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`
Refactor DataSource to have a getAnalysis method()
This removes various parts of the code where while loops and instanceof
checks were being used to walk through the structure of DataSource objects
in order to build a DataSourceAnalysis. Instead we just ask the DataSource
for its analysis and allow the stack to rebuild whatever structure existed.
* Zero-copy local deep storage.
This is useful for local deep storage, since it reduces disk usage and
makes Historicals able to load segments instantaneously.
Two changes:
1) Introduce "druid.storage.zip" parameter for local storage, which defaults
to false. This changes default behavior from writing an index.zip to writing
a regular directory. This is safe to do even during a rolling update, because
the older code actually already handled unzipped directories being present
on local deep storage.
2) In LocalDataSegmentPuller and LocalDataSegmentPusher, use hard links
instead of copies when possible. (Generally this is possible when the
source and destination directory are on the same filesystem.)
* Druid automated quickstart
* remove conf/druid/single-server/quickstart/_common/historical/jvm.config
* Minor changes in python script
* Add lower bound memory for some services
* Additional runtime properties for services
* Update supervise script to accept command arguments, corresponding changes in druid-quickstart.py
* File end newline
* Limit the ability to start multiple instances of a service, documentation changes
* simplify script arguments
* restore changes in medium profile
* run-druid refactor
* compute and pass middle manager runtime properties to run-druid
supervise script changes to process java opts array
use argparse, leave free memory, logging
* Remove extra quotes from mm task javaopts array
* Update logic to compute minimum memory
* simplify run-druid
* remove debug options from run-druid
* resolve the config_path provided
* comment out service specific runtime properties which are computed in the code
* simplify run-druid
* clean up docs, naming changes
* Throw ValueError exception on illegal state
* update docs
* rename args, compute_only -> compute, run_zk -> zk
* update help documentation
* update help documentation
* move task memory computation into separate method
* Add validation checks
* remove print
* Add validations
* remove start-druid bash script, rename start-druid-main
* Include tasks in lower bound memory calculation
* Fix test
* 256m instead of 256g
* caffeine cache uses 5% of heap
* ensure min task count is 2, task count is monotonic
* update configs and documentation for runtime props in conf/druid/single-server/quickstart
* Update docs
* Specify memory argument for each profile in single-server.md
* Update middleManager runtime.properties
* Move quickstart configs to conf/druid/base, add bash launch script, support python2
* Update supervise script
* rename base config directory to auto
* rename python script, changes to pass repeated args to supervise
* remove exmaples/conf/druid/base dir
* add docs
* restore changes in conf dir
* update start-druid-auto
* remove hashref for commands in supervise script
* start-druid-main java_opts array is comma separated
* update entry point script name in python script
* Update help docs
* documentation changes
* docs changes
* update docs
* add support for running indexer
* update supported services list
* update help
* Update python.md
* remove dir
* update .spelling
* Remove dependency on psutil and pathlib
* update docs
* Update get_physical_memory method
* Update help docs
* update docs
* update method to get physical memory on python
* udpate spelling
* update .spelling
* minor change
* Minor change
* memory comptuation for indexer
* update start-druid
* Update python.md
* Update single-server.md
* Update python.md
* run python3 --version to check if python is installed
* Update supervise script
* start-druid: echo message if python not found
* update anchor text
* minor change
* Update condition in supervise script
* JVM not jvm in docs
* Processors for Window Processing
This is an initial take on how to use Processors
for Window Processing. A Processor is an interface
that transforms RowsAndColumns objects.
RowsAndColumns objects are essentially combinations
of rows and columns.
The intention is that these Processors are the start
of a set of operators that more closely resemble what
DB engineers would be accustomed to seeing.
* Wire up windowed processors with a query type that
can run them end-to-end. This code can be used to
actually run a query, so yay!
* Wire up windowed processors with a query type that
can run them end-to-end. This code can be used to
actually run a query, so yay!
* Some SQL tests for window functions. Added wikipedia
data to the indexes available to the
SQL queries and tests validating the windowing
functionality as it exists now.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* Switching emitter. This will allow for a per feed emitter designation.
This will work by looking at an event's feed and direct it to a specific emitter. If no specific feed is specified for a feed.
The emitter can direct the event to a default emitter.
* fix checkstyle issues and make docs for switching emitter use basic event feeds
* fix broken docs, add test, and guard against misconfigurations
* add module test
add switching emitter module test
* fix broken SwitchingEmitterModuleTest
* add apache license to top of test
* fix checkstyle issues
* address comments by adding javadocs, removing a todo, and making druid docs more clear
In a cluster with a large number of streaming tasks (~1000), SegmentAllocateActions
on the overlord can often take very long intervals of time to finish thus causing spikes
in the `task/action/run/time`. This may result in lag building up while a task waits for a
segment to get allocated.
The root causes are:
- large number of metadata calls made to the segments and pending segments tables
- `giant` lock held in `TaskLockbox.tryLock()` to acquire task locks and allocate segments
Since the contention typically arises when several tasks of the same datasource try
to allocate segments for the same interval/granularity, the allocation run times can be
improved by batching the requests together.
Changes
- Add flags
- `druid.indexer.tasklock.batchSegmentAllocation` (default `false`)
- `druid.indexer.tasklock.batchAllocationMaxWaitTime` (in millis) (default `1000`)
- Add methods `canPerformAsync` and `performAsync` to `TaskAction`
- Submit each allocate action to a `SegmentAllocationQueue`, and add to correct batch
- Process batch after `batchAllocationMaxWaitTime`
- Acquire `giant` lock just once per batch in `TaskLockbox`
- Reduce metadata calls by batching statements together and updating query filters
- Except for batching, retain the whole behaviour (order of steps, retries, etc.)
- Respond to leadership changes and fail items in queue when not leader
- Emit batch and request level metrics
SQL test framework extensions
* Capture planner artifacts: logical plan, etc.
* Planner test builder validates the logical plan
* Validation for the SQL resut schema (we already have
validation for the Druid row signature)
* Better Guice integration: properties, reuse Guice modules
* Avoid need for hand-coded expr, macro tables
* Retire some of the test-specific query component creation
* Fix query log hook race condition
Detects self-redirects, redirect loops, long redirect chains, and redirects to unknown servers.
Treat all of these cases as an unavailable service, retrying if the retry policy allows it.
Previously, some of these cases would lead to a prompt, unretryable error. This caused
clients contacting an Overlord during a leader change to fail with error messages like:
org.apache.druid.rpc.RpcException: Service [overlord] redirected too many times
Additionally, a slight refactor of callbacks in ServiceClientImpl improves readability of
the flow through onSuccess.
The batch segment sampling performs significantly better than the older method
of sampling if there are a large number of used segments. It also avoids duplicates.
Changes:
- Make batch segment sampling the default
- Deprecate the property `useBatchedSegmentSampler`
- Remove unused coordinator config `druid.coordinator.loadqueuepeon.repeatDelay`
- Cleanup `KillUnusedSegments`
- Simplify `KillUnusedSegmentsTest`, add better tests, remove redundant tests
Main changes:
1) Convert SeekableStreamIndexTaskClient to an interface, move old code
to SeekableStreamIndexTaskClientSyncImpl, and add new implementation
SeekableStreamIndexTaskClientAsyncImpl that uses ServiceClient.
2) Add "chatAsync" parameter to seekable stream supervisors that causes
the supervisor to use an async task client.
3) In SeekableStreamSupervisor.discoverTasks, adjust logic to avoid making
blocking RPC calls in workerExec threads.
4) In SeekableStreamSupervisor generally, switch from Futures.successfulAsList
to FutureUtils.coalesce, so we can better capture the errors that occurred
with contacting individual tasks.
Other, related changes:
1) Add ServiceRetryPolicy.retryNotAvailable, which controls whether
ServiceClient retries unavailable services. Useful since we do not
want to retry calls unavailable tasks within the service client. (The
supervisor does its own higher-level retries.)
2) Add FutureUtils.transformAsync, a more lambda friendly version of
Futures.transform(f, AsyncFunction).
3) Add FutureUtils.coalesce. Similar to Futures.successfulAsList, but
returns Either instead of using null on error.
4) Add JacksonUtils.readValue overloads for JavaType and TypeReference.
Segment assignments can take very long due to the strategy cost computation
for a large number of segments. This commit allows segment assignments to be
done in a round-robin fashion within a tier. Only segment balancing takes cost-based
decisions to move segments around.
Changes
- Add dynamic config `useRoundRobinSegmentAssignment` with default value false
- Add `RoundRobinServerSelector`. This does not implement the `BalancerStrategy`
as it does not conform to that contract and may also be used in conjunction with a
strategy (round-robin for `RunRules` and a cost strategy for `BalanceSegments`)
- Drops are still cost-based even when round-robin assignment is enabled.
Druid catalog basics
Catalog object model for tables, columns
Druid metadata DB storage (as an extension)
REST API to update the catalog (as an extension)
Integration tests
Model only: no planner integration yet
`cachingCost` strategy has some discrepancies when compared to cost strategy.
This commit addresses two of these by retaining the same behaviour as the `cost` strategy
when computing the cost of moving a segment to a server:
- subtract the self cost of a segment if it is being served by the target server
- subtract the cost of segments that are marked to be dropped
Other changes:
- Add tests to verify fixed strategy. These tests would fail without the fixes made to `CachingCostStrategy.computeCost()`
- Fix the definition of the segment related metrics in the docs.
- Fix some docs issues introduced in #13181
* 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>
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.
* First set of changes for framework
* Second set of changes to move segment map function to data source
* Minot change to server manager
* Removing the createSegmentMapFunction from JoinableFactoryWrapper and moving to JoinDataSource
* Checkstyle fixes
* Patching Eric's fix for injection
* Checkstyle and fixing some CI issues
* Fixing code inspections and some failed tests and one injector for test in avatica
* Another set of changes for CI...almost there
* Equals and hashcode part update
* Fixing injector from Eric + refactoring for broadcastJoinHelper
* Updating second injector. Might revert later if better way found
* Fixing guice issue in JoinableFactory
* Addressing review comments part 1
* Temp changes refactoring
* Revert "Temp changes refactoring"
This reverts commit 9da42a9ef0.
* temp
* Temp discussions
* Refactoring temp
* Refatoring the query rewrite to refer to a datasource
* Refactoring getCacheKey by moving it inside data source
* Nullable annotation check in injector
* Addressing some comments, removing 2 analysis.isJoin() checks and correcting the benchmark files
* Minor changes for refactoring
* Addressing reviews part 1
* Refactoring part 2 with new test cases for broadcast join
* Set for nullables
* removing instance of checks
* Storing nullables in guice to avoid checking on reruns
* Fixing a test case and removing an irrelevant line
* Addressing the atomic reference review comments
* Remove basePersistDirectory from tuning configs.
Since the removal of CliRealtime, it serves no purpose, since it is
always overridden in production using withBasePersistDirectory given
some subdirectory of the task work directory.
Removing this from the tuning config has a benefit beyond removing
no-longer-needed logic: it also avoids the side effect of empty
"druid-realtime-persist" directories getting created in the systemwide
temp directory.
* Test adjustments to appropriately set basePersistDirectory.
* Remove unused import.
* Fix RATC constructor.
* 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
1) Better support for Java 9+ in RuntimeInfo. This means that in many cases,
an actual validation can be done.
2) Clearer log message in cases where an actual validation cannot be done.
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`
Fixes#12822
The framework added here make it easy to write tests that verify the behaviour and interactions
of the following entities under various conditions:
- `DruidCoordinator`
- `HttpLoadQueuePeon`, `LoadQueueTaskMaster`
- coordinator duties: `BalanceSegments`, `RunRules`, `UnloadUnusedSegments`, etc.
- datasource retention rules: `LoadRule`, `DropRule`
Changes:
Add the following main classes:
- `CoordinatorSimulation` and related interfaces to dictate behaviour of simulation
- `CoordinatorSimulationBuilder` to build a simulation.
- `BlockingExecutorService` to keep submitted tasks in queue and execute them
only when explicitly invoked.
Add tests:
- `CoordinatorSimulationBaseTest`, `SegmentLoadingTest`, `SegmentBalancingTest`
- `SegmentLoadingNegativeTest` to contain tests which assert the existing erroneous behaviour
of segment loading. Once the behaviour is fixed, these tests will be moved to the regular
`SegmentLoadingTest`.
Please refer to the README.md in `org.apache.druid.server.coordinator.simulate` for more details
* Converted Druid planner to use statement handlers
Converts the large collection of if-statements for statement
types into a set of classes: one per supported statement type.
Cleans up a few error messages.
* Revisions from review comments
* Build fix
* Build fix
* Resolve merge confict.
* More merges with QueryResponse PR
* More parameterized type cleanup
Forces a rebuild due to a flaky test
* Allocate numCorePartitions using only used segments
* Add corePartition checks in existing test
* Separate committedMaxId and overallMaxId
* Fix bug: replace overall with committed
This commit fixes issues with delayed supervisor termination during certain transient states.
Tasks can be created during supervisor termination and left behind since the cleanup may
not consider these newly added tasks.
#12178 added a lock for the entire process of task creation to prevent such dangling tasks.
But it also introduced a deadlock scenario as follows:
- An invocation of `runInternal` is in progress.
- A `stop` request comes, acquires `stateChangeLock` and submit a `ShutdownNotice`
- `runInternal` keeps waiting to acquire the `stateChangeLock`
- `ShutdownNotice` remains stuck in the notice queue because `runInternal` is still running
- After some timeout, the supervisor goes through a forced termination
Fix:
* `SeekableStreamSupervisor.runInternal` - do not try to acquire lock if supervisor is already stopping
* `SupervisorStateManager.maybeSetState` - do not allow transitions from STOPPING state
* Move web-console dependency from druid-server to distribution
* Add a test to check if the web-console is correctly integrated
* exclude web-console from 'other integration tests'
* Revert "exclude web-console from 'other integration tests'"
This reverts commit 8d72225544.
* Revert "Add a test to check if the web-console is correctly integrated"
This reverts commit d6ac8f3087.
* Expose HTTP Response headers from SqlResource
This change makes the SqlResource expose HTTP response
headers in the same way that the QueryResource exposes them.
Fundamentally, the change is to pipe the QueryResponse
object all the way through to the Resource so that it can
populate response headers. There is also some code
cleanup around DI, as there was a superfluous FactoryFactory
class muddying things up.
* fix bug in /status/properties filtering
* Refactor tests to use jackson for parsing druid.server.hiddenProperties instead of hacky string modifications
* make javadoc more descriptive using example
* add in a sanity assertion that raw properties keyset size is greater than filtered properties keyset size
* 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
Kashif Faraz
somu-imply
Gian Merlino
Rishabh Singh
Paul Rogers
Clint Wylie
imply-cheddar
AmatyaAvadhanula
TSFenwick
Rohan Garg
Tejaswini Bandlamudi
Dr. Sizzles
Abhishek Agarwal
Frank Chen
Lucas Capistrant
Adam Peck