* Support for middle manager less druid, tasks launch as k8s jobs
* Fixing forking task runner test
* Test cleanup, dependency cleanup, intellij inspections cleanup
* Changes per PR review
Add configuration option to disable http/https proxy for the k8s client
Update the docs to provide more detail about sidecar support
* Removing un-needed log lines
* Small changes per PR review
* Upon task completion we callback to the overlord to update the status / locaiton, for slower k8s clusters, this reduces locking time significantly
* Merge conflict fix
* Fixing tests and docs
* update tiny-cluster.yaml
changed `enableTaskLevelLogPush` to `encapsulatedTask`
* Apply suggestions from code review
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Minor changes per PR request
* Cleanup, adding test to AbstractTask
* Add comment in peon.sh
* Bumping code coverage
* More tests to make code coverage happy
* Doh a duplicate dependnecy
* Integration test setup is weird for k8s, will do this in a different PR
* Reverting back all integration test changes, will do in anotbher PR
* use StringUtils.base64 instead of Base64
* Jdk is nasty, if i compress in jdk 11 in jdk 17 the decompressed result is different
Co-authored-by: Rahul Gidwani <r_gidwani@apple.com>
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
Async reads for JDBC:
Prevents JDBC timeouts on long queries by returning empty batches
when a batch fetch takes too long. Uses an async model to run the
result fetch concurrently with JDBC requests.
Fixed race condition in Druid's Avatica server-side handler
Fixed issue with no-user connections
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
Druid currently uses Zookeeper dependent options as the default.
This commit updates the following to use HTTP as the default instead.
- task runner. `druid.indexer.runner.type=remote -> httpRemote`
- load queue peon. `druid.coordinator.loadqueuepeon.type=curator -> http`
- server inventory view. `druid.serverview.type=curator -> http`
* Fixing RACE in HTTP remote task Runner
* Changes in the interface
* Updating documentation
* Adding test cases to SwitchingTaskLogStreamer
* Adding more tests
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.
Refactors the DruidSchema and DruidTable abstractions to prepare for the Druid Catalog.
As we add the catalog, we’ll want to combine physical segment metadata information with “hints” provided by the catalog. This is best done if we tidy up the existing code to more clearly separate responsibilities.
This PR is purely a refactoring move: no functionality changed. There is no difference to user functionality or external APIs. Functionality changes will come later as we add the catalog itself.
DruidSchema
In the present code, DruidSchema does three tasks:
Holds the segment metadata cache
Interfaces with an external schema manager
Acts as a schema to Calcite
This PR splits those responsibilities.
DruidSchema holds the Calcite schema for the druid namespace, combining information fro the segment metadata cache, from the external schema manager and (later) from the catalog.
SegmentMetadataCache holds the segment metadata cache formerly in DruidSchema.
DruidTable
The present DruidTable class is a bit of a kitchen sink: it holds all the various kinds of tables which Druid supports, and uses if-statements to handle behavior that differs between types. Yet, any given DruidTable will handle only one such table type. To more clearly model the actual table types, we split DruidTable into several classes:
DruidTable becomes an abstract base class to hold Druid-specific methods.
DatasourceTable represents a datasource.
ExternalTable represents an external table, such as from EXTERN or (later) from the catalog.
InlineTable represents the internal case in which we attach data directly to a table.
LookupTable represents Druid’s lookup table mechanism.
The new subclasses are more focused: they can be selective about the data they hold and the various predicates since they represent just one table type. This will be important as the catalog information will differ depending on table type and the new structure makes adding that logic cleaner.
DatasourceMetadata
Previously, the DruidSchema segment cache would work with DruidTable objects. With the catalog, we need a layer between the segment metadata and the table as presented to Calcite. To fix this, the new SegmentMetadataCache class uses a new DatasourceMetadata class as its cache entry to hold only the “physical” segment metadata information: it is up to the DruidTable to combine this with the catalog information in a later PR.
More Efficient Table Resolution
Calcite provides a convenient base class for schema objects: AbstractSchema. However, this class is a bit too convenient: all we have to do is provide a map of tables and Calcite does the rest. This means that, to resolve any single datasource, say, foo, we need to cache segment metadata, external schema information, and catalog information for all tables. Just so Calcite can do a map lookup.
There is nothing special about AbstractSchema. We can handle table lookups ourselves. The new AbstractTableSchema does this. In fact, all the rest of Calcite wants is to resolve individual tables by name, and, for commands we don’t use, to provide a list of table names.
DruidSchema now extends AbstractTableSchema. SegmentMetadataCache resolves individual tables (and provides table names.)
DruidSchemaManager
DruidSchemaManager provides a way to specify table schemas externally. In this sense, it is similar to the catalog, but only for datasources. It originally followed the AbstractSchema pattern: it implements provide a map of tables. This PR provides new optional methods for the table lookup and table names operations. The default implementations work the same way that AbstractSchema works: we get the entire map and pick out the information we need. Extensions that use this API should be revised to support the individual operations instead. Druid code no longer calls the original getTables() method.
The PR has one breaking change: since the DruidSchemaManager map is read-only to the rest of Druid, we should return a Map, not a ConcurrentMap.
* 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
* Mid-level service client and updated high-level clients.
Our servers talk to each other over HTTP. We have a low-level HTTP
client (HttpClient) that is super-asynchronous and super-customizable
through its handlers. It's also proven to be quite robust: we use it
for Broker -> Historical communication over the wide variety of query
types and workloads we support.
But the low-level client has no facilities for service location or
retries, which means we have a variety of high-level clients that
implement these in their own ways. Some high-level clients do a better
job than others. This patch adds a mid-level ServiceClient that makes
it easier for high-level clients to be built correctly and harmoniously,
and migrates some of the high-level logic to use ServiceClients.
Main changes:
1) Add ServiceClient org.apache.druid.rpc package. That package also
contains supporting stuff like ServiceLocator and RetryPolicy
interfaces, and a DiscoveryServiceLocator based on
DruidNodeDiscoveryProvider.
2) Add high-level OverlordClient in org.apache.druid.rpc.indexing.
3) Indexing task client creator in TaskServiceClients. It uses
SpecificTaskServiceLocator to find the tasks. This improves on
ClientInfoTaskProvider by caching task locations for up to 30 seconds
across calls, reducing load on the Overlord.
4) Rework ParallelIndexSupervisorTaskClient to use a ServiceClient
instead of extending IndexTaskClient.
5) Rework RemoteTaskActionClient to use a ServiceClient instead of
DruidLeaderClient.
6) Rework LocalIntermediaryDataManager, TaskMonitor, and
ParallelIndexSupervisorTask. As a result, MiddleManager, Peon, and
Overlord no longer need IndexingServiceClient (which internally used
DruidLeaderClient).
There are some concrete benefits over the prior logic, namely:
- DruidLeaderClient does retries in its "go" method, but only retries
exactly 5 times, does not sleep between retries, and does not retry
retryable HTTP codes like 502, 503, 504. (It only retries IOExceptions.)
ServiceClient handles retries in a more reasonable way.
- DruidLeaderClient's methods are all synchronous, whereas ServiceClient
methods are asynchronous. This is used in one place so far: the
SpecificTaskServiceLocator, so we don't need to block a thread trying
to locate a task. It can be used in other places in the future.
- HttpIndexingServiceClient does not properly handle all server errors.
In some cases, it tries to parse a server error as a successful
response (for example: in getTaskStatus).
- IndexTaskClient currently makes an Overlord call on every task-to-task
HTTP request, as a way to find where the target task is. ServiceClient,
through SpecificTaskServiceLocator, caches these target locations
for a period of time.
* Style adjustments.
* For the coverage.
* Adjustments.
* Better behaviors.
* Fixes.
This commit contains the cleanup needed for the new integration test framework.
Changes:
- Fix log lines, misspellings, docs, etc.
- Allow the use of some of Druid's "JSON config" objects in tests
- Fix minor bug in `BaseNodeRoleWatcher`
* ForkingTaskRunner: Set ActiveProcessorCount for tasks.
This prevents various automatically-sized thread pools from being unreasonably
large (we don't want each task to size its pools as if it is the only thing on
the entire machine).
* Fix tests.
* Add missing LifecycleStart annotation.
* ForkingTaskRunner needs ManageLifecycle.
* Add QoSFilters first in the chain.
When a request is suspended and later resumed due to QoS constraints,
its filter chain is restarted. Placing QoSFilters first in the chain
avoids double-execution of other filters.
Fixes an issue where requests deferred by QoS would report 403 Forbidden
due to double-execution of SecuritySanityCheckFilter.
* Smaller changes.
* Add QoS filters in BaseJettyTest.
* Remove unused parameter.
Following up on #12315, which pushed most of the logic of building ImmutableBitmap into BitmapIndex in order to hide the details of how column indexes are implemented from the Filter implementations, this PR totally refashions how Filter consume indexes. The end result, while a rather dramatic reshuffling of the existing code, should be extraordinarily flexible, eventually allowing us to model any type of index we can imagine, and providing the machinery to build the filters that use them, while also allowing for other column implementations to implement the built-in index types to provide adapters to make use indexing in the current set filters that Druid provides.
* 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
* Thread pool for broker
* Updating two tests to improve coverage for new method added
* Updating druidProcessingConfigTest to cover coverage
* Adding missed spelling errors caused in doc
* Adding test to cover lines of new function added
* Make nodeRole available during binding; add support for dynamic registration of DruidService
* fix checkstyle and test
* fix customRole test
* address comments
* add more javadoc
Add support for hadoop 3 profiles . Most of the details are captured in #11791 .
We use a combination of maven profiles and resource filtering to achieve this. Hadoop2 is supported by default and a new maven profile with the name hadoop3 is created. This will allow the user to choose the profile which is best suited for the use case.
* Add the ability to add a context to internally generated druid broker queries
* fix docs
* changes after first CI failure
* cleanup after merge with master
* change default to empty map and improve unit tests
* add doc info and fix checkstyle
* refactor DruidSchema#runSegmentMetadataQuery and add a unit test
* Rename field, fix router documentation
* Add more lines to doc
* Apply doc suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* initial work
* reduce lock in sqlLifecycle
* Integration test for sql canceling
* javadoc, cleanup, more tests
* log level to debug
* fix test
* checkstyle
* fix flaky test; address comments
* rowTransformer
* cancelled state
* use lock
* explode instead of noop
* oops
* unused import
* less aggressive with state
* fix calcite charset
* don't emit metrics when you are not authorized
Fixes#11297.
Description
Description and design in the proposal #11297
Key changed/added classes in this PR
*DataSegmentPusher
*ShuffleClient
*PartitionStat
*PartitionLocation
*IntermediaryDataManager
This PR adds a new property druid.router.sql.enable which allows the
Router to handle SQL queries when set to true.
This change does not affect Avatica JDBC requests and they are still routed
by hashing the Connection ID.
To allow parsing of the request object as a SqlQuery (contained in module druid-sql),
some classes have been moved from druid-server to druid-services with
the same package name.
This PR refactors the code for QueryRunnerFactory#mergeRunners to accept a new interface called QueryProcessingPool instead of ExecutorService for concurrent execution of query runners. This interface will let custom extensions inject their own implementation for deciding which query-runner to prioritize first. The default implementation is the same as today that takes the priority of query into account. QueryProcessingPool can also be used as a regular executor service. It has a dedicated method for accepting query execution work so implementations can differentiate between regular async tasks and query execution tasks. This dedicated method also passes the QueryRunner object as part of the task information. This hook will let custom extensions carry any state from QuerySegmentWalker to QueryProcessingPool#mergeRunners which is not possible currently.
Kashif Faraz
Clint Wylie
Dr. Sizzles
Paul Rogers
AmatyaAvadhanula
Rohan Garg
Abhishek Agarwal
Karan Kumar
Gian Merlino
zachjsh
Xavier Léauté
Suneet Saldanha
Maytas Monsereenusorn
somu-imply
Jihoon Son
Lucas Capistrant
Parag Jain
Yi Yuan