For now we support `_gce_` only if discovery is set to `gce` and all information about GCE is provided (project_id and zone).
But in some cases, people would like to only bind to `_gce_` on a single node (without any elasticsearch cluster).
They could access the machine then from other machines running inside the same project.
This commit adds a new GceMetadataService which is started as soon as the plugin is started so GceNameResolver can use it to resolve `_gce`.
Closes#15724.
When working on #18008 I found while reading the code that we don't filter anymore `repositories.s3.access_key` and `repositories.s3.secret_key`.
Also fixed a typo in REST test
Lucene allows to create a ICUTokenizer with a special config argument
enabling the customization of the rule based iterator by providing
custom rules files.
This commit enable this feature. Users could provide a list of RBBI rule
files to ICU tokenizer.
closes#13146
Now that the current uses of magical camelCase support have been
deprecated, we can remove these in master (sans remaining issues like
BulkRequest). This change removes camel case support from ParseField,
query types, analysis, and settings lookup.
see #8988
* `rename` processor, renamed `to` to `target_field`
* `date` processor, renamed `match_field` to `field` and renamed `match_formats` to `formats`
* `geoip` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
* `attachment` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
Closes#17835
Defaults to `true`.
If anyone is having trouble with this option, you could disable it with `cloud.aws.s3.throttle_retries: false` in `elasticsearch.yml` file.
* Moving from JSON.org to Jackson for request marshallers.
* The Java SDK now supports retry throttling to limit the rate of retries during periods of reduced availability. This throttling behavior can be enabled via ClientConfiguration or via the system property "-Dcom.amazonaws.sdk.enableThrottledRetry".
* Fixed String case conversion issues when running with non English locales.
* AWS SDK for Java introduces a new dynamic endpoint system that can compute endpoints for services in new regions.
* Introducing a new AWS region, ap-northeast-2.
* Added a new metric, HttpSocketReadTime, that records socket read latency. You can enable this metric by adding enableHttpSocketReadMetric to the system property com.amazonaws.sdk.enableDefaultMetrics. For more information, see [Enabling Metrics with the AWS SDK for Java](https://java.awsblog.com/post/Tx3C0RV4NRRBKTG/Enabling-Metrics-with-the-AWS-SDK-for-Java).
* New Client Execution timeout feature to set a limit spent across retries, backoffs, ummarshalling, etc. This new timeout can be specified at the client level or per request.
Also included in this release is the ability to specify the existing HTTP Request timeout per request rather than just per client.
* Added support for RequesterPays for all operations.
* Ignore the 'Connection' header when generating S3 responses.
* Allow users to generate an AmazonS3URI from a string without using URL encoding.
* Fixed issue that prevented creating buckets when using a client configured for the s3-external-1 endpoint.
* Amazon S3 bucket lifecycle configuration supports two new features: the removal of expired object delete markers and an action to abort incomplete multipart uploads.
* Allow TransferManagerConfiguration to accept integer values for multipart upload threshold.
* Copy the list of ETags before sorting https://github.com/aws/aws-sdk-java/pull/589.
* Option to disable chunked encoding https://github.com/aws/aws-sdk-java/pull/586.
* Adding retry on InternalErrors in CompleteMultipartUpload operation. https://github.com/aws/aws-sdk-java/issues/538
* Deprecated two APIs : AmazonS3#changeObjectStorageClass and AmazonS3#setObjectRedirectLocation.
* Added support for the aws-exec-read canned ACL. Owner gets FULL_CONTROL. Amazon EC2 gets READ access to GET an Amazon Machine Image (AMI) bundle from Amazon S3.
* Added support for referencing security groups in peered Virtual Private Clouds (VPCs). For more information see the service announcement at https://aws.amazon.com/about-aws/whats-new/2016/03/announcing-support-for-security-group-references-in-a-peered-vpc/ .
* Fixed a bug in AWS SDK for Java - Amazon EC2 module that returns NPE for dry run requests.
* Regenerated client with new implementation of code generator.
* This feature enables support for DNS resolution of public hostnames to private IP addresses when queried over ClassicLink. Additionally, you can now access private hosted zones associated with your VPC from a linked EC2-Classic instance. ClassicLink DNS support makes it easier for EC2-Classic instances to communicate with VPC resources using public DNS hostnames.
* You can now use Network Address Translation (NAT) Gateway, a highly available AWS managed service that makes it easy to connect to the Internet from instances within a private subnet in an AWS Virtual Private Cloud (VPC). Previously, you needed to launch a NAT instance to enable NAT for instances in a private subnet. Amazon VPC NAT Gateway is available in the US East (N. Virginia), US West (Oregon), US West (N. California), EU (Ireland), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney) regions. To learn more about Amazon VPC NAT, see [New - Managed NAT (Network Address Translation) Gateway for AWS](https://aws.amazon.com/blogs/aws/new-managed-nat-network-address-translation-gateway-for-aws/)
* A default read timeout is now applied when querying data from EC2 metadata service.
This makes all numeric fields including `date`, `ip` and `token_count` use
points instead of the inverted index as a lookup structure. This is expected
to perform worse for exact queries, but faster for range queries. It also
requires less storage.
Notes about how the change works:
- Numeric mappers have been split into a legacy version that is essentially
the current mapper, and a new version that uses points, eg.
LegacyDateFieldMapper and DateFieldMapper.
- Since new and old fields have the same names, the decision about which one
to use is made based on the index creation version.
- If you try to force using a legacy field on a new index or a field that uses
points on an old index, you will get an exception.
- IP addresses now support IPv6 via Lucene's InetAddressPoint and store them
in SORTED_SET doc values using the same encoding (fixed length of 16 bytes
and sortable).
- The internal MappedFieldType that is stored by the new mappers does not have
any of the points-related properties set. Instead, it keeps setting the index
options when parsing the `index` property of mappings and does
`if (fieldType.indexOptions() != IndexOptions.NONE) { // add point field }`
when parsing documents.
Known issues that won't fix:
- You can't use numeric fields in significant terms aggregations anymore since
this requires document frequencies, which points do not record.
- Term queries on numeric fields will now return constant scores instead of
giving better scores to the rare values.
Known issues that we could work around (in follow-up PRs, this one is too large
already):
- Range queries on `ip` addresses only work if both the lower and upper bounds
are inclusive (exclusive bounds are not exposed in Lucene). We could either
decide to implement it, or drop range support entirely and tell users to
query subnets using the CIDR notation instead.
- Since IP addresses now use a different representation for doc values,
aggregations will fail when running a terms aggregation on an ip field on a
list of indices that contains both pre-5.0 and 5.0 indices.
- The ip range aggregation does not work on the new ip field. We need to either
implement range aggs for SORTED_SET doc values or drop support for ip ranges
and tell users to use filters instead. #17700Closes#16751Closes#17007Closes#11513
When it comes to query parsing, either a field is tokenized and it would go
through analysis with its search_analyzer. Or it is not tokenized and the
raw string should be passed to termQuery(). Since numeric fields are not
tokenized and also declare a search analyzer, values would currently go through
analysis twice...
This commit removes `MappedFieldType.value` and simplifies
`MappedFieldType.valueforSearch`. `valueforSearch` was used to post-process
values that come for stored fields (eg. to convert a long back to a string
representation of a date in the case of a date field) and also values that
are extracted from the source but only in the case of GET calls: it would
not be called when performing source filtering on search requests.
`valueforSearch` is now only called for stored fields, since values that are
extracted from the source should already be formatted as expected.
* upgrades numerics to new Point format
* updates geo api changes
* adds GeoPointDistanceRangeQuery as XGeoPointDistanceRangeQuery
* cuts over to ES GeoHashUtils
CBOR is natively supported in Elasticsearch and allows for byte arrays.
This means, that by using CBOR the user can prevent base64 conversions
for the data being sent back and forth.
This PR adds support to extract data from a byte array in addition to
a string. This also required to add a ByteArrayValueSource class.
We have both `Settings.settingsBuilder` and `Settings.builder` that do exactly
the same thing, so we should keep only one. I kept `Settings.builder` since it
has my preference but also it is the one that we use in examples of the Java API.
This PR just adds a new test where we check that we forcing a value in the JSON document actually works as expected:
```json
{
"file": {
"_content": "BASE64"
"_name": "12-240.pdf",
"_language": "en",
"_content_type": "pdf"
}
}
```
Note that we don't support forcing all values. So sending:
```json
{
"file": {
"_content": "BASE64"
"_name": "12-240.pdf",
"_title": "12-240.pdf",
"_keywords": "Div42 Src580 LGE Mechtech",
"_language": "en",
"_content_type": "pdf"
}
}
```
Will have absolutely no effect on fields `title` and `keywords`.
Note that when `_language` is set, it only works if `index.mapping.attachment.detect_language` is set to `true`.
Related to https://discuss.elastic.co/t/mapper-attachments/46615/4
This removes the inconsistent output of IP addresses. The format was parsing-unfriendly and it makes it hard
to reason about API responses, such as to _nodes.
With this change in place, it will never print the hostname as part of the default format, which has the
added benefit that it can be used consistently for URIs, which was not the case when the hostname might
appear at the front with "hostname/ip:port".
`text` fields will have fielddata disabled by default. Fielddata can still be
enabled on an existing index by setting `fielddata=true` in the mappings.
Node roles are now serialized as well, they are not part of the node attributes anymore. DiscoveryNodeService takes care of dividing settings into attributes and roles. DiscoveryNode always requires to pass in attributes and roles separately.
This change moves placeholder replacement to a pkg private class for
settings. It also adds a null check when calling replacement, as
settings objects can still contain null values, because we only prohibit
nulls on file loading. Finally, this cleans up file and stream loading a
bit to not have unnecessary exception wrapping.
We can be better at checking `buffer_size` and `chunk_size` for S3 repositories.
For example, we know that:
* `buffer_size` should be more than `5mb`
* `chunk_size` should be no more than `5tb`
* `buffer_size` should be lower than `chunk_size`
Otherwise, setting `buffer_size` is useless.
For the record:
`chunk_size` is a Snapshot setting whatever the implementation is.
`buffer_size` is an S3 implementation setting.
Let say that you are snapshotting a 500mb file. If you set `chunk_size` to `200mb`, then Snapshot service will call S3 repository to snapshot 3 files with the following sizes:
* `200mb`
* `200mb`
* `100mb`
If you set `buffer_size` to `100mb` (AWS maximum size recommendation), the first file of `200mb` will be uploaded on S3 using the multipart feature in 2 chunks and the workflow is basically the following:
* create the multipart request and get back an `id` from AWS S3 platform
* upload part1: `100mb`
* upload part2: `100mb`
* "commit" the full upload using the `id`.
Closes#17244.
