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articles/synapse-analytics/spark/apache-spark-overview.md

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![Diagram shows Spark SQL, Spark MLib, and GraphX linked to the Spark core engine, above a YARN layer over storage services.](./media/apache-spark-overview/spark-overview.png)
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To learn more, see the following video:
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> [!VIDEO https://www.youtube.com/embed/v=bTdu3PjXN3o]
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## What is Apache Spark
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Apache Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications. Spark also integrates with multiple programming languages to let you manipulate distributed data sets like local collections. There's no need to structure everything as map and reduce operations.
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Apache Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications. Spark also integrates with multiple programming languages to let you manipulate distributed data sets like local collections. There's no need to structure everything as map and reduce operations. You can learn more from the [Apache Spark for Synapse video](https://www.youtube.com/watch?v=bTdu3PjXN3o).
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![Diagram shows Traditional MapReduce, with disk-based apps and Spark, with cache-based operations.](./media/apache-spark-overview/map-reduce-vs-spark.png)
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articles/synapse-analytics/spark/apache-spark-what-is-delta-lake.md

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Delta Lake is an open-source storage layer that brings ACID (atomicity, consistency, isolation, and durability) transactions to Apache Spark and big data workloads.
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The current version of Delta Lake included with Azure Synapse has language support for Scala, PySpark, and .NET and is compatible with Linux Foundation Delta Lake. There are links at the bottom of the page to more detailed examples and documentation.
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To learn more on Delta Lake and Delta tables, see the following video:
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> [!VIDEO https://www.youtube.com/watch?v=B_wyRXlLKok]
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The current version of Delta Lake included with Azure Synapse has language support for Scala, PySpark, and .NET and is compatible with Linux Foundation Delta Lake. There are links at the bottom of the page to more detailed examples and documentation. You can learn more from the [Introduction to Delta Tables video](https://www.youtube.com/watch?v=B_wyRXlLKok).
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## Key features
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articles/synapse-analytics/sql/on-demand-workspace-overview.md

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Serverless SQL pool is a query service over the data in your data lake. It enables you to access your data through the following functionalities:
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- A familiar [T-SQL syntax](overview-features.md) to query data in place without the need to copy or load data into a specialized store. To learn more, see the [T-SQL support](#t-sql-support) section.
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- Integrated connectivity via the T-SQL interface that offers a wide range of business intelligence and ad-hoc querying tools, including the most popular drivers. To learn more, see the [Client tools](#client-tools) section.
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To learn more, see the following video:
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> [!VIDEO https://www.youtube.com/watch?v=rDl58M5PyVw]
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- Integrated connectivity via the T-SQL interface that offers a wide range of business intelligence and ad-hoc querying tools, including the most popular drivers. To learn more, see the [Client tools](#client-tools) section. You can learn more from the [Introduction into Synapse Serverless SQL Pools video](https://www.youtube.com/watch?v=rDl58M5PyVw).
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Serverless SQL pool is a distributed data processing system, built for large-scale data and computational functions. Serverless SQL pool enables you to analyze your Big Data in seconds to minutes, depending on the workload. Thanks to built-in query execution fault-tolerance, the system provides high reliability and success rates even for long-running queries involving large data sets.
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articles/synapse-analytics/sql/query-delta-lake-format.md

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A serverless SQL pool can read Delta Lake files that are created using Apache Spark, Azure Databricks, or any other producer of the Delta Lake format.
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Apache Spark pools in Azure Synapse enable data engineers to modify Delta Lake files using Scala, PySpark, and .NET. Serverless SQL pools help data analysts to create reports
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on Delta Lake files created by data engineers.
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Optionally you can also learn how to query delta lake tables in the following video:
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> [!VIDEO https://www.youtube.com/watch?v=LSIVX0XxVfc]
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on Delta Lake files created by data engineers. You can learn more from the [how to query delta lake tables video](https://www.youtube.com/watch?v=LSIVX0XxVfc).
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## Quickstart example
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