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<!--This reference applies to both [data flows](overview-dataflow.md) and [data flow graphs](concept-dataflow-graphs.md). Both use the same expression language for map, filter, and enrichment transforms. Data flow graphs also support branch and window (accumulate) transforms, which are noted where applicable.-->
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This reference applies to both [data flows](overview-dataflow.md) and [data flow graphs](concept-dataflow-graphs.md). Both use the same expression language for map, filter, and enrichment transforms. Data flow graphs also support branch and window (accumulate) transforms, which are noted where applicable.
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## Positional variables
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|`first($n)`| First value in the window | Error |
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|`last($n)`| Last value in the window | Error |
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<!--For details on using aggregation functions, see [Aggregate data over time](howto-dataflow-graphs-window.md).-->
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For details on using aggregation functions, see [Aggregate data over time](howto-dataflow-graphs-window.md).
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## Conditional logic
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## Related content
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-[Map data by using data flows](concept-dataflow-mapping.md)
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<!--- [Filter data in a data flow](howto-dataflow-filter.md)
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-[Filter data in a data flow](howto-dataflow-filter.md)
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-[Transform data with map in data flow graphs](howto-dataflow-graphs-map.md)
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-[Filter and route data in data flow graphs](howto-dataflow-graphs-filter-route.md)
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-[Aggregate data over time](howto-dataflow-graphs-window.md)
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- [Enrich with external data](howto-dataflow-graphs-enrich.md)-->
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-[Enrich with external data](howto-dataflow-graphs-enrich.md)
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}
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```
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<!-- When using storage destinations (ADLS, Fabric, ADX), the output schema and serialization format are configured on the destination endpoint. See [Configure a data flow destination](howto-configure-dataflow-destination.md#serialize-the-output-with-a-schema). -->
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When using storage destinations (ADLS, Fabric, ADX), the output schema and serialization format are configured on the destination endpoint. See [Configure a data flow destination](howto-configure-dataflow-destination.md#serialize-the-output-with-a-schema).
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# [Kubernetes (preview)](#tab/kubernetes)
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dataDestination: my-container
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```
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<!-- When using storage destinations (ADLS, Fabric, ADX), the output schema and serialization format are configured on the destination endpoint. See [Configure a data flow destination](howto-configure-dataflow-destination.md#serialize-the-output-with-a-schema). -->
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When using storage destinations (ADLS, Fabric, ADX), the output schema and serialization format are configured on the destination endpoint. See [Configure a data flow destination](howto-configure-dataflow-destination.md#serialize-the-output-with-a-schema).
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---
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## What are data flow graphs?
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<!--A [data flow graph](concept-dataflow-graphs.md) is a composable, graph-based pipeline that connects multiple transforms in any topology you define. You can chain, branch, and merge processing steps. Each transform is a pre-built processing unit (map, filter, branch, window, enrichment) that you configure with rules. You configure a data flow graph by creating a `DataflowGraph` custom resource.-->
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A [data flow graph](concept-dataflow-graphs.md) is a composable, graph-based pipeline that connects multiple transforms in any topology you define. You can chain, branch, and merge processing steps. Each transform is a pre-built processing unit (map, filter, branch, window, enrichment) that you configure with rules. You configure a data flow graph by creating a `DataflowGraph` custom resource.
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Data flow graphs are in preview and support MQTT, Kafka, and OpenTelemetry endpoints.
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-**Endpoints**: Both use `DataflowEndpoint` resources to connect to MQTT brokers, Kafka, storage, and other services. See [Prepare endpoints](howto-configure-dataflow-endpoint.md).
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-**Profiles**: Both reference a `DataflowProfile` for scaling and instance configuration. See [Manage data flow profiles](howto-configure-dataflow-profile.md).
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<!--- **Source configuration**: Both support the same source endpoint options (default broker, asset, custom endpoint) and data source (topic) configuration. See [Configure a source](howto-configure-dataflow-source.md).
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-**Source configuration**: Both support the same source endpoint options (default broker, asset, custom endpoint) and data source (topic) configuration. See [Configure a source](howto-configure-dataflow-source.md).
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-**Destination configuration**: Both support static and dynamic destination topics. See [Configure a destination](howto-configure-dataflow-destination.md).
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- **Disk persistence**: Both support `requestDiskPersistence` to survive restarts. See [Configure disk persistence](howto-configure-disk-persistence.md).-->
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-**Disk persistence**: Both support `requestDiskPersistence` to survive restarts. See [Configure disk persistence](howto-configure-disk-persistence.md).
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## When to use which
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