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[[release-notes-8.0.0-alpha1]]
== {es} version 8.0.0-alpha1
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coming[8.0.0]
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The changes listed below have been released for the first time in {es}
8.0.0-alpha1.
2020-02-26 20:40:33 +08:00
[[breaking-8.0.0-alpha1]]
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[discrete]
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=== Breaking changes
Aggregations::
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* Disallow specifying the same percentile multiple times in percentiles aggregation {es-pull}52257[#52257]
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2020-02-27 18:52:27 +08:00
Mapping::
* Dynamic mappings in indices created on 8.0 and later have stricter validation at mapping update time.
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(e.g. incorrect analyzer settings or unknown field types). {es-pull}51233[#51233]
2020-02-27 18:52:27 +08:00
2020-07-16 03:06:47 +08:00
Update by query::
* Unsupported fields provided as part of the script section of the update by query API are now rejected.
2020-04-15 03:36:57 +08:00
Deprecations::
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* Remove undocumented endpoints of hot threads API {es-pull}55109[#55109]
2020-04-15 03:36:57 +08:00
2020-06-04 19:33:28 +08:00
Slow loggers::
* `index.indexing.slowlog.level` and `index.search.slowlog.level` are removed. These settings can be worked around
by using appropriate thresholds. If for instance we want to simulate `index.indexing.slowlog.level` = `INFO` then
all we need to do is to set `index.indexing.slowlog.threshold.index.debug` and
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`index.indexing.slowlog.threshold.index.trace` to `-1` {es-pull}57591[#57591]
2020-06-04 19:33:28 +08:00
2020-12-02 01:49:50 +08:00
Search::
* Consistent treatment of numeric values for range query on date fields without `format` {es-pull}[#63692]
2020-06-16 04:26:30 +08:00
2021-07-27 04:22:11 +08:00
[[enhancement-8.0.0-alpha1]]
[float]
=== Enhancements
Machine learning::
* The Windows build platform for the {ml} C++ code now uses Visual Studio 2019 {ml-pull}1352[#1352]
* The macOS build platform for the {ml} C++ code is now Mojave running Xcode 11.3.1,
or Ubuntu 20.04 running clang 8 for cross compilation {ml-pull}1429[#1429]
* The Linux build platform for the {ml} C++ code is now CentOS 7 running gcc 9.3 {ml-pull}1170[#1170]
* Add a new application for evaluating PyTorch models. The app depends on LibTorch - the C++ front end to PyTorch and performs inference on models stored in the TorchScript format {ml-pull}1902[#1902]