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.
The new config is an extension of the concept of "watchedTiers" where
the Broker can choose to add the info of only the specified tiers to its timeline.
Similarly, with this config, Broker can choose to skip the realtime nodes and
thus it would query only Historical processes for any given segment.
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.
* Remove OffheapIncrementalIndex and clarify aggregator thread-safety needs.
This patch does the following:
- Removes OffheapIncrementalIndex.
- Clarifies that Aggregators are required to be thread safe.
- Clarifies that BufferAggregators and VectorAggregators are not
required to be thread safe.
- Removes thread safety code from some DataSketches aggregators that
had it. (Not all of them did, and that's OK, because it wasn't necessary
anyway.)
- Makes enabling "useOffheap" with groupBy v1 an error.
Rationale for removing the offheap incremental index:
- It is only used in one rare scenario: groupBy v1 (which is non-default)
in "useOffheap" mode (also non-default). So you have to go pretty deep
into the wilderness to get this code to activate in production. It is
never used during ingestion.
- Its existence complicates developer efforts to reason about how
aggregators get used, because the way it uses buffer aggregators is so
different from how every other query engine uses them.
- It doesn't have meaningful testing.
By the way, I do believe that the given way the offheap incremental index
works, it actually didn't require buffer aggregators to be thread-safe.
It synchronizes on "aggregate" and doesn't call "get" until it has
stopped calling "aggregate". Nevertheless, this is a bother to think about,
and for the above reasons I think it makes sense to remove the code anyway.
* Remove things that are now unused.
* Revert removal of getFloat, getLong, getDouble from BufferAggregator.
* OAK-related warnings, suppressions.
* Unused item suppressions.
* docker mem reqs
* Update docs/tutorials/docker.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Sergio Ferragut <sergio.ferragut@imply.io>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Add druid.sql.approxCountDistinct.function property.
The new property allows admins to configure the implementation for
APPROX_COUNT_DISTINCT and COUNT(DISTINCT expr) in approximate mode.
The motivation for adding this setting is to enable site admins to
switch the default HLL implementation to DataSketches.
For example, an admin can set:
druid.sql.approxCountDistinct.function = APPROX_COUNT_DISTINCT_DS_HLL
* Fixes
* Fix tests.
* Remove erroneous cannotVectorize.
* Remove unused import.
* Remove unused test imports.
* 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
### 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.
* Add the ability to add a context to internally generated druid broker queries
* fix docs
* changes after first CI failure
* cleanup after merge with master
* change default to empty map and improve unit tests
* add doc info and fix checkstyle
* refactor DruidSchema#runSegmentMetadataQuery and add a unit test
The new config is an extension of the concept of "watchedTiers" where
the Broker can choose to add the info of only the specified tiers to its timeline.
Similarly, with this config, Broker can choose to ignore the segments being served
by the specified historical tiers. By default, no tier is ignored.
This config is useful when you want a completely isolated tier amongst many other tiers.
Say there are several tiers of historicals Tier T1, Tier T2 ... Tier Tn
and there are several brokers Broker B1, Broker B2 .... Broker Bm
If we want only Broker B1 to query Tier T1, instead of setting a long list of watchedTiers
on each of the other Brokers B2 ... Bm, we could just set druid.broker.segment.ignoredTiers=["T1"]
for these Brokers, while Broker B1 could have druid.broker.segment.watchedTiers=["T1"]
* update docs with X-Druid-SQL-Query-Id
* review comments
* update header description
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
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Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Rename field, fix router documentation
* Add more lines to doc
* Apply doc suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Add handoff wait time to ingestion stats report. Refactor some code for batch handoff
* fix checkstyle
* Add assertion to AbstractITBatchIndexTask to make sure report reflects wait for segments happened
* add docs to the task reports section of doc
* Update sql.md
Added two example queries and adjusted formatting of one that was already there
* Update docs/querying/sql.md
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* Update docs/querying/sql.md
Co-authored-by: Frank Chen <frankchen@apache.org>
* Update docs/querying/sql.md
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* Update docs/querying/sql.md
Co-authored-by: Frank Chen <frankchen@apache.org>
* Update sql.md
Co-authored-by: Frank Chen <frankchen@apache.org>
* add MV_FILTER_ONLY SQL function, and list filter virtual column
* MV_FILTER_NONE and more tests
* formatting
* o yeah, forgot can do easy thing
* style
* hmm why was that there
* test filtering on virtual column
* style
* meh
* do it right
* good bot
* Update index.md
Moved H4s underneath the H3 for the task log location and added hyperlinks.
* Update tasks.md
Added process information around log file generation, and subsumed text from the configuration guide into this explanatory text instead.
* Update tasks.md
.html > .md
* Update docs/ingestion/tasks.md
Co-authored-by: Frank Chen <frankchen@apache.org>
Co-authored-by: Frank Chen <frankchen@apache.org>
* Update description of batchProcessingMode
Update the description to explicitly mention a released version of Druid that the original version was referencing
* Update docs/configuration/index.md
* Update docs/configuration/index.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update granularities.md
Link-back to the ingestion spec as well as Native queries plus examples.
* Update docs/querying/granularities.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/granularities.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Make persists concurrent with ingestion
* Remove semaphore but keep concurrent persists (with add) and add push in the backround as well
* Go back to documented default persists (zero)
* Move to debug
* Remove unnecessary Atomics
* Comments on synchronization (or not) for sinks & sinkMetadata
* Some cleanup for unit tests but they still need further work
* Shutdown & wait for persists and push on close
* Provide support for three existing batch appenderators using batchProcessingMode flag
* Fix reference to wrong appenderator
* Fix doc typos
* Add BatchAppenderators class test coverage
* Add log message to batchProcessingMode final value, fix typo in enum name
* Another typo and minor fix to log message
* LEGACY->OPEN_SEGMENTS, Edit docs
* Minor update legacy->open segments log message
* More code comments, mostly small adjustments to naming etc
* fix spelling
* Exclude BtachAppenderators from Jacoco since it is fully tested but Jacoco still refuses to ack coverage
* Coverage for Appenderators & BatchAppenderators, name change of a method that was still using "legacy" rather than "openSegments"
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* 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
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* Update docs/querying/sql.md
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* Update docs/querying/sql.md
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* Update docs/querying/sql.md
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* Update docs/querying/sql.md
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* Update docs/querying/sql.md
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Co-authored-by: Charles Smith <techdocsmith@gmail.com>
LGTM
* Update native-batch.md
Knowledge from https://the-asf.slack.com/archives/CJ8D1JTB8/p1595434977062400
* Update native-batch.md
* Fixed broken link + some grammar
* 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
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* Update native-batch.md
Some grammatical wizardry.
* Update native-batch.md
* 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
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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
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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
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* Update docs/ingestion/native-batch.md
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* Apply suggestions from code review
remove orphaned links
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* Add details to the Docker tutorial
Added links, explanations and other details to the Docker
tutorial to make it easier for first-time users.
* Fix spelling error
And add "Jupyter" to the spelling dictionary.
* Update docs/tutorials/docker.md
* Update docs/tutorials/docker.md
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* Update docs/tutorials/docker.md
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* Update docs/tutorials/docker.md
* Update docs/tutorials/docker.md
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* Add prometheus-emitter docs
* Update docs/development/extensions.md
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Lucas Capistrant
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Caroline1000
Vaibhav
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