Improve volume and segment index performance #8460
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📝 WalkthroughWalkthroughThis pull request introduces a variety of updates across configuration, backend, and tracing modules. Key changes include the addition of a new C++ indent configuration, updates to the changelog and migration requirements, and a revised Docker image version. The changes also convert bucket position collections from lists to sets, add new JNI methods for native bucket scanning, expand FossilDB API messages and RPC methods, and revise numerous method signatures and internal logic in tracing components to enhance consistency and efficiency. Changes
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🧹 Nitpick comments (5)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (1)
32-36: Implicit execution context parameter might be redundantThe
getWithFallbackmethod takes animplicit ec: ExecutionContextparameter, but the class constructor already provides an execution context. Is there a reason for having both?- def getWithFallback(bucketPosition: BucketPosition)(implicit ec: ExecutionContext): Fox[Array[Byte]] = + def getWithFallback(bucketPosition: BucketPosition): Fox[Array[Byte]] =webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (2)
90-119: Potential performance improvement
Currently, segment retrieval is handled in multiple steps (buffer, fossil, datastore). If the data store client supports a bulk/multi-get call, it may boost performance for large lists of segment IDs.
136-156: Use of mutable vars
This method accumulates hits and misses via mutable lists. Consider a single-pass approach (e.g.foldLeft) to improve readability and reduce side effects.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexService.scala (1)
57-88: Batch processing
Removals and additions are done sequentially. If performance problems arise with large sets of segments, consider a bulk or parallel approach.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala (1)
111-139: Good use of VolumeBucketBuffer for performance optimizationThe introduction of
volumeBucketBufferand the prefill operation aligns with the PR's performance objectives. Batching the bucket operations should significantly improve performance when dealing with multiple buckets, especially with fallback layers.One observation - the
Fox.successful(())at line 111 seems to be just a placeholder. Consider if this is necessary or if it could be removed for clarity.
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util/src/main/scala/com/scalableminds/util/tools/BoxImplicits.scala(1 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/FossilDBClient.scala(3 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala(1 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala(2 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexService.scala(3 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingBucketHelper.scala(6 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingLayer.scala(4 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala(20 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingLayer.scala
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🧬 Code Definitions (4)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (2)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/FossilDBClient.scala (4)
FossilDBClient(44-246)version(41-41)get(108-117)put(198-213)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingBucketHelper.scala (2)
loadBuckets(175-196)saveBuckets(339-354)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingBucketHelper.scala (4)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala (1)
data(492-509)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/TemporaryTracingService.scala (1)
isTemporaryTracing(100-103)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingLayer.scala (1)
lengthOfUnderlyingCubes(96-96)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (1)
put(60-63)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala (3)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexService.scala (2)
updateFromBucket(57-89)getSegmentToBucketIndex(138-167)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (2)
flush(63-72)getWithFallback(32-38)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingLayer.scala (7)
bucketStreamWithVersion(41-43)bucketStreamWithVersion(61-63)bucketProvider(106-111)bucketProvider(111-111)bucketStream(38-41)bucketStream(58-61)bucketStream(119-119)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexService.scala (1)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (3)
getOne(80-90)put(59-69)getMultiple(90-119)
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🔇 Additional comments (49)
util/src/main/scala/com/scalableminds/util/tools/BoxImplicits.scala (1)
27-36: Implementation looks good and follows best practices.The
assertNoFailuremethod efficiently validates that none of the boxes in the sequence are failures, stopping at the first occurrence. The error message is informative by including the count of boxes and the specific failure encountered. This will be useful for validation and error handling in the broader context of volume and segment index processing mentioned in the PR objectives.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (4)
1-21: Well-structured class definition with appropriate dependenciesThe class is properly defined with all necessary dependencies for managing volume bucket data. It extends
VolumeTracingBucketHelperwhich provides core bucket functionality and mixes inProtoGeometryImplicitsfor geometry-related conversions. The class aligns well with the PR objective of improving performance for volume and segment index handling.
23-25: Consider thread safety for mutable bufferThe implementation uses a mutable HashMap without synchronization, which could lead to race conditions if accessed concurrently. While the execution context suggests asynchronous operations, it's worth ensuring thread safety is managed properly at usage sites.
Also, why is the buffer defined as
lazy valrather than a regularval? Is there a specific reason for delaying initialization?
38-59: Efficient implementation of fallback layer handlingThe methods for retrieving bucket data are well-designed, with proper error handling through Box types. The batching of requests in
getMultipleFromFossilOrFallbackLayeris a good optimization that aligns with the PR's performance improvement objectives. The code also properly handles failures and empty results.
60-72: Good implementation of buffer update and flush functionalityThe
putandflushmethods efficiently handle updating and persisting bucket data. Theflushmethod smartly filters only the dirty buckets with valid data, which minimizes unnecessary operations. This implementation should help achieve the performance improvements mentioned in the PR objectives.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/FossilDBClient.scala (7)
97-97: String interpolation simplifiedThe error message formatting has been simplified by removing unnecessary curly braces around the
messageWithCausesvariable.
153-159: Well-structured batch processing implementationThe new
getMultipleKeysByListmethod effectively replacesgetMultipleVersionswith an improved implementation that processes keys in batches, which should reduce load on FossilDB and improve performance. This aligns well with the PR's performance improvement objectives.
160-180: Comprehensive error handling in implementationThe private implementation method handles various response cases well, including successful responses, error messages, and empty responses. The parsing logic is thorough and maintains type safety.
210-213: Error message formatting improvedThe error message has been clarified and made more consistent with other error messages in the class.
215-219: Efficient multi-put implementation with batchingThe new
putMultiplemethod implements batch processing for multiple key-value pairs, which aligns with the PR objective of using "fossilDB multi-put functionalities for bucket updates." The batching approach should significantly improve performance when updating many buckets simultaneously.
220-239: Consistent error handling pattern maintainedThe implementation follows the established pattern of separating the RPC call from error handling, allowing for proper slack notification while maintaining the Fox monad chain. This is consistent with the explanation provided in the past review comment.
153-239:❓ Verification inconclusive
Verify fallback layer functionality with new multi-get/put methods
The PR objectives mention fixing an issue where "segment index did not correctly query the fallback layer during volume bucket updates." Let's verify that the new batch methods properly handle fallback layers.
🏁 Script executed:
#!/bin/bash # Check if there are tests that verify fallback layer functionality with the new methods echo "Searching for tests related to fallback layer functionality..." rg -A 5 -B 5 "fallback.*getMultipleKeysByList|getMultipleKeysByList.*fallback" echo "Checking for usages of the new methods with fallback layers..." rg -A 3 "getMultipleKeysByList.*fallback|putMultiple.*fallback" echo "Checking for volume bucket update implementations that use these methods..." rg -A 5 "VolumeBucket.*update.*getMultipleKeysByList|VolumeBucketBuffer"Length of output: 3695
Ensure Fallback Layer Is Properly Queried in Batch Methods
- The new multi-get (getMultipleKeysByList) and multi-put (putMultiple) methods are meant to support fallback behavior during volume bucket updates, yet no explicit tests or references to fallback scenarios were found in the current code.
- Searches in the codebase (e.g., in VolumeBucketBuffer and VolumeTracingService) show usage of these methods, but they don’t explicitly verify that fallback querying is triggered when needed.
- Please add or update test cases that simulate fallback conditions to confirm that the new methods correctly handle the fallback layer—or clarify how the fallback behavior is implicitly managed if that’s the intended design.
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (12)
6-19: Imports look consistent
The newly added imports appear necessary for the code’s functionality and seem properly scoped.
38-50: Consider concurrency or synchronization
These constructor parameters instantiate amutable.Mapin the class body. If multiple threads may access or modify the buffer concurrently, a concurrency risk arises. Unless usage is guaranteed to be single-threaded, consider enforcing thread-safety (e.g., synchronization or a thread-safe collection).Do you want me to generate a script to search for concurrent usage references to
VolumeSegmentIndexBuffer?
56-57: Already covered in previous comment
The concurrency considerations mentioned above also apply here, as this mutable map stores the buffer contents.
62-66: Potential overwrite concern
This method overwrites any existing bucket positions for the given key. If you intend to merge new positions with existing ones, ensure that’s handled before callingput.Would you like a script to check if calling code might inadvertently discard existing data?
69-78: Batch put logic
Similar overwrite concern as input. If incremental merges are required, retrieve existing data or confirm overwrites are intended.
80-88: Straightforward single-lookup method
WrappinggetMultipleand extracting the head is concise and handles empty results safely withheadOption.map(_._2).toFox.
119-122: Concurrent flush risk
flush()writes buffered updates to storage. If multiple threads call this simultaneously, changes may overwrite each other in the backing store. Validate single-threaded usage or add synchronization.Do you want me to generate a script to locate concurrent
flush()calls?
157-178: Sequential retrieval
Fox.serialCombinedfetches data for each segment ID sequentially. A parallel or bulk approach might reduce latency for large segment sets if supported byvolumeSegmentIndexClient.
180-194: Temporary store retrieval
Mirrors the fossil retrieval logic. If performance becomes critical, consider a multi-get approach similar to the above.
196-212: Fallback retrieval logic
This structured fallback approach is clearly delineated and consistent with the rest of the code.
213-215: Empty bucket array
Provides a convenient zero-filled array for missing data. Straightforward and clear.
216-222: Handling empty fallback
MappingEmptyto a zero-filled array is a concise solution to store constraints.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingBucketHelper.scala (12)
4-17: New imports
Necessary additions for box handling, decompression, and concurrency utilities.
33-43: Compression logic
Method properly checks whether data is already uncompressed before applying LZ4 compression.
44-60: Robust decompression
Wraps LZ4 decompression in try/catch to handle errors gracefully.
80-90: Refined bucket key generation
UsingvolumeTracingIdin place ofdataLayerNameclarifies intent and scope.
92-93: Simplified key prefix
Replacing the old prefix approach withvolumeTracingIdis more direct and cohesive.
175-196: Bulk bucket loading
Collecting fossil data, merging fallback data, and decompressing in one path is well structured.
198-236: Efficient fallback data handling
addFallbackBucketDataneatly identifies empty buckets and fills them from the fallback store. The indexing logic is clear.
238-257: splitIntoBuckets length check
Properly safeguards against partial data returns. Throws an exception for mismatches, which prevents silent truncation.
259-289: Single bucket load with fallback
Nicely falls back if the primary store returns empty. This keeps the code DRY compared to re-implementing loading logic.
310-322: saveBucket compression
Reuses the compression step consistently when saving to temporary or fossil store.
323-354: Bulk bucket saving
Parallel toloadBuckets, enabling multiple buckets to be stored at once.
356-383: Iterators for streaming
Provides efficient streaming in multiple scenarios (with and without version, from temporary store).webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexService.scala (6)
10-13: Imports
These new imports forVec3IntProto,NativeBucketScanner, andBucketPositionsupport the updated segment index logic.
23-23: Liftweb Box usage
Already used throughout the code; consistent approach to handling optional data and errors.
95-107: Removing bucket references
Fetching existing positions, subtracting this bucket, and storing the result is straightforward.
114-128: Adding new bucket references
Retrieves multiple prior positions in one call, then updates them to include the new bucket. Good for avoiding repeated lookups.
130-137: Native bucket scanning
Lazy loading theNativeBucketScannerand transforming the results into aSet[Long]is concise.
138-166: Segment-to-bucket index retrieval
Constructing a read-only buffer to fetch bucket positions ensures no accidental modifications.webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala (7)
90-101: Improved method signature by using volumeLayer parameterThe method now takes a
volumeLayerparameter instead of separatemappingNameandelementClassparameters. This is a good refactoring as it encapsulates related data, simplifies the interface, and promotes consistency with other methods.
158-181: Streamlined bucket update processThe method now properly uses the
volumeBucketBufferto manage bucket data and check prior state, which aligns with the performance improvement goals.The change from direct storage to using
volumeBucketBuffer.putat line 180 enables the buffer to accumulate changes and optimize them (likely using fossilDB multi-put functionality mentioned in the PR objectives).
199-222: Improved segment index handling with SetsThe change to process bucket positions as a Set (line 222) rather than a List aligns with the PR objective of "employing a set for bucket positions to reduce conversions."
127-135: Ensure buffer is properly flushedGood implementation of the buffer flush operation at line 153. This ensures that all changes accumulated in the
volumeBucketBufferare properly committed at the end of the operation.Also applies to: 153-153
287-287: Consider batching loadBucket operationsThe loadBucket operations could potentially be batched for additional performance improvements.
As noted in the previous review comment by MichaelBuessemeyer, batching the loadBucket operations into a single request for all missing buckets could further improve performance, though I understand this is not a high priority since reverts are relatively rare.
136-139: Effective prefilling strategy for performanceThe prefill operation selectively extracts bucket positions from UpdateBucketVolumeAction instances, which is an efficient approach to prepare the buffer before processing individual actions.
762-767: Consistent use of volumeLayer throughout merge operationsThe refactoring to use volumeLayer consistently across merge operations improves code clarity and maintainability while enabling the performance optimizations targeted by this PR.
Also applies to: 795-802
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webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (1)
90-117: Efficient implementation for retrieving multiple segment indicesThe new
getMultiplemethod properly handles the retrieval sequence (buffer → fossilDB/temporary → datastore) and batches operations for better performance, which is in line with the PR objectives of optimizing loading multiple volume buckets.However, line 109 could be optimized further by using a Map directly instead of combining collections.
- allHits = fromBufferHits ++ fromFossilOrTempHits ++ fromDatastoreHits + allHits = (fromBufferHits ++ fromFossilOrTempHits ++ fromDatastoreHits).toMapThis would make the lookups in the following block more efficient, as noted in a previous code review.
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webknossos-datastore/app/com/scalableminds/webknossos/datastore/helpers/SegmentStatistics.scala(4 hunks)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala(2 hunks)
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- webknossos-datastore/app/com/scalableminds/webknossos/datastore/helpers/SegmentStatistics.scala
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webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (12)
38-50: Constructor implementation aligns with performance objectivesThe updated constructor with new parameters
elementClass,mappingName, andisReadOnlysupports the PR's goal of improving performance for volume and segment index handling. TheisReadOnlyparameter replaces the previously reviewedisReaderOnlyparameter.
56-57: Good optimization: Changed data structure for better performanceConverting from
ListOfVec3IntPrototo(Set[Vec3IntProto], Boolean)allows for:
- More efficient set operations (union, intersection)
- Tracking changed bucket positions via the boolean flag
- Selective flushing of only modified entries
This change aligns with the PR objectives of improving performance for bucket updates.
59-67: Enhanced safety with isReadOnly checkThe updated
putmethod now correctly prevents modifications when the buffer is in read-only mode and accepts sets instead of lists for bucket positions, which aligns with the performance improvements mentioned in the PR objectives.
69-78: New batch operation method improves efficiencyThe
putMultiplemethod supports efficient batch operations, which is more performant than callingputmultiple times. This aligns with the PR objective of using fossilDB multi-put functionality for bucket updates.
80-88: Clean API design with separate getOne methodThe new
getOnemethod provides a clean API for single-item retrieval while reusing the batch operation logic fromgetMultiple. This promotes code reuse and maintainability.
119-134: Optimized flush operation with selective updatesThe improved
flushmethod now:
- Checks the
isReadOnlyflag to prevent invalid operations- Only flushes entries marked as changed
- Uses
putMultiplefor fossilDB, which is more efficient than individual putsThis directly supports the PR objective of using fossilDB multi-put functionality for bucket updates.
136-155: Efficient buffer lookup implementationThe method now correctly returns a tuple of hits and misses, with an early exit path for read-only mode. The hits are stored in a map for efficient lookup, which aligns with the performance improvements mentioned in the PR objectives.
157-173: Effective use of batch operations for FossilDB queriesThe implementation now uses
getMultipleKeysByListwith batch size control, which aligns with the PR objective of using fossilDB multi-get functionality for improved performance.
175-189: Consistent implementation for temporary store lookupsThis method follows the same pattern as the other retrieval methods, maintaining consistency in the codebase and correctly handling the temporary store case.
191-206: Optimized datastore query for multiple segmentsThe method now uses
querySegmentIndexForMultipleSegmentsto batch requests, which aligns with the PR objective of optimizing loading multiple volume buckets.
208-210: Memory-efficient empty bucket handlingThe lazy val ensures the empty bucket array is created only once and reused, which is more efficient than creating a new array each time it's needed.
211-216: Well-implemented fallback mechanismThe
bytesWithEmptyFallbackmethod properly handles all possible states of the input box (Empty, Full, Failure), providing a clean fallback mechanism when no data is available. This helps resolve the issue mentioned in the PR objectives where "segment index did not correctly query the fallback layer".
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@MichaelBuessemeyer thanks for your detailed review! I implemented most of the suggestions. I think it’s a good time to do some testing, and if you want you can also already have another look at the code :) |
...om/scalableminds/webknossos/tracingstore/tracings/editablemapping/EditableMappingLayer.scala
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webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala(2 hunks)
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webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (4)
webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/TemporaryTracingService.scala (3)
TemporaryTracingService(18-114)saveVolumeSegmentIndexBuffer(90-95)getVolumeSegmentIndexBufferForKey(59-62)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeBucketBuffer.scala (2)
put(60-63)flush(63-72)webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeTracingService.scala (1)
editableMappingTracingId(183-186)webknossos-datastore/app/com/scalableminds/webknossos/datastore/storage/TemporaryStore.scala (2)
getMultiple(28-33)get(13-18)
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webknossos-tracingstore/app/com/scalableminds/webknossos/tracingstore/tracings/volume/VolumeSegmentIndexBuffer.scala (8)
109-115: Consider using a Map-based approach to improve performance.The current implementation iterates over all segment IDs repeatedly to check if they exist in the combined map. Using a map lookup would be more efficient when working with large datasets.
- allHits = fromBufferHits ++ fromFossilOrTempHits ++ fromDatastoreHits - allHitsFilled = segmentIds.map { segmentId => - allHits.get(segmentId) match { - case Some(positions) => (segmentId, positions) - case None => (segmentId, Set[Vec3IntProto]()) - } - } + allHits = fromBufferHits ++ fromFossilOrTempHits ++ fromDatastoreHits + allHitsFilled = segmentIds.map(segmentId => + (segmentId, allHits.getOrElse(segmentId, Set.empty[Vec3IntProto])) + )
99-101: Move Fox.successful outside of for-comprehension.The current code structure unnecessarily wraps the result in a Fox and then extracts it with <-. Moving the conditional logic outside the for-comprehension would be more efficient.
- (fromFossilOrTempHits, fromFossilOrTempMisses) <- if (toTemporaryStore) - Fox.successful(getMultipleFromTemporaryStoreNoteMisses(fromBufferMisses, mag, additionalCoordinates)) - else getMultipleFromFossilNoteMisses(fromBufferMisses, mag, additionalCoordinates) + (fromFossilOrTempHits, fromFossilOrTempMisses) <- { + if (toTemporaryStore) + Fox.successful(getMultipleFromTemporaryStoreNoteMisses(fromBufferMisses, mag, additionalCoordinates)) + else + getMultipleFromFossilNoteMisses(fromBufferMisses, mag, additionalCoordinates) + }
166-167: Good use of batch processing to optimize performance.Using
getMultipleKeysByListwith a batch size parameter is an excellent performance optimization for handling many segment IDs efficiently, helping to reduce the number of database queries.
208-210: Good optimization using lazy val for empty bucket array.Lazily initializing the empty bucket array is an efficient approach since it's only created when needed and then reused, reducing unnecessary object creation.
211-216: Well-designed fallback mechanism for empty data.The
bytesWithEmptyFallbackmethod provides a clean way to handle empty data by returning a properly initialized empty array instead of failing, improving robustness.
69-78: Good implementation of batch update capability.The
putMultiplemethod aligns with the PR objectives of improving performance for bucket updates by enabling batch operations, which reduces redundant processing when multiple segments need updating.
39-50: Constructor changes align well with architecture improvements.The additional parameters (elementClass, mappingName, isReadOnly) support the performance enhancements mentioned in the PR objectives, particularly for enabling optimized segment index operations and appropriate fallback handling.
56-57: Good data structure change from List to Set.Changing the collection type to
Setfor bucket positions offers performance benefits for lookups and eliminates duplicates, which aligns with the PR's goal of performance optimization.
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MIGRATIONS.unreleased.md (1)
11-11: Fix Markdown Unordered List IndentationThe markdownlint tool reports an indentation issue on line 11. The unordered list item is indented by one space while the expected indentation is 0 spaces. Please remove the leading whitespace to comply with MD007.
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MIGRATIONS.unreleased.md (1)
11-12: Validate FossilDB Version Requirement UpdateThe migration guide now states that FossilDB version
0.1.37(noted asmaster__525:on dockerhub) is required, as per PR [#8460]. This change is clearly documented here. Please ensure this new requirement is reflected in all related configuration files and deployment scripts.🧰 Tools
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volumeBucketDataHasChangedis now set correctly againMeasurements
Steps to test:
TODOs:
Issues:
Follow-Up PR