* add faults tests for the multi stage query
* add too many parttiions fault
* add toomanyinputfilesfault
* programmatically generate the file
* refactor
* Trigger Build
https://github.com/apache/druid/pull/13027 PR replaces `filter` parameter with
`objectGlob` in ingestion input source. However, this will cause existing ingestion
jobs to fail if they are using a filter already. This PR adds old filter functionality
alongside objectGlob to preserve backward compatibility.
Detects self-redirects, redirect loops, long redirect chains, and redirects to unknown servers.
Treat all of these cases as an unavailable service, retrying if the retry policy allows it.
Previously, some of these cases would lead to a prompt, unretryable error. This caused
clients contacting an Overlord during a leader change to fail with error messages like:
org.apache.druid.rpc.RpcException: Service [overlord] redirected too many times
Additionally, a slight refactor of callbacks in ServiceClientImpl improves readability of
the flow through onSuccess.
* fixes BlockLayoutColumnarLongs close method to nullify internal buffer.
* fixes other BlockLayoutColumnar supplier close methods to nullify internal buffers.
* fix spotbugs
* we can read where we want to
we can leave your bounds behind
'cause if the memory is not there
we really don't care
and we'll crash this process of mine
* Attach IO error to parse error when we can't contact Avro schema registry.
The change in #12080 lost the original exception context. This patch
adds it back.
* Add hamcrest-core.
* Fix format string.
The batch segment sampling performs significantly better than the older method
of sampling if there are a large number of used segments. It also avoids duplicates.
Changes:
- Make batch segment sampling the default
- Deprecate the property `useBatchedSegmentSampler`
- Remove unused coordinator config `druid.coordinator.loadqueuepeon.repeatDelay`
- Cleanup `KillUnusedSegments`
- Simplify `KillUnusedSegmentsTest`, add better tests, remove redundant tests
Main changes:
1) Convert SeekableStreamIndexTaskClient to an interface, move old code
to SeekableStreamIndexTaskClientSyncImpl, and add new implementation
SeekableStreamIndexTaskClientAsyncImpl that uses ServiceClient.
2) Add "chatAsync" parameter to seekable stream supervisors that causes
the supervisor to use an async task client.
3) In SeekableStreamSupervisor.discoverTasks, adjust logic to avoid making
blocking RPC calls in workerExec threads.
4) In SeekableStreamSupervisor generally, switch from Futures.successfulAsList
to FutureUtils.coalesce, so we can better capture the errors that occurred
with contacting individual tasks.
Other, related changes:
1) Add ServiceRetryPolicy.retryNotAvailable, which controls whether
ServiceClient retries unavailable services. Useful since we do not
want to retry calls unavailable tasks within the service client. (The
supervisor does its own higher-level retries.)
2) Add FutureUtils.transformAsync, a more lambda friendly version of
Futures.transform(f, AsyncFunction).
3) Add FutureUtils.coalesce. Similar to Futures.successfulAsList, but
returns Either instead of using null on error.
4) Add JacksonUtils.readValue overloads for JavaType and TypeReference.
Currently, a shared lock is acquired only when all other locks are also shared locks.
This commit updates the behaviour and acquires a shared lock only if all locks
of equal or higher priority are either shared locks or are already revoked.
The lock type of locks with lower priority does not matter as they can be revoked.
Eliminates two common sources of noise with Kafka supervisors that have
large numbers of tasks and partitions:
1) Log the report at DEBUG rather than INFO level at each run cycle.
It can get quite large, and can be retrieved via API when needed.
2) Use log4j2.xml to quiet down the org.apache.kafka.clients.consumer.internals
package. Avoids a log message per-partition per-minute as part of seeking
to the latest offset in the reporting thread. In the tasks, where this
sort of logging might be more useful, we have another log message with
the same information: "Seeking partition[%s] to[%s]".
Fixes inclusion of all stream partitions in all tasks.
The PR (Adds Idle feature to `SeekableStreamSupervisor` for inactive stream) - https://github.com/apache/druid/pull/13144 updates the resulting lag calculation map in `KafkaSupervisor` to include all the latest partitions from the stream to set the idle state accordingly rather than the previous way of lag calculation only for the partitions actively being read from the stream. This led to an explosion of metrics in lag reports in cases where 1000s of tasks per supervisor are present.
Changes:
- Add a new method to generate lags for only those partitions a single task is actively reading from while updating the Supervisor reports.
We added compression to the latest/first pair storage, but
the code change was forcing new things to be persisted
with the new format, meaning that any segment created with
the new code cannot be read by the old code. Instead, we
need to default to creating the old format and then remove that default in a future version.
xiaokang
Adarsh Sanjeev
Kashif Faraz
Jill Osborne
Gian Merlino
Laksh Singla
Karan Kumar
Vadim Ogievetsky
Clint Wylie
Tejaswini Bandlamudi
dependabot[bot]
Rohan Garg
AmatyaAvadhanula
Abhishek Agarwal
Adam Peck
Katya Macedo
abhagraw
imply-cheddar