This PR fixes an issue that could occur if druid.query.scheduler.numThreads is configured and any exception occurs after QueryScheduler.run has been called to create a Sequence. This would result in total and/or lane specific locks being acquired, but because the sequence was not actually being evaluated, the "baggage" which typically releases these locks was not being executed. An example of how this can happen is if a group-by having filter, which wraps and transforms this sequence happens to explode while wrapping the sequence. The end result is that the locks are acquired, but never released, eventually halting the ability to execute any queries.
This PR fixes an issue when using 'auto' encoded LONG typed columns and the 'vectorized' query engine. These columns use a delta based bit-packing mechanism, and errors in the vectorized reader would cause it to incorrectly read column values for some bit sizes (1 through 32 bits). This is a regression caused by #11004, which added the optimized readers to improve performance, so impacts Druid versions 0.22.0+.
While writing the test I finally got sad enough about IndexSpec not having a "builder", so I made one, and switched all the things to use it. Apologies for the noise in this bug fix PR, the only real changes are in VSizeLongSerde, and the tests that have been modified to cover the buggy behavior, VSizeLongSerdeTest and ExpressionVectorSelectorsTest. Everything else is just cleanup of IndexSpec usage.
* Make LoggingEmitter more useful
* Skip code coverage for facade classes
* fix spellcheck
* code review
* fix dependency
* logging.md
* fix checkstyle
* Add back jacoco version to main pom
* Fix two concurrency issues with segment fetching.
1) SegmentLocalCacheManager: Fix a concurrency issue where certain directory
cleanup happened outside of directoryWriteRemoveLock. This created the
possibility that segments would be deleted by one thread, while being
actively downloaded by another thread.
2) TaskDataSegmentProcessor (MSQ): Fix a concurrency issue when two stages
in the same process both use the same segment. For example: a self-join
using distributed sort-merge. Prior to this change, the two stages could
delete each others' segments.
3) ReferenceCountingResourceHolder: increment() returns a new ResourceHolder,
rather than a Releaser. This allows it to be passed to callers without them
having to hold on to both the original ResourceHolder *and* a Releaser.
4) Simplify various interfaces and implementations by using ResourceHolder
instead of Pair and instead of split-up fields.
* Add test.
* Fix style.
* Remove Releaser.
* Updates from master.
* Add some GuardedBys.
* Use the correct GuardedBy.
* Adjustments.
* Refresh DruidLeaderClient cache for non-200 responses
* Change local variable name to avoid confusion
* Implicit retries for 503 and 504
* Remove unused imports
* Use argumentmatcher instead of Mockito for #any in test
* Remove flag to disable retry for 503/504
* Remove unused import from test
* Add log line for internal retry
---------
Co-authored-by: Abhishek Singh Chouhan <abhishek.chouhan@salesforce.com>
### Description
This pr fixes a few bugs found with the inputSource security feature.
1. `KillUnusedSegmentsTask` previously had no definition for the `getInputSourceResources`, which caused an unsupportedOperationException to be thrown when this task type was submitted with the inputSource security feature enabled. This task type should not require any input source specific resources, so returning an empty set for this task type now.
2. Fixed a bug where when the input source type security feature is enabled, all of the input source type specific resources used where authenticated against:
`{"resource": {"name": "EXTERNAL", "type": "{INPUT_SOURCE_TYPE}"}, "action": "READ"}`
When they should be instead authenticated against:
`{"resource": {"name": "{INPUT_SOURCE_TYPE}", "type": "EXTERNAL"}, "action": "READ"}`
3. fixed bug where supervisor tasks were not authenticated against the specific input source types used, if input source security feature was enabled.
* Make the tasks run with only a single directory
There was a change that tried to get indexing to run on multiple disks
It made a bunch of changes to how tasks run, effectively hiding the
"safe" directory for tasks to write files into from the task code itself
making it extremely difficult to do anything correctly inside of a task.
This change reverts those changes inside of the tasks and makes it so that
only the task runners are the ones that make decisions about which
mount points should be used for storing task-related files.
It adds the config druid.worker.baseTaskDirs which can be used by the
task runners to know which directories they should schedule tasks inside of.
The TaskConfig remains the authoritative source of configuration for where
and how an individual task should be operating.
### Description
This change allows for input sources used during MSQ ingestion to be authorized for multiple input source types, instead of just 1. Such an input source that allows for multiple types is the CombiningInputSource.
Also fixed bug that caused some input source specific functions to be authorized against the permissions
`
[
new ResourceAction(new Resource(ResourceType.EXTERNAL, ResourceType.EXTERNAL), Action.READ),
new ResourceAction(new Resource(ResourceType.EXTERNAL, {input_source_type}), Action.READ)
]
`
when the inputSource based authorization feature is enabled, when it should instead be authorized against
`
[
new ResourceAction(new Resource(ResourceType.EXTERNAL, {input_source_type}), Action.READ)
]
`
Fixes#13837.
### Description
This change allows for input source type security in the native task layer.
To enable this feature, the user must set the following property to true:
`druid.auth.enableInputSourceSecurity=true`
The default value for this property is false, which will continue the existing functionality of needing authorization to write to the respective datasource.
When this config is enabled, the users will be required to be authorized for the following resource action, in addition to write permission on the respective datasource.
`new ResourceAction(new Resource(ResourceType.EXTERNAL, {INPUT_SOURCE_TYPE}, Action.READ`
where `{INPUT_SOURCE_TYPE}` is the type of the input source being used;, http, inline, s3, etc..
Only tasks that provide a non-default implementation of the `getInputSourceResources` method can be submitted when config `druid.auth.enableInputSourceSecurity=true` is set. Otherwise, a 400 error will be thrown.
changes:
* introduce ColumnFormat to separate physical storage format from logical type. ColumnFormat is now used instead of ColumnCapabilities to get column handlers for segment creation
* introduce new 'auto' type indexer and merger which produces a new common nested format of columns, which is the next logical iteration of the nested column stuff. Essentially this is an automatic type column indexer that produces the most appropriate column for the given inputs, making either STRING, ARRAY<STRING>, LONG, ARRAY<LONG>, DOUBLE, ARRAY<DOUBLE>, or COMPLEX<json>.
* revert NestedDataColumnIndexer, NestedDataColumnMerger, NestedDataColumnSerializer to their version pre #13803 behavior (v4) for backwards compatibility
* fix a bug in RoaringBitmapSerdeFactory if anything actually ever wrote out an empty bitmap using toBytes and then later tried to read it (the nerve!)
Due to race conditions, the BrokerServerView may sometimes try to add a segment to a server which has already been removed from the inventory. This results in an NPE and keeps the BrokerServerView from processing all change requests.
This change introduces the concept of input source type security model, proposed in #13837.. With this change, this feature is only available at the SQL layer, but we will expand to native layer in a follow up PR.
To enable this feature, the user must set the following property to true:
druid.auth.enableInputSourceSecurity=true
The default value for this property is false, which will continue the existing functionality of having the usage all external sources being authorized against the hardcoded resource action
new ResourceAction(new Resource(ResourceType.EXTERNAL, ResourceType.EXTERNAL), Action.READ
When this config is enabled, the users will be required to be authorized for the following resource action
new ResourceAction(new Resource(ResourceType.EXTERNAL, {INPUT_SOURCE_TYPE}, Action.READ
where {INPUT_SOURCE_TYPE} is the type of the input source being used;, http, inline, s3, etc..
Documentation has not been added for the feature as it is not complete at the moment, as we still need to enable this for the native layer in a follow up pr.
* Add segment generator counters to reports
* Remove unneeded annotation
* Fix checkstyle and coverage
* Add persist and merged as new metrics
* Address review comments
* Fix checkstyle
* Create metrics class to handle updating counters
* Address review comments
* Add rowsPushed as a new metrics
changes:
* fixes inconsistent handling of byte[] values between ExprEval.bestEffortOf and ExprEval.ofType, which could cause byte[] values to end up as java toString values instead of base64 encoded strings in ingest time transforms
* improved ExpressionTransform binding to re-use ExprEval.bestEffortOf when evaluating a binding instead of throwing it away
* improved ExpressionTransform array handling, added RowFunction.evalDimension that returns List<String> to back Row.getDimension and remove the automatic coercing of array types that would typically happen to expression transforms unless using Row.getDimension
* added some tests for ExpressionTransform with array inputs
* improved ExpressionPostAggregator to use partial type information from decoration
* migrate some test uses of InputBindings.forMap to use other methods
Changes:
- Set `useRoundRobinSegmentAssignment` in coordinator dynamic config to `true` by default.
- Set `batchSegmentAllocation` in `TaskLockConfig` (used in Overlord runtime properties) to `true` by default.
* Lower default maxRowsInMemory for realtime ingestion.
The thinking here is that for best ingestion throughput, we want
intermediate persists to be as big as possible without using up all
available memory. So, we rely mainly on maxBytesInMemory. The default
maxRowsInMemory (1 million) is really just a safety: in case we have
a large number of very small rows, we don't want to get overwhelmed
by per-row overheads.
However, maximum ingestion throughput isn't necessarily the primary
goal for realtime ingestion. Query performance is also important. And
because query performance is not as good on the in-memory dataset, it's
helpful to keep it from growing too large. 150k seems like a reasonable
balance here. It means that for a typical 5 million row segment, we
won't trigger more than 33 persists due to this limit, which is a
reasonable number of persists.
* Update tests.
* Update server/src/main/java/org/apache/druid/segment/indexing/RealtimeTuningConfig.java
Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
* Fix test.
* Fix link.
---------
Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
* This makes the zookeeper connection retry count configurable. This is presently hardcoded to 29 tries which ends up taking a long time for the druid node to shutdown in case of ZK connectivity loss.
Having a shorter retry count helps k8s deployments to fail fast. In situations where the underlying k8s node loses network connectivity or is no longer able to talk to zookeeper, failing fast can trigger pod restarts which can then reassign the pod to a healthy k8s node.
Existing behavior is preserved, but users can override this property if needed.
* Improve memory efficiency of WrappedRoaringBitmap.
Two changes:
1) Use an int[] for sizes 4 or below.
2) Remove the boolean compressRunOnSerialization. Doesn't save much
space, but it does save a little, and it isn't adding a ton of value
to have it be configurable. It was originally configurable in case
anything broke when enabling it, but it's been a while and nothing
has broken.
* Slight adjustment.
* Adjust for inspection.
* Updates.
* Update snaps.
* Update test.
* Adjust test.
* Fix snaps.
The FiniteFirehoseFactory and InputRowParser classes were deprecated in 0.17.0 (#8823) in favor of InputSource & InputFormat. This PR removes the FiniteFirehoseFactory and all its implementations along with classes solely used by them like Fetcher (Used by PrefetchableTextFilesFirehoseFactory). Refactors classes including tests using FiniteFirehoseFactory to use InputSource instead.
Removing InputRowParser may not be as trivial as many classes that aren't deprecated depends on it (with no alternatives), like EventReceiverFirehoseFactory. Hence FirehoseFactory, EventReceiverFirehoseFactory, and Firehose are marked deprecated.
* Make CompactionSearchPolicy injectable
A small refactoring that makes the search policy for compaction injectable.
Future changes can introduce new search policies that can be configured and
injected so that operators can choose which search policy is best suited for
their cluster.
This will also allow us to de-couple the scheduling of compaction jobs from
the CompactSegments duty, allowing the co-ordinator to schedule compaction
jobs faster than the duty lifecycle.
This PR is made so that it easy to review the future changes.
* fix tests
When both plainText and TLS ports are set in druid, the redirection to a different leader node can fail. This is caused by how we compare a redirect path and the leader locations registered with a druid node. While the registered location has both plainText and TLS port set, the redirect path only has one port since it's a URI.
* merge druid-core, extendedset, and druid-hll into druid-processing to simplify everything
* fix poms and license stuff
* mockito is evil
* allow reset of JvmUtils RuntimeInfo if tests used static injection to override
* Use an HllSketchHolder object to enable optimized merge
HllSketchAggregatorFactory.combine had been implemented using a
pure pair-wise, "make a union -> add 2 things to union -> get sketch"
algorithm. This algorithm does 2 things that was CPU
1) The Union object always builds an HLL_8 sketch regardless of the
target type. This means that when the target type is not HLL_8, we
spent CPU cycles converting to HLL_8 and back over and over again
2) By throwing away the Union object and converting back to the
HllSketch only to build another Union object, we do lots and lots
of copy+conversions of the HllSketch
This change introduces an HllSketchHolder object which can hold onto
a Union object and delay conversion back into an HllSketch until
it is actually needed. This follows the same pattern as the
SketchHolder object for theta sketches.
* Fallback virtual column
This virtual columns enables falling back to another column if
the original column doesn't exist. This is useful when doing
column migrations and you have some old data with column X,
new data with column Y and you want to use Y if it exists, X
otherwise so that you can run a consistent query against all of
the data.
Add a new API to return the history of changes to automatic compaction config history to make it easy for users to see what changes have been made to their auto-compaction config.
The API is scoped per dataSource to allow users to triage issues with an individual dataSource. The API responds with a list of configs when there is a change to either the settings that impact all auto-compaction configs on a cluster or the dataSource in question.
* discover nested columns when using nested column indexer for schemaless
* move useNestedColumnIndexerForSchemaDiscovery from AppendableIndexSpec to DimensionsSpec
Much improved table functions
* Revises properties, definitions in the catalog
* Adds a "table function" abstraction to model such functions
* Specific functions for HTTP, inline, local and S3.
* Extended SQL types in the catalog
* Restructure external table definitions to use table functions
* EXTEND syntax for Druid's extern table function
* Support for array-valued table function parameters
* Support for array-valued SQL query parameters
* Much new documentation
Clint Wylie
George Shiqi Wu
Suneet Saldanha
Gian Merlino
Abhishek Singh Chouhan
zachjsh
Atul Mohan
imply-cheddar
Abhishek Agarwal
soullkk
Kashif Faraz
Paul Rogers
Adarsh Sanjeev
Karan Kumar
Tejaswini Bandlamudi
Lucas Capistrant
AmatyaAvadhanula
Maytas Monsereenusorn