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.
If `keyedFilters` is null it assumes there are unkeyed filters...which
will NPE if the unkeyed filters was actually empty.
This refactors to simplify the filter assignment a bit, adds an empty
check and tidies up some formatting.
Today the `_field_caps` API returns the list of indices where a field
is present only if this field has different types within the requested indices.
However if the request is an index pattern (or an alias, or both...) there
is no way to infer the indices if the response contains only fields that have
the same type in all indices. This commit changes the response to always return
the list of indices in the response. It also adds a way to retrieve unmapped field
in a specific section per field called `unmapped`. This section is created for each field
that is present in some indices but not all if the parameter `include_unmapped` is set to
true in the request (defaults to false).
Adds some validation to prevent duplicate source names from being
used in the composite agg.
Also refactored to use a ConstructingObjectParser and removed the
private ctor and setter for sources, making it mandatory.
* fix#35262 define deprecations of API's as a whole and urls
* document hot threads deprecated paths
* deprecate scroll_id as part of the URL, documented only as part of the body which is a safer behaviour as well
* use version numbers up to patch version
* rest spec parser picks up deprecated paths as paths too
(cherry picked from commit 7e06023e7603b7584bfd9ee4e8a1ccd82c208ce7)
The `composite` aggregation maps unknown fields as numerics, this means that
any `after` value that is set on a query with an unmapped field on some indices
will fail if the provided value is not numeric. This commit changes the default
value source to use keyword instead in order to be able to parse any type of after
values.
Pipelines require single-valued agg or a numeric to be returned.
If they don't get that, they throw an exception. Unfortunately, this
exception text is very confusing to users because it usually arises
from pathing "through" multiple terms aggs. The final target is a numeric,
but it's the intermediary aggs that cause the problem.
This commit adds the current agg name to the exception message
so the user knows which "level" is the issue.
Fixes some documentation urls in the rest-api-spec. Some of these URLs
pointed to 404s and a few others pointed to deprecated documentation
when we have better documentation now. I'm not consistent about `master`
vs `current` because we're not consistent in other places and I think we
should solve all of those at once with something a little more
automatic.
* Replace usages RandomizedTestingTask with built-in Gradle Test (#40978)
This commit replaces the existing RandomizedTestingTask and supporting code with Gradle's built-in JUnit support via the Test task type. Additionally, the previous workaround to disable all tasks named "test" and create new unit testing tasks named "unitTest" has been removed such that the "test" task now runs unit tests as per the normal Gradle Java plugin conventions.
(cherry picked from commit 323f312bbc829a63056a79ebe45adced5099f6e6)
* Fix forking JVM runner
* Don't bump shadow plugin version
This change rejects an illegal combination of flush parameters where
force is true, but wait_if_ongoing is false. This combination is trappy
and should be forbidden.
Closes#36342
A user reported that the same query that takes ~900ms when querying an index
pattern only takes ~50ms when only querying indices that have matches. The
query is a date range query and we confirmed that the `can_match` phase works
as expected. I was able to reproduce this issue locally with a single node: with
900 1-shard indices, a query to an index pattern that matches all indices runs
in ~90ms while a query to the only index that has matches runs in 0-1ms.
This ended up not being related to the `can_match` phase but to the cost of
resolving aliases when querying an index pattern that matches lots of indices.
In that case, we first resolve the index pattern to a list of concrete indices
and then for each concrete index, we check whether it was matched through an
alias, meaning we might have to apply alias filters. Unfortunately this second
per-index operation runs in linear time with the number of matched concrete
indices, which means that alias resolution runs in O(num_indices^2) overall.
So queries get exponentially slower as an index pattern matches more indices.
I reorganized alias resolution into a one-step operation that runs in linear
time with the number of matches indices, and then a per-index operation that
runs in linear time with the number of aliases of this index. This makes alias
resolution run is O(num_indices * num_aliases_per_index) overall instead. When
testing the scenario described above, the `took` went down from ~90ms to ~10ms.
It is still more than the 0-1ms latency that one gets when only querying the
single index that has data, but still much better than what we had before.
Closes#40248
We discussed recently that the cluster state API should be considered
"internal" and therefore our usual cast-iron stability guarantees do not hold
for this API.
However, there are a good number of REST tests that try to identify the master
node. Today they call `GET /_cluster/state` API and extract the master node ID
from the response. In fact many of these tests just want an arbitary node ID
(or perhaps a data node ID) so an alternative is to call `GET _nodes` or `GET
_nodes/data:true` and obtain a node ID from the keys of the `nodes` map in the
response.
This change adds the ability for YAML-based REST tests to extract an arbitrary
key from a map so that they can obtain a node ID from the nodes info API
instead of using the master node ID from the cluster state API.
Relates #40047.
Adds the search_as_you_type field type that acts like a text field optimized
for as-you-type search completion. It creates a couple subfields that analyze
the indexed terms as shingles, against which full terms are queried, and a
prefix subfield that analyze terms as the largest shingle size used and
edge-ngrams, against which partial terms are queried
Adds a match_bool_prefix query type that creates a boolean clause of a term
query for each term except the last, for which a boolean clause with a prefix
query is created.
The match_bool_prefix query is the recommended way of querying a search as you
type field, which will boil down to term queries for each shingle of the input
text on the appropriate shingle field, and the final (possibly partial) term
as a term query on the prefix field. This field type also supports phrase and
phrase prefix queries however
Right now, the stats API only provides refresh metrics regarding
internal refreshes. This isn't very useful and somewhat misleading for
cluster administrators since the internal refreshes are not indicative
of documents being available for search.
In this PR I added a new metric for collecting external refreshes as
they occur and exposing them through the stats API. Now, calling an
endpoint for stats will yield external refresh metrics as well.
Relates #36712
Today we don't return segments stats for closed indices which makes it
hard to tell how much memory such an index would require. With this change
we return the statistics if requested by setting `include_unloaded_segments` to
true on the rest request.
Relates to #39512
This commit removes the cluster state size field from the cluster state
response, and drops the backwards compatibility layer added in 6.7.0 to
continue to support this field. As calculation of this field was
expensive and had dubious value, we have elected to remove this field.
This PR adds an internal REST API for querying context information about
Painless whitelists.
Commands include the following:
GET /_scripts/painless/_context -- retrieves a list of contexts
GET /_scripts/painless/_context?context=%name% retrieves all available
information about the API for this specific context
Computing the compressed size of the cluster state on every invocation
of cluster:monitor/state action is expensive, and the value of this
field is dubious anyway. Therefore we want to remove computing this
field. As a first step, we stop computing and return this field by
default. To avoid breaking users, we will give them a system property to
use to tide them over until the next major release when we will actually
remove this field. This comes with a deprecation warning too, and the
backport to the appropriate minor will also include a note in the
migration guide. There will be a follow-up to remove this field in the
next major version.
the test "Implicitly create a typeless ... typed template"
fails occasionally because the index operation hasn't
propogated to update the index mapping in time for the
following assertion about a dynamically mapped field "bar".
error failed with:
```
field [test-1.mappings.my_type.properties.bar] doesn't have a true value
Expected: not null
but: was null
```
refreshing the index should resolve this timing issue.
Today we have no chance to fetch actual segment stats for segments that
are currently unloaded. This is relevant in the case of frozen indices.
This allows to monitor how much memory a frozen index would use if it was
unfrozen.
Backport support for replicating closed indices (#39499)
Before this change, closed indexes were simply not replicated. It was therefore
possible to close an index and then decommission a data node without knowing
that this data node contained shards of the closed index, potentially leading to
data loss. Shards of closed indices were not completely taken into account when
balancing the shards within the cluster, or automatically replicated through shard
copies, and they were not easily movable from node A to node B using APIs like
Cluster Reroute without being fully reopened and closed again.
This commit changes the logic executed when closing an index, so that its shards
are not just removed and forgotten but are instead reinitialized and reallocated on
data nodes using an engine implementation which does not allow searching or
indexing, which has a low memory overhead (compared with searchable/indexable
opened shards) and which allows shards to be recovered from peer or promoted
as primaries when needed.
This new closing logic is built on top of the new Close Index API introduced in
6.7.0 (#37359). Some pre-closing sanity checks are executed on the shards before
closing them, and closing an index on a 8.0 cluster will reinitialize the index shards
and therefore impact the cluster health.
Some APIs have been adapted to make them work with closed indices:
- Cluster Health API
- Cluster Reroute API
- Cluster Allocation Explain API
- Recovery API
- Cat Indices
- Cat Shards
- Cat Health
- Cat Recovery
This commit contains all the following changes (most recent first):
* c6c42a1 Adapt NoOpEngineTests after #39006
* 3f9993d Wait for shards to be active after closing indices (#38854)
* 5e7a428 Adapt the Cluster Health API to closed indices (#39364)
* 3e61939 Adapt CloseFollowerIndexIT for replicated closed indices (#38767)
* 71f5c34 Recover closed indices after a full cluster restart (#39249)
* 4db7fd9 Adapt the Recovery API for closed indices (#38421)
* 4fd1bb2 Adapt more tests suites to closed indices (#39186)
* 0519016 Add replica to primary promotion test for closed indices (#39110)
* b756f6c Test the Cluster Shard Allocation Explain API with closed indices (#38631)
* c484c66 Remove index routing table of closed indices in mixed versions clusters (#38955)
* 00f1828 Mute CloseFollowerIndexIT.testCloseAndReopenFollowerIndex()
* e845b0a Do not schedule Refresh/Translog/GlobalCheckpoint tasks for closed indices (#38329)
* cf9a015 Adapt testIndexCanChangeCustomDataPath for replicated closed indices (#38327)
* b9becdd Adapt testPendingTasks() for replicated closed indices (#38326)
* 02cc730 Allow shards of closed indices to be replicated as regular shards (#38024)
* e53a9be Fix compilation error in IndexShardIT after merge with master
* cae4155 Relax NoOpEngine constraints (#37413)
* 54d110b [RCI] Adapt NoOpEngine to latest FrozenEngine changes
* c63fd69 [RCI] Add NoOpEngine for closed indices (#33903)
Relates to #33888
This test had been disabled because of test failures, but it only affected the
6.x branch. The fix for 6.x is at #39054. On master/7.x/7.0 we can reenable the
test as-is.
This commit changes the `TransportVerifyShardBeforeCloseAction` so that it
always forces the flush of the shard. It seems that #37961 is not sufficient to
ensure that the translog and the Lucene commit share the exact same max
seq no and global checkpoint information in case of one or more noop
operations have been made.
The `BulkWithUpdatesIT.testThatMissingIndexDoesNotAbortFullBulkRequest`
and `FrozenIndexTests.testFreezeEmptyIndexWithTranslogOps` test this trivial
situation and they both fail 1 on 10 executions.
Relates to #33888
Elasticsearch has long [supported](https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-index_.html#index-versioning) compare and set (a.k.a optimistic concurrency control) operations using internal document versioning. Sadly that approach is flawed and can sometime do the wrong thing. Here's the relevant excerpt from the resiliency status page:
> When a primary has been partitioned away from the cluster there is a short period of time until it detects this. During that time it will continue indexing writes locally, thereby updating document versions. When it tries to replicate the operation, however, it will discover that it is partitioned away. It won’t acknowledge the write and will wait until the partition is resolved to negotiate with the master on how to proceed. The master will decide to either fail any replicas which failed to index the operations on the primary or tell the primary that it has to step down because a new primary has been chosen in the meantime. Since the old primary has already written documents, clients may already have read from the old primary before it shuts itself down. The version numbers of these reads may not be unique if the new primary has already accepted writes for the same document
We recently [introduced](https://www.elastic.co/guide/en/elasticsearch/reference/6.x/optimistic-concurrency-control.html) a new sequence number based approach that doesn't suffer from this dirty reads problem.
This commit removes support for internal versioning as a concurrency control mechanism in favor of the sequence number approach.
Relates to #1078
`CreateIndexRequest#source(Map<String, Object>, ... )`, which is used when
deserializing index creation requests, accidentally accepts mappings that are
nested twice under the type key (as described in the bug report #38266).
This in turn causes us to be too lenient in parsing typeless mappings. In
particular, we accept the following index creation request, even though it
should not contain the type key `_doc`:
```
PUT index?include_type_name=false
{
"mappings": {
"_doc": {
"properties": { ... }
}
}
}
```
There is a similar issue for both 'put templates' and 'put mappings' requests
as well.
This PR makes the minimal changes to detect and reject these typed mappings in
requests. It does not address #38266 generally, or attempt a larger refactor
around types in these server-side requests, as I think this should be done at a
later time.
X-Pack security supports built-in authentication service
`token-service` that allows access tokens to be used to
access Elasticsearch without using Basic authentication.
The tokens are generated by `token-service` based on
OAuth2 spec. The access token is a short-lived token
(defaults to 20m) and refresh token with a lifetime of 24 hours,
making them unsuitable for long-lived or recurring tasks where
the system might go offline thereby failing refresh of tokens.
This commit introduces a built-in authentication service
`api-key-service` that adds support for long-lived tokens aka API
keys to access Elasticsearch. The `api-key-service` is consulted
after `token-service` in the authentication chain. By default,
if TLS is enabled then `api-key-service` is also enabled.
The service can be disabled using the configuration setting.
The API keys:-
- by default do not have an expiration but expiration can be
configured where the API keys need to be expired after a
certain amount of time.
- when generated will keep authentication information of the user that
generated them.
- can be defined with a role describing the privileges for accessing
Elasticsearch and will be limited by the role of the user that
generated them
- can be invalidated via invalidation API
- information can be retrieved via a get API
- that have been expired or invalidated will be retained for 1 week
before being deleted. The expired API keys remover task handles this.
Following are the API key management APIs:-
1. Create API Key - `PUT/POST /_security/api_key`
2. Get API key(s) - `GET /_security/api_key`
3. Invalidate API Key(s) `DELETE /_security/api_key`
The API keys can be used to access Elasticsearch using `Authorization`
header, where the auth scheme is `ApiKey` and the credentials, is the
base64 encoding of API key Id and API key separated by a colon.
Example:-
```
curl -H "Authorization: ApiKey YXBpLWtleS1pZDphcGkta2V5" http://localhost:9200/_cluster/health
```
Closes#34383
This adds a dedicated field mapper that supports nanosecond resolution -
at the price of a reduced date range.
When using the date field mapper, the time is stored as milliseconds since the epoch
in a long in lucene. This field mapper stores the time in nanoseconds
since the epoch - which means its range is much smaller, ranging roughly from
1970 to 2262.
Note that aggregations will still be in milliseconds.
However docvalue fields will have full nanosecond resolution
Relates #27330
James Baiera
Tanguy Leroux
Zachary Tong
Tomas Della Vedova
Russ Cam
jaymode
Jason Tedor
Jim Ferenczi
Zachary Tong
Martijn Laarman
Jim Ferenczi
Nik Everett
Nhat Nguyen
Mark Vieira
Adrien Grand
Alpar Torok
David Turner
Andy Bristol
Mayya Sharipova
Simon Willnauer
Jack Conradson
Ioannis Kakavas
Tal Levy
Lee Hinman
Alan Woodward
Boaz Leskes
Julie Tibshirani
Yogesh Gaikwad
Alexander Reelsen