bhat-vinay commented on code in PR #10865:
URL: https://github.com/apache/hudi/pull/10865#discussion_r1532227150
##########
hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/S3EventsHoodieIncrSource.java:
##########
@@ -112,10 +110,15 @@ public S3EventsHoodieIncrSource(
QueryRunner queryRunner,
CloudDataFetcher cloudDataFetcher) {
super(props, sparkContext, sparkSession, schemaProvider);
+
+ if (getBooleanWithAltKeys(props, ENABLE_EXISTS_CHECK)) {
+ sparkSession.conf().set("spark.sql.files.ignoreMissingFiles", "true");
+ sparkSession.conf().set("spark.sql.files.ignoreCorruptFiles", "true");
Review Comment:
```
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID
0) (192.168.0.101 executor driver): java.io.FileNotFoundException:
File
file:/var/folders/9g/815t_9ns1pg2h631kb3792zw0000gn/T/junit5612947518157164794/data1.json
does not exist
It is possible the underlying files have been updated. You can explicitly
invalidate
the cache in Spark by running 'REFRESH TABLE tableName' command in SQL or by
recreating the Dataset/DataFrame involved.
at
org.apache.spark.sql.errors.QueryExecutionErrors$.readCurrentFileNotFoundError(QueryExecutionErrors.scala:661)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:212)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:270)
at
org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:116)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:136)
at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
```
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