Hope this helps. But what if you have dozens or hundreds of tables to copy? You need to understand the JSON syntax, because that’s the output you use in later activities. Rayis Imayev, They have a source dataset, but they do not have a sink dataset. The main portion of the output for this activity may look this way: I already know that I can get access to the list of files/folders using this ADF expression: Or getting to the first file by referencing a very first element [0] of this JSON array: However, if I want to store the complete output of this activity into a separate Array variable with preserving the option of referencing all nested elements, then this can only be done by wrapping the output into array by using the, (activity('List of files and folders').output), Otherwise you will get a data mismatch error message. Lookup activity in Azure Data Factory. But things aren’t always as straightforward as they could be. will correctly show me 3 elements of this JSON array: Where a list of items for my "For Each" loop activity can be simply set with the following expression: Here is the interesting part, let's say I want to execute another ADF pipeline within my ". If I'm the last one to learn this, I'm still excited , Transforming JSON to CSV with the help of Azure Data Factory - Mapping Data Flows, Transforming JSON to CSV with the help of Azure Data Factory - Wrangling Data Flows, Transforming JSON to CSV with the help of Azure Data Factory - Control Flows, https://opensource.adobe.com/Spry/samples/data_region/JSONDataSetSample.html. Are you gonna In these situations where other functionality is required we need to rely on the extensibility of Custom Activities. Unfortunately, there is no way to receiving databricks output in Data Factory. The thing that I got excited the most while working with JSON file outputs in Data Factory pipelines was that I could still pass JSON arrays between different tasks/activities or pass those arrays to another sub-pipeline as a parameter, and nested elements referencing still worked! Hit the ‘Parse JSON Path’ button this will take a peek at the JSON files and infer it’s structure. You can then chain a ForEach activity that would Loop through the Cities (eg- @activity('Lookup').output.Cities ). You can find the other two parts here: Part 1; Part 2 Custom Activity; Transformation Activity. Now let’s think about Azure Data Factory briefly, as it’s the main reason for the post In version 1 we needed to reference a namespace, class and method to call at runtime. But what if you need to pass a complete output of your ADF activity task further down your pipeline. I was able to create flattened parquet from JSON with very little engineer effort. It works and it's fun! Matt How Matt is a passionate data and analytics professional who enjoys sharing his wealth of experience using Azure services through blogging and conference talks. We’ll be doing the following. Data Factory copies the content of outputs.json and appends it into the Activity Output as the value of the customOutputproperty. Or you need to pass a JSON array elements to another ADF activity or sub-pipeline as the parameter value. Sensitive … Messages that are formatted in a way that makes a lot of sense for message exchange (JSON) but gives ETL/ELT developers a problem to solve. Including escape characters for nested double quotes. Many enterprises maintain a BI/MI facility with some sort of Data warehouse at the beating heart of the analytics platform. Here, both validation activities ValidX and ValidY are connected to SetVar by 'on completion' dependency. If you want to consume the content of outputs.json in downstream activities, you can get the value by using the expression @activity('').output.customOutput. But I’m using parquet as it’s a popular big data format consumable by spark and SQL polybase amongst others. Data Transformation Activities to transform data using compute services such as Azure HDInsight, Azure Batch, and Azure Machine Learning Studio (classic). You’ll need to insert your application identifier in the Base URL field as part of the URL https://api.applicationinsights.io/v1/apps/{app-id}/ 3. There are many methods for performing JSON flattening but in this article, we will take a look at how one might use ADF to accomplish this. Typically Data warehouse technologies apply schema on write and store data in tabular tables/dimensions. Lookup activity can retrieve a dataset from any of the Azure Data Factory-supported data sources. Lookups are similar to copy data activities, except that you only get data from lookups. But things aren’t always as straightforward as they could be. From there navigate to the Access blade. Check out part one here: Azure Data Factory – Get Metadata Activity; Check out part two here: Azure Data Factory – Stored Procedure Activity; Setting up the Lookup Activity in Azure Data Factory v2. I’m sure this will improve over time, but don’t let that stop you from getting started now. Azure Data Factory's (ADF) ForEach and Until activities are designed to handle iterative processing logic. This will become very helpful if you want to pass the JSON output into the next activity of your ADF pipeline to process. I’ve added some brief guidance on Azure Datalake Storage setup including links through to the official Microsoft documentation. You’ll see that I’ve added a carrierCodes array to the elements in the items array. We are going to discuss the ForEach activity in this article. Azure Data Factory v2 (ADFv2) has some significant improvements over v1, and we now consider ADF as a viable platform for most of our cloud based projects. This means no matter whether success, or failure, time out or found file, execution will continue along this path. Once the ForEach activity is complete, you can have a Stored Procedure activity to write the values in the array "values" to the Table. You can do so by writing them into outputs.json … The thing that I got excited the most while working with JSON file outputs in Data Factory pipelines was that I could still pass JSON arrays between different tasks/activities or pass those arrays to another sub-pipeline as a parameter, and nested elements referencing still worked! Get the JSON response in a Web Activity We should be able to use values from the JSON response of a web activity as parameters for the following activities of the pipeline. Once the ForEach activity is complete, you can have a Stored Procedure activity to write the values in the array "values" to the Table. This will add the attributes nested inside the items array as additional column to JSON Path Expression pairs. Many years’ experience working within healthcare, retail and gaming verticals delivering analytics using industry leading methods and technical design patterns. Last week I blogged about using Mapping Data Flows to flatten sourcing JSON file into a flat CSV dataset: Part 1 : Transforming JSON to CSV with the help of Flatten task in Azure Data Factory Today I would like to explore the capabilities of the Wrangling Data Flows in ADF to flatten the very same sourcing JSON … You can use a single linked service for every query to App Insights. Alter the name and select the Azure Data Lake linked-service in the connection tab. Let's get more creative and read a real JSON file where you have more flexibility and control over its content. For the purpose of this article, I’ll just allow my ADF access to the root folder on the Lake. While working with one particular ADF component I then had discovered other possible options to use richness and less constrained JSON file format, which in a nutshell is just a text file with one or more ("key" : "value") pair elements. Say that we want to execute a single pipeline from a configuration table. (So, like… half a copy data activity? Use an Append Variable activity to append to the array "values" each value. This allows us to either use the lookup as a source when using the foreach activity, or to lookup some static or configuration data. Add an Azure Data Lake Storage Gen1 Dataset to the pipeline. Data engineering competencies include Azure Data Factory, Data Lake, Databricks, Stream Analytics, Event Hub, IoT Hub, Functions, Automation, Logic Apps and of course the complete SQL Server business intelligence stack. @nabhishek My output is a dataframe - How do I use the output in a Copy Data activity? I’m using an open source parquet viewer I found to observe the output file. First off, I’ll need an Azure DataLake Store Gen1 linked service. Get the JSON response in a Web Activity We should be able to use values from the JSON response of a web activity as parameters for the following activities of the pipeline.

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