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.hudi.utilities.sources; + +import org.apache.hudi.common.config.TypedProperties; +import org.apache.hudi.common.table.checkpoint.Checkpoint; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.utilities.schema.SchemaProvider; + +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; + +import java.util.concurrent.BrokenBarrierException; +import java.util.concurrent.CountDownLatch; +import java.util.concurrent.CyclicBarrier; +import java.util.concurrent.TimeUnit; +import java.util.concurrent.TimeoutException; +import java.util.concurrent.atomic.AtomicBoolean; + +/** + * A parquet test source that proves continuous-mode multi-table syncs run in parallel. + * + * <p>Every table waits at a shared barrier before producing data, so a sequential implementation would block the first + * table forever and time out. Only concurrent syncs let all tables pass the barrier. + */ +public class ContinuousTestSource extends ParquetDFSSource { + + // When set on a table's properties, that table fails right after passing the barrier, i.e. once all tables started. + public static final String FAIL_AFTER_BARRIER = "hoodie.test.continuous.source.fail.after.barrier"; + + // When set on a table's properties, that table blocks after the barrier until fail fast interrupts it. + public static final String BLOCK_UNTIL_INTERRUPTED = "hoodie.test.continuous.source.block.until.interrupted"; + + // When set on a table's properties, that table blocks after the barrier and fails once releaseFailingTable() + // is called, letting a test choose exactly when the failure happens relative to the other tables. + public static final String FAIL_WHEN_RELEASED = "hoodie.test.continuous.source.fail.when.released"; + + private static final long BARRIER_TIMEOUT_SECONDS = 60; + + // lets awaitUntil be the one that reports a stall. + private static final long RELEASE_TIMEOUT_SECONDS = 300; Review Comment: 🤖 nit: this comment reads like a truncated sentence — could you spell it out, e.g. "Longer than the test's awaitUntil deadline, so a stall is reported by the test rather than by this source"? <sub><i>⚠️ AI-generated; verify before applying. React 👍/👎 to flag quality.</i></sub> ########## hudi-utilities/src/main/java/org/apache/hudi/utilities/streamer/HoodieMultiTableStreamer.java: ########## @@ -461,28 +484,204 @@ 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.error("Ingestion failed for topics: {}", failedTables); + } + } + } + + private void syncSequentially() { for (TableExecutionContext context : tableExecutionContexts) { + String table = Helpers.getTableWithDatabase(context); HoodieStreamer streamer = null; try { streamer = new HoodieStreamer(context.getConfig(), jssc, Option.ofNullable(context.getProperties())); streamer.sync(); - successTables.add(Helpers.getTableWithDatabase(context)); - streamer.shutdownGracefully(); + successTables.add(table); } catch (Exception e) { - log.error("error while running MultiTableDeltaStreamer for table: {}", context.getTableName(), e); - failedTables.add(Helpers.getTableWithDatabase(context)); + log.error("error while running MultiTableDeltaStreamer for table: {}", table, e); + failedTables.add(table); } finally { if (streamer != null) { - streamer.shutdownGracefully(); + shutdownQuietly(streamer, table); } } } + } + + /** + * 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); + } else { + CompletableFuture.allOf(tableFutures.toArray(new CompletableFuture[0])).join(); + } + } finally { + // On an abnormal exit the siblings are still ingesting, since FutureUtils.allOf only cancels their futures. + // Stopping them here rather than in a catch covers every such exit, including an Error, which the workers do + // not catch; it is a no-op on the success path because each table has already shut its ingestion service down. + shutdownRequested.set(true); + interruptAllIngestion(streamerInstances); + // 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) { + String table = Helpers.getTableWithDatabase(context); + // The tables now log concurrently into one driver log, so name the worker after the table it is syncing. + Thread.currentThread().setName("multi-table-streamer-" + table); + 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 interruptAllIngestion() always sees this streamer. + if (shutdownRequested.get()) { + return; + } + streamer.sync(); + // A streamer registered just before fail fast tripped can reach here without ever ingesting: the interrupt + // found no executor to stop, but it had already marked the service shut down, and that flag is what makes + // HoodieIngestionService's loop exit on its first check. Nothing was written, so not a success. + if (!shutdownRequested.get()) { + successTables.add(table); + } + } catch (Exception e) { + 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); + } + } finally { + if (streamer != null) { + shutdownQuietly(streamer, table); + } + } + } + + /** + * Waits until either every table sync finishes successfully or the first one fails. On the first failure, the + * remaining streamers are shut down and a {@link HoodieException} is thrown. {@link FutureUtils#allOf} only trips + * on an <em>exceptional</em> completion, so a table that terminates normally (e.g. via a + * {@link PostWriteTerminationStrategy}) does not abort its siblings. + */ + private static void awaitFailFast(List<CompletableFuture<Void>> tableFutures) { + try { + FutureUtils.allOf(tableFutures).join(); + } catch (CompletionException e) { + Throwable cause = unwrapCompletionException(e); + // An Error is rethrown as is rather than boxed, so the JVM-level failure reaches the caller unchanged. + if (cause instanceof Error) { + throw (Error) cause; + } + log.error("error while running MultiTableDeltaStreamer, shutting down remaining tables as fail fast is enabled", cause); + throw new HoodieException("Fail fast is enabled and a table sync failed in continuous mode.", cause); + } + } + + /** + * Releases a streamer's resources, logging rather than propagating a failure to do so. Closing can throw, and this + * runs in a {@code finally} on the failure path where escaping would mask the table failure and, in + * {@link #syncSequentially()}, abort the tables not synced yet. + */ + private static void shutdownQuietly(HoodieStreamer streamer, String table) { + try { + streamer.shutdownGracefully(); + } catch (Exception e) { + log.warn("error while shutting down the streamer for table: {}", table, e); + } + } + + // A worker failure reaches the waiter wrapped in CompletionException, and FutureUtils.allOf re-wraps it, so the + // real cause can sit under more than one layer. + private static Throwable unwrapCompletionException(CompletionException e) { + Throwable cause = e; + while (cause instanceof CompletionException && cause.getCause() != null) { + cause = cause.getCause(); + } + return cause; + } + + /** + * Two-phase shutdown of the per-table executor: wait for the running syncs to finish, then force-cancel any that + * ignore interruption. Bounded by {@link Constants#SHUTDOWN_TIMEOUT_SECONDS} so a stuck table cannot hang the job. + * + * @return true if all workers terminated, false if any were still running when the timeout elapsed. + */ + private static boolean shutdownExecutor(ExecutorService executor) { + executor.shutdown(); + try { + if (executor.awaitTermination(Constants.SHUTDOWN_TIMEOUT_SECONDS, TimeUnit.SECONDS)) { + return true; + } + executor.shutdownNow(); + if (executor.awaitTermination(Constants.SHUTDOWN_TIMEOUT_SECONDS, TimeUnit.SECONDS)) { + return true; + } + log.error("executor service did not terminate after shutdown"); + return false; + } catch (InterruptedException e) { + executor.shutdownNow(); + Thread.currentThread().interrupt(); + return false; + } + } - log.info("Ingestion was successful for topics: {}", successTables); - if (!failedTables.isEmpty()) { - log.info("Ingestion failed for topics: {}", failedTables); + private static void interruptAllIngestion(List<HoodieStreamer> streamerInstances) { + for (HoodieStreamer streamer : streamerInstances) { + try { + streamer.interruptIngestion(); + } catch (Exception e) { + log.warn("error while interrupting the ingestion of a streamer instance", e); Review Comment: 🤖 nit: it might be worth including the table name here (e.g. `streamer.getConfig().targetTableName`) so this warning can be tied back to a table when several workers are logging into the same driver log. <sub><i>⚠️ AI-generated; verify before applying. React 👍/👎 to flag quality.</i></sub> -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
