* Reverse, pull up lookups in the SQL planner.
Adds two new rules:
1) ReverseLookupRule, which eliminates calls to LOOKUP by doing
reverse lookups.
2) AggregatePullUpLookupRule, which pulls up calls to LOOKUP above
GROUP BY, when the lookup is injective.
Adds configs `sqlReverseLookup` and `sqlPullUpLookup` to control whether
these rules fire. Both are enabled by default.
To minimize the chance of performance problems due to many keys mapping to
the same value, ReverseLookupRule refrains from reversing a lookup if there
are more keys than `inSubQueryThreshold`. The rationale for using this setting
is that reversal works by generating an IN, and the `inSubQueryThreshold`
describes the largest IN the user wants the planner to create.
* Add additional line.
* Style.
* Remove commented-out lines.
* Fix tests.
* Add test.
* Fix doc link.
* Fix docs.
* Add one more test.
* Fix tests.
* Logic, test updates.
* - Make FilterDecomposeConcatRule more flexible.
- Make CalciteRulesManager apply reduction rules til fixpoint.
* Additional tests, simplify code.
Currently, If 2 tasks are consuming from the same partitions, try to publish the segment and update the metadata, the second task can fail because the end offset stored in the metadata store doesn't match with the start offset of the second task. We can fix this by retrying instead of failing.
AFAIK apart from the above issue, the metadata mismatch can happen in 2 scenarios:
- when we update the input topic name for the data source
- when we run 2 replicas of ingestion tasks(1 replica will publish and 1 will fail as the first replica has already updated the metadata).
Implemented the comparable function to compare the last committed end offset and new Sequence start offset. And return a specific error msg for this.
Add retry logic on indexers to retry for this specific error msg.
Updated the existing test case.
The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information. This task encompasses addressing both realtime and finalized segments.
This modification specifically addresses the issue with realtime segments. Tasks will now routinely communicate the schema for realtime segments during the segment announcement process. The Coordinator will identify the schema alongside the segment announcement and subsequently update the schema for realtime segments in the metadata cache.
This PR enables the flag by default to queue excess query requests in the jetty queue. Still keeping the flag so that it can be turned off if necessary. But the flag will be removed in the future.
* Allow overwriting ServerConnector accept queue size
* Use a single config
* Fix spacing
* fix spacing
* fixed value
* read value from environment
* fix spacing
* Unpack value before reading
* check somaxconn on linux only
* Reverse lookup fixes and enhancements.
1) Add a "mayIncludeUnknown" parameter to DimFilter#optimize. This is important
because otherwise the reverse-lookup optimization is done improperly when
the "in" filter appears under a "not", and the lookup extractionFn may return
null for some possible values of the filtered column. The "includeUnknown" test
cases in InDimFilterTest illustrate the difference in behavior.
2) Enhance InDimFilter#optimizeLookup to handle "mayIncludeUnknown", and to be able
to do a reverse lookup in a wider variety of cases.
3) Make "unapply" protected in LookupExtractor, and move callers to "unapplyAll".
The main reason is that MapLookupExtractor, a common implementation, lacks a
reverse mapping and therefore does a scan of the map for each call to "unapply".
For performance sake these calls need to be batched.
* Remove optimize call from BloomDimFilter.
* Follow the law.
* Fix tests.
* Fix imports.
* Switch function.
* Fix tests.
* More tests.
* Minor fixes
* Update docs/development/extensions-contrib/prometheus.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
---------
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Currently in the realtime ingestion (Kafka/Kinesis) case, after publishing the segments, upon acknowledgement from the coordinator that the segments are already placed in some historicals, the peon would unannounce the segments (basically saying the segments are not in this peon anymore to the whole cluster) and drop the segments from cache and sink timeline in one shot.
The in transit queries from the brokers that still thinks the segments are in the peon can get a NullPointer exception when the peon is unsetting the hydrants in the sinks.
The fix would let the peon to wait for a configurable delay period before dropping segments, remove segments from cache etc after the peon unannounce the segments.
This delayed approach is similar to how the historicals handle segments moving out.
Changes
- Add `log` implementation for `AuditManager` alongwith `SQLAuditManager`
- `LoggingAuditManager` simply logs the audit event. Thus, it returns empty for
all `fetchAuditHistory` calls.
- Add new config `druid.audit.manager.type` which can take values `log`, `sql` (default)
- Add new config `druid.audit.manager.logLevel` which can take values `DEBUG`, `INFO`, `WARN`.
This gets activated only if `type` is `log`.
- Remove usage of `ConfigSerde` from `AuditManager` as audit is not just limited to configs
- Add `AuditSerdeHelper` for a single implementation of serialization/deserialization of
audit payload and other utility methods.
The segment allocation algorithm reuses an already allocated pending segment if the new allocation request is made for the same parameters:
datasource
sequence name
same interval
same value of skipSegmentLineageCheck (false for batch append, true for streaming append)
same previous segment id (used only when skipSegmentLineageCheck = false)
The above parameters can thus uniquely identify a pending segment (enforced by the UNIQUE constraint on the sequence_name_prev_id_sha1 column in druid_pendingSegments metadata table).
This reuse is done in order to
allow replica tasks (in case of streaming ingestion) to use the same set of segment IDs.
allow re-run of a failed batch task to use the same segment ID and prevent unnecessary allocations
This PR builds on #13304 to skip compaction for datasources with segments that have their interval start or end coinciding with Eternity interval end-points.
This is needed in order to prevent an issue similar to #13208 as the Coordinator tries to iterate over a large number of intervals when trying to compact an interval with infinite start or end.
### Description
This pr adds an api for retrieving unused segments for a particular datasource. The api supports pagination by the addition of `limit` and `lastSegmentId` parameters. The resulting unused segments are returned with optional `sortOrder`, `ASC` or `DESC` with respect to the matching segments `id`, `start time`, and `end time`, or not returned in any guarenteed order if `sortOrder` is not specified
`GET /druid/coordinator/v1/datasources/{dataSourceName}/unusedSegments?interval={interval}&limit={limit}&lastSegmentId={lastSegmentId}&sortOrder={sortOrder}`
Returns a list of unused segments for a datasource in the cluster contained within an optionally specified interval.
Optional parameters for limit and lastSegmentId can be given as well, to limit results and enable paginated results.
The results may be sorted in either ASC, or DESC order depending on specifying the sortOrder parameter.
`dataSourceName`: The name of the datasource
`interval`: the specific interval to search for unused segments for.
`limit`: the maximum number of unused segments to return information about. This property helps to
support pagination
`lastSegmentId`: the last segment id from which to search for results. All segments returned are > this segment
lexigraphically if sortOrder is null or ASC, or < this segment lexigraphically if sortOrder is DESC.
`sortOrder`: Specifies the order with which to return the matching segments by start time, end time. A null
value indicates that order does not matter.
This PR has:
- [x] been self-reviewed.
- [ ] using the [concurrency checklist](https://github.com/apache/druid/blob/master/dev/code-review/concurrency.md) (Remove this item if the PR doesn't have any relation to concurrency.)
- [x] added documentation for new or modified features or behaviors.
- [ ] a release note entry in the PR description.
- [x] added Javadocs for most classes and all non-trivial methods. Linked related entities via Javadoc links.
- [ ] added or updated version, license, or notice information in [licenses.yaml](https://github.com/apache/druid/blob/master/dev/license.md)
- [x] added comments explaining the "why" and the intent of the code wherever would not be obvious for an unfamiliar reader.
- [x] added unit tests or modified existing tests to cover new code paths, ensuring the threshold for [code coverage](https://github.com/apache/druid/blob/master/dev/code-review/code-coverage.md) is met.
- [ ] added integration tests.
- [x] been tested in a test Druid cluster.
* Add initial draft of MarkDanglingTombstonesAsUnused duty.
* Use overshadowed segments instead of all used segments.
* Add unit test for MarkDanglingSegmentsAsUnused duty.
* Add mock call
* Simplify code.
* Docs
* shorter lines formatting
* metric doc
* More tests, refactor and fix up some logic.
* update javadocs; other review comments.
* Make numCorePartitions as 0 in the TombstoneShardSpec.
* fix up test
* Add tombstone core partition tests
* Update docs/design/coordinator.md
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
* review comment
* Minor cleanup
* Only consider tombstones with 0 core partitions
* Need to register the test shard type to make jackson happy
* test comments
* checkstyle
* fixup misc typos in comments
* Update logic to use overshadowed segments
* minor cleanup
* Rename duty to eternity tombstone instead of dangling. Add test for full eternity tombstone.
* Address review feedback.
---------
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
Description
With CentralizedDatasourceSchema (#14989) feature enabled, metadata for appended segments was not being refreshed. This caused numRows to be 0 for the new segments and would probably cause the datasource schema to not include columns from the new segments.
Analysis
The problem turned out in the new QuerySegmentWalker implementation in the Coordinator. It first finds the segment to be queried in the Coordinator timeline. Then it creates a new timeline of the segments present in the timeline.
The problem was that it is looking up complete partition set in the new timeline. Since the appended segments by themselves do not make a complete partition set, no SegmentMetadataQuery were executed.
Update guava to 32.0.1-jre to address two CVEs: CVE-2020-8908, CVE-2023-2976
This change requires a minor test change to remove assumptions about ordering.
---------
Co-authored-by: Xavier Léauté <xl+github@xvrl.net>
* Fixing failing compaction/parallel index jobs during upgrade due to new actions not available on the overlord.
* Fixing build
* Removing extra space.
* Fixing json getter.
* Review comments.
* Fix NPE caused by realtime segment closing race, fix possible missing-segment retry bug.
Fixes#12168, by returning empty from FireHydrant when the segment is
swapped to null. This causes the SinkQuerySegmentWalker to use
ReportTimelineMissingSegmentQueryRunner, which causes the Broker to look
for the segment somewhere else.
In addition, this patch changes SinkQuerySegmentWalker to acquire references
to all hydrants (subsegments of a sink) at once, and return a
ReportTimelineMissingSegmentQueryRunner if *any* of them could not be acquired.
I suspect, although have not confirmed, that the prior behavior could lead to
segments being reported as missing even though results from some hydrants were
still included.
* Some more test coverage.
* Make numCorePartitions as 0 in the TombstoneShardSpec.
* fix up test
* Add tombstone core partition tests
* review comment
* Need to register the test shard type to make jackson happy
In pull request #14985, a bug was introduced where periodic refresh would skip rebuilding a datasource's schema after encountering a non-existent datasource. This resulted in remaining datasources having stale schema information.
This change addresses the bug and adds a unit test to validate the refresh mechanism's behaviour when a datasource is removed, and other datasources have schema changes.
* Add a unit test that fails when used segments with too many intervals are retrieved.
- This is a failing test case that needs to be ignored.
* Batch the intervals (use 100 as it's consistent with batching in other places).
* move the filtering inside the batch
* Account for limit cross the batch splits.
* Adjustments
* Fixup and add tests
* small refactor
* add more tests.
* remove wrapper.
* Minor edits
* assert out of range
In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal.
To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
* Use filters for pruning properly for hash-joins.
Native used them too aggressively: it might use filters for the RHS
to prune the LHS. MSQ used them not at all. Now, both use them properly,
pruning based on base (LHS) columns only.
* Fix tests.
* Fix style.
* Clear filterFields too.
* Update.
* Add system fields to input sources.
Main changes:
1) The SystemField enum defines system fields "__file_uri", "__file_path",
and "__file_bucket". They are associated with each input entity.
2) The SystemFieldInputSource interface can be added to any InputSource
to make it system-field-capable. It sets up serialization of a list
of configured "systemFields" in the JSON form of the input source, and
provides a method getSystemFieldValue for computing the value of each
system field. Cloud object, HDFS, HTTP, and Local now have this.
* Fix various LocalInputSource calls.
* Fix style stuff.
* Fixups.
* Fix tests and coverage.
ServiceClientImpl logs the cause of every retry, even though we are retrying the connection attempt. This leads to slight pollution in the logs because a lot of the time, the reason for retrying is the same. This is seen primarily in MSQ, when the worker task hasn't launched yet however controller attempts to connect to the worker task, which can lead to scary-looking messages (with INFO log level), even though they are normal.
This PR changes the logging logic to log every 10 (arbitrary number) retries instead of every retry, to reduce the pollution of the logs.
Note: If there are no retries left, the client returns an exception, which would get thrown up by the caller, and therefore this change doesn't hide any important information.
* Use min of scheduler threads and server threads for subquery guardrails.
This allows more memory to be used for subqueries when the query scheduler
is configured to limit queries below the number of server threads. The patch
also refactors the code so SubqueryGuardrailHelper is provided by a Guice
Provider rather than being created by ClientQuerySegmentWalker, to achieve
better separation of concerns.
* Exclude provider from coverage.
* Frames: consider writing singly-valued column when input column hasMultipleValues is UNKNOWN.
Prior to this patch, columnar frames would always write multi-valued columns if
the input column had hasMultipleValues = UNKNOWN. This had the effect of flipping
UNKNOWN to TRUE when copying data into frames, which is problematic because TRUE
causes expressions to assume that string inputs must be treated as arrays.
We now avoid this by flipping UNKNOWN to FALSE if no multi-valuedness
is encountered, and flipping it to TRUE if multi-valuedness is encountered.
* Add regression test case.
Currently the inter Druid communication via rest endpoints is based on json formatted payload. Upon parsing error, there is only a generic exception stating expected json token type and current json token type. There is no detailed error log about the content of the payload causing the violation.
In the micro-service world, the trend is to deploy the Druid servers in k8 with the mesh network. Often the istio proxy or other proxies is used to intercept the network connection between Druid servers. The proxy may give error messages for various reasons. These error messages are not expected by the json parser. The generic error message from Druid can be very misleading as the user may think the message is based on the response from the other Druid server.
For example, this is an example of mysterious error message
QueryInterruptedException{msg=Next token wasn't a START_ARRAY, was[VALUE_STRING] from url[http://xxxxx:8088/druid/v2/], code=Unknown exception, class=org.apache.druid.java.util.common.IAE, host=xxxxx:8088}"
While the context of the message is the following from the proxy when it can't tunnel the network connection.
pstream connect error or disconnect/reset before header
So this very simple PR is just to enhance the logging and get the real underlying message printed out. This would save a lot of head scratching time if Druid is deployed with mesh network.
Co-authored-by: Kai Sun <kai.sun@salesforce.com>
AmatyaAvadhanula
Sam Rash
Kashif Faraz
Gian Merlino
PANKAJ KUMAR
Rishabh Singh
Pranav
Abhishek Agarwal
Jonathan Wei
George Shiqi Wu
Abhishek Radhakrishnan
kaisun2000
zachjsh
Clint Wylie
Vishesh Garg
Jan Werner
Vadim Ogievetsky
Karan Kumar
Laksh Singla
Suneet Saldanha