Test clusters currently has its own set of logic for dealing with
finding different versions of Elasticsearch, downloading them, and
extracting them. This commit converts testclusters to use the
DistributionDownloadPlugin.
This commit creates new base classes for master node actions whose
response types still implement Streamable. This simplifies both finding
remaining classes to convert, as well as creating new master node
actions that use Writeable for their responses.
relates #34389
* HLRC: Fix '+' Not Correctly Encoded in GET Req.
* Encode `+` correctly as `%2B` in URL paths
* Keep encoding `+` as space in URL parameters
* Closes#33077
This commit moves the Supplier variant of HandledTransportAction to have
a different ordering than the Writeable.Reader variant. The Supplier
version is used for the legacy Streamable, and currently having the
location of the Writeable.Reader vs Supplier in the same place forces
using casts of Writeable.Reader to select the correct super constructor.
This change in ordering allows easier migration to Writeable.Reader.
relates #34389
Now that ML job configs are stored in an index rather than
cluster state, availability of the .ml-config index is very
important to the operation of ML. When a cluster starts up
the ML persistent tasks will be considered for node
assignment very early on. It is best in this case if
assignment is deferred until after the .ml-config index is
available.
The introduction of data frame analytics jobs has made this
problem worse, because anomaly detection jobs already waited
for the primary shards of the .ml-state, .ml-anomalies-shared
and .ml-meta indices to be available before doing node
assignment, and by coincidence this would probably lead to
the primary shards of .ml-config also being searchable. But
data frame analytics jobs had no other index checks prior to
this change.
This fixes problem 2 of #44156
By default, we don't check ranges while indexing geo_shapes. As a
result, it is possible to index geoshapes that contain contain
coordinates outside of -90 +90 and -180 +180 ranges. Such geoshapes
will currently break SQL and ML retrieval mechanism. This commit removes
these restriction from the validator is used in SQL and ML retrieval.
When the ML memory tracker is refreshed and a refresh is
already in progress the idea is that the second and
subsequent refresh requests receive the same response as
the currently in progress refresh.
There was a bug that if a refresh failed then the ML
memory tracker's view of whether a refresh was in progress
was not reset, leading to every subsequent request being
registered to receive a response that would never come.
This change makes the ML memory tracker pass on failures
as well as successes to all interested parties and reset
the list of interested parties so that further refresh
attempts are possible after either a success or failure.
This fixes problem 1 of #44156
Custom timestamp overrides provided to the find_file_structure
endpoint produced an invalid Grok pattern if the fractional
seconds separator was a dot rather than a comma or colon.
This commit fixes that problem and adds tests for this sort
of timestamp override.
Fixes#44110
The count should match the number of all df-analytics that
matched the id in the request. However, we set the count
to the number of df-analytics returned which was bound to the
`size` parameter. This commit fixes this by setting the count
to the count of the `get` response.
A bug was introduced in 6.6.0 when we added support for
rollup indices. Rollup caps does NOT support looking at
remote indices, consequently, since we always look up rollup
caps, the datafeed fails with an error if its config
includes a concrete remote index. (When all remote indices
in a datafeed config are wildcards the problem did not
occur.)
The rollups feature does not support remote indices, so if
there is any remote index in a datafeed config (wildcarded
or not), we can skip the rollup cap checks. This PR
implements that change.
This brings TokenizerFactory into line with CharFilterFactory and TokenFilterFactory,
and removes the need to pass around tokenizer names when building custom analyzers.
As this means that TokenizerFactory is no longer a functional interface, the commit also
adds a factory method to TokenizerFactory to make construction simpler.
This introduces a `failed` state to which the data frame analytics
persistent task is set to when something unexpected fails. It could
be the process crashing, the results processor hitting some error,
etc. The failure message is then captured and set on the task state.
From there, it becomes available via the _stats API as `failure_reason`.
The df-analytics stop API now has a `force` boolean parameter. This allows
the user to call it for a failed task in order to reset it to `stopped` after
we have ensured the failure has been communicated to the user.
This commit also adds the analytics version in the persistent task
params as this allows us to prevent tasks to run on unsuitable nodes in
the future.
Renames `_id_copy` to `ml__id_copy` as field names starting with
underscore are deprecated. The new field name `ml__id_copy` was
chosen as an obscure enough field that users won't have in their data.
Otherwise, this field is only intented to be used by df-analytics.
If a job is opened and then closed and does nothing in
between then it should not persist any results or state
documents. This change adapts the no-op job test to
assert no results in addition to no state, and to log
any documents that cause this assertion to fail.
Relates elastic/ml-cpp#512
Relates #43680
The Action base class currently works for both Streamable and Writeable
response types. This commit intorduces StreamableResponseAction, for
which only the legacy Action implementions which provide newResponse()
will extend. This eliminates the need for overriding newResponse() with
an UnsupportedOperationException.
relates #34389
Since #41817 was merged the ml-cpp zip file for any
given version has been cached indefinitely by Gradle.
This is problematic, particularly in the case of the
master branch where the version 8.0.0-SNAPSHOT will
be in use for more than a year.
This change tells Gradle that the ml-cpp zip file is
a "changing" dependency, and to check whether it has
changed every two hours. Two hours is a compromise
between checking on every build and annoying developers
with slow internet connections and checking rarely
causing bug fixes in the ml-cpp code to take a long
time to propagate through to elasticsearch PRs that
rely on them.
This commit adds support for multiple source indices.
In order to deal with multiple indices having different mappings,
it attempts a best-effort approach to merge the mappings assuming
there are no conflicts. In case conflicts exists an error will be
returned.
To allow users creating custom mappings for special use cases,
the destination index is now allowed to exist before the analytics
job runs. In addition, settings are no longer copied except for
the `index.number_of_shards` and `index.number_of_replicas`.
* Deduplicate org.elasticsearch.xpack.core.dataframe.utils.TimeUtils and org.elasticsearch.xpack.core.ml.utils.time.TimeUtils into a common class: org.elasticsearch.xpack.core.common.time.TimeUtils.
* Add unit tests for parseTimeField and parseTimeFieldToInstant methods
This change introduces a new setting,
xpack.ml.process_connect_timeout, to enable
the timeout for one of the external ML processes
to connect to the ES JVM to be increased.
The timeout may need to be increased if many
processes are being started simultaneously on
the same machine. This is unlikely in clusters
with many ML nodes, as we balance the processes
across the ML nodes, but can happen in clusters
with a single ML node and a high value for
xpack.ml.node_concurrent_job_allocations.
This merges the initial work that adds a framework for performing
machine learning analytics on data frames. The feature is currently experimental
and requires a platinum license. Note that the original commits can be
found in the `feature-ml-data-frame-analytics` branch.
A new set of APIs is added which allows the creation of data frame analytics
jobs. Configuration allows specifying different types of analysis to be performed
on a data frame. At first there is support for outlier detection.
The APIs are:
- PUT _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}/_stats
- POST _ml/data_frame/analysis/{id}/_start
- POST _ml/data_frame/analysis/{id}/_stop
- DELETE _ml/data_frame/analysis/{id}
When a data frame analytics job is started a persistent task is created and started.
The main steps of the task are:
1. reindex the source index into the dest index
2. analyze the data through the data_frame_analyzer c++ process
3. merge the results of the process back into the destination index
In addition, an evaluation API is added which packages commonly used metrics
that provide evaluation of various analysis:
- POST _ml/data_frame/_evaluate
The error message if the native controller failed to run
(for example due to running Elasticsearch on an unsupported
platform) was not easy to understand. This change removes
pointless detail from the message and adds some hints about
likely causes.
Fixes#42341
This commit replaces usages of Streamable with Writeable for the
AcknowledgedResponse and its subclasses, plus associated actions.
Note that where possible response fields were made final and default
constructors were removed.
This is a large PR, but the change is mostly mechanical.
Relates to #34389
Backport of #43414
After the network disruption a partition is created,
one side of which can form a cluster the other can't.
Ensure requests are sent to a node on the correct side
of the cluster
This commit removes some very old test logging annotations that appeared
to be added to investigate test failures that are long since closed. If
these are needed, they can be added back on a case-by-case basis with a
comment associating them to a test failure.
* Return 0 for negative "free" and "total" memory reported by the OS
We've had a situation where the MX bean reported negative values for the
free memory of the OS, in those rare cases we want to return a value of
0 rather than blowing up later down the pipeline.
In the event that there is a serialization or creation error with regard
to memory use, this adds asserts so the failure will occur as soon as
possible and give us a better location for investigation.
Resolves#42157
* Fix test passing in invalid memory value
* Fix another test passing in invalid memory value
* Also change mem check in MachineLearning.machineMemoryFromStats
* Add background documentation for why we prevent negative return values
* Clarify comment a bit more
This trace logging looks like it was copy/pasted from another test,
where the logging in that test was only added to investigate a test
failure. This commit removes the trace logging.
The ML failover tests sometimes need to wait for jobs to be
assigned to new nodes following a node failure. They wait
10 seconds for this to happen. However, if the node that
failed was the master node and a new master was elected then
this 10 seconds might not be long enough as a refresh of the
memory stats will delay job assignment. Once the memory
refresh completes the persistent task will be assigned when
the next cluster state update occurs or after the periodic
recheck interval, which defaults to 30 seconds. Rather than
increase the length of the wait for assignment to 31 seconds,
this change decreases the periodic recheck interval to 1
second.
Fixes#43289
We were stopping a node in the cluster at a time when
the replica shards of the .ml-state index might not
have been created. This change moves the wait for
green status to a point where the .ml-state index
exists.
Fixes#40546Fixes#41742
Forward port of #43111
A static code analysis revealed that we are not closing
the input stream in the post_data endpoint. This
actually makes no difference in practice, as the
particular InputStream implementation in this case is
org.elasticsearch.common.bytes.BytesReferenceStreamInput
and its close() method is a no-op. However, it is good
practice to close the stream anyway.
