Hadoop 2 often causes red security scans on Druid distribution because of the dependencies it brings. We want to move away from Hadoop 2 and provide Hadoop 3 distribution available. Switch druid to building with Hadoop 3 by default. Druid will still be compatible with Hadoop 2 and users can build hadoop-2 compatible distribution using hadoop2 profile.
* Compaction: Block input specs not aligned with segmentGranularity.
When input intervals are not aligned with segmentGranularity, data may be
overshadowed if it lies in the space between the input intervals and the
output segmentGranularity.
In MSQ REPLACE, this is a validation error. IMO the same behavior makes
sense for compaction tasks. In case anyone was depending on the ability
to compact nonaligned intervals, a configuration parameter
allowNonAlignedInterval is provided. I don't expect it to be used much.
* Remove unused.
* ITCompactionTaskTest uses non-aligned intervals.
* MSQ: Support multiple result columns with the same name.
This is allowed in SQL, and is supported by the regular SQL endpoint.
We retain a validation that INSERT ... SELECT does not allow multiple
columns with the same name, because column names in segments must be
unique.
* 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.
Create the docker image in case of maven dependencies cache restore failure too as env.sh file is removed on maven rebuild.
Increase java heap size for security IT failing with error
* 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
* Unify the handling of HTTP between SQL and Native
The SqlResource and QueryResource have been
using independent logic for things like error
handling and response context stuff. This
became abundantly clear and painful during a
change I was making for Window Functions, so
I unified them into using the same code for
walking the response and serializing it.
Things are still not perfectly unified (it would
be the absolute best if the SqlResource just
took SQL, planned it and then delegated the
query run entirely to the QueryResource), but
this refactor doesn't take that fully on.
The new code leverages async query processing
from our jetty container, the different
interaction model with the Resource means that
a lot of tests had to be adjusted to align with
the async query model. The semantics of the
tests remain the same with one exception: the
SqlResource used to not log requests that failed
authorization checks, now it does.
* Always return sketches from DS_HLL, DS_THETA, DS_QUANTILES_SKETCH.
These aggregation functions are documented as creating sketches. However,
they are planned into native aggregators that include finalization logic
to convert the sketch to a number of some sort. This creates an
inconsistency: the functions sometimes return sketches, and sometimes
return numbers, depending on where they lie in the native query plan.
This patch changes these SQL aggregators to _never_ finalize, by using
the "shouldFinalize" feature of the native aggregators. It already
existed for theta sketches. This patch adds the feature for hll and
quantiles sketches.
As to impact, Druid finalizes aggregators in two cases:
- When they appear in the outer level of a query (not a subquery).
- When they are used as input to an expression or finalizing-field-access
post-aggregator (not any other kind of post-aggregator).
With this patch, the functions will no longer be finalized in these cases.
The second item is not likely to matter much. The SQL functions all declare
return type OTHER, which would be usable as an input to any other function
that makes sense and that would be planned into an expression.
So, the main effect of this patch is the first item. To provide backwards
compatibility with anyone that was depending on the old behavior, the
patch adds a "sqlFinalizeOuterSketches" query context parameter that
restores the old behavior.
Other changes:
1) Move various argument-checking logic from runtime to planning time in
DoublesSketchListArgBaseOperatorConversion, by adding an OperandTypeChecker.
2) Add various JsonIgnores to the sketches to simplify their JSON representations.
3) Allow chaining of ExpressionPostAggregators and other PostAggregators
in the SQL layer.
4) Avoid unnecessary FieldAccessPostAggregator wrapping in the SQL layer,
now that expressions can operate on complex inputs.
5) Adjust return type to thetaSketch (instead of OTHER) in
ThetaSketchSetBaseOperatorConversion.
* Fix benchmark class.
* Fix compilation error.
* Fix ThetaSketchSqlAggregatorTest.
* Hopefully fix ITAutoCompactionTest.
* Adjustment to ITAutoCompactionTest.
In clusters with a large number of segments, the duty `MarkAsUnusedOvershadowedSegments`
can take a long very long time to finish. This is because of the costly invocation of
`timeline.isOvershadowed` which is done for every used segment in every coordinator run.
Changes
- Use `DataSourceSnapshot.getOvershadowedSegments` to get all overshadowed segments
- Iterate over this set instead of all used segments to identify segments that can be marked as unused
- Mark segments as unused in the DB in batches rather than one at a time
- Refactor: Add class `SegmentTimeline` for ease of use and readability while using a
`VersionedIntervalTimeline` of segments.
* Refactor Calcite test "framework" for planner tests
Refactors the current Calcite tests to make it a bit easier
to adjust the set of runtime objects used within a test.
* Move data creation out of CalciteTests into TestDataBuilder
* Move "framework" creation out of CalciteTests into
a QueryFramework
* Move injector-dependent functions from CalciteTests
into QueryFrameworkUtils
* Wrapper around the planner factory, etc. to allow
customization.
* Bulk of the "framework" created once per class rather
than once per test.
* Refactor tests to use a test builder
* Change all testQuery() methods to use the test builder.
Move test execution & verification into a test runner.
We introduce two new configuration keys that refine the query context security model controlled by druid.auth.authorizeQueryContextParams. When that value is set to true then two other configuration options become available:
druid.auth.unsecuredContextKeys: The set of query context keys that do not require a security check. Use this for the "white-list" of key to allow. All other keys go through the existing context key security checks.
druid.auth.securedContextKeys: The set of query context keys that do require a security check. Use this when you want to allow all but a specific set of keys: only these keys go through the existing context key security checks.
Both are set using JSON list format:
druid.auth.securedContextKeys=["secretKey1", "secretKey2"]
You generally set one or the other values. If both are set, unsecuredContextKeys acts as exceptions to securedContextKeys.
In addition, Druid defines two query context keys which always bypass checks because Druid uses them internally:
sqlQueryId
sqlStringifyArrays
* Add interpolation to JsonConfigurator
* Fix checkstyle
* Fix tests by removing common-text override
* Add back commons-text without version
* Remove unused hadoopDir configs
* Move some stuff to hopefully pass coverage
This commit is a first draft of the revised integration test framework which provides:
- A new directory, integration-tests-ex that holds the new integration test structure. (For now, the existing integration-tests is left unchanged.)
- Maven module druid-it-tools to hold code placed into the Docker image.
- Maven module druid-it-image to build the Druid-only test image from the tarball produced in distribution. (Dependencies live in their "official" image.)
- Maven module druid-it-cases that holds the revised tests and the framework itself. The framework includes file-based test configuration, test-specific clients, test initialization and updated versions of some of the common test support classes.
The integration test setup is primarily a huge mass of details. This approach refactors many of those details: from how the image is built and configured to how the Docker Compose scripts are structured to test configuration. An extensive set of "readme" files explains those details. Rather than repeat that material here, please consult those files for explanations.
* Refactor SqlLifecycle into statement classes
Create direct & prepared statements
Remove redundant exceptions from tests
Tidy up Calcite query tests
Make PlannerConfig more testable
* Build fixes
* Added builder to SqlQueryPlus
* Moved Calcites system properties to saffron.properties
* Build fix
* Resolve merge conflict
* Fix IntelliJ inspection issue
* Revisions from reviews
Backed out a revision to Calcite tests that didn't work out as planned
* Build fix
* Fixed spelling errors
* Fixed failed test
Prepare now enforces security; before it did not.
* Rebase and fix IntelliJ inspections issue
* Clean up exception handling
* Fix handling of JDBC auth errors
* Build fix
* More tweaks to security messages
Kinesis ingestion requires all shards to have at least 1 record at the required position in druid.
Even if this is satisified initially, resharding the stream can lead to empty intermediate shards. A significant delay in writing to newly created shards was also problematic.
Kinesis shard sequence numbers are big integers. Introduce two more custom sequence tokens UNREAD_TRIM_HORIZON and UNREAD_LATEST to indicate that a shard has not been read from and that it needs to be read from the start or the end respectively.
These values can be used to avoid the need to read at least one record to obtain a sequence number for ingesting a newly discovered shard.
If a record cannot be obtained immediately, use a marker to obtain the relevant shardIterator and use this shardIterator to obtain a valid sequence number. As long as a valid sequence number is not obtained, continue storing the token as the offset.
These tokens (UNREAD_TRIM_HORIZON and UNREAD_LATEST) are logically ordered to be earlier than any valid sequence number.
However, the ordering requires a few subtle changes to the existing mechanism for record sequence validation:
The sequence availability check ensures that the current offset is before the earliest available sequence in the shard. However, current token being an UNREAD token indicates that any sequence number in the shard is valid (despite the ordering)
Kinesis sequence numbers are inclusive i.e if current sequence == end sequence, there are more records left to read.
However, the equality check is exclusive when dealing with UNREAD tokens.
* Refactor Guice initialization
Builders for various module collections
Revise the extensions loader
Injector builders for server startup
Move Hadoop init to indexer
Clean up server node role filtering
Calcite test injector builder
* Revisions from review comments
* Build fixes
* Revisions from review comments
* Druid planner now makes only one pass through Calcite planner
Resolves the issue that required two parse/plan cycles: one
for validate, another for plan. Creates a clone of the Calcite
planner and validator to resolve the conflict that prevented
the merger.
* Fixes for the Avatica JDBC driver
Correctly implement regular and prepared statements
Correctly implement result sets
Fix race condition with contexts
Clarify when parameters are used
Prepare for single-pass through the planner
* Addressed review comments
* Addressed review comment
Tejaswini Bandlamudi
Gian Merlino
Atul Mohan
Clint Wylie
AdheipSingh
hqx871
Abhishek Radhakrishnan
Abhishek Agarwal
Paul Rogers
Maytas Monsereenusorn
abhagraw
Karan Kumar
imply-cheddar
Kashif Faraz
Rohan Garg
Frank Chen
Laksh Singla
Vadim Ogievetsky
Adam Peck
Xavier Léauté
AmatyaAvadhanula