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What changes were proposed in this pull request?

Why are the changes needed?

Does this PR introduce any user-facing change?

How was this patch tested?

@sonarqubecloud
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} catch (InvalidOperationException e) {
// This means there are tables of something in the database
throw new InvalidOperationException("There are still objects in the default " +
"database for catalog " + catName);
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nit: should we also throw stack trace?

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IMO the message can tell the enough about the exception, we don't need to pollute the log file

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sonarqubecloud bot commented Jan 4, 2026

public void drop_database_req(final DropDatabaseRequest req)
public AsyncOperationResp drop_database_req(final DropDatabaseRequest req)
throws NoSuchObjectException, InvalidOperationException, MetaException {
startFunction("drop_database", ": " + req.getName());
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If the operation is async, the recorded API time will be not the operation finished cost time, should we record it in the handler?

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nice catch, will try the timing in handler

LOG.warn("Error from isWritable", ex);
throw new MetaException("Table partition not deleted since " + dir.getParent()
+ " access cannot be checked: " + ex.getMessage());
return resp;
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If the returned partitions of resp is empty, the client can not know if it's finished or still running.

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for add partitions, it's not asynchronous, this method wouldn't return until the handler finishes the job,

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Got it.

Comment on lines +4653 to +4655
part_vals = getPartValsFromName(t, dropPartitionReq.getPartName());
}
partNames.add(Warehouse.makePartName(t.getPartitionKeys(), part_vals));
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Suggested change
part_vals = getPartValsFromName(t, dropPartitionReq.getPartName());
}
partNames.add(Warehouse.makePartName(t.getPartitionKeys(), part_vals));
partNames.add(dropPartitionReq.getPartName());
} else {
partNames.add(Warehouse.makePartName(t.getPartitionKeys(), part_vals));
}

AbstractOperationHandler<DropDatabaseRequest, DropDatabaseHandler.DropDatabaseResult> dropDatabaseOp =
AbstractOperationHandler.offer(this, req);
AbstractOperationHandler.OperationStatus status = dropDatabaseOp.getOperationStatus();
if (status.isFinished() && dropDatabaseOp.getResult() != null && dropDatabaseOp.getResult().isSuccess()) {
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dropDatabaseOp.getResult() != null is redundant and can be removed.

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if the handler is canceled, the dropDatabaseOp.getResult() might be null, will add the comment

// a copy is required to allow incremental replication to work correctly.
if (func.getResourceUris() != null && !func.getResourceUris().isEmpty()) {
for (ResourceUri uri : func.getResourceUris()) {
if (uri.getUri().toLowerCase().startsWith("hdfs:") && needsCm) {
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This function can fast-return if needsCm is false.

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nice catch, will do

private A result;
private boolean async;
private Future<A> future;
private ExecutorService executor;
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Is it better to use a shared thread pool for the operation handler? In the current implementation, the number of threads is not bounded, which could lead to resource exhaustion or even crashes.

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The number of handler's threads is limited by the max threads the thrift server can spawn, which is set by hive.metastore.server.max.threads.

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@dengzhhu653 dengzhhu653 Jan 5, 2026

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In production, I think we shouldn't not have such a high drop databases/table operations happens near the same time, usually the database is the bottleneck before the Metastore hits the limit, if this is the case, we can tune down the hive.metastore.server.max.threads.

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In the async mode, a thread may trigger multiple operation handlers, so the hive.metastore.server.max.threads could not limit total threads here. If we configure a fixed size pool for the async operations, it can help limit service traffic to some extent.

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Usually the new handler runs inside the same thread as the parent, such as DropDatabaseHandler, involves multiple DropTableHandlers, these DropTableHandlers runs inside the same thread as the DropDatabaseHandler

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@dengzhhu653 dengzhhu653 Jan 6, 2026

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Usually the new handler runs inside the same thread as the parent, such as DropDatabaseHandler, involves multiple DropTableHandlers, these DropTableHandlers run inside the same thread as the DropDatabaseHandler

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Oh I mean that for async request, the HMSHandler thread could create an operation handler where the executor starts a new thread. Then the HMSHandler thread finish this request immediatly and could handle another request where it may produce another new thread.

If such async request is frequent, it may lead to an explosion in the number of threads.

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Though Metastore handles the async request in background, the client doesn't, it pings the server for the status until the end:

while (!resp.isFinished() && !Thread.currentThread().isInterrupted()) {
resp = client.drop_database_req(req);
if (resp.getMessage() != null) {
LOG.info(resp.getMessage());
}
}

the client will know whether the request is successful or not as usual at the end, and the Metastore needs a handler thread to answer the request.

the HMSHandler thread finish this request immediatly

result = async ? future.get(timeout, TimeUnit.MILLISECONDS) : future.get();

Now it will wait for 5 seconds before answering the API for long running drop unless the request is satisfied within this timeout, then we can get the result.

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There are customized clients based on ThriftHiveMetastore.Iface, which may not guarantee such behavior.

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asyncDrop defaults to false, unless it's specified explicitly as true, then the customized client should take care of his case.

dropRequest.setEnvContext(context);
// Drop the table but not its data
dropRequest.setDeleteData(false);
dropRequest.setDropPartitions(true);
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Better to explicitly disable asyncDrop here:

        dropRequest.setAsyncDrop(false);

Comment on lines +4099 to +4100
AbstractOperationHandler<DropPartitionsRequest, DropPartitionsHandler.DropPartitionsResult> dropPartsOp =
AbstractOperationHandler.offer(this, request);
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Such calls can be changed as following, including other related api:

Suggested change
AbstractOperationHandler<DropPartitionsRequest, DropPartitionsHandler.DropPartitionsResult> dropPartsOp =
AbstractOperationHandler.offer(this, request);
DropPartitionsHandler dropPartsOp = (DropPartitionsHandler) AbstractOperationHandler.offer(this, request);

@saihemanth-cloudera
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A couple of test failures seem to be related to this patch.

wh.addToChangeManagement(funcCmPath);
}
if (req.isDeleteData()) {
// Moving the data deletion out of the async handler.
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I think we should move this into the operation handler, because if a thrift client only calls this api once in async mode, then such cleanup code would never be run.

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@dengzhhu653 dengzhhu653 Jan 6, 2026

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In async mode, the client still need to ping the server for the operation status until the end, the client needs to know whether the request is a failure or not.
The main reason is the TUGIBasedProcessor/TUGIAssumingProcessor might close the shared FileSystem behind, causing the "java.io.IOException: Filesystem closed" for the handler running in background.

Still we need to address this "Filesystem closed" issue, as we don't know whether there are Filesystem operations in the Metastore listeners.

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FileSystem.closeAllForUGI(clientUgi); in TUGIAssumingProcessor seems a bug, assume that there are two requests with same ugi to handle the same path uri concurrently, it may also hit the "Filesystem closed" issue.

This is indeed a tricky problem, not sure if we can only remove cache for inactive ugi to solve it. And for this thread, it still has an issue if the client crush between two pings before the operation handler finished, the cleanup code will not take effect either.

return execute();
} finally {
afterExecute();
OPID_CLEANER.schedule(() -> OPID_TO_HANDLER.remove(id), 1, TimeUnit.HOURS);
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Should we consider adding a OPID_TO_STATUS? Because a thrift client should be able to get the result of an operation id even if the operation is finished, but now if the operation finished all things are removed.

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the result is stored at the future,

result = async ? future.get(timeout, TimeUnit.MILLISECONDS) : future.get();

the status can be determined by the status of this future, which would be cleared 1 hours later

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5 participants