* Remove `es-test-dir` book-scoped variable
* Remove `plugins-examples-dir` book-scoped variable
* Remove `:dependencies-dir:` and `:xes-repo-dir:` book-scoped variables
- In `index.asciidoc`, two variables (`:dependencies-dir:` and `:xes-repo-dir:`) were removed.
- In `sql/index.asciidoc`, the `:sql-tests:` path was updated to fuller path
- In `esql/index.asciidoc`, the `:esql-tests:` path was updated idem
* Replace `es-repo-dir` with `es-ref-dir`
* Move `:include-xpack: true` to few files that use it, remove from index.asciidoc
* Initial import for TDigest forking.
* Fix MedianTest.
More work needed for TDigestPercentile*Tests and the TDigestTest (and
the rest of the tests) in the tdigest lib to pass.
* Fix Dist.
* Fix AVLTreeDigest.quantile to match Dist for uniform centroids.
* Update docs/changelog/96086.yaml
* Fix `MergingDigest.quantile` to match `Dist` on uniform distribution.
* Add merging to TDigestState.hashCode and .equals.
Remove wrong asserts from tests and MergingDigest.
* Fix style violations for tdigest library.
* Fix typo.
* Fix more style violations.
* Fix more style violations.
* Fix remaining style violations in tdigest library.
* Update results in docs based on the forked tdigest.
* Fix YAML tests in aggs module.
* Fix YAML tests in x-pack/plugin.
* Skip failing V7 compat tests in modules/aggregations.
* Fix TDigest library unittests.
Remove redundant serializing interfaces from the library.
* Remove YAML test versions for older releases.
These tests don't address compatibility issues in mixed cluster tests as
the latter contain a mix of older and newer nodes, so the output depends
on which node is picked as a data node since the forked TDigest library
is not backwards compatible (produces slightly different results).
* Fix test failures in docs and mixed cluster.
* Reduce buffer sizes in MergingDigest to avoid oom.
* Exclude more failing V7 compatibility tests.
* Update results for JdbcCsvSpecIT tests.
* Update results for JdbcDocCsvSpecIT tests.
* Revert unrelated change.
* More test fixes.
* Use version skips instead of blacklisting in mixed cluster tests.
* Switch TDigestState back to AVLTreeDigest.
* Update docs and tests with AVLTreeDigest output.
* Update flaky test.
* Remove dead code, esp around tracking of incoming data.
* Update docs/changelog/96086.yaml
* Delete docs/changelog/96086.yaml
* Remove explicit compression calls.
This was added to prevent concurrency tests from failing, but it leads
to reduces precision. Submit this to see if the concurrency tests are
still failing.
* Revert "Remove explicit compression calls."
This reverts commit 5352c96f65.
* Remove explicit compression calls to MedianAbsoluteDeviation input.
* Add unittests for AVL and merging digest accuracy.
* Fix spotless violations.
* Delete redundant tests and benchmarks.
* Fix spotless violation.
* Use the old implementation of AVLTreeDigest.
The latest library version is 50% slower and less accurate, as verified
by ComparisonTests.
* Update docs with latest percentile results.
* Update docs with latest percentile results.
* Remove repeated compression calls.
* Update more percentile results.
* Use approximate percentile values in integration tests.
This helps with mixed cluster tests, where some of the tests where
blocked.
* Fix expected percentile value in test.
* Revert in-place node updates in AVL tree.
Update quantile calculations between centroids and min/max values to
match v.3.2.
* Add SortingDigest and HybridDigest.
The SortingDigest tracks all samples in an ArrayList that
gets sorted for quantile calculations. This approach
provides perfectly accurate results and is the most
efficient implementation for up to millions of samples,
at the cost of bloated memory footprint.
The HybridDigest uses a SortingDigest for small sample
populations, then switches to a MergingDigest. This
approach combines to the best performance and results for
small sample counts with very good performance and
acceptable accuracy for effectively unbounded sample
counts.
* Remove deps to the 3.2 library.
* Remove unused licenses for tdigest.
* Revert changes for SortingDigest and HybridDigest.
These will be submitted in a follow-up PR for enabling MergingDigest.
* Remove unused Histogram classes and unit tests.
Delete dead and commented out code, make the remaining tests run
reasonably fast. Remove unused annotations, esp. SuppressWarnings.
* Remove Comparison class, not used.
* Revert "Revert changes for SortingDigest and HybridDigest."
This reverts commit 2336b11598.
* Use HybridDigest as default tdigest implementation
Add SortingDigest as a simple structure for percentile calculations that
tracks all data points in a sorted array. This is a fast and perfectly
accurate solution that leads to bloated memory allocation.
Add HybridDigest that uses SortingDigest for small sample counts, then
switches to MergingDigest. This approach delivers extreme
performance and accuracy for small populations while scaling
indefinitely and maintaining acceptable performance and accuracy with
constant memory allocation (15kB by default).
Provide knobs to switch back to AVLTreeDigest, either per query or
through ClusterSettings.
* Small fixes.
* Add javadoc and tests.
* Add javadoc and tests.
* Remove special logic for singletons in the boundaries.
While this helps with the case where the digest contains only
singletons (perfect accuracy), it has a major issue problem
(non-monotonic quantile function) when the first singleton is followed
by a non-singleton centroid. It's preferable to revert to the old
version from 3.2; inaccuracies in a singleton-only digest should be
mitigated by using a sorted array for small sample counts.
* Revert changes to expected values in tests.
This is due to restoring quantile functions to match head.
* Revert changes to expected values in tests.
This is due to restoring quantile functions to match head.
* Tentatively restore percentile rank expected results.
* Use cdf version from 3.2
Update Dist.cdf to use interpolation, use the same cdf
version in AVLTreeDigest and MergingDigest.
* Revert "Tentatively restore percentile rank expected results."
This reverts commit 7718dbba59.
* Revert remaining changes compared to main.
* Revert excluded V7 compat tests.
* Exclude V7 compat tests still failing.
* Exclude V7 compat tests still failing.
* Remove ClusterSettings tentatively.
* Initial import for TDigest forking.
* Fix MedianTest.
More work needed for TDigestPercentile*Tests and the TDigestTest (and
the rest of the tests) in the tdigest lib to pass.
* Fix Dist.
* Fix AVLTreeDigest.quantile to match Dist for uniform centroids.
* Update docs/changelog/96086.yaml
* Fix `MergingDigest.quantile` to match `Dist` on uniform distribution.
* Add merging to TDigestState.hashCode and .equals.
Remove wrong asserts from tests and MergingDigest.
* Fix style violations for tdigest library.
* Fix typo.
* Fix more style violations.
* Fix more style violations.
* Fix remaining style violations in tdigest library.
* Update results in docs based on the forked tdigest.
* Fix YAML tests in aggs module.
* Fix YAML tests in x-pack/plugin.
* Skip failing V7 compat tests in modules/aggregations.
* Fix TDigest library unittests.
Remove redundant serializing interfaces from the library.
* Remove YAML test versions for older releases.
These tests don't address compatibility issues in mixed cluster tests as
the latter contain a mix of older and newer nodes, so the output depends
on which node is picked as a data node since the forked TDigest library
is not backwards compatible (produces slightly different results).
* Fix test failures in docs and mixed cluster.
* Reduce buffer sizes in MergingDigest to avoid oom.
* Exclude more failing V7 compatibility tests.
* Update results for JdbcCsvSpecIT tests.
* Update results for JdbcDocCsvSpecIT tests.
* Revert unrelated change.
* More test fixes.
* Use version skips instead of blacklisting in mixed cluster tests.
* Switch TDigestState back to AVLTreeDigest.
* Update docs and tests with AVLTreeDigest output.
* Update flaky test.
* Remove dead code, esp around tracking of incoming data.
* Remove explicit compression calls.
This was added to prevent concurrency tests from failing, but it leads
to reduces precision. Submit this to see if the concurrency tests are
still failing.
* Update docs/changelog/96086.yaml
* Delete docs/changelog/96086.yaml
* Revert "Remove explicit compression calls."
This reverts commit 5352c96f65.
* Remove explicit compression calls to MedianAbsoluteDeviation input.
* Add unittests for AVL and merging digest accuracy.
* Fix spotless violations.
* Delete redundant tests and benchmarks.
* Fix spotless violation.
* Use the old implementation of AVLTreeDigest.
The latest library version is 50% slower and less accurate, as verified
by ComparisonTests.
* Update docs with latest percentile results.
* Update docs with latest percentile results.
* Remove repeated compression calls.
* Update more percentile results.
* Use approximate percentile values in integration tests.
This helps with mixed cluster tests, where some of the tests where
blocked.
* Fix expected percentile value in test.
* Revert in-place node updates in AVL tree.
Update quantile calculations between centroids and min/max values to
match v.3.2.
* Add SortingDigest and HybridDigest.
The SortingDigest tracks all samples in an ArrayList that
gets sorted for quantile calculations. This approach
provides perfectly accurate results and is the most
efficient implementation for up to millions of samples,
at the cost of bloated memory footprint.
The HybridDigest uses a SortingDigest for small sample
populations, then switches to a MergingDigest. This
approach combines to the best performance and results for
small sample counts with very good performance and
acceptable accuracy for effectively unbounded sample
counts.
* Remove deps to the 3.2 library.
* Remove unused licenses for tdigest.
* Revert changes for SortingDigest and HybridDigest.
These will be submitted in a follow-up PR for enabling MergingDigest.
* Remove unused Histogram classes and unit tests.
Delete dead and commented out code, make the remaining tests run
reasonably fast. Remove unused annotations, esp. SuppressWarnings.
* Remove Comparison class, not used.
* Revert "Revert changes for SortingDigest and HybridDigest."
This reverts commit 2336b11598.
* Use HybridDigest as default tdigest implementation
Add SortingDigest as a simple structure for percentile calculations that
tracks all data points in a sorted array. This is a fast and perfectly
accurate solution that leads to bloated memory allocation.
Add HybridDigest that uses SortingDigest for small sample counts, then
switches to MergingDigest. This approach delivers extreme
performance and accuracy for small populations while scaling
indefinitely and maintaining acceptable performance and accuracy with
constant memory allocation (15kB by default).
Provide knobs to switch back to AVLTreeDigest, either per query or
through ClusterSettings.
* Add javadoc and tests.
* Remove ClusterSettings tentatively.
* Restore bySize function in TDigest and subclasses.
* Update Dist.cdf to match the rest.
Update tests.
* Revert outdated test changes.
* Revert outdated changes.
* Small fixes.
* Update docs/changelog/96794.yaml
* TDigestState uses MergingDigest by default.
* Make HybridDigest the default implementation.
* Update boxplot documentation.
* Use HybridDigest for real.
* Restore AVLTreeDigest as the default in TDigestState.
TDigest.createHybridDigest nw returns the right type.
The switch in TDigestState will happen in a separate PR
as it requires many test updates.
* Use execution_hint in tdigest spec.
* Restore expected test values.
* Fix Dist.cdf for empty digest.
* Bump up TransportVersion.
* More test updates.
* Bump up TransportVersion for real.
* Restore V7 compat blacklisting.
* HybridDigest uses its final implementation during deserialization.
* Restore the right TransportVersion in TDigestState.read
* More test fixes.
* More test updates.
* Use TDigestExecutionHint instead of strings.
* Add link to TDigest javadoc.
* Spotless fix.
* Small fixes.
* Bump up TransportVersion.
* Bump up the TransportVersion, again.
* Update docs/changelog/96904.yaml
* Delete 96794.yaml
Delete existing changelog to get a new one.
* Restore previous changelog.
* Rename 96794.yaml to 96794.yaml
* Update breaking change notes in changelog.
* Remove mapping value from changelog.
* Set a valid breaking area.
* Use HybridDigest as default TDigest impl.
* Update docs/changelog/96904.yaml
* Use TDigestExecutionHint in MedianAbsoluteDeviationAggregator.
* Update changelog and comment in blacklisted V7 compat tests.
* Update breaking area in changelog.
Removes `testenv` annotations and related code. These annotations originally let you skip x-pack snippet tests in the docs. However, that's no longer possible.
Relates to #79309, #31619
Related to issue #77823
This does the following:
- Updates several asciidoc files that contained code snippets with
invalid JSON, most involving unnecessary trailing commas.
- Makes the switch from the Groovy JSON parser to the Jackson parser,
pursuant to the general goal of eliminating Groovy dependence.
- Makes testing of JSON validity at build time more strict.
Note that this update still allows backslash escaping for any
character. Currently that matters because of the file
"docs/reference/ml/anomaly-detection/apis/get-datafeed-stats.asciidoc",
specifically this part:
"attributes" : {
"ml.machine_memory" :
"$body.datafeeds.0.node.attributes.ml\.machine_memory",
"ml.max_open_jobs" : "512"
}
It's not clear to me what change, if any, is appropriate there. So,
I've left in the escaped period and configured the parser to ignore
it for the time being.
This adds a new pipeline aggregation for calculating Kolmogorov–Smirnov test for a given sample and buckets path.
For now, the buckets path resolution needs to be `_count`. But, this may be relaxed in the future.
It accepts a parameter `fractions` that indicates the distribution of documents from some other pre-calculated sample.
This particular version of the K-S test is Two-sample, meaning, it calculates if the `fractions` and the distribution of `_count` values in the buckets_path are taken from the same distribution.
This in combination with the hypothesis alternatives (`less`, `greater`, `two_sided`) and sampling logic (`upper_tail`, `lower_tail`, `uniform`) allow for flexibility and usefulness when comparing two samples and determining the likelihood of them being from the same overall distribution.
Usage:
```
POST correlate_latency/_search?size=0&filter_path=aggregations
{
"aggs": {
"buckets": {
"terms": { <1>
"field": "version",
"size": 2
},
"aggs": {
"latency_ranges": {
"range": { <2>
"field": "latency",
"ranges": [
{ "to": 0.0 },
{ "from": 0, "to": 105 },
{ "from": 105, "to": 225 },
{ "from": 225, "to": 445 },
{ "from": 445, "to": 665 },
{ "from": 665, "to": 885 },
{ "from": 885, "to": 1115 },
{ "from": 1115, "to": 1335 },
{ "from": 1335, "to": 1555 },
{ "from": 1555, "to": 1775 },
{ "from": 1775 }
]
}
},
"ks_test": { <3>
"bucket_count_ks_test": {
"buckets_path": "latency_ranges>_count",
"alternative": ["less", "greater", "two_sided"]
}
}
}
}
}
}
```
This commit adds a new pipeline aggregation that allows correlation within the aggregation frame work in bucketed values.
The initial function is a `count_correlation` function. The purpose of which is to correlate the count in a consistent number of buckets with a pre calculated indicator. The indicator and the aggregated buckets should related to the same metrics with in documents.
Example for correlating terms within a `service.version.keyword` with latency percentiles. The percentiles and provided correlation indicator both refer to the same source data where the indicator was previously calculated.:
```
GET apm-7.12.0-transaction-generated/_search
{
"size": 0,
"aggs": {
"field_terms": {
"terms": {
"field": "service.version.keyword",
"size": 20
},
"aggs": {
"latency_range": {
"range": {
"field": "transaction.duration.us",
"ranges": [<snip>],
"keyed": true
}
},
"correlation": {
"bucket_correlation": {
"buckets_path": "latency_range>_count",
"count_correlation": {
"indicator": {
"expectations": [<snip>],
"doc_count": 20000
}
}
}
}
}
}
}
}
```
Moves the search sort docs from the deprecated 'Request Body Search'
page to a new subpage of 'Run a search'.
No substantive changes were made to the content.
Per 49554 I added standard deviation sampling and variance sampling to the extended stats interface.
Closes#49554
Co-authored-by: Igor Motov <igor@motovs.org>
This aggregation will perform normalizations of metrics
for a given series of data in the form of bucket values.
The aggregations supports the following normalizations
- rescale 0-1
- rescale 0-100
- percentage of sum
- mean normalization
- z-score normalization
- softmax normalization
To specify which normalization is to be used, it can be specified
in the normalize agg's `normalizer` field.
For example:
```
{
"normalize": {
"buckets_path": <>,
"normalizer": "percent"
}
}
```
Closes#51005.
Similar to what the moving function aggregation does, except merging windows of percentiles
sketches together instead of cumulatively merging final metrics
This adds a pipeline aggregation that calculates the cumulative
cardinality of a field. It does this by iteratively merging in the
HLL sketch from consecutive buckets and emitting the cardinality up
to that point.
This is useful for things like finding the total "new" users that have
visited a website (as opposed to "repeat" visitors).
This is a Basic+ aggregation and adds a new Data Science plugin
to house it and future advanced analytics/data science aggregations.
Introduce shift field to MovingFunction aggregation.
By default, shift = 0. Behavior, in this case, is the same as before.
Increasing shift by 1 moves starting window position by 1 to the right.
To simply include current bucket to the window, use shift = 1
For center alignment (n/2 values before and after the current bucket), use shift = window / 2
For right alignment (n values after the current bucket), use shift = window.
The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
