* 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
This commit contains changes made to the existing ITs to support the new ITs.
Changes:
- Make the "custom node role" code usable by the new ITs.
- Use flag `-DskipITs` to skips the integration tests but runs unit tests.
- Use flag `-DskipUTs` skips unit tests but runs the "new" integration tests.
- Expand the existing Druid profile, `-P skip-tests` to skip both ITs and UTs.
* Remove null and empty fields from native queries
* Test fixes
* Attempted IT fix.
* Revisions from review comments
* Build fixes resulting from changes suggested by reviews
* IT fix for changed segment size
The web-console (indirectly) calls the Overlord’s GET tasks API to fetch the tasks' summary which in turn queries the metadata tasks table. This query tries to fetch several columns, including payload, of all the rows at once. This introduces a significant memory overhead and can cause unresponsiveness or overlord failure when the ingestion tab is opened multiple times (due to several parallel calls to this API)
Another thing to note is that the task table (the payload column in particular) can be very large. Extracting large payloads from such tables can be very slow, leading to slow UI. While we are fixing the memory pressure in the overlord, we can also fix the slowness in UI caused by fetching large payloads from the table. Fetching large payloads also puts pressure on the metadata store as reported in the community (Metadata store query performance degrades as the tasks in druid_tasks table grows · Issue #12318 · apache/druid )
The task summaries returned as a response for the API are several times smaller and can fit comfortably in memory. So, there is an opportunity here to fix the memory usage, slow ingestion, and under-pressure metadata store by removing the need to handle large payloads in every layer we can. Of course, the solution becomes complex as we try to fix more layers. With that in mind, this page captures two approaches. They vary in complexity and also in the degree to which they fix the aforementioned problems.
Issue:
Even though `CompactionTuningConfig` allows a `maxColumnsToMerge` config
(to optimize memory usage, particulary for datasources with many dimensions),
the corresponding client object `ClientCompactionTaskQueryTuningConfig`
(used by the coordinator duty `CompactSegments` to trigger auto-compaction)
does not contain this field. Thus, the value of `maxColumnsToMerge` specified
in any datasource compaction config is ignored.
Changes:
- Add field `maxColumnsToMerge` in `ClientCompactionTaskQueryTuningConfig`
and `UserCompactionTaskQueryTuningConfig`
- Fix tests
* SQL: Add is_active to sys.segments, update examples and docs.
is_active is short for:
(is_published = 1 AND is_overshadowed = 0) OR is_realtime = 1
It's important because this represents "all the segments that should
be queryable, whether or not they actually are right now". Most of the
time, this is the set of segments that people will want to look at.
The web console already adds this filter to a lot of its queries,
proving its usefulness.
This patch also reworks the caveat at the bottom of the sys.segments
section, so its information is mixed into the description of each result
field. This should make it more likely for people to see the information.
* Wording updates.
* Adjustments for spellcheck.
* Adjust IT.
The query context is a way that the user gives a hint to the Druid query engine, so that they enforce a certain behavior or at least let the query engine prefer a certain plan during query planning. Today, there are 3 types of query context params as below.
Default context params. They are set via druid.query.default.context in runtime properties. Any user context params can be default params.
User context params. They are set in the user query request. See https://druid.apache.org/docs/latest/querying/query-context.html for parameters.
System context params. They are set by the Druid query engine during query processing. These params override other context params.
Today, any context params are allowed to users. This can cause
1) a bad UX if the context param is not matured yet or
2) even query failure or system fault in the worst case if a sensitive param is abused, ex) maxSubqueryRows.
This PR adds an ability to limit context params per user role. That means, a query will fail if you have a context param set in the query that is not allowed to you. To do that, this PR adds a new built-in resource type, QUERY_CONTEXT. The resource to authorize has a name of the context param (such as maxSubqueryRows) and the type of QUERY_CONTEXT. To allow a certain context param for a user, the user should be granted WRITE permission on the context param resource. Here is an example of the permission.
{
"resourceAction" : {
"resource" : {
"name" : "maxSubqueryRows",
"type" : "QUERY_CONTEXT"
},
"action" : "WRITE"
},
"resourceNamePattern" : "maxSubqueryRows"
}
Each role can have multiple permissions for context params. Each permission should be set for different context params.
When a query is issued with a query context X, the query will fail if the user who issued the query does not have WRITE permission on the query context X. In this case,
HTTP endpoints will return 403 response code.
JDBC will throw ForbiddenException.
Note: there is a context param called brokerService that is used only by the router. This param is used to pin your query to run it in a specific broker. Because the authorization is done not in the router, but in the broker, if you have brokerService set in your query without a proper permission, your query will fail in the broker after routing is done. Technically, this is not right because the authorization is checked after the context param takes effect. However, this should not cause any user-facing issue and thus should be OK. The query will still fail if the user doesn’t have permission for brokerService.
The context param authorization can be enabled using druid.auth.authorizeQueryContextParams. This is disabled by default to avoid any hassle when someone upgrades his cluster blindly without reading release notes.
* Make tombstones ingestible by having them return an empty result set.
* Spotbug
* Coverage
* Coverage
* Remove unnecessary exception (checkstyle)
* Fix integration test and add one more to test dropExisting set to false over tombstones
* Force dropExisting to true in auto-compaction when the interval contains only tombstones
* Checkstyle, fix unit test
* Changed flag by mistake, fixing it
* Remove method from interface since this method is specific to only DruidSegmentInputentity
* Fix typo
* Adapt to latest code
* Update comments when only tombstones to compact
* Move empty iterator to a new DruidTombstoneSegmentReader
* Code review feedback
* Checkstyle
* Review feedback
* Coverage
* add impl
* add impl
* fix checkstyle
* add impl
* add unit test
* fix stuff
* fix stuff
* fix stuff
* add unit test
* add more unit tests
* add more unit tests
* add IT
* add IT
* add IT
* add IT
* add ITs
* address comments
* fix test
* fix test
* fix test
* address comments
* address comments
* address comments
* fix conflict
* fix checkstyle
* address comments
* fix test
* fix checkstyle
* fix test
* fix test
* fix IT
The current default value of inputSegmentSizeBytes is 400MB, which is pretty
low for most compaction use cases. Thus most users are forced to override the
default.
The default value is now increased to Long.MAX_VALUE.
listShards API was used to get all the shards for kinesis ingestion to improve its resiliency as part of #12161.
However, this may require additional permissions in the IAM policy where the stream is present. (Please refer to: https://docs.aws.amazon.com/kinesis/latest/APIReference/API_ListShards.html).
A dynamic configuration useListShards has been added to KinesisSupervisorTuningConfig to control the usage of this API and prevent issues upon upgrade. It can be safely turned on (and is recommended when using kinesis ingestion) by setting this configuration to true.
* Store null columns in the segments
* fix test
* remove NullNumericColumn and unused dependency
* fix compile failure
* use guava instead of apache commons
* split new tests
* unused imports
* address comments
* finds complete and active tasks from the same snapshot
* overlord resource
* unit test
* integration test
* javadoc and cleanup
* more cleanup
* fix test and add more
* Tombstone support for replace functionality
* A used segment interval is the interval of a current used segment that overlaps any of the input intervals for the spec
* Update compaction test to match replace behavior
* Adapt ITAutoCompactionTest to work with tombstones rather than dropping segments. Add support for tombstones in the broker.
* Style plus simple queriableindex test
* Add segment cache loader tombstone test
* Add more tests
* Add a method to the LogicalSegment to test whether it has any data
* Test filter with some empty logical segments
* Refactor more compaction/dropexisting tests
* Code coverage
* Support for all empty segments
* Skip tombstones when looking-up broker's timeline. Discard changes made to tool chest to avoid empty segments since they will no longer have empty segments after lookup because we are skipping over them.
* Fix null ptr when segment does not have a queriable index
* Add support for empty replace interval (all input data has been filtered out)
* Fixed coverage & style
* Find tombstone versions from lock versions
* Test failures & style
* Interner was making this fail since the two segments were consider equal due to their id's being equal
* Cleanup tombstone version code
* Force timeChunkLock whenever replace (i.e. dropExisting=true) is being used
* Reject replace spec when input intervals are empty
* Documentation
* Style and unit test
* Restore test code deleted by mistake
* Allocate forces TIME_CHUNK locking and uses lock versions. TombstoneShardSpec added.
* Unused imports. Dead code. Test coverage.
* Coverage.
* Prevent killer from throwing an exception for tombstones. This is the killer used in the peon for killing segments.
* Fix OmniKiller + more test coverage.
* Tombstones are now marked using a shard spec
* Drop a segment factory.json in the segment cache for tombstones
* Style
* Style + coverage
* style
* Add TombstoneLoadSpec.class to mapper in test
* Update core/src/main/java/org/apache/druid/segment/loading/TombstoneLoadSpec.java
Typo
Co-authored-by: Jonathan Wei <jon-wei@users.noreply.github.com>
* Update docs/configuration/index.md
Missing
Co-authored-by: Jonathan Wei <jon-wei@users.noreply.github.com>
* Typo
* Integrated replace with an existing test since the replace part was redundant and more importantly, the test file was very close or exceeding the 10 min default "no output" CI Travis threshold.
* Range does not work with multi-dim
Co-authored-by: Jonathan Wei <jon-wei@users.noreply.github.com>
* upgrade Airline to Airline 2
https://github.com/airlift/airline is no longer maintained, updating to
https://github.com/rvesse/airline (Airline 2) to use an actively
maintained version, while minimizing breaking changes.
Note, this is a backwards incompatible change, and extensions relying on
the CliCommandCreator extension point will also need to be updated.
* fix dependency checks where jakarta.inject is now resolved first instead
of javax.inject, due to Airline 2 using jakarta
* remove use of mocks for ServiceMetricEvent
* simplify KafkaEmitterTests by moving to Mockito
* speed up KafkaEmitterTest by adjusting reporting frequency in tests
* remove unnecessary easymock and JUnitParams dependencies
Problem:
- When a kinesis stream is resharded, the original shards are closed.
Any intermediate shard created in the process is eventually closed as well.
- If a shard is closed before any record is put into it, it can be safely ignored for ingestion.
- It is expensive to determine if a closed shard is empty, since it requires a call to the Kinesis cluster.
Changes:
- Maintain a cache of closed empty and closed non-empty shards in `KinesisSupervisor`
- Add config `skipIngorableShards` to `KinesisSupervisorTuningConfig`
- The caches are used and updated only when `skipIgnorableShards = true`
This fixes intermittent, spurious failures that we've observed in
the Kinesis sharding integration tests due to Kinesis taking
longer than the code expected to start a sharding operation. The
method that's changed is part of the integration test suite and
only used by the test cases that we've seen are flaky.
Prior to this change, the tests expected a sharding operation to
start in 9 seconds (30 retries * 300ms delay/retry). This change
bumps the number of retries to 100, giving Kinesis 30 seconds to
start the sharding.
This PR also makes a small, clarifying change to the condition
used to determine if sharding has started. Instead of checking if
the number of shards has increased (which was technically correct
even if the test is reducing the number of shards due to a Kinesis
implementation detail), we now just check if the shard count has
changed.
Paul Rogers
Tejaswini Bandlamudi
Frank Chen
Laksh Singla
Vadim Ogievetsky
Adam Peck
Abhishek Agarwal
Xavier Léauté
AmatyaAvadhanula
Rohan Garg
Kashif Faraz
Maytas Monsereenusorn
Clint Wylie
Jihoon Son
superivaj
Gian Merlino
TSFenwick
Agustin Gonzalez
AmatyaAvadhanula
Daniel Koepke