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Merged
merged 9 commits into from
Mar 4, 2020
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[DOCS] Add 7.6.1. release notes #52874

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cca1b92
[DOCS] Add 7.6.1. release notes
ywelsch Feb 27, 2020
135f983
[DOCS] Adds link to release notes
lcawl Feb 27, 2020
47390d5
[DOCS] Fixes broken links to ml-cpp issues
lcawl Feb 27, 2020
8e30aed
Remove PR that was closed but not merged
ywelsch Feb 28, 2020
0c04b54
Remove closed but unmerged PR
ywelsch Feb 28, 2020
3491129
Cosmetic changes
ywelsch Feb 28, 2020
28e6339
Remove closed but unmerged PR
ywelsch Feb 28, 2020
796ac4e
remove closed but unmerged PR
ywelsch Feb 28, 2020
678ad77
Remove coming tag
jrodewig Mar 4, 2020
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1 change: 1 addition & 0 deletions docs/reference/release-notes.asciidoc
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Expand Up @@ -6,6 +6,7 @@

This section summarizes the changes in each release.

* <<release-notes-7.6.1>>
* <<release-notes-7.6.0>>
* <<release-notes-7.5.2>>
* <<release-notes-7.5.1>>
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95 changes: 87 additions & 8 deletions docs/reference/release-notes/7.6.asciidoc
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[[release-notes-7.6.1]]
== {es} version 7.6.1

coming[7.6.1]
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Can we remove coming[7.6.1] before merging this today?

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Removed with 678ad77.


Also see <<breaking-changes-7.6,Breaking changes in 7.6>>.

[[bug-7.6.1]]
[float]
=== Bug fixes

Aggregations::
* Decode max and min optimization more carefully {pull}52336[#52336] (issue: {issue}52220[#52220])
* Fix a DST error in date_histogram {pull}52016[#52016] (issue: {issue}50265[#50265])

Audit::
* Logfile audit settings validation {pull}52537[#52537] (issues: {issue}47038[#47038], {issue}47711[#47711], {issue}52357[#52357])

CCR::
* Fix shard follow task cleaner under security {pull}52347[#52347] (issues: {issue}44702[#44702], {issue}51971[#51971])

Distributed::
* Adjust global checkpoint background sync condition {pull}52444[#52444] (issue: {issue}52223[#52223])

Engine::
* Refresh should not fail already closed engine {pull}51281[#51281] (issue: {issue}48414[#48414])

Features/CAT APIs::
* fix npe in RestPluginsAction {pull}52620[#52620] (issue: {issue}45321[#45321])

Features/ILM+SLM::
* ILM fix the init step to actually be retryable {pull}52076[#52076]

Features/Ingest::
* Handle errors when evaluating if conditions in processors {pull}52543[#52543] (issue: {issue}52339[#52339])

Features/Monitoring::
* Fix NPE in cluster state collector for monitoring {pull}52371[#52371] (issue: {issue}52317[#52317])

Features/Stats::
* Switch to AtomicLong for "IngestCurrent" metric to prevent negative values {pull}52581[#52581] (issues: {issue}52406[#52406], {issue}52411[#52411])

Infra/Packaging::
* Limit _FILE env var support to specific vars {pull}52525[#52525] (issue: {issue}52503[#52503])

Machine Learning::
* Don't return inflated definition when storing trained models {pull}52573[#52573]
* Validate tree feature index is within range {pull}52460[#52460]

Network::
* Remove seeds dependency for remote cluster settings {pull}52796[#52796]

Reindex::
* Reindex: allow comma separated source indices {pull}52044[#52044] (issue: {issue}51949[#51949])

SQL::
* SQL: supplement input checks on received request parameters {pull}52229[#52229]
* SQL: Fix issue with timezone when paginating {pull}52101[#52101] (issue: {issue}51258[#51258])
* SQL: Fix issue with timezone for JDBC pagination {pull}52080[#52080] (issue: {issue}51258[#51258])
* SQL: Add string to interval converters {pull}51945[#51945] (issue: {issue}45915[#45915])
* SQL: Fix ORDER BY on aggregates and GROUPed BY fields {pull}51894[#51894] (issue: {issue}50355[#50355])
* SQL: Fix milliseconds handling in intervals {pull}51675[#51675] (issue: {issue}41635[#41635])
* SQL: selecting a literal from grouped by query generates error {pull}41964[#41964] (issues: {issue}41413[#41413], {issue}41951[#41951])

Snapshot/Restore::
* Fix Non-Verbose Snapshot List Missing Empty Snapshots {pull}52433[#52433]

Store::
* Fix synchronization in ByteSizeCachingDirectory {pull}52512[#52512]



[[upgrade-7.6.1]]
[float]
=== Upgrades

Authentication::
* Update oauth2-oidc-sdk to 7.0 {pull}52489[#52489] (issue: {issue}48409[#48409])

[[release-notes-7.6.0]]
== {es} version 7.6.0

Expand Down Expand Up @@ -77,7 +156,7 @@ Machine Learning::
* Explain data frame analytics API {pull}49455[#49455]
* Machine learning model inference ingest processor {pull}49052[#49052]
* Implement accuracy metric for multi-class classification {pull}47772[#47772] (issue: {issue}48759[#48759])
* Add feature importance values to classification and regression results (using tree
* Add feature importance values to classification and regression results (using tree
SHapley Additive exPlanation, or SHAP) {ml-pull}857[#857]

Mapping::
Expand Down Expand Up @@ -241,23 +320,23 @@ Machine Learning::
estimating maximum memory usage {ml-pull}781[#781]
* Stratified fractional cross validation for regression {ml-pull}784[#784]
* Added `geo_point` supported output for `lat_long` function records {ml-pull}809[#809], {pull}47050[#47050]
* Use a random bag of the data to compute the loss function derivatives for each
* Use a random bag of the data to compute the loss function derivatives for each
new tree which is trained for both regression and classification {ml-pull}811[#811]
* Emit `prediction_probability` field alongside prediction field in ml results {ml-pull}818[#818]
* Reduce memory usage of {ml} native processes on Windows {ml-pull}844[#844]
* Reduce runtime of classification and regression {ml-pull}863[#863]
* Stop early training a classification and regression forest when the validation
* Stop early training a classification and regression forest when the validation
error is no longer decreasing {ml-pull}875[#875]
* Emit `prediction_field_name` in data frame analytics results using the type
* Emit `prediction_field_name` in data frame analytics results using the type
provided as `prediction_field_type` parameter {ml-pull}877[#877]
* Improve performance updating quantile estimates {ml-pull}881[#881]
* Migrate to use Bayesian optimisation for initial hyperparameter value line
* Migrate to use Bayesian optimisation for initial hyperparameter value line
searches and stop early if the expected improvement is too small {ml-pull}903[#903]
* Stop cross-validation early if the predicted test loss has a small chance of
* Stop cross-validation early if the predicted test loss has a small chance of
being smaller than for the best parameter values found so far {ml-pull}915[#915]
* Optimize decision threshold for classification to maximize minimum class recall {ml-pull}926[#926]
* Include categorization memory usage in the `model_bytes` field in
`model_size_stats`, so that it is taken into account in node assignment
* Include categorization memory usage in the `model_bytes` field in
`model_size_stats`, so that it is taken into account in node assignment
decisions {ml-pull}927[#927] (issue:{ml-issue}724[#724])

Mapping::
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