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Adds delay parameter explanation
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explore-analyze/transforms/transform-checkpoints.md

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Using a simple periodic timer, the {{transform}} checks for changes to the source indices. This check is done based on the interval defined in the transform’s `frequency` property.
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If new data is ingested with a slight delay, it might not be immediately available when the transform runs. To prevent missing documents, you can use the `delay` parameter in the `sync` configuration. This shifts the search window backward, ensuring that late-arriving data is included before a checkpoint processes it. Adjusting this value based on your data ingestion patterns can help ensure completeness.
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If the source indices remain unchanged or if a checkpoint is already in progress then it waits for the next timer.
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If changes are found a checkpoint is created.

explore-analyze/transforms/transform-usage.md

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* You want to create summary tables to optimize queries.
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For example, if you have a high level dashboard that is accessed by a large number of users and it uses a complex aggregation over a large dataset, it may be more efficient to create a {{transform}} to cache results. Thus, each user doesn’t need to run the aggregation query.
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* You need to account for late-arriving data.
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In some cases, data might not be immediately available when a transform runs, leading to missing records in the destination index. This can happen due to ingestion delays, where documents take a few seconds or minutes to become searchable after being indexed. To handle this, the `delay` parameter in the transform’s sync configuration allows you to postpone processing new data. Instead of always querying the most recent records, the transform will skip a short period of time (e.g., 60 seconds) to ensure all relevant data has arrived before processing.
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For example, if a transform runs every 5 minutes, it usually processes data from 5 minutes ago up to the current time. However, if you set `delay` to 60 seconds, the transform will instead process data from 6 minutes ago up to 1 minute ago, making sure that any documents that arrived late are included. By adjusting the `delay` parameter, you can improve the accuracy of transformed data while still maintaining near real-time results.

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