elasticsearch/docs/reference/transform/limitations.asciidoc

[role="xpack"]
[[transform-limitations]]
= {transform-cap} limitations
[subs="attributes"]
++++
<titleabbrev>Limitations</titleabbrev>
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The following limitations and known problems apply to the {version} release of 
the Elastic {transform} feature:

[discrete]
[[transform-ui-limitation]]
== {transforms-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 {transforms} UI (earler {dataframe} UI) will not work. Please wait until all 
nodes have been upgraded to the newer version before using the {transforms} UI.

[discrete]
[[transform-rolling-upgrade-limitation]]
== {transforms-cap} reassignment suspended during a rolling upgrade from 7.2 and 7.3

If your cluster contains mixed version nodes, for example during a rolling
upgrade from 7.2 or 7.3 to a newer version, {transforms} whose nodes are stopped 
will not be reassigned until the upgrade is complete. After the upgrade is done, 
{transforms} resume automatically; no action is required.

[discrete]
[[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.

[discrete]
[[transform-kibana-limitations]]
== Up to 1,000 {transforms} are supported

A single cluster will support up to 1,000 {transforms}. When using the 
<<get-transform,GET {transforms} API>> a total `count` of {transforms} 
is returned. Use the `size` and `from` parameters to enumerate through the full 
list.

[discrete]
[[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 
<<search-aggregations-metrics-scripted-metric-aggregation,`scripted_metrics`>>
or <<search-aggregations-pipeline-bucket-script-aggregation,`bucket_scripts`>>, 
<<dynamic-mapping,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, 
<<indices-create-index,create a custom destination index>> or 
<<indices-templates,define an index template>>.

[discrete]
[[transform-batch-limitations]]
== Batch {transforms} may not account for changed documents

A batch {transform} uses a 
<<search-aggregations-bucket-composite-aggregation,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.

[discrete]
[[transform-consistency-limitations]]
== {ctransform-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 destination index.

[discrete]
[[transform-deletion-limitations]]
== Deleting a {transform} does not delete the destination index or {kib} index pattern

When deleting a {transform} using `DELETE _transform/index` 
neither the destination index nor the {kib} index pattern, should one have been 
created, are deleted. These objects must be deleted separately.

[discrete]
[[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 <<circuit-breaker,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 {ctransforms}, 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.

[discrete]
[[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 
<<query-dsl-terms-query,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 <<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.

[discrete]
[[transform-scheduling-limitations]]
== {ctransform-cap} scheduling limitations

A {ctransform} 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.

[discrete]
[[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.

[discrete]
[[transform-availability-limitations]]
== {ctransforms-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.

[discrete]
[[transform-date-nanos]]
== Support for date nanoseconds data type

If your data uses the <<date_nanos,date nanosecond data type>>, aggregations
are nonetheless on millisecond resolution. This limitation also affects the
aggregations in your {transforms}.


[discrete]
[[transform-data-streams-destination]]
== Data streams as destination indices are not supported

{transforms-cap} update data in the destination index which requires writing 
into the destination. <<data-streams>> are designed to be append-only, which 
means you cannot send update or delete requests directly to a data stream. For 
this reason, data streams are not supported as destination indices for 
{transforms}.


[discrete]
[[transform-ilm-destination]]
== ILM as destination index may cause duplicated documents

<<index-lifecycle-management,ILM>> is not recommended to use as a {transform} 
destination index. {transforms-cap} update documents in the current destination, 
and cannot delete documents in the indices previously used by ILM. This may lead 
to duplicated documents when you use {transforms} combined with ILM in case of a 
rollover.

If you use ILM to have time-based indices, please consider using the 
<<date-index-name-processor>> instead. The processor works without duplicated 
documents if your {transform} contains a `group_by` based on `date_histogram`.


[discrete]
[[transform-painless-imitation]]
== Using scripts in {transforms}

{transforms-cap} support scripting in every case when aggregations support them. 
However, there are certain factors you might want to consider when using scripts 
in {transforms}:

* {transforms-cap} cannot deduce index mappings for output fields when the 
  fields are created by a script. In this case, you might want to create the 
  mappings of the destination index yourself prior to creating the transform.

* Scripted fields may increase the runtime of the {transform}.
  
* {transforms-cap} cannot optimize queries when you use scripts for all the 
  groupings defined in `group_by`, you will receive a warning message when you 
  use scripts this way.