2016-03-13 16:17:48 -04:00
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[[breaking_50_mapping_changes]]
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=== Mapping changes
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==== `string` fields replaced by `text`/`keyword` fields
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The `string` field datatype has been replaced by the `text` field for full
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text analyzed content, and the `keyword` field for not-analyzed exact string
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values. For backwards compatibility purposes, during the 5.x series:
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* `string` fields on pre-5.0 indices will function as before.
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* New `string` fields can be added to pre-5.0 indices as before.
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* `text` and `keyword` fields can also be added to pre-5.0 indices.
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* When adding a `string` field to a new index, the field mapping will be
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rewritten as a `text` or `keyword` field if possible, otherwise
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an exception will be thrown. Certain configurations that were possible
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with `string` fields are no longer possible with `text`/`keyword` fields
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such as enabling `term_vectors` on a not-analyzed `keyword` field.
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2016-03-18 12:01:27 -04:00
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==== Default string mappings
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String mappings now have the following default mappings:
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2016-05-12 12:43:01 -04:00
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[source,js]
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2016-03-18 12:01:27 -04:00
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---------------
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{
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"type": "text",
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"fields": {
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"keyword": {
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"type": "keyword",
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"ignore_above": 256
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}
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}
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}
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---------------
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This allows to perform full-text search on the original field name and to sort
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and run aggregations on the sub keyword field.
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Use the new points API to index numeric fields. #17746
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. #17700
Closes #16751
Closes #17007
Closes #11513
2016-04-01 05:07:35 -04:00
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==== Numeric fields
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Numeric fields are now indexed with a completely different data-structure, called
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BKD tree, that is expected to require less disk space and be faster for range
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queries than the previous way that numerics were indexed.
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Term queries will return constant scores now, while they used to return higher
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scores for rare terms due to the contribution of the document frequency, which
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this new BKD structure does not record. If scoring is needed, then it is advised
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to map the numeric fields as <<keyword,`keyword`s>> too.
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Note that this <<keyword,`keyword`>> mapping do not need to replace the numeric
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mapping. For instance if you need both sorting and scoring on your numeric field,
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you could map it both as a number and a `keyword` using <<multi-fields>>:
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[source,js]
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--------------------------------------------------
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2016-04-29 10:42:03 -04:00
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PUT my_index
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Use the new points API to index numeric fields. #17746
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. #17700
Closes #16751
Closes #17007
Closes #11513
2016-04-01 05:07:35 -04:00
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{
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"mappings": {
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"my_type": {
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"properties": {
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"my_number": {
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"type": "long",
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"fields": {
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"keyword": {
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"type": "keyword"
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}
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}
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}
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}
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}
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}
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}
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--------------------------------------------------
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2016-05-09 09:42:23 -04:00
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// CONSOLE
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Use the new points API to index numeric fields. #17746
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. #17700
Closes #16751
Closes #17007
Closes #11513
2016-04-01 05:07:35 -04:00
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Also the `precision_step` parameter is now irrelevant and will be rejected on
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indices that are created on or after 5.0.
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2016-06-20 12:06:31 -04:00
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==== `_timestamp` and `_ttl`
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The `_timestamp` and `_ttl` fields were deprecated and are now removed. As a
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replacement for `_timestamp`, you should populate a regular date field with the
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current timestamp on application side. For `_ttl`, you should either use
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time-based indices when applicable, or cron a delete-by-query with a range
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query on a timestamp field
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2016-03-13 16:17:48 -04:00
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==== `index` property
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On all field datatypes (except for the deprecated `string` field), the `index`
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property now only accepts `true`/`false` instead of `not_analyzed`/`no`. The
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`string` field still accepts `analyzed`/`not_analyzed`/`no`.
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==== Doc values on unindexed fields
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Previously, setting a field to `index:no` would also disable doc-values. Now,
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doc-values are always enabled on numeric and boolean fields unless
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`doc_values` is set to `false`.
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==== Floating points use `float` instead of `double`
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When dynamically mapping a field containing a floating point number, the field
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now defaults to using `float` instead of `double`. The reasoning is that
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floats should be more than enough for most cases but would decrease storage
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requirements significantly.
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2016-03-18 12:01:27 -04:00
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==== `norms`
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`norms` now take a boolean instead of an object. This boolean is the replacement
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for `norms.enabled`. There is no replacement for `norms.loading` since eager
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loading of norms is not useful anymore now that norms are disk-based.
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2016-03-13 16:17:48 -04:00
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==== `fielddata.format`
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Setting `fielddata.format: doc_values` in the mappings used to implicitly
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enable doc-values on a field. This no longer works: the only way to enable or
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disable doc-values is by using the `doc_values` property of mappings.
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2016-04-18 15:00:27 -04:00
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==== `fielddata.filter.regex`
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2016-03-18 12:01:27 -04:00
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Regex filters are not supported anymore and will be dropped on upgrade.
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2016-03-13 16:17:48 -04:00
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==== Source-transform removed
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The source `transform` feature has been removed. Instead, use an ingest pipeline
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==== `_parent` field no longer indexed
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The join between parent and child documents no longer relies on indexed fields
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and therefore from 5.0.0 onwards the `_parent` field is no longer indexed. In
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2016-04-26 02:35:42 -04:00
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order to find documents that refer to a specific parent id, the new
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2016-03-13 16:17:48 -04:00
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`parent_id` query can be used. The GET response and hits inside the search
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response still include the parent id under the `_parent` key.
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==== Source `format` option
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The `_source` mapping no longer supports the `format` option. It will still be
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accepted for indices created before the upgrade to 5.0 for backwards
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compatibility, but it will have no effect. Indices created on or after 5.0
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will reject this option.
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==== Object notation
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Core types no longer support the object notation, which was used to provide
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per document boosts as follows:
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2016-05-12 12:43:01 -04:00
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[source,js]
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2016-03-13 16:17:48 -04:00
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---------------
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{
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"value": "field_value",
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"boost": 42
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}
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---------------
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==== Boost accuracy for queries on `_all`
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Per-field boosts on the `_all` are now compressed into a single byte instead
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of the 4 bytes used previously. While this will make the index much more
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space-efficient, it also means that index time boosts will be less accurately
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encoded.
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2016-06-21 15:33:25 -04:00
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==== `_ttl` and `_timestamp` cannot be created
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You can no longer create indexes with `_ttl` or `_timestamp` enabled. Indexes
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with them enabled created before 5.0 will continue to work.
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You should replace `_timestamp` in new indexes by adding a field to your source
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either in the application producing the data or with an ingest pipline like
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this one:
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[source,js]
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---------------
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PUT _ingest/pipeline/timestamp
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{
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"description" : "Adds a timestamp field at the current time",
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"processors" : [ {
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"set" : {
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"field": "timestamp",
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"value": "{{_ingest.timestamp}}"
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}
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} ]
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}
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PUT newindex/type/1?pipeline=timestamp
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{
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"example": "data"
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}
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GET newindex/type/1
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---------------
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// CONSOLE
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Which produces
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[source,js]
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---------------
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{
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"_source": {
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"example": "data",
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"timestamp": "2016-06-21T18:48:55.560+0000"
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},
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...
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}
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---------------
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// TESTRESPONSE[s/\.\.\./"found": true, "_id": "1", "_index": "newindex", "_type": "type", "_version": 1/]
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// TESTRESPONSE[s/"2016-06-21T18:48:55.560\+0000"/"$body._source.timestamp"/]
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If you have an old index created with 2.x that has `_timestamp` enabled then
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you can migrate it to a new index with the a `timestamp` field in the source
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with reindex:
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[source,js]
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---------------
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POST _reindex
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{
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"source": {
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"index": "oldindex"
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},
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"dest": {
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"index": "newindex"
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},
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"script": {
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"lang": "painless",
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"inline": "ctx._source.timestamp = ctx._timestamp; ctx._timestamp = null"
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}
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}
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---------------
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// CONSOLE
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// TEST[s/^/PUT oldindex\nGET _cluster\/health?wait_for_status=yellow\n/]
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You can replace `_ttl` with time based index names (preferred) or by adding a
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cron job which runs a delete-by-query on a timestamp field in the source
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document. If you had documents like this:
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[source,js]
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---------------
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POST index/type/_bulk
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{"index":{"_id":1}}
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{"example": "data", "timestamp": "2016-06-21T18:48:55.560+0000" }
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{"index":{"_id":2}}
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{"example": "data", "timestamp": "2016-04-21T18:48:55.560+0000" }
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---------------
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// CONSOLE
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Then you could delete all of the documents from before June 1st with:
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[source,js]
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---------------
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POST index/type/_delete_by_query
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{
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"query": {
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"range" : {
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"timestamp" : {
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"lt" : "2016-05-01"
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}
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}
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}
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}
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---------------
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// CONSOLE
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// TEST[continued]
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IMPORTANT: Keep in mind that deleting documents from an index is very expensive
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compared to deleting whole indexes. That is why time based indexes are
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recommended over this sort of thing and why `_ttl` was deprecated in the first
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place.
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