* change kafka lookups module to not commit offsets
The current behaviour of the Kafka lookup extractor is to not commit
offsets by assigning a unique ID to the consumer group and setting
auto.offset.reset to earliest. This does the job but also pollutes the
Kafka broker with a bunch of "ghost" consumer groups that will never again be
used.
To fix this, we now set enable.auto.commit to false, which prevents the
ghost consumer groups being created in the first place.
* update docs to include new enable.auto.commit setting behaviour
* update kafka-lookup-extractor documentation
Provide some additional detail on functionality and configuration.
Hopefully this will make it clearer how the extractor works for
developers who aren't so familiar with Kafka.
* add comments better explaining the logic of the code
* add spelling exceptions for kafka lookup docs
* remove kafka lookup records from factory when record tombstoned
* update kafka lookup docs to include tombstone behaviour
* change test wait time down to 10ms
Co-authored-by: David Palmer <david.palmer@adscale.co.nz>
Kinesis ingestion requires all shards to have at least 1 record at the required position in druid.
Even if this is satisified initially, resharding the stream can lead to empty intermediate shards. A significant delay in writing to newly created shards was also problematic.
Kinesis shard sequence numbers are big integers. Introduce two more custom sequence tokens UNREAD_TRIM_HORIZON and UNREAD_LATEST to indicate that a shard has not been read from and that it needs to be read from the start or the end respectively.
These values can be used to avoid the need to read at least one record to obtain a sequence number for ingesting a newly discovered shard.
If a record cannot be obtained immediately, use a marker to obtain the relevant shardIterator and use this shardIterator to obtain a valid sequence number. As long as a valid sequence number is not obtained, continue storing the token as the offset.
These tokens (UNREAD_TRIM_HORIZON and UNREAD_LATEST) are logically ordered to be earlier than any valid sequence number.
However, the ordering requires a few subtle changes to the existing mechanism for record sequence validation:
The sequence availability check ensures that the current offset is before the earliest available sequence in the shard. However, current token being an UNREAD token indicates that any sequence number in the shard is valid (despite the ordering)
Kinesis sequence numbers are inclusive i.e if current sequence == end sequence, there are more records left to read.
However, the equality check is exclusive when dealing with UNREAD tokens.
* 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>
* Adding zstandard compression library
* 1. Took @clintropolis's advice to have ZStandard decompressor use the byte array when the buffers are not direct.
2. Cleaned up checkstyle issues.
* Fixing zstandard version to latest stable version in pom's and updating license files
* Removing zstd from benchmarks and adding to processing (poms)
* fix the intellij inspection issue
* Removing the prefix v for the version in the license check for ztsd
* Fixing license checks
Co-authored-by: Rahul Gidwani <r_gidwani@apple.com>
* fix(docs): clarify what s3 permissions are needed based on the permissions model
* fix typo
* Update docs/development/extensions-core/s3.md
Co-authored-by: Jihoon Son <jihoonson@apache.org>
Co-authored-by: Jihoon Son <jihoonson@apache.org>
amazon-kinesis-client was not covered undered the apache license and required separate insertion in the kinesis extension.
This can now be avoided since it is covered, and including it within druid helps prevent incompatibilities.
Allows enabling of deaggregation out of the box by packaging amazon-kinesis-client (1.14.4) with druid for kinesis ingestion.
listShards API was used to get all the shards for kinesis ingestion to improve its resiliency as part of #12161.
However, this may require additional permissions in the IAM policy where the stream is present. (Please refer to: https://docs.aws.amazon.com/kinesis/latest/APIReference/API_ListShards.html).
A dynamic configuration useListShards has been added to KinesisSupervisorTuningConfig to control the usage of this API and prevent issues upon upgrade. It can be safely turned on (and is recommended when using kinesis ingestion) by setting this configuration to true.
* Docs: Masking S3 creds and some rewording
Knowledge transfer from https://groups.google.com/g/druid-user/c/FydcpFrA688
* Removed bold in one of the quote sections
* Update s3.md
* Update s3.md
Quick grammar change
* Update docs/development/extensions-core/s3.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/development/extensions-core/s3.md
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* Update docs/development/extensions-core/s3.md
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* Update docs/development/extensions-core/s3.md
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* Update docs/development/extensions-core/s3.md
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* Update s3.md
Typo
* Update docs/development/extensions-core/s3.md
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* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
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* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update s3.md
Active lang
* Update s3.md
LAng nit
* Update native-batch.md
LAng nit
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Grammar tidy-up and link fix
Corrected 2 x links to old page H2s, resolved the question around precedence, and some other grammatical changes.
* Update docs/development/extensions-core/s3.md
* Update s3.md
Removed an Erroneous E
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Azure Blob storage has multiple modes of authentication. One of them is Shared access resource
. This is very useful in cases when we do not want to add the account key in the druid properties .
* refactor and link fixes
* add sql docs to left nav
* code format for needle
* updated web console script
* link fixes
* update earliest/latest functions
* edits for grammar and style
* more link fixes
* another link
* update with #12226
* update .spelling file
* 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
* Make nodeRole available during binding; add support for dynamic registration of DruidService
* fix checkstyle and test
* fix customRole test
* address comments
* add more javadoc
under "Aggregators", about the lgK setting, it said "Must be a power of 2 from 4 to 21 inclusively." 21 is not a power of 2, nor is 12, the given default. I think there may have been confusion because lgK represents log2 of K. We could say "K must be a power of 2...", or just say lgK must be between 4 and 21.
* Support routing data through an HTTP proxy
* Support routing data through an HTTP proxy
This adds the ability for the HttpClient to connect through an HTTP proxy. We
augment the channel factory to check if it is supposed to be proxied and, if so,
we connect to the proxy host first, issue a CONNECT command through to the final
recipient host and *then* give the channel to the normal http client for usage.
* add docs
* address comments
Co-authored-by: imply-cheddar <86940447+imply-cheddar@users.noreply.github.com>
Enhanced the ExtractionNamespace interface in lookups-cached-global core extension with the ability to set a maxHeapPercentage for the cache of the respective namespace. The reason for adding this functionality, is make it easier to detect when a lookup table grows to a size that the underlying service cannot handle, because it does not have enough memory. The default value of maxHeap for the interface is -1, which indicates that no maxHeapPercentage has been set. For the JdbcExtractionNamespace and UriExtractionNamespace implementations, the default value is null, which will cause the respective service that the lookup is loaded in, to warn when its cache is beyond mxHeapPercentage of the service's configured max heap size. If a positive non-null value is set for the namespace's maxHeapPercentage config, this value will be honored for all services that the respective lookup is loaded onto, and consequently log warning messages when the cache of the respective lookup grows beyond this respective percentage of the services configured max heap size. Warnings are logged every time that either Uri based or Jdbc based lookups are regenerated, if the maxHeapPercentage constraint is violated. No other implementations will log warnings at this time. No error is thrown when the size exceeds the maxHeapPercentage at this time, as doing so could break functionality for existing users. Previously the JdbcCacheGenerator generated its cache by materializing all rows of the underling table in memory at once; this made it difficult to log warning messages in the case that the results from the jdbc query were very large and caused the service to run out of memory. To help with this, this pr makes it so that the jdbc query results are instead streamed through an iterator.
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.
### Description
Today we ingest a number of high cardinality metrics into Druid across dimensions. These metrics are rolled up on a per minute basis, and are very useful when looking at metrics on a partition or client basis. Events is another class of data that provides useful information about a particular incident/scenario inside a Kafka cluster. Events themselves are carried inside kafka payload, but nonetheless there are some very useful metadata that is carried in kafka headers that can serve as useful dimension for aggregation and in turn bringing better insights.
PR(https://github.com/apache/druid/pull/10730) introduced support of Kafka headers in InputFormats.
We still need an input format to parse out the headers and translate those into relevant columns in Druid. Until that’s implemented, none of the information available in the Kafka message headers would be exposed. So first there is a need to write an input format that can parse headers in any given format(provided we support the format) like we parse payloads today. Apart from headers there is also some useful information present in the key portion of the kafka record. We also need a way to expose the data present in the key as druid columns. We need a generic way to express at configuration time what attributes from headers, key and payload need to be ingested into druid. We need to keep the design generic enough so that users can specify different parsers for headers, key and payload.
This PR is designed to solve the above by providing wrapper around any existing input formats and merging the data into a single unified Druid row.
Lets look at a sample input format from the above discussion
"inputFormat":
{
"type": "kafka", // New input format type
"headerLabelPrefix": "kafka.header.", // Label prefix for header columns, this will avoid collusions while merging columns
"recordTimestampLabelPrefix": "kafka.", // Kafka record's timestamp is made available in case payload does not carry timestamp
"headerFormat": // Header parser specifying that values are of type string
{
"type": "string"
},
"valueFormat": // Value parser from json parsing
{
"type": "json",
"flattenSpec": {
"useFieldDiscovery": true,
"fields": [...]
}
},
"keyFormat": // Key parser also from json parsing
{
"type": "json"
}
}
Since we have independent sections for header, key and payload, it will enable parsing each section with its own parser, eg., headers coming in as string and payload as json.
KafkaInputFormat will be the uber class extending inputFormat interface and will be responsible for creating individual parsers for header, key and payload, blend the data resolving conflicts in columns and generating a single unified InputRow for Druid ingestion.
"headerFormat" will allow users to plug parser type for the header values and will add default header prefix as "kafka.header."(can be overridden) for attributes to avoid collision while merging attributes with payload.
Kafka payload parser will be responsible for parsing the Value portion of the Kafka record. This is where most of the data will come from and we should be able to plugin existing parser. One thing to note here is that if batching is performed, then the code is augmenting header and key values to every record in the batch.
Kafka key parser will handle parsing Key portion of the Kafka record and will ingest the Key with dimension name as "kafka.key".
## KafkaInputFormat Class:
This is the class that orchestrates sending the consumerRecord to each parser, retrieve rows, merge the columns into one final row for Druid consumption. KafkaInputformat should make sure to release the resources that gets allocated as a part of reader in CloseableIterator<InputRow> during normal and exception cases.
During conflicts in dimension/metrics names, the code will prefer dimension names from payload and ignore the dimension either from headers/key. This is done so that existing input formats can be easily migrated to this new format without worrying about losing information.
* Configurable maxStreamLength for doubles sketches
* fix equals/hashcode and it test failure
* fix test
* fix it test
* benchmark
* doc
* grouping key
* fix comment
* dependency check
* Update docs/development/extensions-core/datasketches-quantiles.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Add prometheus-emitter docs
* Update docs/development/extensions.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
This change updates doc to clarify when and how a change to druid.auth.authenticator.basic.credentialIterations takes effect: changes apply only to new users or existing users upon changing their password via the credentials API, which may not be the expectation.
* HLL lgK and a tip
Knowledge transfer from https://the-asf.slack.com/archives/CJ8D1JTB8/p1600699967024200. Attempted to make a connection between the SQL HLL function and the HLL underneath without getting too complicated. Also added a note about using K over 16 being pretty much pointless.
* Corrected spelling
* Create datasketches-hll.md
Put roll-up back to rollup
* Update docs/development/extensions-core/datasketches-hll.md
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
This PR splits current SegmentLoader into SegmentLoader and SegmentCacheManager.
SegmentLoader - this class is responsible for building the segment object but does not expose any methods for downloading, cache space management, etc. Default implementation delegates the download operations to SegmentCacheManager and only contains the logic for building segments once downloaded. . This class will be used in SegmentManager to construct Segment objects.
SegmentCacheManager - this class manages the segment cache on the local disk. It fetches the segment files to the local disk, can clean up the cache, and in the future, support reserve and release on cache space. [See https://github.com/Make SegmentLoader extensible and customizable #11398]. This class will be used in ingestion tasks such as compaction, re-indexing where segment files need to be downloaded locally.
* Avro union support
* Document new union support
* Add support for AvroStreamInputFormat and fix checkstyle
* Extend multi-member union test schema and format
* Some additional docs and add Enums to spelling
* Rename explodeUnions -> extractUnions
* explode -> extract
* ByType
* Correct spelling error
David Palmer
Hamish Ball
AmatyaAvadhanula
Gian Merlino
317brian
Jianhuan Liu
Rui Chen
Victoria Lim
Dr. Sizzles
Apoorv Gupta
Katya Macedo
AmatyaAvadhanula
Peter Marshall
Frank Chen
Karan Kumar
Jihoon Son
jacobtolar
Charles Smith
benkrug
Maytas Monsereenusorn
zachjsh
lokesh-lingarajan
Vaibhav
zhangyue19921010
Jeet Patel
Clint Wylie
sthetland
Yi Yuan
Paul Rogers
Abhishek Agarwal
Joseph Glanville