* 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.
changes:
* long and double value columns are now written directly, at the same time as writing out the 'intermediary' dictionaryid column with unsorted ids
* remove reverse value lookup from GlobalDictionaryIdLookup since it is no longer needed
* more consistent expression error messages
* review stuff
* add NamedFunction for Function, ApplyFunction, and ExprMacro to share common stuff
* fixes
* add expression transform name to transformer failure, better parse_json error messaging
-Add classes for writing cell values in LZ4 block compressed format.
Payloads are indexed by element number for efficient random lookup
-update SerializablePairLongStringComplexMetricSerde to use block
compression
-SerializablePairLongStringComplexMetricSerde also uses delta encoding
of the Long by doing 2-pass encoding: buffers first to find min/max
numbers and delta-encodes as integers if possible
Entry points for doing block-compressed storage of byte[] payloads
are the CellWriter and CellReader class. See
SerializablePairLongStringComplexMetricSerde for how these are used
along with how to do full column-based storage (delta encoding here)
which includes 2-pass encoding to compute a column header
* FrameFile: Java 17 compatibility.
DataSketches Memory.map is not Java 17 compatible, and from discussions
with the team, is challenging to make compatible with 17 while also
retaining compatibility with 8 and 11. So, in this patch, we switch away
from Memory.map and instead use the builtin JDK mmap functionality. Since
it only supports maps up to Integer.MAX_VALUE, we also implement windowing
in FrameFile, such that we can still handle large files.
Other changes:
1) Add two new "map" functions to FileUtils, which we use in this patch.
2) Add a footer checksum to the FrameFile format. Individual frames
already have checksums, but the footer was missing one.
* Changes for static analysis.
* wip
* Fixes.
* Fix accounting of bytesAdded in ReadableByteChunksFrameChannel.
Could cause WorkerInputChannelFactory to get into an infinite loop when
reading the footer of a frame file.
* Additional tests.
During ingestion, if a row containing multiple values for a numeric dimension is encountered,
the whole ingestion task fails. Ideally, this should just be registered as a parse exception.
Changes:
- Remove `instanceof List` check from `LongDimensionIndexer`, `FloatDimensionIndexer` and `DoubleDimensionIndexer`.
Any invalid type, including list, throws a parse exception in `DimensionHandlerUtils.convertObjectToXXX`
methods. `ParseException` is already handled in `OnHeapIncrementalIndex` and does not fail the entire task.
* json_value adjustments
changes:
* native json_value expression now has optional 3rd argument to specify type, which will cast all values to the specified type
* rework how JSON_VALUE is wired up in SQL. Now we are using a custom convertlet to translate JSON_VALUE(... RETURNING type) into dedicated JSON_VALUE_BIGINT, JSON_VALUE_DOUBLE, JSON_VALUE_VARCHAR, JSON_VALUE_ANY instead of using the calcite StandardConvertletTable that wraps JSON_VALUE_ANY in a CAST, so that we preserve the typing of JSON_VALUE to pass down to the native expression as the 3rd argument
* fix json_value_any to be usable by humans too, coverage
* fix bug
* checkstyle
* checkstyle
* review stuff
* validate that options to json_value are the supported options rather than ignore them
* remove more legacy undocumented functions
* KLL sketch
* added documentation
* direct static refs
* direct static refs
* fixed test
* addressed review points
* added KLL sketch related terms
* return a copy from get
* Copy unions when returning them from "get".
* Remove redundant "final".
Co-authored-by: AlexanderSaydakov <AlexanderSaydakov@users.noreply.github.com>
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
The method wasn't following its contract, leading to pollution of the
overall planner context, when really we just want to create a new
context for a specific query.
* Error handling improvements for frame channels.
Two changes:
1) Send errors down in-memory channels (BlockingQueueFrameChannel) on
failure. This ensures that in situations where a chain of processors
has been set up on a single machine, all processors see the root
cause error. In particular, this means the final processor in the
chain reports the root cause error, which ensures that someone with
a handle to the final processor will get the proper error.
2) Update FrameFileHttpResponseHandler to expect that the final fetch,
rather than being simply empty, is also empty with a special header.
This ensures that the handler is able to tell the difference between
an empty fetch due to being at EOF, and an empty fetch due to a
truncated HTTP response (after the 200 OK and headers are sent down,
but before any content appears).
* Fix tests, imports.
* Checkstyle!
* 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
* Introduce defaultOnDiskStorage config for groupBy
* add debug log to groupby query config
* Apply config change suggestion from review
* Remove accidental new lines
* update default value of new default disk storage config
* update debug log to have more descriptive text
* Make maxOnDiskStorage and defaultOnDiskStorage HumanRedadableBytes
* improve test coverage
* Provide default implementation to new default method on advice of reviewer
In the current druid code base, we have the interface DataSegmentPusher which allows us to push segments to the appropriate deep storage without the extension being worried about the semantics of how to push too deep storage.
While working on #12262, whose some part of the code will go as an extension, I realized that we do not have an interface that allows us to do basic "write, get, delete, deleteAll" operations on the appropriate deep storage without let's say pulling the s3-storage-extension dependency in the custom extension.
Hence, the idea of StorageConnector was born where the storage connector sits inside the druid core so all extensions have access to it.
Each deep storage implementation, for eg s3, GCS, will implement this interface.
Now with some Jackson magic, we bind the implementation of the correct deep storage implementation on runtime using a type variable.
* Adjust "in" filter null behavior to match "selector".
Now, both of them match numeric nulls if constructed with a "null" value.
This is consistent as far as native execution goes, but doesn't match
the behavior of SQL = and IN. So, to address that, this patch also
updates the docs to clarify that the native filters do match nulls.
This patch also updates the SQL docs to describe how Boolean logic is
handled in addition to how NULL values are handled.
Fixes#12856.
* Fix test.
* Frame processing and channels.
Follow-up to #12745. This patch adds three new concepts:
1) Frame channels are interfaces for doing nonblocking reads and writes
of frames.
2) Frame processors are interfaces for doing nonblocking processing of
frames received from input channels and sent to output channels.
3) Cluster-by keys, which can be used for sorting or partitioning.
The patch also adds SuperSorter, a user of these concepts, both to
illustrate how they are used, and also because it is going to be useful
in future work.
Central classes:
- ReadableFrameChannel. Implementations include
BlockingQueueFrameChannel (in-memory channel that implements both interfaces),
ReadableFileFrameChannel (file-based channel),
ReadableByteChunksFrameChannel (byte-stream-based channel), and others.
- WritableFrameChannel. Implementations include BlockingQueueFrameChannel
and WritableStreamFrameChannel (byte-stream-based channel).
- ClusterBy, a sorting or partitioning key.
- FrameProcessor, nonblocking processor of frames. Implementations include
FrameChannelBatcher, FrameChannelMerger, and FrameChannelMuxer.
- FrameProcessorExecutor, an executor service that runs FrameProcessors.
- SuperSorter, a class that uses frame channels and processors to
do parallel external merge sort of any amount of data (as long as there
is enough disk space).
* Additional tests, fixes.
* Changes from review.
* Better implementation for ReadableInputStreamFrameChannel.
* Rename getFrameFileReference -> newFrameFileReference.
* Add InterruptedException to runIncrementally; add more tests.
* Cancellation adjustments.
* Review adjustments.
* Refactor BlockingQueueFrameChannel, rename doneReading and doneWriting to close.
* Additional changes from review.
* Additional changes.
* Fix test.
* Adjustments.
* Adjustments.
* 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
* Improved Java 17 support and Java runtime docs.
1) Add a "Java runtime" doc page with information about supported
Java versions, garbage collection, and strong encapsulation..
2) Update asm and equalsverifier to versions that support Java 17.
3) Add additional "--add-opens" lines to surefire configuration, so
tests can pass successfully under Java 17.
4) Switch openjdk15 tests to openjdk17.
5) Update FrameFile to specifically mention Java runtime incompatibility
as the cause of not being able to use Memory.map.
6) Update SegmentLoadDropHandler to log an error for Errors too, not
just Exceptions. This is important because an IllegalAccessError is
encountered when the correct "--add-opens" line is not provided,
which would otherwise be silently ignored.
7) Update example configs to use druid.indexer.runner.javaOptsArray
instead of druid.indexer.runner.javaOpts. (The latter is deprecated.)
* Adjustments.
* Use run-java in more places.
* Add run-java.
* Update .gitignore.
* Exclude hadoop-client-api.
Brought in when building on Java 17.
* Swap one more usage of java.
* Fix the run-java script.
* Fix flag.
* Include link to Temurin.
* Spelling.
* Update examples/bin/run-java
Co-authored-by: Xavier Léauté <xl+github@xvrl.net>
Co-authored-by: Xavier Léauté <xl+github@xvrl.net>
add NumericRangeIndex interface and BoundFilter support
changes:
* NumericRangeIndex interface, like LexicographicalRangeIndex but for numbers
* BoundFilter now uses NumericRangeIndex if comparator is numeric and there is no extractionFn
* NestedFieldLiteralColumnIndexSupplier.java now supports supplying NumericRangeIndex for single typed numeric nested literal columns
* better faster stronger and (ever so slightly) more understandable
* more tests, fix bug
* fix style
* Automatic sizing for GroupBy dictionary sizes.
Merging and selector dictionary sizes currently both default to 100MB.
This is not optimal, because it can lead to OOM on small servers and
insufficient resource utilization on larger servers. It also invites
end users to try to tune it when queries run out of dictionary space,
which can make things worse if the end user sets it to too high.
So, this patch:
- Adds automatic tuning for selector and merge dictionaries. Selectors
use up to 15% of the heap and merge buffers use up to 30% of the heap
(aggregate across all queries).
- Updates out-of-memory error messages to emphasize enabling disk
spilling vs. increasing memory parameters. With the memory parameters
automatically sized, it is more likely that an end user will get
benefit from enabling disk spilling.
- Removes the query context parameters that allow lowering of configured
dictionary sizes. These complicate the calculation, and I don't see a
reasonable use case for them.
* Adjust tests.
* Review adjustments.
* Additional comment.
* Remove unused import.
Clint Wylie
Frank Chen
imply-cheddar
Gian Merlino
Rohan Garg
sr
Abhishek Agarwal
Kashif Faraz
Alexander Saydakov
Adarsh Sanjeev
Paul Rogers
Lucas Capistrant
Karan Kumar
Suneet Saldanha
Jonathan Wei
Maytas Monsereenusorn