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.
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.
* working
* Lazily load segmentKillers, segmentMovers, and segmentArchivers
* more tests
* test-jar plugin
* more coverage
* lazy client
* clean up changes
* checkstyle
* i did not change the branch condition
* adjust failure rate to run tests faster
* javadocs
* checkstyle
* Use Druid's extension loading for integration test instead of maven
* fix maven command
* override config path
* load input format extensions and kafka by default; add prepopulated-data group
* all docker-composes are overridable
* fix s3 configs
* override config for all
* fix docker_compose_args
* fix security tests
* turn off debug logs for overlord api calls
* clean up stuff
* revert docker-compose.yml
* fix override config for query error test; fix circular dependency in docker compose
* add back some dependencies in docker compose
* new maven profile for integration test
* example file filter
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.
* Revert "Require Datasource WRITE authorization for Supervisor and Task access (#11718)"
This reverts commit f2d6100124.
* Revert "Require DATASOURCE WRITE access in SupervisorResourceFilter and TaskResourceFilter (#11680)"
This reverts commit 6779c4652d.
* Fix docs for the reverted commits
* Fix and restore deleted tests
* Fix and restore SystemSchemaTest
Follow up PR for #11680
Description
Supervisor and Task APIs are related to ingestion and must always require Datasource WRITE
authorization even if they are purely informative.
Changes
Check Datasource WRITE in SystemSchema for tables "supervisors" and "tasks"
Check Datasource WRITE for APIs /supervisor/history and /supervisor/{id}/history
Check Datasource for all Indexing Task APIs
Fixes#11297.
Description
Description and design in the proposal #11297
Key changed/added classes in this PR
*DataSegmentPusher
*ShuffleClient
*PartitionStat
*PartitionLocation
*IntermediaryDataManager
* support using mariadb connector with mysql extensions
* cleanup and more tests
* fix test
* javadocs, more tests, etc
* style and more test
* more test more better
* missing pom
* more pom
With this change, Druid will only support ZooKeeper 3.5.x and later.
In order to support Java 15 we need to switch to ZK 3.5.x client libraries and drop support for ZK 3.4.x
(see #10780 for the detailed reasons)
* remove ZooKeeper 3.4.x compatibility
* exclude additional ZK 3.5.x netty dependencies to ensure we use our version
* keep ZooKeeper version used for integration tests in sync with client library version
* remove the need to specify ZK version at runtime for docker
* add support to run integration tests with JDK 15
* build and run unit tests with Java 15 in travis
* Do not stop retrying when an exception is encountered. Save & propagate last exception if retry count is exceeded.
* Add one more log message to help with debugging
* Limit schema registry heap to attempt to control OOMs
* upgrade to Apache Kafka 2.8.0 (release notes:
https://downloads.apache.org/kafka/2.8.0/RELEASE_NOTES.html)
* pass Kafka version as a Docker argument in integration tests
to keep in sync with maven version
* fix use of internal Kafka APIs in integration tests
* JavaScript script engine support was removed in JDK 15: skip those tests for JDKs without it
* Fix flaky HTTP client tests with Java 15
* Switch from CMS to G1GC in integration tests, since CMS is no longer available in JDK 15
* DruidInputSource: Fix issues in column projection, timestamp handling.
DruidInputSource, DruidSegmentReader changes:
1) Remove "dimensions" and "metrics". They are not necessary, because we
can compute which columns we need to read based on what is going to
be used by the timestamp, transform, dimensions, and metrics.
2) Start using ColumnsFilter (see below) to decide which columns we need
to read.
3) Actually respect the "timestampSpec". Previously, it was ignored, and
the timestamp of the returned InputRows was set to the `__time` column
of the input datasource.
(1) and (2) together fix a bug in which the DruidInputSource would not
properly read columns that are used as inputs to a transformSpec.
(3) fixes a bug where the timestampSpec would be ignored if you attempted
to set the column to something other than `__time`.
(1) and (3) are breaking changes.
Web console changes:
1) Remove "Dimensions" and "Metrics" from the Druid input source.
2) Set timestampSpec to `{"column": "__time", "format": "millis"}` for
compatibility with the new behavior.
Other changes:
1) Add ColumnsFilter, a new class that allows input readers to determine
which columns they need to read. Currently, it's only used by the
DruidInputSource, but it could be used by other columnar input sources
in the future.
2) Add a ColumnsFilter to InputRowSchema.
3) Remove the metric names from InputRowSchema (they were unused).
4) Add InputRowSchemas.fromDataSchema method that computes the proper
ColumnsFilter for given timestamp, dimensions, transform, and metrics.
5) Add "getRequiredColumns" method to TransformSpec to support the above.
* Various fixups.
* Uncomment incorrectly commented lines.
* Move TransformSpecTest to the proper module.
* Add druid.indexer.task.ignoreTimestampSpecForDruidInputSource setting.
* Fix.
* Fix build.
* Checkstyle.
* Misc fixes.
* Fix test.
* Move config.
* Fix imports.
* Fixup.
* Fix ShuffleResourceTest.
* Add import.
* Smarter exclusions.
* Fixes based on tests.
Also, add TIME_COLUMN constant in the web console.
* Adjustments for tests.
* Reorder test data.
* Update docs.
* Update docs to say Druid 0.22.0 instead of 0.21.0.
* Fix test.
* Fix ITAutoCompactionTest.
* Changes from review & from merging.
* Ability to use mirror of archive.apache.org
* Ability to use mirror of archive.apache.org: documentation
* Ability to use mirror of archive.apache.org: fix int test Dockerfile: missing COPY instruction
* move integration tests from ZooKeeper 3.4.x to 3.5.x
* run a subset of our integration tests with ZK 3.4 for backwards compatibility testing.
* remove need to build separate docker-base image
- use multi-stage build for the base image
- use openjdk base image instead of building our own JDK base
- workaround Debian not including MySQL by using MariaDB
- download mysql connector directly instead of using distro version
* fix incorrect openssl command failing on Debian
* keep mysql connector version in sync with pom version
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix checkstyle
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix test
* fix test
* add log
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* address comments
* fix checkstyle
* fix checkstyle
* add config to skip overhead memory calculation
* add test for the skipBytesInMemoryOverheadCheck config
* add docs
* fix checkstyle
* fix checkstyle
* fix spelling
* address comments
* fix travis
* address comments
* integration test for coordinator and overlord leadership, added sys.servers is_leader column
* docs
* remove not needed
* fix comments
* fix compile heh
* oof
* revert unintended
* fix tests, split out docker-compose file selection from starting cluster, use docker-compose down to stop cluster
* fixes
* style
* dang
* heh
* scripts are hard
* fix spelling
* fix thing that must not matter since was already wrong ip, log when test fails
* needs more heap
* fix merge
* less aggro
* Fixes and tests related to the Indexer process.
Three bugs fixed:
1) Indexers would not announce themselves as segment servers if they
did not have storage locations defined. This used to work, but was
broken in #9971. Fixed this by adding an "isSegmentServer" method
to ServerType and updating SegmentLoadDropHandler to always announce
if this method returns true.
2) Certain batch task types were written in a way that assumed "isReady"
would be called before "run", which is not guaranteed. In particular,
they relied on it in order to initialize "taskLockHelper". Fixed this
by updating AbstractBatchIndexTask to ensure "isReady" is called
before "run" for these tasks.
3) UnifiedIndexerAppenderatorsManager did not properly handle complex
datasources. Introduced DataSourceAnalysis in order to fix this.
Test changes:
1) Add a new "docker-compose.cli-indexer.yml" config that spins up an
Indexer instead of a MiddleManager.
2) Introduce a "USE_INDEXER" environment variable that determines if
docker-compose will start up an Indexer or a MiddleManager.
3) Duplicate all the jdk8 tests and run them in both MiddleManager and
Indexer mode.
4) Various adjustments to encourage fail-fast errors in the Docker
build scripts.
5) Various adjustments to speed up integration tests and reduce memory
usage.
6) Add another Mac-specific approach to determining a machine's own IP.
This was useful on my development machine.
7) Update segment-count check in ITCompactionTaskTest to eliminate a
race condition (it was looking for 6 segments, which only exist
together briefly, until the older 4 are marked unused).
Javadoc updates:
1) AbstractBatchIndexTask: Added javadocs to determineLockGranularityXXX
that make it clear when taskLockHelper will be initialized as a side
effect. (Related to the second bug above.)
2) Task: Clarified that "isReady" is not guaranteed to be called before
"run". It was already implied, but now it's explicit.
3) ZkCoordinator: Clarified deprecation message.
4) DataSegmentServerAnnouncer: Clarified deprecation message.
* Fix stop_cluster script.
* Fix sanity check in script.
* Fix hashbang lines.
* Test and doc adjustments.
* Additional tests, and adjustments for tests.
* Split ITs back out.
* Revert change to druid_coordinator_period_indexingPeriod.
* Set Indexer capacity to match MM.
* Bump up Historical memory.
* Bump down coordinator, overlord memory.
* Bump up Broker memory.
1) Accelerate coordinator runs to speed up segment load after publishing.
2) For streaming ingestion tests, Instead of waiting 3 minutes for data to
load, wait until the expected number of rows is loaded.
Also updates segment-count check in ITCompactionTaskTest to eliminate a
race condition (it was looking for 6 segments, which only exist together
briefly, until the older 4 are marked unused).
* Working
* add test
* doc
* fix test
* split other integration test
* exclude other-index from other tests
* doc anchor fix
* adjust task slots and number of merge tasks
* spell check
* reduce maxNumConcurrentSubTasks to 1
* maxNumConcurrentSubtasks for range partitinoing
* reduce memory for historical
* change group name
* Fix handling of 'join' on top of 'union' datasources.
The problem is that unions are typically rewritten into a series of
individual queries on the underlying tables, but this isn't done when
the union is wrapped in a join.
The main changes are in UnionQueryRunner:
1) Replace an instanceof UnionQueryRunner check with DataSourceAnalysis.
2) Replace a "query.withDataSource" call with a new function, "Queries.withBaseDataSource".
Together, these enable UnionQueryRunner to "see through" a join.
* Tests.
* Adjust heap sizes for integration tests.
* Different approach, more tests.
* Tweak.
* Styling.
* Segment backed broadcast join IndexedTable
* fix comments
* fix tests
* sharing is caring
* fix test
* i hope this doesnt fix it
* filter by schema to maybe fix test
* changes
* close join stuffs so it does not leak, allow table to directly make selector factory
* oops
* update comment
* review stuffs
* better check
Tejaswini Bandlamudi
Maytas Monsereenusorn
Rohan Garg
Kashif Faraz
Jihoon Son
Suneet Saldanha
Frank Chen
Karan Kumar
Clint Wylie
Parag Jain
zachjsh
Xavier Léauté
Agustin Gonzalez
Yi Yuan
Himadri Singh
Gian Merlino
Vyatcheslav Mogilevsky
Atul Mohan