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Copy file name to clipboardExpand all lines: articles/search/search-howto-index-cosmosdb-gremlin.md
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@@ -74,7 +74,7 @@ For this call, specify a [preview REST API version](search-api-preview.md) (2020
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1. Set "container" to the collection. The "name" property is required and it specifies the ID of the graph. The "query" property is optional. The query default is `g.V()`. To index the edges, set the query to `g.E()`.
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<!--1. [Set "dataChangeDetectionPolicy"](#DataChangeDetectionPolicy) if data is volatile and you want the indexer to pick up just the new and updated items on subsequent runs. Incremental progress will be enabled by default using `_ts` as the high water mark column.-->
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1.[Set "dataChangeDetectionPolicy"](#DataChangeDetectionPolicy) if data is volatile and you want the indexer to pick up just the new and updated items on subsequent runs. Incremental progress will be enabled by default using `_ts` as the high water mark column.
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1.[Set "dataDeletionDetectionPolicy"](#DataDeletionDetectionPolicy) if you want to remove search documents from a search index when the source item is deleted.
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1. [Specify field mappings](search-indexer-field-mappings.md) if there are differences in field name or type, or if you need multiple versions of a source field in the search index.
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1. See [Create an indexer](search-howto-create-indexers.md) for more information about other properties.
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<a name="DataChangeDetectionPolicy"></a>
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## Indexing changed documents
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The purpose of a data change detection policy is to efficiently identify changed data items. Currently, the only supported policy is the [`HighWaterMarkChangeDetectionPolicy`](/dotnet/api/azure.search.documents.indexes.models.highwatermarkchangedetectionpolicy) using the `_ts` (timestamp) property provided by Azure Cosmos DB, which is specified in the data source definition as follows:
Copy file name to clipboardExpand all lines: articles/search/search-howto-index-cosmosdb-mongodb.md
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Using this policy is highly recommended to ensure good indexer performance.
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<aname="IncrementalProgress"></a>
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### Incremental progress and custom queries
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Incremental progress during indexing ensures that if indexer execution is interrupted by transient failures or execution time limit, the indexer can pick up where it left off next time it runs, instead of having to reindex the entire collection from scratch. This is especially important when indexing large collections.
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To enable incremental progress when using a custom query, ensure that your query orders the results by the `_ts` column. This enables periodic check-pointing that Azure Cognitive Search uses to provide incremental progress in the presence of failures.
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In some cases, even if your query contains an `ORDER BY [collection alias]._ts` clause, Azure Cognitive Search may not infer that the query is ordered by the `_ts`. You can tell Azure Cognitive Search that results are ordered by using the `assumeOrderByHighWaterMarkColumn` configuration property. To specify this hint, create or update your indexer as follows:
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