[GitHub] [druid] techdocsmith commented on a change in pull request #10935: First refactor of compaction

[GitBox <gi...@apache.org>]

techdocsmith commented on a change in pull request #10935:
URL: https://github.com/apache/druid/pull/10935#discussion_r590830543



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File path: docs/ingestion/compaction.md
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+---
+id: compaction
+title: "Compaction"
+description: "Defines compaction and automatic compaction (auto-compaction or autocompaction) as a strategy for segment optimization. Use cases for compaction. Describes compaction task configuration."
+---
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+
+Compaction in Apache Druid is a strategy to optimize segment size. Compaction tasks read an existing set of segments for a given time range and combine the data into a new "compacted" set of segments. The compacted segments are generally larger, but there are fewer of them. Compaction can sometimes increase performance because it reduces the number of segments and, consequently, the per-segment processing and the memory overhead required for ingestion and for querying paths.
+
+As a strategy, compaction is effective when you have data arriving out of chronological order resulting in lots of small segments. For example if you are appending data using `appendToExisting` for [native batch](./native_batch.md) ingestion. Conversely, if you are rewriting your data with each ingestion task, you don't need to use compaction. See [Segment optimization](../operations/segment-optimization.md) for guidance to determine if compaction will help in your case.
+
+## Types of segment compaction
+You can configure the Druid Coordinator to perform automatic compaction, also called auto-compaction, for a datasource. Using a segment search policy, the coordinator periodically identifies segments for compaction starting with the newest to oldest. When segments can benefit from compaction, the coordinator automatically submits a compaction task. 
+
+Automatic compaction works in most use cases and should be your first option. To learn more about automatic compaction, see [Compacting Segments](../design/coordinator.md#compacting-segments).
+
+In cases where you require more control over compaction, you can manually submit compaction tasks. For example:
+- Automatic compaction is too slow.
+- You want to force compaction for a specific time range.
+- Compacting recent data before older data suboptimal is suboptimal in your environment.
+
+See [Setting up a manual compaction task](#setting-up-manual-compaction) more about manual compaction tasks.
+
+
+## Data handling with compaction
+During compaction, Druid overwrites the original set of segments with the compacted set without modifying the data. During compaction Druid locks the segments for the time interval being compacted to ensure data consistency.
+
+If an ingestion task needs to write data to a segment for a time interval locked for compaction, the ingestion task supersedes the compaction task and the compaction task fails without finishing. For manual compaction tasks you can adjust the input spec interval to avoid conflicts between ingestion and compaction. For automatic compaction, you can set the `skipOffsetFromLatest` key to adjustment the auto compaction starting point from the current time to reduce the chance of conflicts between ingestion and compaction. See [Compaction dynamic configuration](../configuration/index.md#compaction-dynamic-configuration) for more information.
+
+### Segment granularity handling
+
+Unless you modify the segment granularity in the [granularity spec](#compaction-granularity-spec), Druid attempts to retain the granularity for the compacted segments. When segments have different segment granularities with no overlap in interval Druid creates a separate compaction task for each to retain the segment granularity in the compacted segment. If segments have different segment granularities before compaction but there is some overlap in interval, Druid attempts find start and end of the overlapping interval and uses the closest segment granularity level for the compacted segment.

Review comment:
       @maytasm , I think by trying to clarify the behavior here, I made it more confusing. Can you help me with @2bethere 's questions?




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