* Optimise S3 storage writing for MSQ durable storage
* Get rid of static ConcurrentHashMap
* Fix static checks
* Fix tests
* Remove unused constructor parameter chunkValidation + relevant cleanup
* Assert etags as String instead of Integer
* Fix flaky test
* Inject executor service
* Make threadpool size dynamic based on number of cores
* Fix S3StorageDruidModuleTest
* Fix S3StorageConnectorProviderTest
* Fix injection issues
* Add S3UploadConfig to manage maximum number of concurrent chunks dynamically based on chunk size
* Address the minor review comments
* Refactor S3UploadConfig + ExecutorService into S3UploadManager
* Address review comments
* Make updateChunkSizeIfGreater() synchronized instead of recomputeMaxConcurrentNumChunks()
* Address the minor review comments
* Fix intellij-inspections check
* Refactor code to use futures for maxNumConcurrentChunks. Also use executor service with blocking queue for backpressure semantics.
* Update javadoc
* Get rid of cyclic dependency injection between S3UploadManager and S3OutputConfig
* Fix RetryableS3OutputStreamTest
* Remove unnecessary synchronization parts from RetryableS3OutputStream
* Update javadoc
* Add S3UploadManagerTest
* Revert back to S3StorageConnectorProvider extends S3OutputConfig
* Address Karan's review comments
* Address Kashif's review comments
* Change a log message to debug
* Address review comments
* Fix intellij-inspections check
* Fix checkstyle
---------
Co-authored-by: asdf2014 <asdf2014@apache.org>
Currently, export creates the files at the provided destination. The addition of the manifest file will provide a list of files created as part of the manifest. This will allow easier consumption of the data exported from Druid, especially for automated data pipelines
* Move retries into DataSegmentPusher implementations.
The individual implementations know better when they should and should
not retry. They can also generate better error messages.
The inspiration for this patch was a situation where EntityTooLarge was
generated by the S3DataSegmentPusher, and retried uselessly by the
retry harness in PartialSegmentMergeTask.
* Fix missing var.
* Adjust imports.
* Tests, comments, style.
* Remove unused import.
* Fix capacity response in mm-less ingestion (#14888)
Changes:
- Fix capacity response in mm-less ingestion.
- Add field usedClusterCapacity to the GET /totalWorkerCapacity response.
This API should be used to get the total ingestion capacity on the overlord.
- Remove method `isK8sTaskRunner` from interface `TaskRunner`
* Using Map to perform comparison
* Minor Change
---------
Co-authored-by: George Shiqi Wu <george.wu@imply.io>
* + Fix for Flaky Test
* + Replacing TreeMap with LinkedHashMap
* + Changing data structure from LinkedHashMap to HashMap
* Fixed flaky test in S3DataSegmentPusherConfigTest.testSerializationValidatingMaxListingLength
* Minor Changes
* Add system fields to input sources.
Main changes:
1) The SystemField enum defines system fields "__file_uri", "__file_path",
and "__file_bucket". They are associated with each input entity.
2) The SystemFieldInputSource interface can be added to any InputSource
to make it system-field-capable. It sets up serialization of a list
of configured "systemFields" in the JSON form of the input source, and
provides a method getSystemFieldValue for computing the value of each
system field. Cloud object, HDFS, HTTP, and Local now have this.
* Fix various LocalInputSource calls.
* Fix style stuff.
* Fixups.
* Fix tests and coverage.
* Update S3 retry logic based on the underlying cause in case of IOException.
4xx and other errors wrapped in IOException for instance aren't retriable.
* Fix CI
This change is meant to fix a issue where passing too large of a task payload to the mm-less task runner will cause the peon to fail to startup because the payload is passed (compressed) as a environment variable (TASK_JSON). In linux systems the limit for a environment variable is commonly 128KB, for windows systems less than this. Setting a env variable longer than this results in a bunch of "Argument list too long" errors.
The Azure connector is introduced and MSQ's fault tolerance and durable storage can now be used with Microsoft Azure's blob storage. Also, the results of newly introduced queries from deep storage can now store and fetch the results from Azure's blob storage.
* allow for batched delete of segments instead of deleting segment data one by one
create new batchdelete method in datasegment killer that has default functionality
of iterating through all segments and calling delete on them. This will enable
a slow rollout of other deepstorage implementations to move to a batched delete
on their own time
* cleanup batchdelete segments
* batch delete with the omni data deleter
cleaned up code
just need to add tests and docs for this functionality
* update java doc to explain how it will try to use batch if function is overwritten
* rename killBatch to kill
add unit tests
* add omniDataSegmentKillerTest for deleting multiple segments at a time. fix checkstyle
* explain test peculiarity better
* clean up batch kill in s3.
* remove unused return value. cleanup comments and fix checkstyle
* default to batch delete. more specific java docs. list segments that couldn't be deleted
if there was a client error or server error
* simplify error handling
* add tests where an exception is thrown when killing multiple s3 segments
* add test for failing to delete two calls with the s3 client
* fix javadoc for kill(List<DataSegment> segments) clean up tests remove feature flag
* fix typo in javadocs
* fix test failure
* fix checkstyle and improve tests
* fix intellij inspections issues
* address comments, make delete multiple segments not assume same bucket
* fix test errors
* better grammar and punctuation. fix test. and better logging for exception
* remove unused code
* avoid extra arraylist instantiation
* fix broken test
* fix broken test
* fix tests to use assert.throws
This adds a new contrib extension: druid-iceberg-extensions which can be used to ingest data stored in Apache Iceberg format. It adds a new input source of type iceberg that connects to a catalog and retrieves the data files associated with an iceberg table and provides these data file paths to either an S3 or HDFS input source depending on the warehouse location.
Two important dependencies associated with Apache Iceberg tables are:
Catalog : This extension supports reading from either a Hive Metastore catalog or a Local file-based catalog. Support for AWS Glue is not available yet.
Warehouse : This extension supports reading data files from either HDFS or S3. Adapters for other cloud object locations should be easy to add by extending the AbstractInputSourceAdapter.
* S3: Attach SSE key to doesObjectExist calls.
We did not previously attach the SSE key to the doesObjectExist request,
leading to an inconsistency that may cause problems on "S3-compatible"
implementations. This patch implements doesObjectExist using similar
logic to the S3 client itself, but calls our implementation of
getObjectMetadata rather than the S3 client's, ensuring the request
is decorated with the SSE key.
* Fix tests.
* fix typo in s3 docs. add readme to s3 module.
* Update extensions-core/s3-extensions/README.md
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
* cleanup readme for s3 extension and link to repo markdown doc instead of web docs
---------
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
* return task status reported by peon
* Write TaskStatus to file in AbstractTask.cleanUp
* Get TaskStatus from task log
* Fix merge conflicts in AbstractTaskTest
* Add unit tests for TaskLogPusher, TaskLogStreamer, NoopTaskLogs to satisfy code coverage
* Add license headerss
* Fix style
* Remove unknown exception declarations
* "maxResultsSize" has been removed from the S3OutputConfig and a default "chunkSize" of 100MiB is now present. This change primarily affects users who wish to use durable storage for MSQ jobs.
### 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.
* Always use file sizes when determining batch ingest splits.
Main changes:
1) Update CloudObjectInputSource and its subclasses (S3, GCS,
Azure, Aliyun OSS) to use SplitHintSpecs in all cases. Previously, they
were only used for prefixes, not uris or objects.
2) Update ExternalInputSpecSlicer (MSQ) to consider file size. Previously,
file size was ignored; all files were treated as equal weight when
determining splits.
A side effect of these changes is that we'll make additional network
calls to find the sizes of objects when users specify URIs or objects
as opposed to prefixes. IMO, this is worth it because it's the only way
to respect the user's split hint and task assignment settings.
Secondary changes:
1) S3, Aliyun OSS: Use getObjectMetadata instead of listObjects to get
metadata for a single object. This is a simpler call that is also
expected to be less expensive.
2) Azure: Fix a bug where getBlobLength did not populate blob
reference attributes, and therefore would not actually retrieve the
blob length.
3) MSQ: Align dynamic slicing logic between ExternalInputSpecSlicer and
TableInputSpecSlicer.
4) MSQ: Adjust WorkerInputs to ensure there is always at least one
worker, even if it has a nil slice.
* Add msqCompatible to testGroupByWithImpossibleTimeFilter.
* Fix tests.
* Add additional tests.
* Remove unused stuff.
* Remove more unused stuff.
* Adjust thresholds.
* Remove irrelevant test.
* Fix comments.
* Fix bug.
* Updates.
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.
* Reworking s3 connector with
1. Adding retries
2. Adding max fetch size
3. Using s3Utils for most of the api's
4. Fixing bugs in DurableStorageCleaner
5. Moving to Iterator for listDir call
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.
* 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
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
This commit adds a new class `InputStats` to track the total bytes processed by a task.
The field `processedBytes` is published in task reports along with other row stats.
Major changes:
- Add class `InputStats` to track processed bytes
- Add method `InputSourceReader.read(InputStats)` to read input rows while counting bytes.
> Since we need to count the bytes, we could not just have a wrapper around `InputSourceReader` or `InputEntityReader` (the way `CountableInputSourceReader` does) because the `InputSourceReader` only deals with `InputRow`s and the byte information is already lost.
- Classic batch: Use the new `InputSourceReader.read(inputStats)` in `AbstractBatchIndexTask`
- Streaming: Increment `processedBytes` in `StreamChunkParser`. This does not use the new `InputSourceReader.read(inputStats)` method.
- Extend `InputStats` with `RowIngestionMeters` so that bytes can be exposed in task reports
Other changes:
- Update tests to verify the value of `processedBytes`
- Rename `MutableRowIngestionMeters` to `SimpleRowIngestionMeters` and remove duplicate class
- Replace `CacheTestSegmentCacheManager` with `NoopSegmentCacheManager`
- Refactor `KafkaIndexTaskTest` and `KinesisIndexTaskTest`
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.
* Use standard library to correctly glob and stop at the correct folder structure when filtering cloud objects.
Removed:
import org.apache.commons.io.FilenameUtils;
Add:
import java.nio.file.FileSystems;
import java.nio.file.PathMatcher;
import java.nio.file.Paths;
* Forgot to update CloudObjectInputSource as well.
* Fix tests.
* Removed unused exceptions.
* Able to reduced user mistakes, by removing the protocol and the bucket on filter.
* add 1 more test.
* add comment on filterWithoutProtocolAndBucket
* Fix lint issue.
* Fix another lint issue.
* Replace all mention of filter -> objectGlob per convo here:
https://github.com/apache/druid/pull/13027#issuecomment-1266410707
* fix 1 bad constructor.
* Fix the documentation.
* Don’t do anything clever with the object path.
* Remove unused imports.
* Fix spelling error.
* Fix incorrect search and replace.
* Addressing Gian’s comment.
* add filename on .spelling
* Fix documentation.
* fix documentation again
Co-authored-by: Didip Kerabat <didip@apple.com>
Akshat Jain
Adarsh Sanjeev
Karan Kumar
Gian Merlino
Jonathan Wei
Krishna Anandan
Abhishek Radhakrishnan
Laksh Singla
George Shiqi Wu
Rohan Garg
Rishabh Singh
zachjsh
YongGang
Pranav
TSFenwick
Abhishek Agarwal
AmatyaAvadhanula
Atul Mohan
Nicholas Lippis
Clint Wylie
Tejaswini Bandlamudi
Paul Rogers
Kashif Faraz
Didip Kerabat