A new field called `inference_config` is now added to the trained model config object. This new field allows for default inference settings from analytics or some external model builder.
The inference processor can still override whatever is set as the default in the trained model config.
Secondary authorization headers are to be used to facilitate Kibana spaces support + ML jobs/datafeeds.
Now on PUT/Update/Preview datafeed, and PUT data frame analytics the secondary authorization is preferred over the primary (if provided).
closes https://github.com/elastic/elasticsearch/issues/53801
This adds two new fields to category definitions.
- `num_matches` indicating how many documents have been seen by this category
- `preferred_to_categories` indicating which other categories this particular category supersedes when messages are categorized.
These fields are only guaranteed to be up to date after a `_flush` or `_close`
native change: https://github.com/elastic/ml-cpp/pull/1062
This is a simple naming change PR, to fix the fact that "metadata" is a
single English word, and for too long we have not followed general
naming conventions for it. We are also not consistent about it, for
example, METADATA instead of META_DATA if we were trying to be
consistent with MetaData (although METADATA is correct when considered
in the context of "metadata"). This was a simple find and replace across
the code base, only taking a few minutes to fix this naming issue
forever.
It is possible for ML jobs to open lazily if the "allow_lazy_open"
option in the job config is set to true. Such jobs wait in the
"opening" state until a node has sufficient capacity to run them.
This commit fixes the bug that prevented datafeeds for jobs lazily
waiting assignment from being started. The state of such datafeeds
is "starting", and they can be stopped by the stop datafeed API
while in this state with or without force.
Fixes#53763
Adds a new parameter for classification that enables choosing whether to assign labels to
maximise accuracy or to maximise the minimum class recall.
Fixes#52427.
Adds a new `default_field_map` field to trained model config objects.
This allows the model creator to supply field map if it knows that there should be some map for inference to work directly against the training data.
The use case internally is having analytics jobs supply a field mapping for multi-field fields. This allows us to use the model "out of the box" on data where we trained on `foo.keyword` but the `_source` only references `foo`.
Adds reporting of memory usage for data frame analytics jobs.
This commit introduces a new index pattern `.ml-stats-*` whose
first concrete index will be `.ml-stats-000001`. This index serves
to store instrumentation information for those jobs.
This adds a new configurable field called `indices_options`. This allows users to create or update the indices_options used when a datafeed reads from an index.
This is necessary for the following use cases:
- Reading from frozen indices
- Allowing certain indices in multiple index patterns to not exist yet
These index options are available on datafeed creation and update. Users may specify them as URL parameters or within the configuration object.
closes https://github.com/elastic/elasticsearch/issues/48056
This change adds support for the following new model_size_stats
fields:
- categorized_doc_count
- total_category_count
- frequent_category_count
- rare_category_count
- dead_category_count
- categorization_status
Relates #50749
Changes the find_file_structure response to include a CSV
ingest processor in the ingest pipeline it suggests.
Previously the Kibana file upload functionality parsed CSV
in the browser, but by parsing CSV in the ingest pipeline
it makes the Kibana file upload functionality more easily
interchangable with Filebeat such that the configurations
it creates can more easily be used to import data with the
same structure repeatedly in production.
Adds a new URL parameter, `tags` to the GET _ml/inference/<model_id> endpoint.
This parameter allows the list of models to be further reduced to those who contain all the provided tags.
Object fields cannot be used as features. At the moment _explain
API includes them and even worse it allows it does not error when
an object field is excluded. This creates the expectation to the
user that all children fields will also be excluded while it's not
the case.
This commit omits object fields from the _explain API and also
adds an error if an object field is included or excluded.
Adds a new parameter to regression and classification that enables computation
of importance for the top most important features. The computation of the importance
is based on SHAP (SHapley Additive exPlanations) method.
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.
Closes#48124
The docs/reference/redirects.asciidoc file stores a list of relocated or
deleted pages for the Elasticsearch Reference documentation.
This prunes several older redirects that are no longer needed and
don't require work to fix broken links in other repositories.
Co-Authored-By: Przemysław Witek <przemyslaw.witek@elastic.co>
Co-Authored-By: David Roberts <dave.roberts@elastic.co>
Co-Authored-By: Ed Savage <32410745+edsavage@users.noreply.github.com>
This adds a new `randomize_seed` for regression and classification.
When not explicitly set, the seed is randomly generated. One can
reuse the seed in a similar job in order to ensure the same docs
are picked for training.
This adds a `_source` setting under the `source` setting of a data
frame analytics config. The new `_source` is reusing the structure
of a `FetchSourceContext` like `analyzed_fields` does. Specifying
includes and excludes for source allows selecting which fields
will get reindexed and will be available in the destination index.
Closes#49531
The categorization job wizard in the ML UI will use this
information when showing the effect of the chosen categorization
analyzer on a sample of input.
This commit replaces the _estimate_memory_usage API with
a new API, the _explain API.
The API consolidates information that is useful before
creating a data frame analytics job.
It includes:
- memory estimation
- field selection explanation
Memory estimation is moved here from what was previously
calculated in the _estimate_memory_usage API.
Field selection is a new feature that explains to the user
whether each available field was selected to be included or
not in the analysis. In the case it was not included, it also
explains the reason why.
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
Adds the following parameters to `outlier_detection`:
- `compute_feature_influence` (boolean): whether to compute or not
feature influence scores
- `outlier_fraction` (double): the proportion of the data set assumed
to be outlying prior to running outlier detection
- `standardization_enabled` (boolean): whether to apply standardization
to the feature values
* [DOCS] Adds examples to the PUT dfa and the evaluate dfa APIs.
* [DOCS] Removes extra lines from examples.
* Update docs/reference/ml/df-analytics/apis/evaluate-dfanalytics.asciidoc
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
* Update docs/reference/ml/df-analytics/apis/put-dfanalytics.asciidoc
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
* [DOCS] Explains examples.
* [DOCS] Adds regression analytics resources and examples to the data frame analytics APIs.
Co-Authored-By: Benjamin Trent <ben.w.trent@gmail.com>
Co-Authored-By: Tom Veasey <tveasey@users.noreply.github.com>
* [DOCS] Adds outlier detection params to the data frame analytics resources.
Co-Authored-By: Tom Veasey <tveasey@users.noreply.github.com>
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
Though we allow CCS within datafeeds, users could prevent nodes from accessing remote clusters. This can cause mysterious errors and difficult to troubleshoot.
This commit adds a check to verify that `cluster.remote.connect` is enabled on the current node when a datafeed is configured with a remote index pattern.
Previously, the stats API reports a progress percentage
for DF analytics tasks that are running and are in the
`reindexing` or `analyzing` state.
This means that when the task is `stopped` there is no progress
reported. Thus, one cannot distinguish between a task that never
run to one that completed.
In addition, there are blind spots in the progress reporting.
In particular, we do not account for when data is loaded into the
process. We also do not account for when results are written.
This commit addresses the above issues. It changes progress
to being a list of objects, each one describing the phase
and its progress as a percentage. We currently have 4 phases:
reindexing, loading_data, analyzing, writing_results.
When the task stops, progress is persisted as a document in the
state index. The stats API now reports progress from in-memory
if the task is running, or returns the persisted document
(if there is one).
This PR addresses the feedback in https://github.com/elastic/ml-team/issues/175#issuecomment-512215731.
* Adds an example to `analyzed_fields`
* Includes `source` and `dest` objects inline in the resource page
* Lists `model_memory_limit` in the PUT API page
* Amends the `analysis` section in the resource page
* Removes Properties headings in subsections
This PR adds the reference documentation pages of the data frame analytics APIs (PUT, START, STOP, GET, GET stats, DELETE, Evaluate) to the ML APIs pool.
The existing language was misleading about the model snapshots and where they are located. Saying "to disk" sounds like files external to Elasticsearch IMO. It raises the obvious question, where on disk? which node? Is it in the Elasticsearch snapshot repo? The model snapshots are held in an internal index.
The machine learning feature of xpack has native binaries with a
different commit id than the rest of code. It is currently exposed in
the xpack info api. This commit adds that commit information to the ML
info api, so that it may be removed from the info api.
* [ML] Adding support for geo_shape, geo_centroid, geo_point in datafeeds
* only supporting doc_values for geo_point fields
* moving validation into GeoPointField ctor
This change adds the earliest and latest timestamps into
the field stats for fields of type "date" in the output of
the ML find_file_structure endpoint. This will enable the
cards for date fields in the file data visualizer in the UI
to be made to look more similar to the cards for date
fields in the index data visualizer in the UI.
When analysing a semi-structured text file the
find_file_structure endpoint merges lines to form
multi-line messages using the assumption that the
first line in each message contains the timestamp.
However, if the timestamp is misdetected then this
can lead to excessive numbers of lines being merged
to form massive messages.
This commit adds a line_merge_size_limit setting
(default 10000 characters) that halts the analysis
if a message bigger than this is created. This
prevents significant CPU time being spent subsequently
trying to determine the internal structure of the
huge bogus messages.
This change contains a major refactoring of the timestamp
format determination code used by the ML find file structure
endpoint.
Previously timestamp format determination was done separately
for each piece of text supplied to the timestamp format finder.
This had the drawback that it was not possible to distinguish
dd/MM and MM/dd in the case where both numbers were 12 or less.
In order to do this sensibly it is best to look across all the
available timestamps and see if one of the numbers is greater
than 12 in any of them. This necessitates making the timestamp
format finder an instantiable class that can accumulate evidence
over time.
Another problem with the previous approach was that it was only
possible to override the timestamp format to one of a limited
set of timestamp formats. There was no way out if a file to be
analysed had a timestamp that was sane yet not in the supported
set. This is now changed to allow any timestamp format that can
be parsed by a combination of these Java date/time formats:
yy, yyyy, M, MM, MMM, MMMM, d, dd, EEE, EEEE, H, HH, h, mm, ss,
a, XX, XXX, zzz
Additionally S letter groups (fractional seconds) are supported
providing they occur after ss and separated from the ss by a dot,
comma or colon. Spacing and punctuation is also permitted with
the exception of the question mark, newline and carriage return
characters, together with literal text enclosed in single quotes.
The full list of changes/improvements in this refactor is:
- Make TimestampFormatFinder an instantiable class
- Overrides must be specified in Java date/time format - Joda
format is no longer accepted
- Joda timestamp formats in outputs are now derived from the
determined or overridden Java timestamp formats, not stored
separately
- Functionality for determining the "best" timestamp format in
a set of lines has been moved from TextLogFileStructureFinder
to TimestampFormatFinder, taking advantage of the fact that
TimestampFormatFinder is now an instantiable class with state
- The functionality to quickly rule out some possible Grok
patterns when looking for timestamp formats has been changed
from using simple regular expressions to the much faster
approach of using the Shift-And method of sub-string search,
but using an "alphabet" consisting of just 1 (representing any
digit) and 0 (representing non-digits)
- Timestamp format overrides are now much more flexible
- Timestamp format overrides that do not correspond to a built-in
Grok pattern are mapped to a %{CUSTOM_TIMESTAMP} Grok pattern
whose definition is included within the date processor in the
ingest pipeline
- Grok patterns that correspond to multiple Java date/time
patterns are now handled better - the Grok pattern is accepted
as matching broadly, and the required set of Java date/time
patterns is built up considering all observed samples
- As a result of the more flexible acceptance of Grok patterns,
when looking for the "best" timestamp in a set of lines
timestamps are considered different if they are preceded by
a different sequence of punctuation characters (to prevent
timestamps far into some lines being considered similar to
timestamps near the beginning of other lines)
- Out-of-the-box Grok patterns that are considered now include
%{DATE} and %{DATESTAMP}, which have indeterminate day/month
ordering
- The order of day/month in formats with indeterminate day/month
order is determined by considering all observed samples (plus
the server locale if the observed samples still do not suggest
an ordering)
Relates #38086Closes#35137Closes#35132
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.
Specifying an inline script in an "inline" field
was deprecated in 5.x. The new field name is
"source".
(Since 6.x still accepts "inline" I will only backport
this docs change as far as 7.0.)
This change does the following:
1. Makes the per-node setting xpack.ml.max_open_jobs
into a cluster-wide dynamic setting
2. Changes the job node selection to continue to use the
per-node attributes storing the maximum number of open
jobs if any node in the cluster is older than 7.1, and
use the dynamic cluster-wide setting if all nodes are on
7.1 or later
3. Changes the docs to reflect this
4. Changes the thread pools for native process communication
from fixed size to scaling, to support the dynamic nature
of xpack.ml.max_open_jobs
5. Renames the autodetect thread pool to the job comms
thread pool to make clear that it will be used for other
types of ML jobs (data frame analytics in particular)
Closes#29809
the get-ml-info API documentation tested that the
response show that ML's `upgrade_mode` was false.
For reasons that may be true due to other tests running in
parallel or not cleaning themselves up, this may not be
guaranteed. Since the actual value here is not of importance,
this commit relaxes the requirement that upgrade_mode be
static.
Now that ML configurations are stored in the .ml-config
index rather than in cluster state there is a possibility
that some users may try to add configurations directly to
the index. Allowing this creates a variety of problems
including possible data exflitration attacks (depending on
how security is set up), so this commit adds warnings
against allowing writes to the .ml-config index other than
via the ML APIs.
In 7.x Java timestamp formats are the default timestamp format and
there is no need to prefix them with "8". (The "8" prefix was used
in 6.7 to distinguish Java timestamp formats from Joda timestamp
formats.)
This change removes the "8" prefixes from timestamp formats in the
output of the ML file structure finder.
* ML: Add MlMetadata.upgrade_mode and API
* Adding tests
* Adding wait conditionals for the upgrade_mode call to return
* Adding tests
* adjusting format and tests
* Adjusting wait conditions for api return and msgs
* adjusting doc tests
* adding upgrade mode tests to black list
The ML file structure finder has always reported both Joda
and Java time format strings. This change makes the Java time
format strings the ones that are incorporated into mappings
and ingest pipeline definitions.
The BWC syntax of prepending "8" to these formats is used.
This will need to be removed once Java time format strings
become the default in Elasticsearch.
This commit also removes direct imports of Joda classes in the
structure finder unit tests. Instead the core Joda BWC class
is used.
* Default include_type_name to false for get and put mappings.
* Default include_type_name to false for get field mappings.
* Add a constant for the default include_type_name value.
* Default include_type_name to false for get and put index templates.
* Default include_type_name to false for create index.
* Update create index calls in REST documentation to use include_type_name=true.
* Some minor clean-ups around the get index API.
* In REST tests, use include_type_name=true by default for index creation.
* Make sure to use 'expression == false'.
* Clarify the different IndexTemplateMetaData toXContent methods.
* Fix FullClusterRestartIT#testSnapshotRestore.
* Fix the ml_anomalies_default_mappings test.
* Fix GetFieldMappingsResponseTests and GetIndexTemplateResponseTests.
We make sure to specify include_type_name=true during xContent parsing,
so we continue to test the legacy typed responses. XContent generation
for the typeless responses is currently only covered by REST tests,
but we will be adding unit test coverage for these as we implement
each typeless API in the Java HLRC.
This commit also refactors GetMappingsResponse to follow the same appraoch
as the other mappings-related responses, where we read include_type_name
out of the xContent params, instead of creating a second toXContent method.
This gives better consistency in the response parsing code.
* Fix more REST tests.
* Improve some wording in the create index documentation.
* Add a note about types removal in the create index docs.
* Fix SmokeTestMonitoringWithSecurityIT#testHTTPExporterWithSSL.
* Make sure to mention include_type_name in the REST docs for affected APIs.
* Make sure to use 'expression == false' in FullClusterRestartIT.
* Mention include_type_name in the REST templates docs.
* [ML] Job and datafeed mappings with index template (#32719)
Index mappings for the configuration documents
* [ML] Job config document CRUD operations (#32738)
* [ML] Datafeed config CRUD operations (#32854)
* [ML] Change JobManager to work with Job config in index (#33064)
* [ML] Change Datafeed actions to read config from the config index (#33273)
* [ML] Allocate jobs based on JobParams rather than cluster state config (#33994)
* [ML] Return missing job error when .ml-config is does not exist (#34177)
* [ML] Close job in index (#34217)
* [ML] Adjust finalize job action to work with documents (#34226)
* [ML] Job in index: Datafeed node selector (#34218)
* [ML] Job in Index: Stop and preview datafeed (#34605)
* [ML] Delete job document (#34595)
* [ML] Convert job data remover to work with index configs (#34532)
* [ML] Job in index: Get datafeed and job stats from index (#34645)
* [ML] Job in Index: Convert get calendar events to index docs (#34710)
* [ML] Job in index: delete filter action (#34642)
This changes the delete filter action to search
for jobs using the filter to be deleted in the index
rather than the cluster state.
* [ML] Job in Index: Enable integ tests (#34851)
Enables the ml integration tests excluding the rolling upgrade tests and a lot of fixes to
make the tests pass again.
* [ML] Reimplement established model memory (#35500)
This is the 7.0 implementation of a master node service to
keep track of the native process memory requirement of each ML
job with an associated native process.
The new ML memory tracker service works when the whole cluster
is upgraded to at least version 6.6. For mixed version clusters
the old mechanism of established model memory stored on the job
in cluster state was used. This means that the old (and complex)
code to keep established model memory up to date on the job object
has been removed in 7.0.
Forward port of #35263
* [ML] Need to wait for shards to replicate in distributed test (#35541)
Because the cluster was expanded from 1 node to 3 indices would
initially start off with 0 replicas. If the original node was
killed before auto-expansion to 1 replica was complete then
the test would fail because the indices would be unavailable.
* [ML] DelayedDataCheckConfig index mappings (#35646)
* [ML] JIndex: Restore finalize job action (#35939)
* [ML] Replace Version.CURRENT in streaming functions (#36118)
* [ML] Use 'anomaly-detector' in job config doc name (#36254)
* [ML] Job In Index: Migrate config from the clusterstate (#35834)
Migrate ML configuration from clusterstate to index for closed jobs
only once all nodes are v6.6.0 or higher
* [ML] Check groups against job Ids on update (#36317)
* [ML] Adapt to periodic persistent task refresh (#36633)
* [ML] Adapt to periodic persistent task refresh
If https://github.com/elastic/elasticsearch/pull/36069/files is
merged then the approach for reallocating ML persistent tasks
after refreshing job memory requirements can be simplified.
This change begins the simplification process.
* Remove AwaitsFix and implement TODO
* [ML] Default search size for configs
* Fix TooManyJobsIT.testMultipleNodes
Two problems:
1. Stack overflow during async iteration when lots of
jobs on same machine
2. Not effectively setting search size in all cases
* Use execute() instead of submit() in MlMemoryTracker
We don't need a Future to wait for completion
* [ML][TEST] Fix NPE in JobManagerTests
* [ML] JIindex: Limit the size of bulk migrations (#36481)
* [ML] Prevent updates and upgrade tests (#36649)
* [FEATURE][ML] Add cluster setting that enables/disables config migration (#36700)
This commit adds a cluster settings called `xpack.ml.enable_config_migration`.
The setting is `true` by default. When set to `false`, no config migration will
be attempted and non-migrated resources (e.g. jobs, datafeeds) will be able
to be updated normally.
Relates #32905
* [ML] Snapshot ml configs before migrating (#36645)
* [FEATURE][ML] Split in batches and migrate all jobs and datafeeds (#36716)
Relates #32905
* SQL: Fix translation of LIKE/RLIKE keywords (#36672)
* SQL: Fix translation of LIKE/RLIKE keywords
Refactor Like/RLike functions to simplify internals and improve query
translation when chained or within a script context.
Fix#36039Fix#36584
* Fixing line length for EnvironmentTests and RecoveryTests (#36657)
Relates #34884
* Add back one line removed by mistake regarding java version check and
COMPAT jvm parameter existence
* Do not resolve addresses in remote connection info (#36671)
The remote connection info API leads to resolving addresses of seed
nodes when invoked. This is problematic because if a hostname fails to
resolve, we would not display any remote connection info. Yet, a
hostname not resolving can happen across remote clusters, especially in
the modern world of cloud services with dynamically chaning
IPs. Instead, the remote connection info API should be providing the
configured seed nodes. This commit changes the remote connection info to
display the configured seed nodes, avoiding a hostname resolution. Note
that care was taken to preserve backwards compatibility with previous
versions that expect the remote connection info to serialize a transport
address instead of a string representing the hostname.
* [Painless] Add boxed type to boxed type casts for method/return (#36571)
This adds implicit boxed type to boxed types casts for non-def types to create asymmetric casting relative to the def type when calling methods or returning values. This means that a user calling a method taking an Integer can call it with a Byte, Short, etc. legally which matches the way def works. This creates consistency in the casting model that did not previously exist.
* SNAPSHOTS: Adjust BwC Versions in Restore Logic (#36718)
* Re-enables bwc tests with adjusted version conditions now that #36397 enables concurrent snapshots in 6.6+
* ingest: fix on_failure with Drop processor (#36686)
This commit allows a document to be dropped when a Drop processor
is used in the on_failure fork of the processor chain.
Fixes#36151
* Initialize startup `CcrRepositories` (#36730)
Currently, the CcrRepositoryManger only listens for settings updates
and installs new repositories. It does not install the repositories that
are in the initial settings. This commit, modifies the manager to
install the initial repositories. Additionally, it modifies the ccr
integration test to configure the remote leader node at startup, instead
of using a settings update.
* [TEST] fix float comparison in RandomObjects#getExpectedParsedValue
This commit fixes a test bug introduced with #36597. This caused some
test failure as stored field values comparisons would not work when CBOR
xcontent type was used.
Closes#29080
* [Geo] Integrate Lucene's LatLonShape (BKD Backed GeoShapes) as default `geo_shape` indexing approach (#35320)
This commit exposes lucene's LatLonShape field as the
default type in GeoShapeFieldMapper. To use the new
indexing approach, simply set "type" : "geo_shape" in
the mappings without setting any of the strategy, precision,
tree_levels, or distance_error_pct parameters. Note the
following when using the new indexing approach:
* geo_shape query does not support querying by
MULTIPOINT.
* LINESTRING and MULTILINESTRING queries do not
yet support WITHIN relation.
* CONTAINS relation is not yet supported.
The tree, precision, tree_levels, distance_error_pct,
and points_only parameters are deprecated.
* TESTS:Debug Log. IndexStatsIT#testFilterCacheStats
* ingest: support default pipelines + bulk upserts (#36618)
This commit adds support to enable bulk upserts to use an index's
default pipeline. Bulk upsert, doc_as_upsert, and script_as_upsert
are all supported.
However, bulk script_as_upsert has slightly surprising behavior since
the pipeline is executed _before_ the script is evaluated. This means
that the pipeline only has access the data found in the upsert field
of the script_as_upsert. The non-bulk script_as_upsert (existing behavior)
runs the pipeline _after_ the script is executed. This commit
does _not_ attempt to consolidate the bulk and non-bulk behavior for
script_as_upsert.
This commit also adds additional testing for the non-bulk behavior,
which remains unchanged with this commit.
fixes#36219
* Fix duplicate phrase in shrink/split error message (#36734)
This commit removes a duplicate "must be a" from the shrink/split error
messages.
* Deprecate types in get_source and exist_source (#36426)
This change adds a new untyped endpoint `{index}/_source/{id}` for both the
GET and the HEAD methods to get the source of a document or check for its
existance. It also adds deprecation warnings to RestGetSourceAction that emit
a warning when the old deprecated "type" parameter is still used. Also updating
documentation and tests where appropriate.
Relates to #35190
* Revert "[Geo] Integrate Lucene's LatLonShape (BKD Backed GeoShapes) as default `geo_shape` indexing approach (#35320)"
This reverts commit 5bc7822562.
* Enhance Invalidate Token API (#35388)
This change:
- Adds functionality to invalidate all (refresh+access) tokens for all users of a realm
- Adds functionality to invalidate all (refresh+access)tokens for a user in all realms
- Adds functionality to invalidate all (refresh+access) tokens for a user in a specific realm
- Changes the response format for the invalidate token API to contain information about the
number of the invalidated tokens and possible errors that were encountered.
- Updates the API Documentation
After back-porting to 6.x, the `created` field will be removed from master as a field in the
response
Resolves: #35115
Relates: #34556
* Add raw sort values to SearchSortValues transport serialization (#36617)
In order for CCS alternate execution mode (see #32125) to be able to do the final reduction step on the CCS coordinating node, we need to serialize additional info in the transport layer as part of each `SearchHit`. Sort values are already present but they are formatted according to the provided `DocValueFormat` provided. The CCS node needs to be able to reconstruct the lucene `FieldDoc` to include in the `TopFieldDocs` and `CollapseTopFieldDocs` which will feed the `mergeTopDocs` method used to reduce multiple search responses (one per cluster) into one.
This commit adds such information to the `SearchSortValues` and exposes it through a new getter method added to `SearchHit` for retrieval. This info is only serialized at transport and never printed out at REST.
* Watcher: Ensure all internal search requests count hits (#36697)
In previous commits only the stored toXContent version of a search
request was using the old format. However an executed search request was
already disabling hit counts. In 7.0 hit counts will stay enabled by
default to allow for proper migration.
Closes#36177
* [TEST] Ensure shard follow tasks have really stopped.
Relates to #36696
* Ensure MapperService#getAllMetaFields elements order is deterministic (#36739)
MapperService#getAllMetaFields returns an array, which is created out of
an `ObjectHashSet`. Such set does not guarantee deterministic hash
ordering. The array returned by its toArray may be sorted differently
at each run. This caused some repeatability issues in our tests (see #29080)
as we pick random fields from the array of possible metadata fields,
but that won't be repeatable if the input array is sorted differently at
every run. Once setting the tests seed, hppc picks that up and the sorting is
deterministic, but failures don't repeat with the seed that gets printed out
originally (as a seed was not originally set).
See also https://issues.carrot2.org/projects/HPPC/issues/HPPC-173.
With this commit, we simply create a static sorted array that is used for
`getAllMetaFields`. The change is in production code but really affects
only testing as the only production usage of this method was to iterate
through all values when parsing fields in the high-level REST client code.
Anyways, this seems like a good change as returning an array would imply
that it's deterministically sorted.
* Expose Sequence Number based Optimistic Concurrency Control in the rest layer (#36721)
Relates #36148
Relates #10708
* [ML] Mute MlDistributedFailureIT
This endpoint was not previously documented as it was not
particularly useful to end users. However, since the HLRC
will support the endpoint we need some documentation to
link to.
The purpose of the endpoint is to provide defaults and
limits used by ML. These are needed to fully understand
configurations that have missing values because the missing
value means the default should be used.
Relates #35777
* ML: Adding missing datacheck to datafeedjob
* Adding client side and docs
* Making adjustments to validations
* Making values default to on, having more sensible limits
* Intermittent commit, still need to figure out interval
* Adjusting delayed data check interval
* updating docs
* Making parameter Boolean, so it is nullable
* bumping bwc to 7 before backport
* changing to version current
* moving delayed data check config its own object
* Separation of duties for delayed data detection
* fixing checkstyles
* fixing checkstyles
* Adjusting default behavior so that null windows are allowed
* Mentioning the default value
* Fixing comments, syncing up validations
The file structure finder endpoint can find the NDJSON
(newline-delimited JSON) file format, but called it
`json`. This change renames the `format` for this file
structure to `ndjson`, which is more precise and will
hopefully avoid confusion.
* Replace custom type names with _doc in REST examples.
* Avoid using two mapping types in the percolator docs.
* Rename doc -> _doc in the main repository README.
* Also replace some custom type names in the HLRC docs.
This commit moves the definition of domainSplit into java and exposes it
as a painless whitelist extension. The method also no longer needs
params, and version which ignores params is added and deprecated.
The ingest pipeline that is produced is very simple. It
contains a grok processor if the format is semi-structured
text, a date processor if the format contains a timestamp,
and a remove processor if required to remove the interim
timestamp field parsed out of semi-structured text.
Eventually the UI should offer the option to customize the
pipeline with additional processors to perform other data
preparation steps before ingesting data to an index.
This changes the delete job API by adding
the choice to delete a job asynchronously.
The commit adds a `wait_for_completion` parameter
to the delete job request. When set to `false`,
the action returns immediately and the response
contains the task id.
This also changes the handling of subsequent
delete requests for a job that is already being
deleted. It now uses the task framework to check
if the job is being deleted instead of the cluster
state. This is a beneficial for it is going to also
be working once the job configs are moved out of the
cluster state and into an index. Also, force delete
requests that are waiting for the job to be deleted
will not proceed with the deletion if the first task
fails. This will prevent overloading the cluster. Instead,
the failure is communicated better via notifications
so that the user may retry.
Finally, this makes the `deleting` property of the job
visible (also it was renamed from `deleted`). This allows
a client to render a deleting job differently.
Closes#32836
This change fixes a potential deadlock problem in the unit
test introduced in #34117.
It also removes a piece of debug code and corrects a docs
formatting problem that were both added in that same PR.
This can be used to restrict the amount of CPU a single
structure finder request can use.
The timeout is not implemented precisely, so requests
may run for slightly longer than the timeout before
aborting.
The default is 25 seconds, which is a little below
Kibana's default timeout of 30 seconds for calls to
Elasticsearch APIs.
Previously the timestamp_formats field in the response
from the find_file_structure endpoint contained Joda
timestamp formats. This change makes that clear by
renaming the field to joda_timestamp_formats, and also
adds a java_timestamp_formats field containing the
equivalent Java time format strings.
Previously numeric values in the field_stats created by the
find_file_structure endpoint were always output with a
decimal point. This looked unfriendly and unnatural for
fields that clearly store integer values. This change
converts integer values to type Integer before output in
the file structure field stats.
Lisa Cawley
István Zoltán Szabó
Benjamin Trent
Jason Tedor
Dimitris Athanasiou
David Roberts
Tom Veasey
David Kyle
Darren LaCasse
Przemysław Witek
James Rodewig
Orhan Toy
Matthew Adams
Ryan Ernst
Zachary Tong
Russ Cam
Tal Levy
Alexander Reelsen
Christoph Büscher
Julie Tibshirani
Ed Savage
Kazuhiro Sera