Releases: filodb/FiloDB
Releases · filodb/FiloDB
v0.9.17.2 Release
Features
- [TSDB] Support for present_over_time , group and sgn functions PromQL function.
- [TSDB] Support to enable partial results for metadata queries. This fixes all or nothing scenarios for metadata queries where incomplete results are acceptable over no results. Responds with HTTP code 206 instead of 200 when results are partial.
- [TSDB] Performant Host Monitoring let us define “target-schemas” allows performant querying by colocating frequently joined data. More details on this feature to come soon in a blog post.
- [TSDB] Support subqueries in FILODB.
- [TSDB] Support for simple OR regex on shared label values:
- sum(
container_memory_working_set_bytes{
ws="aci-kubernetes",
ns="us-east-1a",
exported_namespace=~"(kube-namespace-1|kube-namespace-2)"
}
)
- sum(
Bug Fixes
- [TSDB] SinglePartitionPlanner bug preventing joins on raw and recording rules.
- [TSDB] InternalError shard(s?) should have dropped into "error" state and been reassigned
- [TSDB] Label-values query with !~ regex filters out too many results
- [TSDB] Compliance in behavior with Prometheus when != is used with a non existent label.
- [TSDB] Check for query timeouts in long-lived aggregations and joins so expensive queries are stopped in time.
- [TSDB] Fix metadata query routing when a regex filter is/isn’t given in the query.
- [TSDB] Make label-names api PromQL-compatible.
- [TSDB] Fix inconsistent results when binary joins operate on data both older and newer than now-7d.
- [TSDB] Failed Index lookup caused by large regex. Label regex now capped to 1 KB.
Performance enhancements
- [TSDB] Added support for stateful sets in FiloDB enabling faster shard recovery times by using block storage for index storage over container local storage.
- [TSDB] Label values query performance has been improved significantly with Lucene faceting. At high load, shard level latency for this query decreased from 5s to 16ms (300x).
- [TSDB] More performant label-values queries: queries for workspace and/or namespace values will now always bypass the storage engine when filters include only workspace and/or namespace labels.
- [TSDB] Optimization of binary joins by reducing data export when queried time range is beyond recent 7d.
- [TSDB] Track and log query stats for expensive queries. Future releases will enforce strict limits and block queries that scan/export large volume of data
v0.9.15.3 Release
perf(core): Increase default token scan split to 20 (#1280)
v0.9.12.2 Release
Release 0.9.12.2
v0.9.11 Release
Merge Integration to Main 0.9.11
v0.9.10 Release
Merge branch 'integration' into main 0.9.10
v0.9.9 Release
Release 0.9.9
v0.9.8 Release
Release 0.9.8
v0.9.7 release
Release Notes
New features / Enhancements
- Support
__name__
in group by, without, on and ignoring [PR 711] - Apply data size restrictions per query to ensure very large queries don’t destabilize TSDB [PR 748]
Reliability Improvements
- Add utility method to verify histogram column [PR 731]
- Utility to convert ColumnFilters in LogicalPlan [PR 751]
- Timeout query immediately if it stayed in actor mailbox for too long [PR 761]
Bug Fixes
- Fix premature memory reclamation when data is fetched from Cassandra, which can sometimes cause incorrect query results when memory is saturated (various PRs)
- Queries requiring full paging of data from Cassandra sometimes returned incomplete results [PR 774]
- Addressed long lookback queries returning incomplete results [PR 743]
v0.9.5 Release
Merge integration to master for 0.9.5
v0.9.3 Release - Major MultiSchema Features
- MultiSchema support. Each metric will now have a type: counter, gauge, histogram, or summary. Types are used for optimizing downsampling and queries, and optimizing storage for histograms. Metadata queries will return a new type label describing the time series type, and filtering by metric type is possible. Type is auto-detected in the open source gateway when using Telegraf as input source.
- Support for first class histograms: transports and stores histogram buckets as a single entity and time series, rather than a separate time series for each bucket. Leads to huge savings for storage as well as Kafka. See the README notes about First-Class Histograms for more details on query changes.
- Many PromQL functions added, including predict_linear, stddev, stdvar, and others
- More efficient index and chunk persistence and querying to/from Cassandra
Due to changes in the format of keys, indices and other tables in Cassandra, this new release will not be able to read from older Cassandra tables and truncation or deploy to new environment will be necessary.