* [ML] changing to not use global bulk indexing parameters in conjunction with add(object) calls (#62694)
* [ML] changing to not use global bulk indexing parameters in conjunction with add(object) calls
global parameters, outside of the global index, are ignored for internal callers in certain cases.
If the interal caller is adding requests via the following methods:
```
- BulkRequest#add(IndexRequest)
- BulkRequest#add(UpdateRequest)
- BulkRequest#add(DocWriteRequest)
- BulkRequest#add(DocWriteRequest[])
```
It is better to specifically set the desired parameters on the requests before they are added
to the bulk request object.
This commit addresses this issue for the ML plugin
* unmuting test
This allows the `check-migration` step to move past the allocation check
if the tier routing settings are manually unset.
This helps a user unblock ILM in case a tier is removed (ie. if the warm tier
is decommissioned this will allow users to resume the ILM policies stuck in
`check-migration` waiting for the warm nodes to become available and the managed
index to allocate. this allows the index to allocate on the other available tiers)
(cherry picked from commit d7a1eaa7f51d0972d10c0df1d3cd77d6b755dd41)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This commit adds the `index.routing.allocation.prefer._tier` setting to the
`DataTierAllocationDecider`. This special-purpose allocation setting lets a user specify a
preference-based list of tiers for an index to be assigned to. For example, if the setting were set
to:
```
"index.routing.allocation.prefer._tier": "data_hot,data_warm,data_content"
```
If the cluster contains any nodes with the `data_hot` role, the decider will only allow them to be
allocated on the `data_hot` node(s). If there are no `data_hot` nodes, but there are `data_warm` and
`data_content` nodes, then the index will be allowed to be allocated on `data_warm` nodes.
This allows us to specify an index's preference for tier(s) without causing the index to be
unassigned if no nodes of a preferred tier are available.
Subsequent work will change the ILM migration to make additional use of this setting.
Relates to #60848
This commit adjusts the following APIs so now they not only support an `_all` case, but wildcard patterned Ids as well.
- `GET _ml/calendars/<calendar_id>/events`
- `GET _ml/calendars/<calendar_id>`
- `GET _ml/anomaly_detectors/<job_id>/model_snapshots/<snapshot_id>`
- `DELETE _ml/anomaly_detectors/<job_id>/_forecast/<forecast_id>`
* [ML] Add new include flag to GET inference/<model_id> API for model training metadata (#61922)
Adds new flag include to the get trained models API
The flag initially has two valid values: definition, total_feature_importance.
Consequently, the old include_model_definition flag is now deprecated.
When total_feature_importance is included, the total_feature_importance field is included in the model metadata object.
Including definition is the same as previously setting include_model_definition=true.
* fixing test
* Update x-pack/plugin/core/src/test/java/org/elasticsearch/xpack/core/ml/action/GetTrainedModelsRequestTests.java
Removes methods that were no longer used regarding version 5.4 doc ids of ModelState.
Also adds clean up of 5.4 model state and quantile docs in the daily maintenance.
Backport of #62434
Faster sequential access for stored fields
Spinoff of #61806
Today retrieving stored fields at search time is optimized for random access.
So we make no effort to keep state in order to not decompress the same data
multiple times because two documents might be in the same compressed block.
This strategy is acceptable when retrieving a top N sorted by score since
there is no guarantee that documents will be on the same block.
However, we have some use cases where the document to retrieve might be
completely sequential:
Scrolls or normal search sorted by document id.
Queries on Runtime fields that extract from _source.
This commit exposes a sequential stored fields reader in the
custom leaf reader that we use at search time.
That allows to leverage the merge instances of stored fields readers that
are optimized for sequential access.
This change focuses on the fetch phase for now and leverages the merge instances
for stored fields only if all documents to retrieve are adjacent.
Applying the same logic in the source lookup of runtime fields should
be trivial but will be done in a follow up.
The speedup on queries sorted by doc id is significant.
I played with the scroll task of the http_logs rally track
on my laptop and had the following result:
| Metric | Task | Baseline | Contender | Diff | Unit |
|--------------------------------------------------------------:|-------:|------------:|------------:|---------:|--------:|
| Total Young Gen GC | | 0.199 | 0.231 | 0.032 | s |
| Total Old Gen GC | | 0 | 0 | 0 | s |
| Store size | | 17.9704 | 17.9704 | 0 | GB |
| Translog size | | 2.04891e-06 | 2.04891e-06 | 0 | GB |
| Heap used for segments | | 0.820332 | 0.820332 | 0 | MB |
| Heap used for doc values | | 0.113979 | 0.113979 | 0 | MB |
| Heap used for terms | | 0.37973 | 0.37973 | 0 | MB |
| Heap used for norms | | 0.03302 | 0.03302 | 0 | MB |
| Heap used for points | | 0 | 0 | 0 | MB |
| Heap used for stored fields | | 0.293602 | 0.293602 | 0 | MB |
| Segment count | | 541 | 541 | 0 | |
| Min Throughput | scroll | 12.7872 | 12.8747 | 0.08758 | pages/s |
| Median Throughput | scroll | 12.9679 | 13.0556 | 0.08776 | pages/s |
| Max Throughput | scroll | 13.4001 | 13.5705 | 0.17046 | pages/s |
| 50th percentile latency | scroll | 524.966 | 251.396 | -273.57 | ms |
| 90th percentile latency | scroll | 577.593 | 271.066 | -306.527 | ms |
| 100th percentile latency | scroll | 664.73 | 272.734 | -391.997 | ms |
| 50th percentile service time | scroll | 522.387 | 248.776 | -273.612 | ms |
| 90th percentile service time | scroll | 573.118 | 267.79 | -305.328 | ms |
| 100th percentile service time | scroll | 660.642 | 268.963 | -391.678 | ms |
| error rate | scroll | 0 | 0 | 0 | % |
Closes#62024
The data frame structure in c++ has a limit on 2^32 documents. This commit
adds a check that the number of documents involved in the analysis are
less than that and fails to start otherwise. That saves the cost of
reindexing when it is unnecessary.
Backport of #62547
This adds ILM support for automatically migrating the managed
indices between data tiers.
This proposal makes use of a MigrateAction that is injected
(similar to how the Unfollow action is injected) in phases that
don't define index allocation rules using the AllocateAction or
don't explicitly define the MigrateAction itself (regardless if it's
enabled or disabled).
(cherry picked from commit c1746afffd61048d0c12d3a77e6d8191a804ed49)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
ReplaceDataStreamBackingIndexStep#performAction seems to perform an equality
check on an original Index and the write indexes names, but because this
compares an Index instance to a String, the condition can never be met. This PR
changes this comparison.
Since #61857 we test using BCJSSE (Bouncy Castle SSL) when running on
Zulu8 because Azul have backported SSL changes from Java11 into their
Java8 JRE which prevents us from using Sun JSSE in FIPS mode.
BCJSSE uses different exception messages than Sun JSSE, so we needed
to update
RestrictedTrustManagerTests.testThatDelegateTrustManagerIsRespected
to reflect the fact that sometimes we might be receive BCJSSE error
messages on a Java8 JVM
Resolves: #62281
Current implementations of the indexer are using aggregations.
Thus each search step executes a search action. However,
we can generalize that to allow for any action that returns a `SearchResponse`.
This commit abstracts the search phase from the search action.
Backport of #61739
With the addition of sub aggregations like filter, the validation could fail if 2 sub aggs use the
same output name. This change makes validation sub-agg aware.
fixes#57814
The OpenID Connect specification defines a number of ways for a
client (RP) to authenticate itself to the OP when accessing the
Token Endpoint. We currently only support `client_secret_basic`.
This change introduces support for 2 additional authentication
methods, namely `client_secret_post` (where the client credentials
are passed in the body of the POST request to the OP) and
`client_secret_jwt` where the client constructs a JWT and signs
it using the the client secret as a key.
Support for the above, and especially `client_secret_jwt` in our
integration tests meant that the OP we use ( Connect2id server )
should be able to validate the JWT that we send it from the RP.
Since we run the OP in docker and it listens on an ephemeral port
we would have no way of knowing the port so that we can configure
the ES running via the testcluster to know the "correct" Token
Endpoint, and even if we did, this would not be the Token Endpoint
URL that the OP would think it listens on. To alleviate this, we
run an ES single node cluster in docker, alongside the OP so that
we can configured it with the correct hostname and port within
the docker network.
Co-authored-by: Ioannis Kakavas <ioannis@elastic.co>
AuthorizationService#authorize uses the thread context to carry the result of the
authorisation as transient headers. The listener argument to the `authorize` method
must necessarily observe the header values. This PR makes it so that
the authorisation transient headers (`_indices_permissions` and `_authz_info`, but
NOT `_originating_action_name`) of the child action override the ones of the parent action.
Co-authored-by: Tim Vernum tim@adjective.org
This was missing and caused nodes to drop out of the cluster on serialization failures
when ever one tried to get an enrich policy task by name.
The test in here is a little dirty but I figured it would be nice to have an actual reproducer
for the issue and I couldn't find any infrastructure to nicely time the tasks so I put this on
top of existing test infra.
* Add "synthetics-*-*" templates for synthetics fleet data
For the Elastic Agent we currently have `logs` and `metrics`, however, synthetic data doesn't belong
with those and thus we should have a place for it to live. This would be data reported from
heartbeat and under the 'monitoring' category.
This commit adds a composable index template for `synthetics-*-*` indices similar to the work in
#56709 and #57629.
Resolves#61665
Similar to the work in #60994 where we introduced the `data_hot`, `data_warm`, etc node roles. This
introduces a new `data_content` node role to be used for the Content tier.
Currently this tier is not used anywhere, but subsequent work will use this tier.
Relates to #60848
Backport of #62059 to 7.x branch.
Return a 404 http status code when attempting to delete a non existing data stream.
However only return a 404 when targeting a data stream without any wildcards.
Closes#62022
This commit addresses a super minor misalignment with master, applying exactly the same change that was made as part of #62057, which was backported before point in time APIs were backported.
If shards are relocated to new nodes, then searches with a point in time
will fail, although a pit keeps search contexts open. This commit solves
this problem by reducing info used by SearchShardIterator and always
including the matching nodes when resolving a point in time.
Closes#61627
This commit introduces a new API that manages point-in-times in x-pack
basic. Elasticsearch pit (point in time) is a lightweight view into the
state of the data as it existed when initiated. A search request by
default executes against the most recent point in time. In some cases,
it is preferred to perform multiple search requests using the same point
in time. For example, if refreshes happen between search_after requests,
then the results of those requests might not be consistent as changes
happening between searches are only visible to the more recent point in
time.
A point in time must be opened before being used in search requests. The
`keep_alive` parameter tells Elasticsearch how long it should keep a
point in time around.
```
POST /my_index/_pit?keep_alive=1m
```
The response from the above request includes a `id`, which should be
passed to the `id` of the `pit` parameter of search requests.
```
POST /_search
{
"query": {
"match" : {
"title" : "elasticsearch"
}
},
"pit": {
"id": "46ToAwMDaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQNpZHkFdXVpZDIrBm5vZGVfMwAAAAAAAAAAKgFjA2lkeQV1dWlkMioGbm9kZV8yAAAAAAAAAAAMAWICBXV1aWQyAAAFdXVpZDEAAQltYXRjaF9hbGw_gAAAAA==",
"keep_alive": "1m"
}
}
```
Point-in-times are automatically closed when the `keep_alive` is
elapsed. However, keeping point-in-times has a cost; hence,
point-in-times should be closed as soon as they are no longer used in
search requests.
```
DELETE /_pit
{
"id" : "46ToAwMDaWR4BXV1aWQxAgZub2RlXzEAAAAAAAAAAAEBYQNpZHkFdXVpZDIrBm5vZGVfMwAAAAAAAAAAKgFjA2lkeQV1dWlkMioGbm9kZV8yAAAAAAAAAAAMAWIBBXV1aWQyAAA="
}
```
#### Notable works in this change:
- Move the search state to the coordinating node: #52741
- Allow searches with a specific reader context: #53989
- Add the ability to acquire readers in IndexShard: #54966
Relates #46523
Relates #26472
Co-authored-by: Jim Ferenczi <jimczi@apache.org>
When a tree model is provided, it is possible that it is a stump.
Meaning, it only has one node with no splits
This implies that the tree has no features. In this case,
having zero feature_names is appropriate. In any other case,
this should be considered a validation failure.
This commit adds the validation if there is more than 1 node,
that the feature_names in the model are non-empty.
closes#60759
- Adds missing mappings for `alpha`, `gamma`, and `lambda`.
- Corrects name of `soft_tree_depth_limit` and `soft_tree_depth_tolerance`.
- Removes unused `regularization_depth_penalty_multiplier`,
`regularization_leaf_weight_penalty_multiplier` and
`regularization_tree_size_penalty_multiplier`.
Backport of #61980
At the end of the rolling upgrade tests check the mappings of the concrete
.ml and .transform-internal indices match the mappings in the templates.
When the templates change, the tests should prove that the mappings have
been updated in the new cluster.
This change moves watcher, ILM history and SLM history templates to composable templates.
Versions are updated to reflect the switch. Only change to the templates themselves is added `_meta` to mark them as managed
* [ML] adds new n_gram_encoding custom processor (#61578)
This adds a new `n_gram_encoding` feature processor for analytics and inference.
The focus of this processor is simple ngram encodings that allow:
- multiple ngrams [1..5]
- Prefix, infix, suffix
Previously, we added a copy of the `_id` during reindexing and sorted
the destination index on that. This allowed us to traverse the docs in the
destination index in a stable order multiple times and with efficiency.
However, the destination index being sorted means we cannot have `nested`
typed fields. This is a problem as it does not allow us to provide
a good experience with our evaluate API when it comes to computing
metrics for specific classes, features, etc.
This commit changes the approach in order to result to a destination
index that allows nested fields.
Instead of adding a copy of the `_id` field, we now add an incremental
id that we can use to traverse the docs in a stable order. We also
ensure we always assign the same incremental id to the same doc from
the source indices by sorting on `_seq_no` during reindexing. That
in combination with the reindexing API using scroll gives us a stable
order as scroll uses the (`_index`, `_doc`, shard_id) tuple to resolve ties.
The extractor now does not need to scroll. Instead we sort on the incremental
id and we do ranged searches to avoid the sort-all-docs overhead.
Finally, the `TestDocsIterator` is simply changed to search_after the incremental id.
With these changes data frame analytics jobs do not use scroll at any part.
Having all these in place, the commit adds the `nested` types to the necessary
fields of `classification` and `regression` analyses results.
Backport of #61943
When a user authenticates via OpenID Connect we copy information from
the OIDC claims into the user's metadata in a particular format.
This commit adds a test that metadata in that format can be used in a
mustache template for Document Level Security.
Backport of: #60030
A role mapping with the following content:
"rules": { "field": { "userid" : "admin" } }
will never match because `userid` is not a valid field. The correct
field is `username`.
This change adds DEBUG logging when an undefined field is referenced.
The choice to use DEBUG rather than INFO/WARN is that the set of
fields is partially dynamic (e.g. the `metadata.*` fields), so
it may be perfectly reasonable to check a field that is not defined
for that user. For example this rule:
"rules": { "field": { "metadata.ranking" : "A" } }
would generate a log message for an unranked user, which would
erroneously suggest that such a rule is an error.
This DEBUG logging will assist in diagnosing problems, without
introducing that confusion.
Backport of: #61246
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
During a rolling upgrade it is possible that a worker node will be upgraded before
the master in which case the DFA templates will not have been installed.
Before a DFA task starts check that the latest template is installed and install it if necessary.
System indices can be snapshotted and are therefore potential candidates
to be mounted as searchable snapshot indices. As of today nothing
prevents a snapshot to be mounted under an index name starting with .
and this can lead to conflicting situations because searchable snapshot
indices are read-only and Elasticsearch expects some system indices
to be writable; because searchable snapshot indices will soon use an
internal system index (#60522) to speed up recoveries and we should
prevent the system index to be itself a searchable snapshot index
(leading to some deadlock situation for recovery).
This commit introduces a changes to prevent snapshots to be mounted
as a system index.
This commit addresses two issues:
- per class feature importance is now written out for binary classification (logistic regression)
- The `class_name` in per class feature importance now matches what is written in the `top_classes` array.
backport of https://github.com/elastic/elasticsearch/pull/61597
- don't do encoding of asynchExecutionId if it is already provided in
the encoded form
- create a new instance of AsyncExecutionId after checks for
correctness are done
This commit adds the functionality to allocate newly created indices on nodes in the "hot" tier by
default when they are created.
This does not break existing behavior, as nodes with the `data` role are considered to be part of
the hot tier. Users that separate their deployments by using the `data_hot` (and `data_warm`,
`data_cold`, `data_frozen`) roles will have their data allocated on the hot tier nodes now by
default.
This change is a little more complicated than changing the default value for
`index.routing.allocation.include._tier` from null to "data_hot". Instead, this adds the ability to
have a plugin inject a setting into the builder for a newly created index. This has the benefit of
allowing this setting to be visible as part of the settings when retrieving the index, for example:
```
// Create an index
PUT /eggplant
// Get an index
GET /eggplant?flat_settings
```
Returns the default settings now of:
```json
{
"eggplant" : {
"aliases" : { },
"mappings" : { },
"settings" : {
"index.creation_date" : "1597855465598",
"index.number_of_replicas" : "1",
"index.number_of_shards" : "1",
"index.provided_name" : "eggplant",
"index.routing.allocation.include._tier" : "data_hot",
"index.uuid" : "6ySG78s9RWGystRipoBFCA",
"index.version.created" : "8000099"
}
}
}
```
After the initial setting of this setting, it can be treated like any other index level setting.
This new setting is *not* set on a new index if any of the following is true:
- The index is created with an `index.routing.allocation.include.<anything>` setting
- The index is created with an `index.routing.allocation.exclude.<anything>` setting
- The index is created with an `index.routing.allocation.require.<anything>` setting
- The index is created with a null `index.routing.allocation.include._tier` value
- The index was created from an existing source metadata (shrink, clone, split, etc)
Relates to #60848
If a TLS-protected connection closes unexpectedly then today we often
emit a `WARN` log, typically one of the following:
io.netty.handler.codec.DecoderException: javax.net.ssl.SSLHandshakeException: Insufficient buffer remaining for AEAD cipher fragment (2). Needs to be more than tag size (16)
io.netty.handler.codec.DecoderException: javax.net.ssl.SSLException: Received close_notify during handshake
We typically only report unexpectedly-closed connections at `DEBUG`
level, but these two messages don't follow that rule and generate a lot
of noise as a result. This commit adjusts the logging to report these
two exceptions at `DEBUG` level only.
Nhat Nguyen
Benjamin Trent
Andrei Dan
Lee Hinman
David Turner
Dimitris Athanasiou
Jim Ferenczi
Christoph Büscher
Tim Vernum
Lyudmila Fokina
Hendrik Muhs
Yang Wang
Albert Zaharovits
Armin Braun
Martijn van Groningen
Luca Cavanna
Yannick Welsch
David Kyle
Przemko Robakowski
Ignacio Vera
Tanguy Leroux
Mayya Sharipova