OpenSearch/docs/reference/transform/limitations.asciidoc

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[role="xpack"]
[[transform-limitations]]
=== {transform-cap} limitations
[subs="attributes"]
++++
<titleabbrev>Limitations</titleabbrev>
++++
beta[]
The following limitations and known problems apply to the 7.4 release of
the Elastic {dataframe} feature:
[float]
[[transform-compatibility-limitations]]
==== Beta {transforms} do not have guaranteed backwards or forwards compatibility
Whilst {transforms} are beta, it is not guaranteed that a
{transform} created in a previous version of the {stack} will be able
to start and operate in a future version. Neither can support be provided for
{transform} tasks to be able to operate in a cluster with mixed node
versions.
Please note that the output of a {transform} is persisted to a
destination index. This is a normal {es} index and is not affected by the beta
status.
[float]
[[transform-ui-limitation]]
==== {dataframe-cap} UI will not work during a rolling upgrade from 7.2
If your cluster contains mixed version nodes, for example during a rolling
upgrade from 7.2 to a newer version, and {transforms} have been
created in 7.2, the {dataframe} UI will not work. Please wait until all nodes
have been upgraded to the newer version before using the {dataframe} UI.
[float]
[[transform-datatype-limitations]]
==== {dataframe-cap} data type limitation
{dataframes-cap} do not (yet) support fields containing arrays in the UI or
the API. If you try to create one, the UI will fail to show the source index
table.
[float]
[[transform-ccs-limitations]]
==== {ccs-cap} is not supported
{ccs-cap} is not supported for {transforms}.
[float]
[[transform-kibana-limitations]]
==== Up to 1,000 {transforms} are supported
A single cluster will support up to 1,000 {transforms}.
When using the
{ref}/get-transform.html[GET {transforms} API] a total
`count` of {transforms} is returned. Use the `size` and `from` parameters to
enumerate through the full list.
[float]
[[transform-aggresponse-limitations]]
==== Aggregation responses may be incompatible with destination index mappings
When a {transform} is first started, it will deduce the mappings
required for the destination index. This process is based on the field types of
the source index and the aggregations used. If the fields are derived from
{ref}/search-aggregations-metrics-scripted-metric-aggregation.html[`scripted_metrics`]
or {ref}/search-aggregations-pipeline-bucket-script-aggregation.html[`bucket_scripts`],
{ref}/dynamic-mapping.html[dynamic mappings] will be used. In some instances the
deduced mappings may be incompatible with the actual data. For example, numeric
overflows might occur or dynamically mapped fields might contain both numbers
and strings. Please check {es} logs if you think this may have occurred. As a
workaround, you may define custom mappings prior to starting the
{transform}. For example,
{ref}/indices-create-index.html[create a custom destination index] or
{ref}/indices-templates.html[define an index template].
[float]
[[transform-batch-limitations]]
==== Batch {transforms} may not account for changed documents
A batch {transform} uses a
{ref}/search-aggregations-bucket-composite-aggregation.html[composite aggregation]
which allows efficient pagination through all buckets. Composite aggregations
do not yet support a search context, therefore if the source data is changed
(deleted, updated, added) while the batch {dataframe} is in progress, then the
results may not include these changes.
[float]
[[transform-consistency-limitations]]
==== {cdataframe-cap} consistency does not account for deleted or updated documents
While the process for {transforms} allows the continual recalculation
of the {transform} as new data is being ingested, it does also have
some limitations.
Changed entities will only be identified if their time field
has also been updated and falls within the range of the action to check for
changes. This has been designed in principle for, and is suited to, the use case
where new data is given a timestamp for the time of ingest.
If the indices that fall within the scope of the source index pattern are
removed, for example when deleting historical time-based indices, then the
composite aggregation performed in consecutive checkpoint processing will search
over different source data, and entities that only existed in the deleted index
will not be removed from the {dataframe} destination index.
Depending on your use case, you may wish to recreate the {transform}
entirely after deletions. Alternatively, if your use case is tolerant to
historical archiving, you may wish to include a max ingest timestamp in your
aggregation. This will allow you to exclude results that have not been recently
updated when viewing the {dataframe} destination index.
[float]
[[transform-deletion-limitations]]
==== Deleting a {transform} does not delete the {dataframe} destination index or {kib} index pattern
When deleting a {transform} using `DELETE _data_frame/transforms/index`
neither the {dataframe} destination index nor the {kib} index pattern, should
one have been created, are deleted. These objects must be deleted separately.
[float]
[[transform-aggregation-page-limitations]]
==== Handling dynamic adjustment of aggregation page size
During the development of {transforms}, control was favoured over
performance. In the design considerations, it is preferred for the
{transform} to take longer to complete quietly in the background
rather than to finish quickly and take precedence in resource consumption.
Composite aggregations are well suited for high cardinality data enabling
pagination through results. If a {ref}/circuit-breaker.html[circuit breaker]
memory exception occurs when performing the composite aggregated search then we
try again reducing the number of buckets requested. This circuit breaker is
calculated based upon all activity within the cluster, not just activity from
{transforms}, so it therefore may only be a temporary resource
availability issue.
For a batch {transform}, the number of buckets requested is only ever
adjusted downwards. The lowering of value may result in a longer duration for the
{transform} checkpoint to complete. For {cdataframes}, the number of
buckets requested is reset back to its default at the start of every checkpoint
and it is possible for circuit breaker exceptions to occur repeatedly in the
{es} logs.
The {transform} retrieves data in batches which means it calculates
several buckets at once. Per default this is 500 buckets per search/index
operation. The default can be changed using `max_page_search_size` and the
minimum value is 10. If failures still occur once the number of buckets
requested has been reduced to its minimum, then the {transform} will
be set to a failed state.
[float]
[[transform-dynamic-adjustments-limitations]]
==== Handling dynamic adjustments for many terms
For each checkpoint, entities are identified that have changed since the last
time the check was performed. This list of changed entities is supplied as a
{ref}/query-dsl-terms-query.html[terms query] to the {transform}
composite aggregation, one page at a time. Then updates are applied to the
destination index for each page of entities.
The page `size` is defined by `max_page_search_size` which is also used to
define the number of buckets returned by the composite aggregation search. The
default value is 500, the minimum is 10.
The index setting
{ref}/index-modules.html#dynamic-index-settings[`index.max_terms_count`] defines
the maximum number of terms that can be used in a terms query. The default value
is 65536. If `max_page_search_size` exceeds `index.max_terms_count` the
{transform} will fail.
Using smaller values for `max_page_search_size` may result in a longer duration
for the {transform} checkpoint to complete.
[float]
[[transform-scheduling-limitations]]
==== {cdataframe-cap} scheduling limitations
A {cdataframe} periodically checks for changes to source data. The functionality
of the scheduler is currently limited to a basic periodic timer which can be
within the `frequency` range from 1s to 1h. The default is 1m. This is designed
to run little and often. When choosing a `frequency` for this timer consider
your ingest rate along with the impact that the {transform}
search/index operations has other users in your cluster. Also note that retries
occur at `frequency` interval.
[float]
[[transform-failed-limitations]]
==== Handling of failed {transforms}
Failed {transforms} remain as a persistent task and should be handled
appropriately, either by deleting it or by resolving the root cause of the
failure and re-starting.
When using the API to delete a failed {transform}, first stop it using
`_stop?force=true`, then delete it.
[float]
[[transform-availability-limitations]]
==== {cdataframes-cap} may give incorrect results if documents are not yet available to search
After a document is indexed, there is a very small delay until it is available
to search.
A {ctransform} periodically checks for changed entities between the
time since it last checked and `now` minus `sync.time.delay`. This time window
moves without overlapping. If the timestamp of a recently indexed document falls
within this time window but this document is not yet available to search then
this entity will not be updated.
If using a `sync.time.field` that represents the data ingest time and using a
zero second or very small `sync.time.delay`, then it is more likely that this
issue will occur.