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Merge pull request #18013 from pmasl/patch-923
Update intelligent-query-processing.md
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docs/relational-databases/performance/intelligent-query-processing.md

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# Intelligent query processing in SQL databases
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[!INCLUDE [SQL Server Azure SQL Database](../../includes/applies-to-version/sql-asdb.md)]
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[!INCLUDE [SQL Server Azure SQL Database Azure SQL Managed Instance](../../includes/applies-to-version/sql-asdb-asdbmi.md)]
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The intelligent query processing (IQP) feature family includes features with broad impact that improve the performance of existing workloads with minimal implementation effort to adopt.
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The following table details all intelligent query processing features, along with any requirement they have for database compatibility level.
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| **IQP Feature** | **Supported in Azure SQL Database** | **Supported in SQL Server** |**Description** |
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| --- | --- | --- |--- |
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| **IQP Feature** | **Supported in [!INCLUDE[ssSDSfull](../../includes/sssdsfull-md.md)] and [!INCLUDE[ssSDSMIfull](../../includes/sssdsmifull-md.md)]** | **Supported in [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)]** |**Description** |
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| ---------------- | ------- | ------- | ---------------- |
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| [Adaptive Joins (Batch Mode)](#batch-mode-adaptive-joins) | Yes, under compatibility level 140| Yes, starting in [!INCLUDE[ssSQL17](../../includes/sssql17-md.md)] under compatibility level 140|Adaptive joins dynamically select a join type during runtime based on actual input rows.|
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| [Approximate Count Distinct](#approximate-query-processing) | Yes| Yes, starting in [!INCLUDE[sql-server-2019](../../includes/sssqlv15-md.md)]|Provide approximate COUNT DISTINCT for big data scenarios with the benefit of high performance and a low memory footprint. |
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| [Batch Mode on Rowstore](#batch-mode-on-rowstore) | Yes, under compatibility level 150| Yes, starting in [!INCLUDE[sql-server-2019](../../includes/sssqlv15-md.md)] under compatibility level 150|Provide batch mode for CPU-bound relational DW workloads without requiring columnstore indexes. |
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1. An initial check of table sizes, operators used, and estimated cardinalities in the input query.
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2. Additional checkpoints, as the optimizer discovers new, cheaper plans for the query. If these alternative plans don't make significant use of batch mode, the optimizer stops exploring batch mode alternatives.
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If batch mode on rowstore is used, you see the actual run mode as **batch mode** in the query plan. The scan operator uses batch mode for on-disk heaps and B-tree indexes. This batch mode scan can evaluate batch mode bitmap filters. You might also see other batch mode operators in the plan. Examples are hash joins, hash-based aggregates, sorts, window aggregates, filters, concatenation, and compute scalar operators.
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### Remarks

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