Azure Data Factory: Visual Tools enabled in public preview

Data di pubblicazione: 16 gennaio, 2018

Senior Program Manager, Azure Data Factory

Azure Data Factory (ADF) v2 public preview was announced at Microsoft Ignite on Sep 25, 2017. With ADF v2, we added flexibility to ADF app model and enabled control flow constructs that now facilitates looping, branching, conditional constructs, on-demand executions and flexible scheduling in various programmatic interfaces like Python, .Net, Powershell, REST APIs, ARM templates. One of the consistent pieces of customer feedback we received, is to enable a rich interactive visual authoring and monitoring experience allowing users to create, configure, test, deploy and monitor data integration pipelines without any friction. We listened to your feedback and are happy to announce the release of visual tools for ADF v2. The main goal of the ADF visual tools is to allow you to be productive with ADF by getting pipelines up & running quickly without requiring to write a single line of code. You can use a simple and intuitive code free interface to drag and drop activities on a pipeline canvas, perform test runs, debug iteratively, deploy & monitor your pipeline runs. With this release, we are also providing guided tours on how to use the enabled visual authoring & monitoring features and also an ability to give us valuable feedback.

Our goal with visual tools for ADF v2 is to increase productivity and efficiency for both new and advanced users with intuitive experiences. You can get started by clicking the Author & Monitor tile in your provisioned v2 data factory blade.

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Check out some of the exciting features enabled with the new visual tools in ADF v2. You can also watch the short video below.

 

Get Started Quickly

  1. Create your first ADF v2 pipeline

  2. Quickly Copy Data from a bunch of data sources using the copy wizard

  3. Configure SSIS IR to lift and shift SSIS packages to Azure

  4. Set up code repo (VSTS GIT) for source control, collaboration, versioning etc..

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Visual Authoring

Author Control Flow Pipelines

Create pipelines, drag and drop activities, connect them on-success, on-failure, on-completion.

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Create Azure & Self Hosted Integration runtimes

Create a self hosted integration runtime for hybrid data movement or an Azure-SSIS IR for lifting and shifting SSIS packages to Azure. Create linked service connections to your data stores or compute.

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Support for all control flow activities running on Azure computes

Control Flow Activities:

  • HDInsight Hive, HDInsight Pig, HDInsight Map Reduce, HDI Streaming, HDI Spark, U-SQL, Stored Procedure, Web, For Each, Get Metadata, Look up, Execute Pipeline

Support for Azure Computes:

  • HDI (on-demand, BYOC), ADLA, Azure Batch

Iterative development and debugging

Do Test Runs before attaching a trigger on the pipeline and running on-demand or on a schedule.

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Parameterize pipelines and datasets

Parameterize using expressions, system variables.

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Rich Validation Support

You can now validate your pipelines to know about missed property configurations or incorrect configurations. Simply click the Validate button in the pipeline canvas. This will generate the validation output in side drawer. You can then click on each entry to go straight to the location of the missing validation.

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Trigger pipelines

Trigger on-demand, run pipelines on schedule.

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Use VSTS GIT

VSTS GIT for source control, collaboration, versioning, etc.

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Copy Data

Data Stores (65)

Support for 65 data stores. 18 stores with first class support that require users to provide just configuration values. The remaining 47 stores can be used with JSON.

18 stores with first class support:

  • Azure Blob, Azure CosmosDB, Azure Database for MySQL, Azure Data Lake Store, Amazon Redshift, Amazon S3, Azure SQL DW, Azure SQL, Azure Table, File System, HDFS, MySQL, ODBC, Oracle, Salesforce, SAP HANA, SAP BW, SQL Server

47 Stores with JSON support:

  • Search Index, Cassandra, HTTP file, Mongo DB, OData, Relational table, Dynamics 365, Dynamics CRM, Web table, AWS Marketplace, PostgreSQL, Concur, Couchbase, Drill, Oracle Eloqua, Google Big Query, Greenplum, HBase, Hive, HubSpot, Apache Impala, Jira, Magento, MariaDB, Marketo, PayPal, Phoenix, Presto, QuickBooks, ServiceNow, Shopify, Spark, Square, Xero, Zoho, DB2, FTP, GE Historian, Informix, Microsoft Access, MongoDB, SAP Cloud for customer

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Use copy wizard to quickly copy data from a bunch of data sources

The familiar ADF v1 copy wizard is now available in ADF v2 to do one-time quick import. Copy Wizard generates pipelines with copy activities on authoring canvas. The copy activities can now be extended to run other activities like Spark, USQL, Stored Proc etc. on-success, on-failure etc. and create the entire control flow pipeline.

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Guided tour

Click on the Information Icon in the lower left. You can then click Guided tour to get step by step instructions on how to visually monitor your pipeline and activity runs.

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Feedback

Click on the Feedback icon to give us feedback on various features or any issues that you may be facing.

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Select data factory

Hover on the Data Factory icon on the top left. Click on the Arrow icon to see a list of Azure subscriptions and data factories that you can monitor.

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Visual Monitoring

List View Monitoring

Monitor pipeline, activity & trigger runs with a simple list view interface. All the runs are displayed in local browser time zone. You can change the time zone and all the date time fields will snap to the selected time zone.

Monitor Pipeline Runs:

List view showcasing each pipeline run for your data factory v2 pipelines.

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Monitor Activity Runs:

List view showcasing activity runs corresponding to each pipeline run. Click Activity Runs icon under the Actions column to view activity runs for each pipeline run.

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Important note: You need to click the Refresh icon on top to refresh the list of pipeline and activity runs. Auto-refresh is currently not supported.

Monitor Trigger Runs:

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Rich ordering and filtering

Order pipeline runs in desc/asc by Run Start and filter pipeline runs pipeline name, run start and run status.

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Add/Remove columns to list view

Right click the list view header and choose columns that you want to appear in the list view.

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Reorder columns widths in list view

Increase and decrease the column widths in list view by simply hovering over the column header.

Monitor Integration Runtimes

Monitor health of your Self Hosted, Azure, Azure-SSIS Integration runtimes.

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Cancel/Re-run your pipeline runs

Cancel a pipeline run or re-run a pipeline run with already defined parameters.

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This is the first public release of ADF v2 visual tools We are continuously working to refresh the released bits with new features based on customer feedback. Get more information and detailed steps for using the ADF v2 visual tools.

Get started building pipelines easily and quickly using Azure Data Factory. If you have any feature requests or want to provide feedback, please visit the Azure Data Factory forum.