* Previously, we mentioned multiple times that each nested object was indexed as its own document. This is repetitive, and is also a bit confusing in the context of `index.mapping.nested_fields.limit`, as that applies to the number of distinct `nested` types in the mappings, not the number of nested objects. We now just describe the issue once at the beginning of the section, to illustrate why `nested` types can be expensive.
* Reference the ongoing example to clarify the meaning of the two settings.
Addresses #28363.
* Deprecate CommonTermsQuery and cutoff_frequency
Since the max_score optimization landed in Elasticsearch 7,
the CommonTermsQuery is redundant and slower. Moreover the
cutoff_frequency parameter for MatchQuery and MultiMatchQuery
is redundant.
Relates to #27096
With the removal of node.max_local_storage_nodes, there is no need anymore to keep the data in
subfolders indexed by a node ordinal. This commit makes it so that ES 8.0 will store data directly in
$DATA_DIR instead of $DATA_DIR/nodes/$nodeOrdinal.
Upon startup, Elasticsearch will check to see if there is data in the old location, and automatically
move it to the new location. This automatic migration only works if $nodeOrdinal is 0, i.e., multiple
node instances have not previously run on the same data path, which required for
node.max_local_storage_nodes to explicitly be configured.
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
We deprecated these settings awhile ago, in favor of cluster.remote. In
7.x we were gentle and provided automatic upgrade of these settings to
the new settings. Now it is time for them to go. This commit removes the
deprecated search.remote settings.
This setting, which prior to Elasticsearch 5 was enabled by default and caused all kinds of
confusion, has since been disabled by default and is not recommended for production use. The
preferred way going forward is for users to explicitly specify separate data folders for each started
node to ensure that each node is consistently assigned to the same data path.
Relates to #42426
We deprecated `restoreShard` and `snapshotShard` in #42213
This change removes the deprecated methods and their usage and adds
a note in the migration docs.
Removes all deprecated type-related methods from the QueryBuilders helper class
and from tests using them. Also removing related docs tests and doc pages
refering to the `type` query. All removed methods have been deprecated since
version 7.0.
Downgrading an Elasticsearch node to an earlier version is unsupported, because
we do not make any attempt to guarantee that a node can read any of the on-disk
data written by a future version. Yet today we do not actively prevent
downgrades, and sometimes users will attempt to roll back a failed upgrade with
an in-place downgrade and get into an unrecoverable state.
This change adds the current version of the node to the node metadata file, and
checks the version found in this file against the current version at startup.
If the node cannot be sure of its ability to read the on-disk data then it
refuses to start, preserving any on-disk data in its upgraded state.
This change also adds a command-line tool to overwrite the node metadata file
without performing any version checks, to unsafely bypass these checks and
recover the historical and lenient behaviour.
This commit removes the deprecated migrate tool which was used to
migrate users from the file realm to native realm when the native realm
was first created.
Adds a note that restarting half-or-more of the master-eligible nodes means
you're no longer doing a rolling upgrade, and may need to upgrade all the
things before the cluster returns to health.
Configurations are stored in the .data-frame-internal-1
index, but users should not add configurations directly to
the index as additional information to enable access control
is added. This adds a warning against allowing access to the
internal index.
The migrate tool was added when the native realm was created, to aid
users in converting from file realms that were per node, into the
cluster managed native realm. While this tool was useful at the time,
users should now be using the native realm directly. This commit
deprecates the tool, to be removed in a followup for 8.0.
Adds an initial limited implementations of geo features to SQL. This implementation is based on the [OpenGIS® Implementation Standard for Geographic information - Simple feature access](http://www.opengeospatial.org/standards/sfs), which is the current standard for GIS system implementation. This effort is concentrate on SQL option AKA ISO 19125-2.
## Queries that are supported as a result of this initial implementation
### Metadata commands
- `DESCRIBE table` - returns the correct column types `GEOMETRY` for geo shapes and geo points.
- `SHOW FUNCTIONS` - returns a list that includes supported `ST_` functions
- `SYS TYPES` and `SYS COLUMNS` display correct types `GEO_SHAPE` and `GEO_POINT` for geo shapes and geo points accordingly.
### Returning geoshapes and geopoints from elasticsearch
- `SELECT geom FROM table` - returns the geoshapes and geo_points as libs/geo objects in JDBC or as WKT strings in console.
- `SELECT ST_AsWKT(geom) FROM table;` and `SELECT ST_AsText(geom) FROM table;`- returns the geoshapes ang geopoints in their WKT representation;
### Using geopoints to elasticsearch
- The following functions will be supported for geopoints in queries, sorting and aggregations: `ST_GeomFromText`, `ST_X`, `ST_Y`, `ST_Z`, `ST_GeometryType`, and `ST_Distance`. In most cases when used in queries, sorting and aggregations, these function are translated into script. These functions can be used in the SELECT clause for both geopoints and geoshapes.
- `SELECT * FROM table WHERE ST_Distance(ST_GeomFromText(POINT(1 2), point) < 10;` - returns all records for which `point` is located within 10m from the `POINT(1 2)`. In this case the WHERE clause is translated into a range query.
## Limitations:
Geoshapes cannot be used in queries, sorting and aggregations as part of this initial effort. In order to fully take advantage of geoshapes we would need to have access to geoshape doc values, which is coming in #37206. `ST_Z` cannot be used on geopoints in queries, sorting and aggregations since we don't store altitude in geo_point doc values.
Relates to #29872
