89 lines
3.8 KiB
Plaintext
89 lines
3.8 KiB
Plaintext
[role="xpack"]
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[[transform-checkpoints]]
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=== How {transform} checkpoints work
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++++
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<titleabbrev>How checkpoints work</titleabbrev>
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++++
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beta[]
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Each time a {transform} examines the source indices and creates or
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updates the destination index, it generates a _checkpoint_.
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If your {transform} runs only once, there is logically only one
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checkpoint. If your {transform} runs continuously, however, it creates
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checkpoints as it ingests and transforms new source data.
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To create a checkpoint, the {ctransform}:
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. Checks for changes to source indices.
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+
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Using a simple periodic timer, the {transform} checks for changes to
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the source indices. This check is done based on the interval defined in the
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transform's `frequency` property.
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+
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If the source indices remain unchanged or if a checkpoint is already in progress
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then it waits for the next timer.
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. Identifies which entities have changed.
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+
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The {transform} searches to see which entities have changed since the
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last time it checked. The `sync` configuration object in the {transform}
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identifies a time field in the source indices. The {transform} uses the values
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in that field to synchronize the source and destination indices.
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. Updates the destination index (the {dataframe}) with the changed entities.
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+
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--
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The {transform} applies changes related to either new or changed
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entities to the destination index. The set of changed entities is paginated. For
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each page, the {transform} performs a composite aggregation using a
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`terms` query. After all the pages of changes have been applied, the checkpoint
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is complete.
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--
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This checkpoint process involves both search and indexing activity on the
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cluster. We have attempted to favor control over performance while developing
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{transforms}. We decided it was preferable for the
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{transform} to take longer to complete, rather than to finish quickly
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and take precedence in resource consumption. That being said, the cluster still
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requires enough resources to support both the composite aggregation search and
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the indexing of its results.
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TIP: If the cluster experiences unsuitable performance degradation due to the
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{transform}, stop the {transform}. Consider whether you can apply a
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source query to the {transform} to reduce the scope of data it
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processes. Also consider whether the cluster has sufficient resources in place
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to support both the composite aggregation search and the indexing of its
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results.
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[discrete]
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[[ml-transform-checkpoint-errors]]
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==== Error handling
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Failures in {transforms} tend to be related to searching or indexing.
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To increase the resiliency of {transforms}, the cursor positions of
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the aggregated search and the changed entities search are tracked in memory and
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persisted periodically.
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Checkpoint failures can be categorized as follows:
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* Temporary failures: The checkpoint is retried. If 10 consecutive failures
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occur, the {transform} has a failed status. For example, this
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situation might occur when there are shard failures and queries return only
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partial results.
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* Irrecoverable failures: The {transform} immediately fails. For
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example, this situation occurs when the source index is not found.
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* Adjustment failures: The {transform} retries with adjusted settings.
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For example, if a parent circuit breaker memory errors occur during the
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composite aggregation, the {transform} receives partial results. The aggregated
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search is retried with a smaller number of buckets. This retry is performed at
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the interval defined in the `frequency` property for the {transform}. If the
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search is retried to the point where it reaches a minimal number of buckets, an
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irrecoverable failure occurs.
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If the node running the {transforms} fails, the {transform} restarts
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from the most recent persisted cursor position. This recovery process might
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repeat some of the work the {transform} had already done, but it ensures data
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consistency.
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