voonhous commented on code in PR #7669:
URL: https://github.com/apache/hudi/pull/7669#discussion_r1090228224
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hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/table/action/commit/FlinkDeletePartitionCommitActionExecutor.java:
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@@ -98,4 +103,42 @@ private List<String> getAllExistingFileIds(String
partitionPath) {
// because new commit is not complete. it is safe to mark all existing
file Ids as old files
return
table.getSliceView().getLatestFileSlices(partitionPath).map(FileSlice::getFileId).distinct().collect(Collectors.toList());
}
+
+ /**
+ * Check if there are any pending table service actions (requested +
inflight) on a table affecting the partitions to
+ * be dropped.
+ * <p>
+ * This check is to prevent a drop-partition from proceeding should a
partition have a table service action in
+ * the pending stage. If this is allowed to happen, the filegroup that is an
input for a table service action, might
+ * also be a candidate for being replaced. As such, when the table service
action and drop-partition commits are
+ * committed, there will be two commits replacing a single filegroup.
+ * <p>
+ * For example, a timeline might have an execution order as such:
+ * 000.replacecommit.requested (clustering filegroup_1 + filegroup_2 ->
filegroup_3)
+ * 001.replacecommit.requested, 001.replacecommit.inflight,
0001.replacecommit (drop_partition to replace filegroup_1)
+ * 000.replacecommit.inflight (clustering is executed now)
+ * 000.replacecommit (clustering completed)
+ * For an execution order as shown above, 000.replacecommit and
001.replacecommit will both flag filegroup_1 to be replaced.
+ * This will cause downstream duplicate key errors when a map is being
constructed.
+ */
+ private void checkPreconditions() {
+ List<String> instantsOfOffendingPendingTableServiceAction = new
ArrayList<>();
+ // ensure that there are no pending inflight clustering/compaction
operations involving this partition
+ SyncableFileSystemView fileSystemView = (SyncableFileSystemView)
table.getSliceView();
+
+ Stream.concat(fileSystemView.getPendingCompactionOperations(),
fileSystemView.getPendingLogCompactionOperations())
+ .filter(op -> partitions.contains(op.getRight().getPartitionPath()))
+ .forEach(op ->
instantsOfOffendingPendingTableServiceAction.add(op.getLeft()));
+
+ fileSystemView.getFileGroupsInPendingClustering()
+ .filter(fgIdInstantPair ->
partitions.contains(fgIdInstantPair.getLeft().getPartitionPath()))
+ .forEach(x ->
instantsOfOffendingPendingTableServiceAction.add(x.getRight().getTimestamp()));
+
+ if (instantsOfOffendingPendingTableServiceAction.size() > 0) {
+ throw new HoodieDeletePartitionException("Failed to drop partitions. "
Review Comment:
In such a case, the Spark-SQL session might get stuck waiting for extended
periods of time if there are multiple compaction/clustering plans involving the
partition to be dropped.
If there are 5 compaction/clustering jobs involving a partition, we will
need to wait for all 5 pending jobs to finish before we can drop the partition.
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