ApproximateHistogram - seems unlikely
SegmentAnalyzer - unclear if this is an actual issue
GenericIndexedWriter - unclear if this is an actual issue
IncrementalIndexRow and OnheapIncrementalIndex are non-issues becaus it's very
unlikely for the number of dims to be large enough to hit the overflow
condition
* IntelliJ inspections cleanup
* Standard Charset object can be used
* Redundant Collection.addAll() call
* String literal concatenation missing whitespace
* Statement with empty body
* Redundant Collection operation
* StringBuilder can be replaced with String
* Type parameter hides visible type
* fix warnings in test code
* more test fixes
* remove string concatenation inspection error
* fix extra curly brace
* cleanup AzureTestUtils
* fix charsets for RangerAdminClient
* review comments
* Allow Cloud SegmentKillers to be instantiated without segment bucket or path
This change fixes a bug that was introduced that causes ingestion
to fail if data is ingested from one of the supported cloud storages
(Azure, Google, S3), and the user is using another type of storage
for deep storage. In this case the all segment killer implementations
are instantiated. A change recently made forced a dependency between
the supported cloud storage type SegmentKiller classes and the
deep storage configuration for that storage type being set, which
forced the deep storage bucket and prefix to be non-null. This caused
a NullPointerException to be thrown when instantiating the
SegmentKiller classes during ingestion.
To fix this issue, the respective deep storage segment configs for the
cloud storage types supported in druid are now allowed to have nullable
bucket and prefix configurations
* * Allow google deep storage bucket to be null
Fixes an issue where splitting an HDFS input source for use in native
parallel batch ingestion would cause the subtasks to get a split with an
invalid HDFS path.
* fix nullhandling exceptions related to test ordering
Tests might get executed in different order depending on the maven
version and the test environment. This may lead to "NullHandling module
not initialized" errors for some tests where we do not initialize
null-handling explicitly.
* use InitializedNullHandlingTest
* druid pac4j security extension for OpenID Connect OAuth 2.0 authentication
* update version in druid-pac4j pom
* introducing unauthorized resource filter
* authenticated but authorized /unified-webconsole.html
* use httpReq.getRequestURI() for matching callback path
* add documentation
* minor doc addition
* licesne file updates
* make dependency analyze succeed
* fix doc build
* hopefully fixes doc build
* hopefully fixes license check build
* yet another try on fixing license build
* revert unintentional changes to website folder
* update version to 0.18.0-SNAPSHOT
* check session and its expiry on each request
* add crypto service
* code for encrypting the cookie
* update doc with cookiePassphrase
* update license yaml
* make sessionstore in Pac4jFilter private non static
* make Pac4jFilter fields final
* okta: use sha256 for hmac
* remove incubating
* add UTs for crypto util and session store impl
* use standard charsets
* add license header
* remove unused file
* add org.objenesis.objenesis to license.yaml
* a bit of nit changes in CryptoService and embedding EncryptionResult for clarity
* rename alg to cipherAlgName
* take cipher alg name, mode and padding as input
* add java doc for CryptoService and make it more understandable
* another UT for CryptoService
* cache pac4j Config
* use generics clearly in Pac4jSessionStore
* update cookiePassphrase doc to mention PasswordProvider
* mark stuff Nullable where appropriate in Pac4jSessionStore
* update doc to mention jdbc
* add error log on reaching callback resource
* javadoc for Pac4jCallbackResource
* introduce NOOP_HTTP_ACTION_ADAPTER
* add correct module name in license file
* correct extensions folder name in licenses.yaml
* replace druid-kubernetes-extensions to druid-pac4j
* cache SecureRandom instance
* rename UnauthorizedResourceFilter to AuthenticationOnlyResourceFilter
* Azure deep storage does not work with datasource name containing non-ASCII chars
Fixed a bug where recording the segment file location fails when
using Azure Deep Storage, if the datasource has any special
characters
* * update jacoco thresholds
* * resolve merge conflicts
* address review comments
* Ability to Delete task logs and segments from Google Storage
* implement ability to delete all tasks logs or all task logs
written before a particular date when written to Google storage
* implement ability to delete all segments from Google deep storage
* * Address review comments
* Ability to Delete task logs and segments from Azure Storage
* implement ability to delete all tasks logs or all task logs
written before a particular date when written to Azure storage
* implement ability to delete all segments from Azure deep storage
* * Address review comments
* Broker: Add ability to inline subqueries.
The main changes:
- ClientQuerySegmentWalker: Add ability to inline queries.
- Query: Add "getSubQueryId" and "withSubQueryId" methods.
- QueryMetrics: Add "subQueryId" dimension.
- ServerConfig: Add new "maxSubqueryRows" parameter, which is used by
ClientQuerySegmentWalker to limit how many rows can be inlined per
query.
- IndexedTableJoinMatcher: Allow creating keys on top of unknown types,
by assuming they are strings. This is useful because not all types are
known for fields in query results.
- InlineDataSource: Store RowSignature rather than component parts. Add
more zealous "equals" and "hashCode" methods to ease testing.
- Moved QuerySegmentWalker test code from CalciteTests and
SpecificSegmentsQueryWalker in druid-sql to QueryStackTests in
druid-server. Use this to spin up a new ClientQuerySegmentWalkerTest.
* Adjustments from CI.
* Fix integration test.
* add kinesis lag metric
* fixes
* heh
* do it right this time
* more test
* split out supervisor report lags into lagMillis, remove latest offsets from kinesis supervisor report since always null, review stuffs
* Move RowSignature from druid-sql to druid-processing and make use of it.
1) Moved (most of) RowSignature from sql to processing. Left behind the SQL-specific
stuff in a RowSignatures utility class. It also picked up some new convenience
methods along the way.
2) There were a lot of places in the code where Map<String, ValueType> was used to
associate columns with type info. These are now all replaced with RowSignature.
3) QueryToolChest's resultArrayFields method is replaced with resultArraySignature,
and it now provides type info.
* Fix up extensions.
* Various fixes
* Ability to Delete task logs and segments from S3
* implement ability to delete all tasks logs or all task logs
written before a particular date when written to S3
* implement ability to delete all segments from S3 deep storage
* upgrade version of aws SDK in use
* * update licenses for updated AWS SDK version
* * fix bug in iterating through results from S3
* revert back to original version of AWS SDK
* * Address review comments
* * Fix failing dependency check
* Harmonization and bug-fixing for selector and filter behavior on unknown types.
- Migrate ValueMatcherColumnSelectorStrategy to newer ColumnProcessorFactory
system, and set defaultType COMPLEX so unknown types can be dynamically matched.
- Remove ValueGetters in favor of ColumnComparisonFilter doing its own thing.
- Switch various methods to use convertObjectToX when casting to numbers, rather
than ad-hoc and inconsistent logic.
- Fix bug in RowBasedExpressionColumnValueSelector: isBindingArray should return
true even for 0- or 1- element arrays.
- Adjust various javadocs.
* Add throwParseExceptions option to Rows.objectToNumber, switch back to that.
* Update tests.
* Adjust moment sketch tests.
* Skip empty files for local, hdfs, and cloud input sources
* split hint spec doc
* doc for skipping empty files
* fix typo; adjust tests
* unnecessary fluent iterable
* address comments
* fix test
* use the right lists
* fix test
* fix test
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* fix build failure
* fix failing build
* fix failing build
* Code cleanup
* fix failing test
* Removed CloudConfigProperties and make specific class for each cloudInputSource
* Removed CloudConfigProperties and make specific class for each cloudInputSource
* pass s3ConfigProperties for split
* lazy init s3client
* update docs
* fix docs check
* address comments
* add ServerSideEncryptingAmazonS3.Builder
* fix failing checkstyle
* fix typo
* wrap the ServerSideEncryptingAmazonS3.Builder in a provider
* added java docs for S3InputSource constructor
* added java docs for S3InputSource constructor
* remove wrap the ServerSideEncryptingAmazonS3.Builder in a provider
* Move Azure extension into Core
Moving the azure extension into Core.
* * Fix build failure
* * Add The MIT License (MIT) to list of compatible licenses
* * Address review comments
* * change reference to contrib azure to core azure
* * Fix spelling mistakes.
* Add common optional dependencies for extensions
Include hadoop-aws and postgres JDBC connector jar to improve
out-of-the-box experience for extensions. The mysql JDBC connector jar
is not bundled as it is GPL.
* Update docs
* Fix typo
* Create splits of multiple files for parallel indexing
* fix wrong import and npe in test
* use the single file split in tests
* rename
* import order
* Remove specific local input source
* Update docs/ingestion/native-batch.md
Co-Authored-By: sthetland <steve.hetland@imply.io>
* Update docs/ingestion/native-batch.md
Co-Authored-By: sthetland <steve.hetland@imply.io>
* doc and error msg
* fix build
* fix a test and address comments
Co-authored-by: sthetland <steve.hetland@imply.io>
* add Expr.stringify which produces parseable expression strings, parser support for null values in arrays, and parser support for empty numeric arrays
* oops, macros are expressions too
* style
* spotbugs
* qualified type arrays
* review stuffs
* simplify grammar
* more permissive array parsing
* reuse expr joiner
* fix it
* Add Azure config options for segment prefix and max listing length
Added configuration options to allow the user to specify the prefix
within the segment container to store the segment files. Also
added a configuration option to allow the user to specify the
maximum number of input files to stream for each iteration.
* * Fix test failures
* * Address review comments
* * add dependency explicitly to pom
* * update docs
* * Address review comments
* * Address review comments
* Run IntelliJ inspections on Travis
Running IntelliJ inspections currently takes about 90 minutes, but they
can be run in about 30 minutes on Travis.
* Restore assert statements
* Use ExecutorService instead of ScheduledExecutorService where necessary - #9286
* Added inspection rule to prohibit ScheduledExecutorService assignment to ExecutorService
* IMPLY-1946: Improve code quality and unit test coverage of the Azure extension
* Update unit tests to increase test coverage for the extension
* Clean up any messy code
* Enfore code coverage as part of tests.
* * Update azure extension pom to remove unnecessary things
* update jacoco thresholds
* * updgrade version of azure-storage library version uses to
most upto-date version
* implement Azure InputSource reader and deprecate Azure FireHose
* implement azure InputSource reader
* deprecate Azure FireHose implementation
* * exclude common libraries that are included from druid core
* Implement more of Azure input source.
* * Add tests
* * Add more tests
* * deprecate azure firehose
* * added more tests
* * rollback fix for google cloud batch ingestion bug. Will be
fixed in another PR.
* * Added javadocs for all azure related classes
* Addressed review comments
* * Remove dependency on org.apache.commons:commons-collections4
* Fix LGTM warnings
* Add com.google.inject.extensions:guice-assistedinject to licenses
* * rename classes as suggested in review comments
* * Address review comments
* * Address review comments
* * Address review comments
* Codestyle - use java style array declaration
Replaced C-style array declarations with java style declarations and marked
the intelliJ inspection as an error
* cleanup test code
* Forbid easily misused HashSet and HashMap constructors
* Add two LinkedHashMap constructors to forbidden-apis and create utility method as replacement for them
* Fix visibility of constant in CollectionUtils.java
* Make an exception for an instance of LinkedHashMap#<init>(int) because proper sizing is used
* revert changes to sql module tests that should be in separate PR
* Finish reverting changes to sql module tests that were flagged in checkstyle during CI
* Add netty dependency resulting from SupressForbidden
* Add MemoryOpenHashTable, a table similar to ByteBufferHashTable.
With some key differences to improve speed and design simplicity:
1) Uses Memory rather than ByteBuffer for its backing storage.
2) Uses faster hashing and comparison routines (see HashTableUtils).
3) Capacity is always a power of two, allowing simpler design and more
efficient implementation of findBucket.
4) Does not implement growability; instead, leaves that to its callers.
The idea is this removes the need for subclasses, while still giving
callers flexibility in how to handle table-full scenarios.
* Fix LGTM warnings.
* Adjust dependencies.
* Remove easymock from druid-benchmarks.
* Adjustments from review.
* Fix datasketches unit tests.
* Fix checkstyle.
By default native batch ingestion was only getting a batch of 10
files at a time when used with google cloud. The Default for other
cloud providers is 1024, and should be similar for google cloud.
The low batch size was caused by mistype. This change updates the
batch size to 1024 when using google cloud.
* Guicify druid sql module
Break up the SQLModule in to smaller modules and provide a binding that
modules can use to register schemas with druid sql.
* fix some tests
* address code review
* tests compile
* Working tests
* Add all the tests
* fix up licenses and dependencies
* add calcite dependency to druid-benchmarks
* tests pass
* rename the schemas
* SQL join support for lookups.
1) Add LookupSchema to SQL, so lookups show up in the catalog.
2) Add join-related rels and rules to SQL, allowing joins to be planned into
native Druid queries.
* Add two missing LookupSchema calls in tests.
* Fix tests.
* Fix typo.
This is important because if a user has the hdfs extension loaded, but is not
using hdfs deep storage, then they will not have storageDirectory set and will
get the following error:
IllegalArgumentException: Can not create a Path from an empty string
at io.druid.storage.hdfs.HdfsDataSegmentKiller.<init>(HdfsDataSegmentKiller.java:47)
This scenario is realistic: it comes up when someone has the hdfs extension
loaded because they want to use HdfsInputSource, but don't want to use hdfs for
deep storage.
Fixes#4694.
* Add LookupJoinableFactory.
Enables joins where the right-hand side is a lookup. Includes an
integration test.
Also, includes changes to LookupExtractorFactoryContainerProvider:
1) Add "getAllLookupNames", which will be needed to eventually connect
lookups to Druid's SQL catalog.
2) Convert "get" from nullable to Optional return.
3) Swap out most usages of LookupReferencesManager in favor of the
simpler LookupExtractorFactoryContainerProvider interface.
* Fixes for tests.
* Fix another test.
* Java 11 message fix.
* Fixups.
* Fixup benchmark class.
* intelliJ inspections cleanup
- remove redundant escapes
- performance warnings
- access static member via instance reference
- static method declared final
- inner class may be static
Most of these changes are aesthetic, however, they will allow inspections to
be enabled as part of CI checks going forward
The valuable changes in this delta are:
- using StringBuilder instead of string addition in a loop
indexing-hadoop/.../Utils.java
processing/.../ByteBufferMinMaxOffsetHeap.java
- Use class variables instead of static variables for parameterized test
processing/src/.../ScanQueryLimitRowIteratorTest.java
* Add intelliJ inspection warnings as errors to druid profile
* one more static inner class
* Reconcile terminology and method naming to 'used/unused segments'; Don't use terms 'enable/disable data source'; Rename MetadataSegmentManager to MetadataSegments; Make REST API methods which mark segments as used/unused to return server error instead of an empty response in case of error
* Fix brace
* Import order
* Rename withKillDataSourceWhitelist to withSpecificDataSourcesToKill
* Fix tests
* Fix tests by adding proper methods without interval parameters to IndexerMetadataStorageCoordinator instead of hacking with Intervals.ETERNITY
* More aligned names of DruidCoordinatorHelpers, rename several CoordinatorDynamicConfig parameters
* Rename ClientCompactTaskQuery to ClientCompactionTaskQuery for consistency with CompactionTask; ClientCompactQueryTuningConfig to ClientCompactionTaskQueryTuningConfig
* More variable and method renames
* Rename MetadataSegments to SegmentsMetadata
* Javadoc update
* Simplify SegmentsMetadata.getUnusedSegmentIntervals(), more javadocs
* Update Javadoc of VersionedIntervalTimeline.iterateAllObjects()
* Reorder imports
* Rename SegmentsMetadata.tryMark... methods to mark... and make them to return boolean and the numbers of segments changed and relay exceptions to callers
* Complete merge
* Add CollectionUtils.newTreeSet(); Refactor DruidCoordinatorRuntimeParams creation in tests
* Remove MetadataSegmentManager
* Rename millisLagSinceCoordinatorBecomesLeaderBeforeCanMarkAsUnusedOvershadowedSegments to leadingTimeMillisBeforeCanMarkAsUnusedOvershadowedSegments
* Fix tests, refactor DruidCluster creation in tests into DruidClusterBuilder
* Fix inspections
* Fix SQLMetadataSegmentManagerEmptyTest and rename it to SqlSegmentsMetadataEmptyTest
* Rename SegmentsAndMetadata to SegmentsAndCommitMetadata to reduce the similarity with SegmentsMetadata; Rename some methods
* Rename DruidCoordinatorHelper to CoordinatorDuty, refactor DruidCoordinator
* Unused import
* Optimize imports
* Rename IndexerSQLMetadataStorageCoordinator.getDataSourceMetadata() to retrieveDataSourceMetadata()
* Unused import
* Update terminology in datasource-view.tsx
* Fix label in datasource-view.spec.tsx.snap
* Fix lint errors in datasource-view.tsx
* Doc improvements
* Another attempt to please TSLint
* Another attempt to please TSLint
* Style fixes
* Fix IndexerSQLMetadataStorageCoordinator.createUsedSegmentsSqlQueryForIntervals() (wrong merge)
* Try to fix docs build issue
* Javadoc and spelling fixes
* Rename SegmentsMetadata to SegmentsMetadataManager, address other comments
* Address more comments
* Add JoinableFactory interface and use it in the query stack.
Also includes InlineJoinableFactory, which enables joining against
inline datasources. This is the first patch where a basic join query
actually works. It includes integration tests.
* Fix test issues.
* Adjustments from code review.
* Add HashJoinSegment, a virtual segment for joins.
An initial step towards #8728. This patch adds enough functionality to implement a joining
cursor on top of a normal datasource. It does not include enough to actually do a query. For
that, future patches will need to wire this low-level functionality into the query language.
* Fixups.
* Fix missing format argument.
* Various tests and minor improvements.
* Changes.
* Remove or add tests for unused stuff.
* Fix up package locations.
Previously jackson-mapper-asl was excluded to remove a security
vulnerability; however, it is required for functionality (e.g.,
org.apache.hadoop.security.token.delegation.web.DelegationTokenAuthenticator).
* Add avro dependency to parquet extension
If the parquet extension is loaded and an ingestionSpec uses the older format
specifying a 'parser' instead of using an 'inputFormat' the job fails
with the following error
java.lang.TypeNotPresentException: Type org.apache.avro.generic.GenericRecord not present
This change removes the exclusion of the avro package so that the missing
class can be found.
* Address review comments and add dependency version
* S3: Improvements to prefix listing (including fix for an infinite loop)
1) Fixes#9097, an infinite loop that occurs when more than one batch
of objects is retrieved during a prefix listing.
2) Removes the Access Denied fallback code added in #4444. I don't think
the behavior is reasonable: its purpose is to fall back from a prefix
listing to a single-object access, but it's only activated when the
end user supplied a prefix, so it would be better to simply fail, so
the end user knows that their request for a prefix-based load is not
going to work. Presumably the end user can switch from supplying
'prefixes' to supplying 'uris' if desired.
3) Filters out directory placeholders when walking prefixes.
4) Splits LazyObjectSummariesIterator into its own class and adds tests.
* Adjust S3InputSourceTest.
* Changes from review.
* Include hamcrest-core.
* Parallel indexing single dim partitions
Implements single dimension range partitioning for native parallel batch
indexing as described in #8769. This initial version requires the
druid-datasketches extension to be loaded.
The algorithm has 5 phases that are orchestrated by the supervisor in
`ParallelIndexSupervisorTask#runRangePartitionMultiPhaseParallel()`.
These phases and the main classes involved are described below:
1) In parallel, determine the distribution of dimension values for each
input source split.
`PartialDimensionDistributionTask` uses `StringSketch` to generate
the approximate distribution of dimension values for each input
source split. If the rows are ungrouped,
`PartialDimensionDistributionTask.UngroupedRowDimensionValueFilter`
uses a Bloom filter to skip rows that would be grouped. The final
distribution is sent back to the supervisor via
`DimensionDistributionReport`.
2) The range partitions are determined.
In `ParallelIndexSupervisorTask#determineAllRangePartitions()`, the
supervisor uses `StringSketchMerger` to merge the individual
`StringSketch`es created in the preceding phase. The merged sketch is
then used to create the range partitions.
3) In parallel, generate partial range-partitioned segments.
`PartialRangeSegmentGenerateTask` uses the range partitions
determined in the preceding phase and
`RangePartitionCachingLocalSegmentAllocator` to generate
`SingleDimensionShardSpec`s. The partition information is sent back
to the supervisor via `GeneratedGenericPartitionsReport`.
4) The partial range segments are grouped.
In `ParallelIndexSupervisorTask#groupGenericPartitionLocationsPerPartition()`,
the supervisor creates the `PartialGenericSegmentMergeIOConfig`s
necessary for the next phase.
5) In parallel, merge partial range-partitioned segments.
`PartialGenericSegmentMergeTask` uses `GenericPartitionLocation` to
retrieve the partial range-partitioned segments generated earlier and
then merges and publishes them.
* Fix dependencies & forbidden apis
* Fixes for integration test
* Address review comments
* Fix docs, strict compile, sketch check, rollup check
* Fix first shard spec, partition serde, single subtask
* Fix first partition check in test
* Misc rewording/refactoring to address code review
* Fix doc link
* Split batch index integration test
* Do not run parallel-batch-index twice
* Adjust last partition
* Split ITParallelIndexTest to reduce runtime
* Rename test class
* Allow null values in range partitions
* Indicate which phase failed
* Improve asserts in tests
* Address security vulnerabilities CVSS >= 7
Update dependencies to address security vulnerabilities with CVSS scores
of 7 or higher. A new Travis CI job is added to prevent new
high/critical security vulnerabilities from being added.
Updated dependencies:
- api-util 1.0.0 -> 1.0.3
- jackson 2.9.10 -> 2.10.1
- kafka 2.1.0 -> 2.1.1
- libthrift 0.10.0 -> 0.13.0
- protobuf 3.2.0 -> 3.11.0
The following high/critical security vulnerabilities are currently
suppressed (so that the new Travis CI job can be added now) and are left
as future work to fix:
- hibernate-validator:5.2.5
- jackson-mapper-asl:1.9.13
- libthrift:0.6.1
- netty:3.10.6
- nimbus-jose-jwt:4.41.1
* Rename EDL1 license file
* Fix inspection errors
* add prefixes support to google input source, making it symmetrical-ish with s3
* docs
* more better, and tests
* unused
* formatting
* javadoc
* dependencies
* oops
* review comments
* better javadoc
* Exclude unneeded hadoop transitive dependencies
These dependencies are provided by core:
- com.squareup.okhttp:okhttp
- commons-beanutils:commons-beanutils
- org.apache.commons:commons-compress
- org.apache.zookepper:zookeeper
These dependencies are not needed and are excluded because they contain
security vulnerabilities:
- commons-beanutils:commons-beanutils-core
- org.codehaus.jackson:jackson-mapper-asl
* Simplify exclusions + separate unneeded/vulnerable
* Do not exclude jackson-mapper-asl
* Support orc format for native batch ingestion
* fix pom and remove wrong comment
* fix unnecessary condition check
* use flatMap back to handle exception properly
* move exceptionThrowingIterator to intermediateRowParsingReader
* runtime
* add s3 input source for native batch ingestion
* add docs
* fixes
* checkstyle
* lazy splits
* fixes and hella tests
* fix it
* re-use better iterator
* use key
* javadoc and checkstyle
* exception
* oops
* refactor to use S3Coords instead of URI
* remove unused code, add retrying stream to handle s3 stream
* remove unused parameter
* update to latest master
* use list of objects instead of object
* serde test
* refactor and such
* now with the ability to compile
* fix signature and javadocs
* fix conflicts yet again, fix S3 uri stuffs
* more tests, enforce uri for bucket
* javadoc
* oops
* abstract class instead of interface
* null or empty
* better error
* Fix the potential race SplittableInputSource.getNumSplits() and SplittableInputSource.createSplits() in TaskMonitor
* Fix docs and javadoc
* Add unit tests for large or small estimated num splits
* add override
* Add FileUtils.createTempDir() and enforce its usage.
The purpose of this is to improve error messages. Previously, the error
message on a nonexistent or unwritable temp directory would be
"Failed to create directory within 10,000 attempts".
* Further updates.
* Another update.
* Remove commons-io from benchmark.
* Fix tests.
* add parquet support to native batch
* cleanup
* implement toJson for sampler support
* better binaryAsString test
* docs
* i hate spellcheck
* refactor toMap conversion so can be shared through flattenerMaker, default impls should be good enough for orc+avro, fixup for merge with latest
* add comment, fix some stuff
* adjustments
* fix accident
* tweaks
* HDFS input source
Add support for using HDFS as an input source. In this version, commas
or globs are not supported in HDFS paths.
* Fix forbidden api
* Address review comments
* Tidy up lifecycle, query, and ingestion logging.
The goal of this patch is to improve the clarity and usefulness of
Druid's logging for cluster operators. For more information, see
https://twitter.com/cowtowncoder/status/1195469299814555648.
Concretely, this patch does the following:
- Changes a lot of INFO logs to DEBUG, and DEBUG to TRACE, with the
goal of reducing redundancy and improving clarity by avoiding
showing rarely-useful log messages. This includes most "starting"
and "stopping" messages, and most messages related to individual
columns.
- Adds new log4j2 templates that show operators how to enabled DEBUG
logging for certain important packages.
- Eliminate stack traces for query errors, unless log level is DEBUG
or more. This is useful because query errors often indicate user
error rather than system error, but dumping stack trace often gave
operators the impression that there was a system failure.
- Adds task id to Appenderator, AppenderatorDriver thread names. In
the default log4j2 configuration, this will put them in log lines
as well. It's very useful if a user is using the Indexer, where
multiple tasks run in the same JVM.
- More consistent terminology when it comes to "sequences" (sets of
segments that are handed-off together by Kafka ingestion) and
"offsets" (cursors in partitions). These terms had been confused in
some log messages due to the fact that Kinesis calls offsets
"sequence numbers".
- Replaces some ugly toString calls with either the JSONification or
something more operator-accessible (like a URL or segment identifier,
instead of JSON object representing the same).
* Adjustments.
* Adjust integration test.