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Every morning its data engineering team receives the previous day's raw orders, and analysts expect a clean daily sales-by-truck table to be ready by 6:00 AM. Today, a teammate opens two notebooks and runs them by hand. One cleans the raw orders, and the other builds the daily sales table.\u003C/p\u003E\n","\u003Cp\u003EIn this Quickstart, you'll turn those two notebooks into a scheduled pipeline with Pipeline Builder, a visual designer in Snowflake Workspaces. You drag notebooks onto a canvas, connect them to set the order they run in, and deploy. Pipeline Builder creates the tasks, the task graph, and the Code Bundles that package your code. You don't write \u003Ccode\u003ECREATE TASK\u003C/code\u003E statements by hand.\u003C/p\u003E\n","\u003Cp\u003EEach pipeline is also a DCM project. Before anything changes in your account, you see a plan of every object a deployment will create, alter, or drop.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E Pipeline Builder is in public preview.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA Snowflake account (or \u003Ca href=\"https://signup.snowflake.com/\"\u003Efree trial\u003C/a\u003E) in a region where Pipeline Builder and Snowpark Container Services are available\u003C/li\u003E\u003Cli\u003EFamiliarity with SQL and basic Python\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to turn notebooks into tasks by dragging them onto the Pipeline Builder canvas\u003C/li\u003E\u003Cli\u003EHow connecting tasks creates a task graph, and how to schedule the graph as one unit\u003C/li\u003E\u003Cli\u003EHow to plan and deploy a pipeline as a DCM project, and how the declarative model creates, alters, and drops objects\u003C/li\u003E\u003Cli\u003EHow to run and monitor a deployed task graph in Snowsight\u003C/li\u003E\u003Cli\u003EHow to generate a pipeline draft with CoCo\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Need\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EThe ACCOUNTADMIN role, or an admin who can run the role and grants block in the next step. Creating the warehouse, compute pool, and database requires ACCOUNTADMIN.\u003C/li\u003E\u003Cli\u003EAccess to Workspaces in Snowsight\u003C/li\u003E\u003Cli\u003EThe \u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder\"\u003Ecompanion repo\u003C/a\u003E, which you clone into a workspace in the next step. It's public, so you don't need a GitHub account.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA Tasty Bytes daily sales pipeline: a task graph that cleans raw food truck orders, then builds a daily sales table per truck, on a 6:00 AM schedule\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-console\"\u003ERAW.ORDERS ──> clean_orders_task (notebook) ──> STAGING.ORDERS_CLEAN\n                     │\n                     v\n               daily_sales_task (notebook) ──> ANALYTICS.DAILY_TRUCK_SALES\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESetup\u003C/h2\u003E\n","\u003Cp\u003EIn this step, you clone the companion repo into a workspace, then run its setup script to create the role, warehouse, compute pool, database, and sample data this Quickstart uses. Do this step as ACCOUNTADMIN: make sure ACCOUNTADMIN is selected in your Snowsight user menu in the lower-left corner.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E If you don't have ACCOUNTADMIN access, ask your Snowflake admin to create an API integration named \u003Ccode\u003ETASTY_PIPELINE_QS_GIT_INT\u003C/code\u003E that allows \u003Ccode\u003Ehttps://github.com/Snowflake-Labs\u003C/code\u003E, grant your role \u003Ccode\u003EUSAGE\u003C/code\u003E on it, and run \u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder/blob/main/setup.sql\"\u003Esetup.sql\u003C/a\u003E with your user name. Then clone the repo with the steps below and skip to Switch to the guide role.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EGet the companion repo\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn Snowsight, click \u003Cstrong\u003EWorkspaces\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the workspaces UI, click \u003Cstrong\u003ECreate new Git workspace\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFor \u003Cstrong\u003ERepository URL\u003C/strong\u003E, enter \u003Ccode\u003Ehttps://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder\u003C/code\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ENext to \u003Cstrong\u003EAPI integration\u003C/strong\u003E, select \u003Cstrong\u003E+ API Integration\u003C/strong\u003E, and fill in the \u003Cstrong\u003ECreate API Integration\u003C/strong\u003E dialog:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EFor \u003Cstrong\u003EName\u003C/strong\u003E, enter \u003Ccode\u003ETASTY_PIPELINE_QS_GIT_INT\u003C/code\u003E. Use this exact name, so \u003Cstrong\u003Ecleanup.sql\u003C/strong\u003E can drop it at the end.\u003C/li\u003E\u003Cli\u003EFor \u003Cstrong\u003EAllowed prefixes\u003C/strong\u003E, enter \u003Ccode\u003Ehttps://github.com/Snowflake-Labs\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EFor \u003Cstrong\u003EAllowed authentication secrets\u003C/strong\u003E, select \u003Cstrong\u003ENone\u003C/strong\u003E. The repo is public, so it doesn't need a secret.\u003C/li\u003E\u003Cli\u003ELeave \u003Cstrong\u003EEnable OAuth authentication\u003C/strong\u003E cleared, and select \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-api-integration.png?v=d0fdcebc\" alt=\"Create API Integration dialog\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EBack in the \u003Cstrong\u003ECreate workspace from Git repository\u003C/strong\u003E dialog, select \u003Cstrong\u003EPublic repository\u003C/strong\u003E. You can't push changes back to the repo with public authentication, and this Quickstart doesn't need to. Leave \u003Cstrong\u003EWorkspace name\u003C/strong\u003E as it fills in from the URL.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-workspace-from-git.png?v=d0fdcebc\" alt=\"Create workspace from Git repository dialog\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe workspace opens with \u003Cstrong\u003Esetup.sql\u003C/strong\u003E, \u003Cstrong\u003Ecleanup.sql\u003C/strong\u003E, \u003Cstrong\u003E01_clean_orders.ipynb\u003C/strong\u003E, and \u003Cstrong\u003E02_daily_sales.ipynb\u003C/strong\u003E.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImportant:\u003C/strong\u003E The repo gets fixes over time, so pull the latest changes now, before you start. Once you move the notebooks into your pipeline's folder later in this Quickstart, your workspace has local changes, and pulling again can conflict with them.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ERun the setup script\u003C/h3\u003E\n","\u003Cp\u003EOpen \u003Cstrong\u003Esetup.sql\u003C/strong\u003E, replace \u003Ccode\u003E<your_username>\u003C/code\u003E with your Snowflake user name, and run the whole file as ACCOUNTADMIN.\u003C/p\u003E\n","\u003Cp\u003EHere's what the script does:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ECreates the \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E role and grants it to you and to \u003Ccode\u003ESYSADMIN\u003C/code\u003E\u003C/li\u003E\u003Cli\u003ECreates the \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E warehouse and the \u003Ccode\u003ETASTY_PIPELINE_QS_POOL\u003C/code\u003E compute pool. Notebooks in Pipeline Builder run on a compute pool.\u003C/li\u003E\u003Cli\u003ECreates the \u003Ccode\u003ETASTY_PIPELINE_QS_DB\u003C/code\u003E database and makes the guide role its owner, so the role can create the schemas, tables, tasks, task graphs, Code Bundles, and DCM project the pipeline needs\u003C/li\u003E\u003Cli\u003EGrants the guide role \u003Ccode\u003EEXECUTE TASK\u003C/code\u003E on the account\u003C/li\u003E\u003Cli\u003ECreates a RAW, STAGING, ANALYTICS, and PIPELINE schema. The PIPELINE schema holds the pipeline's tasks, task graph, Code Bundle, and DCM project.\u003C/li\u003E\u003Cli\u003ESeeds about 5,000 Tasty Bytes orders, plus 200 duplicate orders and 50 invalid orders for the pipeline to clean up\u003C/li\u003E\u003Cli\u003ECreates a \u003Ccode\u003ERUN_LOG\u003C/code\u003E table that the optional Advanced modules write to\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThe last statement returns \u003Ccode\u003Eraw_rows\u003C/code\u003E = \u003Ccode\u003E5250\u003C/code\u003E.\u003C/p\u003E\n","\u003Ch3\u003ESwitch to the guide role\u003C/h3\u003E\n","\u003Cp\u003EYou create the pipeline in the next step, and it has to be created with the guide role. If you create it as ACCOUNTADMIN, deployments and runs fail with privilege errors.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn the lower-left corner of Snowsight, select your name.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ESwitch role\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ETASTY_PIPELINE_QS_ROLE\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EConfirm that your name in the lower-left corner now shows \u003Cstrong\u003ETASTY_PIPELINE_QS_ROLE\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EChanging the role selector inside a SQL file doesn't count. Pipeline Builder uses the role in your user menu.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECreate the Pipeline\u003C/h2\u003E\n","\u003Cp\u003EA Pipeline Builder pipeline lives in a project folder in your workspace. Let's create one.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn Snowsight, open your workspace.\u003C/li\u003E\u003Cli\u003EIn the file explorer, select \u003Cstrong\u003EAdd new\u003C/strong\u003E, and then select \u003Cstrong\u003EPipeline Builder\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ECreate Pipeline Builder\u003C/strong\u003E dialog, enter \u003Ccode\u003EPipeline_builder_quickstart\u003C/code\u003E for the \u003Cstrong\u003EName\u003C/strong\u003E. Pipeline Builder creates a folder with this name for the pipeline.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ESelect database and schema\u003C/strong\u003E, and select \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE\u003C/code\u003E. This is where the pipeline's DCM project object is created.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-pipeline-dialog.png?v=d0fdcebc\" alt=\"Create Pipeline Builder dialog\"\u003E\u003C/p\u003E\n","\u003Cp\u003EPipeline Builder creates a \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E project folder and opens an empty canvas. The folder contains:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003Emanifest.yml\u003C/strong\u003E: the DCM project's manifest, including its deployment target\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003Esources/\u003C/strong\u003E: a folder for DCM definition files\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EWhen you add your first task, Pipeline Builder also creates \u003Cstrong\u003Epipeline.yml\u003C/strong\u003E, which holds the tasks, task graphs, and Code Bundles you build on the canvas. You won't edit these files in this Quickstart. Pipeline Builder writes to them for you.\u003C/p\u003E\n","\u003Cp\u003EOpen \u003Cstrong\u003Emanifest.yml\u003C/strong\u003E and confirm that the target's \u003Ccode\u003Eproject_owner\u003C/code\u003E is \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E. If it shows another role, such as \u003Ccode\u003EACCOUNTADMIN\u003C/code\u003E, see Troubleshooting before you continue.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/project-folder.png?v=d0fdcebc\" alt=\"Pipeline_builder_quickstart project folder\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EMove the notebooks into the pipeline\u003C/h3\u003E\n","\u003Cp\u003ENow add the two notebooks your teammate has been running by hand. They came with the companion repo, at the root of your workspace. Pipeline Builder can only turn files inside the pipeline's project folder into tasks, so move them there first.\u003C/p\u003E\n","\u003Cp\u003EIn the file explorer, drag \u003Cstrong\u003E01_clean_orders.ipynb\u003C/strong\u003E and \u003Cstrong\u003E02_daily_sales.ipynb\u003C/strong\u003E into the \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E folder. Drop them at the root of the folder, not in \u003Cstrong\u003Esources/\u003C/strong\u003E or \u003Cstrong\u003Eout/\u003C/strong\u003E. Pipeline Builder can't turn files in those two folders into tasks.\u003C/p\u003E\n","\u003Cp\u003EHere's what the notebooks do:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003E01_clean_orders.ipynb\u003C/strong\u003E drops the invalid rows, removes the duplicates, and writes \u003Ccode\u003ESTAGING.ORDERS_CLEAN\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003E02_daily_sales.ipynb\u003C/strong\u003E aggregates the clean orders into one row per day, truck, and city in \u003Ccode\u003EANALYTICS.DAILY_TRUCK_SALES\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EBoth use fully qualified table names, because a notebook that runs as a task doesn't have a current database or schema\u003C/li\u003E\u003C/ul\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E You can open each notebook and run its cell to check it works. Running it now also creates the tables early, which is fine: the pipeline replaces them on every run.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/notebook-sql-cell.png?v=d0fdcebc\" alt=\"Notebook with a single SQL cell\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ETurn Notebooks into Tasks\u003C/h2\u003E\n","\u003Cp\u003EThis is where Pipeline Builder starts saving you work. You drag your notebooks onto the canvas, without publishing them or uploading files to a stage.\u003C/p\u003E\n","\u003Cp\u003EIf the canvas isn't open, go back to it: select the \u003Cstrong\u003EPipeline Builder\u003C/strong\u003E tab for \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E at the top of the editor, or, in the file explorer, hover over the \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E folder and select the \u003Cstrong\u003EOpen pipeline builder\u003C/strong\u003E icon. Keep the file explorer visible next to the canvas, then drag \u003Cstrong\u003E01_clean_orders.ipynb\u003C/strong\u003E from the file explorer and drop it anywhere on the canvas.\u003C/p\u003E\n","\u003Cp\u003EPipeline Builder adds a card with a \u003Cstrong\u003ENotebook\u003C/strong\u003E badge and opens the task's settings drawer. Behind the scenes, it also creates a Code Bundle that packages the project's code so Snowflake can run it, and fills in a default runtime, compute pool, and warehouse.\u003C/p\u003E\n","\u003Cp\u003EIn the drawer, on the \u003Cstrong\u003EGeneral\u003C/strong\u003E tab:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EConfirm that \u003Cstrong\u003EName\u003C/strong\u003E is \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.clean_orders_task\u003C/code\u003E. Pipeline Builder names the task after the file and the project's database and schema. Names in Pipeline Builder are always fully qualified.\u003C/li\u003E\u003Cli\u003EConfirm that \u003Cstrong\u003EEntrypoint\u003C/strong\u003E points at \u003Cstrong\u003E01_clean_orders.ipynb\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003EExecution\u003C/strong\u003E, for \u003Cstrong\u003EWarehouse\u003C/strong\u003E, set to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/first-task-drawer.png?v=d0fdcebc\" alt=\"Task drawer for clean_orders_task\"\u003E\u003C/p\u003E\n","\u003Cp\u003EOn the \u003Cstrong\u003ESpecification\u003C/strong\u003E tab:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EFor \u003Cstrong\u003ECompute pool\u003C/strong\u003E, set to \u003Ccode\u003ETASTY_PIPELINE_QS_POOL\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EFor \u003Cstrong\u003EQuery warehouse\u003C/strong\u003E, set to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E. This warehouse runs the SQL that the notebook issues.\u003C/li\u003E\u003Cli\u003ELeave \u003Cstrong\u003ERuntime version\u003C/strong\u003E at its default.\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E If a field shows an error with a \u003Cstrong\u003EFix\u003C/strong\u003E action, the value is close to an existing object, for example a name with the wrong case. Select \u003Cstrong\u003EFix\u003C/strong\u003E to correct it.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/specification-tab.png?v=d0fdcebc\" alt=\"Specification tab\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EAdd the second task\u003C/h3\u003E\n","\u003Cp\u003ENow drag \u003Cstrong\u003E02_daily_sales.ipynb\u003C/strong\u003E onto the right side of the \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E card. When the \u003Cstrong\u003ERun After\u003C/strong\u003E hint appears, drop the file.\u003C/p\u003E\n","\u003Cp\u003EPipeline Builder adds a second task, connects the two cards, and makes the new task run after \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E. The new task reuses the same Code Bundle.\u003C/p\u003E\n","\u003Cp\u003EIn its drawer, confirm that \u003Cstrong\u003EName\u003C/strong\u003E is \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.daily_sales_task\u003C/code\u003E, and under \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E. On the \u003Cstrong\u003ESpecification\u003C/strong\u003E tab, select the same compute pool and query warehouse as the first task.\u003C/p\u003E\n","\u003Cp\u003EThen select the \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E card and check its \u003Cstrong\u003EWarehouse\u003C/strong\u003E again. Connecting the tasks can clear it. If it's empty, set it to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EYou now have two connected cards on the canvas. You can also connect cards by dragging from the outgoing connector on the right of one card to the incoming connector on the left of another.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/two-tasks-connected.png?v=d0fdcebc\" alt=\"Two connected tasks on the canvas\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESchedule the Task Graph\u003C/h2\u003E\n","\u003Cp\u003EWhen you connected the two tasks, Pipeline Builder quietly did something else: it created a task graph that contains both of them. A task graph is a first-class object that holds the schedule, run policies, and the defaults its tasks inherit. \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E has no predecessors, so it's the graph's root.\u003C/p\u003E\n","\u003Cp\u003EPipeline Builder also moved any values the tasks share, such as the warehouse, into the graph's task defaults. Let's look.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ESelect \u003Cstrong\u003EObjects\u003C/strong\u003E on the canvas toolbar, and then select \u003Cstrong\u003ETask graphs\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect the task graph that Pipeline Builder created.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003ETask graph object\u003C/strong\u003E, set \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.TASTY_DAILY_SALES_GRAPH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003ETask graph settings\u003C/strong\u003E, for \u003Cstrong\u003ESchedule\u003C/strong\u003E, select \u003Cstrong\u003ECron\u003C/strong\u003E. Enter \u003Ccode\u003E0 6 * * *\u003C/code\u003E, and select your time zone (e.g., \u003Ccode\u003E0 6 * * * UTC\u003C/code\u003E).\u003C/li\u003E\u003Cli\u003EFor \u003Cstrong\u003EDesired state\u003C/strong\u003E, leave \u003Cstrong\u003ESuspended\u003C/strong\u003E. You'll run the graph manually for now, so it doesn't start running on a schedule and using credits before you're ready.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003ETask defaults\u003C/strong\u003E, confirm that \u003Cstrong\u003EWarehouse\u003C/strong\u003E is \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E. Any task in the graph that doesn't set its own warehouse uses this one.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003ETasks in this graph\u003C/strong\u003E, confirm both tasks are listed, with \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E marked \u003Cstrong\u003ERoot\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYou can open the same settings from any task: select the task, select the \u003Cstrong\u003EGraph\u003C/strong\u003E tab, and then select \u003Cstrong\u003EEdit graph settings\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/task-graph-settings.png?v=d0fdcebc\" alt=\"Task graph settings\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EPlan and Deploy\u003C/h2\u003E\n","\u003Cp\u003ENothing you've built exists in your account yet. A pipeline doesn't run until you deploy it, and deploying starts with a plan that shows exactly what will change.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003EDeploy\u003C/strong\u003E in the upper-right corner of the canvas. If you don't see it, collapse the workspace's bottom pane.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the \u003Cstrong\u003EReview planned changes\u003C/strong\u003E dialog, review the list. This first deployment creates the Code Bundle, the \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E and \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E tasks, and the \u003Cstrong\u003ETASTY_DAILY_SALES_GRAPH\u003C/strong\u003E task graph. It also lists an \u003Cstrong\u003EALTER\u003C/strong\u003E on \u003Cstrong\u003ETASTY_PIPELINE_QS_ROLE\u003C/strong\u003E. Confirm that this row names \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E. If it names \u003Ccode\u003EACCOUNTADMIN\u003C/code\u003E, the pipeline was created with the wrong role. Cancel and see Troubleshooting.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/review-planned-changes.png?v=d0fdcebc\" alt=\"Review planned changes dialog\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003EDeploy\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EWhile the deployment runs, the \u003Cstrong\u003EDeploy\u003C/strong\u003E button changes to \u003Cstrong\u003ECancel\u003C/strong\u003E. When it finishes, a \u003Cstrong\u003EDeployed Project\u003C/strong\u003E button appears next to \u003Cstrong\u003EDeploy\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003EThis plan-then-deploy loop comes from DCM. The project files describe the objects you want, not the steps to create them. Each deployment compares the files with your account and creates, alters, or drops objects to match, in the right order.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ERun and Monitor\u003C/h2\u003E\n","\u003Cp\u003EThe graph is deployed but suspended. Let's run it once now, ahead of its 6:00 AM schedule.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003EDeployed Project\u003C/strong\u003E. The DCM project opens in Snowsight on the \u003Cstrong\u003EObjects\u003C/strong\u003E tab, which lists the tasks, task graph, and Code Bundle the project manages.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/deployed-project-objects.png?v=d0fdcebc\" alt=\"Deployed project objects\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003ETASTY_DAILY_SALES_GRAPH\u003C/strong\u003E to open its details page.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect the \u003Cstrong\u003EGraph\u003C/strong\u003E tab, and then select the \u003Cstrong\u003ERun Task Graph\u003C/strong\u003E (play) icon in the toolbar above the graph.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/run-task-graph.png?v=d0fdcebc\" alt=\"Run Task Graph icon on the Graph tab\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ETo watch the run while it's in progress, open a task's details page (for example, select \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E on the \u003Cstrong\u003EObjects\u003C/strong\u003E tab of the DCM project) and select its \u003Cstrong\u003ERun History\u003C/strong\u003E tab. The task graph's \u003Cstrong\u003EOverview\u003C/strong\u003E tab shows the run once it finishes.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYou can also run the graph from SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EEXECUTE TASK GRAPH TASTY_PIPELINE_QS_DB.PIPELINE.TASTY_DAILY_SALES_GRAPH;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EA task that belongs to a task graph runs only as part of its graph. You can't run \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E on its own.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E The first run after the compute pool resumes can take a few minutes while the pool starts. If a notebook task fails quickly on that first run, run the graph again once the pool is active.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EWhen both tasks succeed, check the output:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT city, SUM(orders) AS orders, SUM(revenue) AS revenue\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES\nGROUP BY city\nORDER BY revenue DESC;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou should see five cities. Check the clean row count too:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT COUNT(*) AS clean_orders FROM TASTY_PIPELINE_QS_DB.STAGING.ORDERS_CLEAN;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou should see \u003Ccode\u003Eclean_orders\u003C/code\u003E = \u003Ccode\u003E5000\u003C/code\u003E: the 200 duplicates and the 50 invalid orders are gone.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EChange It Like Code\u003C/h2\u003E\n","\u003Cp\u003EBecause the pipeline is a DCM project, every deployment brings your account in line with the project files. Let's see what that means in practice.\u003C/p\u003E\n","\u003Ch3\u003ERedeploy with no changes\u003C/h3\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003EDeploy\u003C/strong\u003E again without changing anything. Pipeline Builder shows "No changes to deploy." and doesn't deploy. Deployments are safe to repeat.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/no-changes-to-deploy.png?v=d0fdcebc\" alt=\"No changes to deploy\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EAdd a task\u003C/h3\u003E\n","\u003Cp\u003EAnalysts have asked for a daily leaderboard of the top five trucks. Let's add a SQL task after \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E that rebuilds it on every run. A SQL task is also how you run stored procedures or any other Snowflake object from a pipeline.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EHover over the \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E card, select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector, and then select \u003Cstrong\u003ESQL\u003C/strong\u003E. Pipeline Builder adds a new card that runs after \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESet \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.top_trucks_task\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE OR REPLACE TABLE TASTY_PIPELINE_QS_DB.ANALYTICS.TOP_TRUCKS AS\nSELECT truck_id, city, SUM(revenue) AS revenue\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES\nGROUP BY ALL\nORDER BY revenue DESC\nLIMIT 5;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003EDeploy\u003C/strong\u003E. The plan shows \u003Cstrong\u003ETOP_TRUCKS_TASK\u003C/strong\u003E as a task to create and an \u003Cstrong\u003EALTER\u003C/strong\u003E on \u003Cstrong\u003ETASTY_PIPELINE_QS_ROLE\u003C/strong\u003E. Confirm the \u003Cstrong\u003EALTER\u003C/strong\u003E row still names \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E, and then select \u003Cstrong\u003EDeploy\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-add-task.png?v=d0fdcebc\" alt=\"Plan for adding a task\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EDelete a task\u003C/h3\u003E\n","\u003Cp\u003ENow suppose the analysts change their minds. On the \u003Cstrong\u003Etop_trucks_task\u003C/strong\u003E card, select the \u003Cstrong\u003E⋮\u003C/strong\u003E menu, and then select \u003Cstrong\u003EDelete\u003C/strong\u003E. Select \u003Cstrong\u003EDeploy\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003EThis time, the plan shows \u003Cstrong\u003Etop_trucks_task\u003C/strong\u003E as a task to drop. Deleting a card removes it from the project files, and the next deployment drops the task from your account. You never write a \u003Ccode\u003EDROP TASK\u003C/code\u003E.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E The deployment drops the task, but not the \u003Ccode\u003ETOP_TRUCKS\u003C/code\u003E table the task created if it ran. DCM manages the objects defined in the project, such as tasks, task graphs, and Code Bundles. Tables that your code creates at run time aren't part of the project.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-drop-task.png?v=d0fdcebc\" alt=\"Plan for deleting a task\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ETurn on the schedule (optional)\u003C/h3\u003E\n","\u003Cp\u003ETo have Tasty Bytes' sales table ready every morning, open the task graph settings: select \u003Cstrong\u003EObjects\u003C/strong\u003E on the canvas toolbar, select \u003Cstrong\u003ETask graphs\u003C/strong\u003E, and then select \u003Cstrong\u003ETASTY_DAILY_SALES_GRAPH\u003C/strong\u003E. Set \u003Cstrong\u003EDesired state\u003C/strong\u003E to \u003Cstrong\u003EResumed\u003C/strong\u003E, and deploy. The graph then runs every day at 6:00 AM. If you do this, remember to clean up at the end of the Quickstart so the graph stops running.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EBuild with CoCo\u003C/h2\u003E\n","\u003Cp\u003EYou've built a pipeline card by card. Now let's have CoCo draft one from a description.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn the file explorer, select \u003Cstrong\u003EAdd new\u003C/strong\u003E, and then select \u003Cstrong\u003EPipeline Builder\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ECreate Pipeline Builder\u003C/strong\u003E dialog, enter \u003Ccode\u003Etasty_menu_popularity\u003C/code\u003E for the \u003Cstrong\u003EName\u003C/strong\u003E, and select \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE\u003C/code\u003E for \u003Cstrong\u003EDatabase and schema\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003EGenerate with Cortex\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003EPrompt\u003C/strong\u003E field, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-console\"\u003EBuild a weekly pipeline for Tasty Bytes over TASTY_PIPELINE_QS_DB.RAW.ORDERS.\nStep 1: a SQL task that writes weekly order counts and revenue per city to\nTASTY_PIPELINE_QS_DB.ANALYTICS.WEEKLY_CITY_SALES.\nStep 2: a SQL task, after step 1, that writes the top city for each week to\nTASTY_PIPELINE_QS_DB.ANALYTICS.WEEKLY_TOP_CITY.\nPut all tasks in TASTY_PIPELINE_QS_DB.PIPELINE, use warehouse TASTY_PIPELINE_QS_WH,\nand schedule the graph every Monday at 7:00 AM America/Los_Angeles, suspended.\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003ESelect \u003Cstrong\u003EGenerate\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ECoCo writes the tasks, the connection between them, and the task graph settings to the new project's definition file, so you can review its work on the canvas before anything is deployed. Select each card to check its SQL. To check the schedule, select \u003Cstrong\u003EObjects\u003C/strong\u003E on the canvas toolbar, select \u003Cstrong\u003ETask graphs\u003C/strong\u003E, and then select the graph CoCo created. If it looks right, select \u003Cstrong\u003EDeploy\u003C/strong\u003E to plan and deploy it the same way as the first pipeline.\u003C/p\u003E\n","\u003Cp\u003ETo change an existing pipeline with CoCo, open the CoCo chat in your workspace and use the \u003Ccode\u003E/pipeline-builder\u003C/code\u003E skill. For example, ask it to add a task to \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EAdvanced: Optional Modules\u003C/h2\u003E\n","\u003Cp\u003EYou've built, deployed, run, and changed a pipeline. That's the core of Pipeline Builder. The modules below go further. Each one starts from the \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E pipeline as you left it in Change It Like Code, and none depend on each other, so pick the ones that match your pipelines.\u003C/p\u003E\n","\u003Cp\u003EEach module ends with a deployment. To compare what changed, review the \u003Cstrong\u003EReview planned changes\u003C/strong\u003E dialog before you select \u003Cstrong\u003EDeploy\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003EBefore you start, make sure you're back on the \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E canvas, not the pipeline CoCo generated in the previous step. Select its \u003Cstrong\u003EPipeline Builder\u003C/strong\u003E tab, or, in the file explorer, hover over the \u003Cstrong\u003EPipeline_builder_quickstart\u003C/strong\u003E folder and select the \u003Cstrong\u003EOpen pipeline builder\u003C/strong\u003E icon.\u003C/p\u003E\n","\u003Cp\u003EFor every task you add in these modules, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E under \u003Cstrong\u003EExecution\u003C/strong\u003E on the task's \u003Cstrong\u003EGeneral\u003C/strong\u003E tab, as you did for the first two tasks.\u003C/p\u003E\n","\u003Cp\u003ESeveral modules write to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG\u003C/code\u003E, a small log table that \u003Cstrong\u003Esetup.sql\u003C/strong\u003E already created. It has three columns: \u003Ccode\u003Elogged_at\u003C/code\u003E, \u003Ccode\u003Esource\u003C/code\u003E, and \u003Ccode\u003Emessage\u003C/code\u003E.\u003C/p\u003E\n","\u003Ch3\u003EA1: Branch on a Return Value\u003C/h3\u003E\n","\u003Cp\u003ETasty Bytes wants to reprocess everything when order volume is high, and take a lighter path otherwise. You'll build three tasks: one that decides, and one for each branch. To keep the focus on branching, each branch task writes a row to \u003Ccode\u003ERUN_LOG\u003C/code\u003E. In a real pipeline, that's where the full or incremental logic would go.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-console\"\u003Eclean_orders_task ──> CHECK_VOLUME ──> FULL_PATH\n                                  └──> INCREMENTAL_PATH\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch4\u003EStep 1: Create the deciding task\u003C/h4\u003E\n","\u003Cp\u003E\u003Ccode\u003ECHECK_VOLUME\u003C/code\u003E counts the clean orders and sets its return value to \u003Ccode\u003EFULL\u003C/code\u003E if there are more than 4,000, or \u003Ccode\u003EINCREMENTAL\u003C/code\u003E otherwise. Tasks that run after it can read that value.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EHover over the \u003Cstrong\u003Eclean_orders_task\u003C/strong\u003E card and select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector to add a \u003Cstrong\u003ESQL\u003C/strong\u003E task.\u003C/li\u003E\u003Cli\u003ESet \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.CHECK_VOLUME\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EEXECUTE IMMEDIATE $$\nDECLARE\n  path STRING;\nBEGIN\n  SELECT IFF(COUNT(*) > 4000, 'FULL', 'INCREMENTAL') INTO :path\n  FROM TASTY_PIPELINE_QS_DB.STAGING.ORDERS_CLEAN;\n  CALL SYSTEM$SET_RETURN_VALUE(:path);\nEND;\n$$;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe block computes the path into a variable first, because \u003Ccode\u003ESYSTEM$SET_RETURN_VALUE\u003C/code\u003E only accepts a constant or a variable, not a subquery.\u003C/p\u003E\n","\u003Ch4\u003EStep 2: Create the full refresh branch\u003C/h4\u003E\n","\u003Cp\u003E\u003Ccode\u003EFULL_PATH\u003C/code\u003E stands in for a full reprocess. It logs \u003Ccode\u003EFULL_PATH\u003C/code\u003E to \u003Ccode\u003ERUN_LOG\u003C/code\u003E, and it runs only when \u003Ccode\u003ECHECK_VOLUME\u003C/code\u003E returned \u003Ccode\u003EFULL\u003C/code\u003E.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EHover over the \u003Cstrong\u003ECHECK_VOLUME\u003C/strong\u003E card and select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector to add a \u003Cstrong\u003ESQL\u003C/strong\u003E task.\u003C/li\u003E\u003Cli\u003ESet \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.FULL_PATH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('FULL_PATH', 'Full refresh branch ran');\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/full-path-general.png?v=d0fdcebc\" alt=\"FULL_PATH General tab\"\u003E\u003C/p\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003ESelect the \u003Cstrong\u003ETask\u003C/strong\u003E tab. Under \u003Cstrong\u003EDependencies\u003C/strong\u003E > \u003Cstrong\u003EAdditional conditions\u003C/strong\u003E, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESYSTEM$GET_PREDECESSOR_RETURN_VALUE('CHECK_VOLUME') = 'FULL'\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/branching-condition.png?v=d0fdcebc\" alt=\"Branching condition on FULL_PATH\"\u003E\u003C/p\u003E\n","\u003Ch4\u003EStep 3: Create the incremental branch\u003C/h4\u003E\n","\u003Cp\u003E\u003Ccode\u003EINCREMENTAL_PATH\u003C/code\u003E stands in for the lighter path. It logs \u003Ccode\u003EINCREMENTAL_PATH\u003C/code\u003E to \u003Ccode\u003ERUN_LOG\u003C/code\u003E, and it runs only when \u003Ccode\u003ECHECK_VOLUME\u003C/code\u003E returned \u003Ccode\u003EINCREMENTAL\u003C/code\u003E.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EHover over the \u003Cstrong\u003ECHECK_VOLUME\u003C/strong\u003E card and select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector again to add a second \u003Cstrong\u003ESQL\u003C/strong\u003E task.\u003C/li\u003E\u003Cli\u003ESet \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.INCREMENTAL_PATH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EUnder \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('INCREMENTAL_PATH', 'Incremental branch ran');\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003ESelect the \u003Cstrong\u003ETask\u003C/strong\u003E tab. Under \u003Cstrong\u003EDependencies\u003C/strong\u003E > \u003Cstrong\u003EAdditional conditions\u003C/strong\u003E, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESYSTEM$GET_PREDECESSOR_RETURN_VALUE('CHECK_VOLUME') = 'INCREMENTAL'\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E \u003Ccode\u003ESYSTEM$GET_PREDECESSOR_RETURN_VALUE\u003C/code\u003E takes the name of a predecessor task without its database and schema, so the condition uses \u003Ccode\u003E'CHECK_VOLUME'\u003C/code\u003E. The name is case-sensitive.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/branching-incremental.png?v=d0fdcebc\" alt=\"Branching condition on INCREMENTAL_PATH\"\u003E\u003C/p\u003E\n","\u003Ch4\u003EStep 4: Deploy and run\u003C/h4\u003E\n","\u003Cp\u003EDeploy the pipeline, and then run the task graph.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-branching.png?v=d0fdcebc\" alt=\"Plan for the branching tasks\"\u003E\u003C/p\u003E\n","\u003Cp\u003EWhen the run finishes, check which branch ran:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT logged_at, source, message\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG\nORDER BY logged_at;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Ccode\u003EORDERS_CLEAN\u003C/code\u003E has 5,000 rows, so you should see only \u003Ccode\u003EFULL_PATH\u003C/code\u003E. \u003Ccode\u003EINCREMENTAL_PATH\u003C/code\u003E doesn't write a row, because its condition isn't met.\u003C/p\u003E\n","\u003Ch3\u003EA2: Handle Failures\u003C/h3\u003E\n","\u003Cp\u003EWhen a step fails, you want to know. A task with the \u003Cstrong\u003EAt least one failed\u003C/strong\u003E condition runs only when something upstream fails.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EHover over the \u003Cstrong\u003Edaily_sales_task\u003C/strong\u003E card and select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector to add a \u003Cstrong\u003ESQL\u003C/strong\u003E task. Set \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.FORCE_FAIL\u003C/code\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E under \u003Cstrong\u003EExecution\u003C/strong\u003E, and enter \u003Ccode\u003ESELECT 1/0;\u003C/code\u003E in the \u003Cstrong\u003ESource\u003C/strong\u003E editor. This stands in for a step that breaks.\u003C/li\u003E\u003Cli\u003EHover over the \u003Cstrong\u003EFORCE_FAIL\u003C/strong\u003E card and select \u003Cstrong\u003E+\u003C/strong\u003E on its outgoing connector to add a \u003Cstrong\u003ESQL\u003C/strong\u003E task. Set \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.ON_FAILURE\u003C/code\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E under \u003Cstrong\u003EExecution\u003C/strong\u003E, and in the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('ON_FAILURE', 'A pipeline step failed');\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EOn the \u003Cstrong\u003EON_FAILURE\u003C/strong\u003E drawer, select the \u003Cstrong\u003ETask\u003C/strong\u003E tab, and under \u003Cstrong\u003EDependencies\u003C/strong\u003E, set \u003Cstrong\u003EPredecessors condition\u003C/strong\u003E to \u003Cstrong\u003EAt least one failed\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/failure-condition.png?v=d0fdcebc\" alt=\"At least one failed condition on ON_FAILURE\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003EDeploy and run the graph.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFORCE_FAIL\u003C/strong\u003E fails, and \u003Cstrong\u003EON_FAILURE\u003C/strong\u003E runs and writes to \u003Ccode\u003ERUN_LOG\u003C/code\u003E. In production, the handler could call a stored procedure that sends an alert. When you're done, delete both cards and deploy.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-failure-handler.png?v=d0fdcebc\" alt=\"Plan for the failure handler\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EA3: Add a Finalizer\u003C/h3\u003E\n","\u003Cp\u003EA finalizer task runs after all other tasks in the graph finish, whether they succeeded or failed. It's a good place for cleanup or a run summary. A finalizer can't also be a member of the graph, so you create it as a standalone task first and then attach it to the graph.\u003C/p\u003E\n","\u003Cp\u003E\u003Ccode\u003ERUN_SUMMARY\u003C/code\u003E stands in for an end-of-run report. It writes one row to \u003Ccode\u003ERUN_LOG\u003C/code\u003E with the number of daily sales rows the run produced.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ESelect \u003Cstrong\u003ECreate\u003C/strong\u003E on the canvas toolbar, and then select \u003Cstrong\u003ESQL\u003C/strong\u003E. Don't connect the new card to anything.\u003C/li\u003E\u003Cli\u003ESet \u003Cstrong\u003EName\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_DB.PIPELINE.RUN_SUMMARY\u003C/code\u003E, and under \u003Cstrong\u003EExecution\u003C/strong\u003E, set \u003Cstrong\u003EWarehouse\u003C/strong\u003E to \u003Ccode\u003ETASTY_PIPELINE_QS_WH\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003ESource\u003C/strong\u003E editor, enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nSELECT 'RUN_SUMMARY', COUNT(*) || ' daily sales rows'\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003E\n","\u003Cp\u003EOpen the task graph settings: select \u003Cstrong\u003EObjects\u003C/strong\u003E on the canvas toolbar, select \u003Cstrong\u003ETask graphs\u003C/strong\u003E, and then select \u003Cstrong\u003ETASTY_DAILY_SALES_GRAPH\u003C/strong\u003E. You can also select any task in the graph, select its \u003Cstrong\u003EGraph\u003C/strong\u003E tab, and then select \u003Cstrong\u003EEdit graph settings\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUnder \u003Cstrong\u003ETask graph settings\u003C/strong\u003E, for \u003Cstrong\u003EFinalizer task\u003C/strong\u003E, select \u003Cstrong\u003ERUN_SUMMARY\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/finalizer-setting.png?v=d0fdcebc\" alt=\"Finalizer task setting\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EDeploy, and then run the task graph.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EWhen the run finishes, check \u003Ccode\u003ERUN_LOG\u003C/code\u003E:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT logged_at, source, message\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG\nORDER BY logged_at;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe last row is from \u003Ccode\u003ERUN_SUMMARY\u003C/code\u003E, written after every other task in the graph finished. On the graph's \u003Cstrong\u003EGraph\u003C/strong\u003E tab in Snowsight, the finalizer appears with a \u003Cstrong\u003EFinalized by\u003C/strong\u003E label.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/finalizer-graph.png?v=d0fdcebc\" alt=\"Task graph with a finalizer\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ETroubleshooting\u003C/h2\u003E\n","\u003Cp\u003EMost problems in this Quickstart come from creating the pipeline with a role other than \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E. The pipeline's owner role is set when you create it, so switching your Snowsight role afterward doesn't change which role deploys.\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EError or symptom\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECause\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EFix\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ECreating the pipeline fails with "ACCOUNTADMIN must have CREATE DCM PROJECT on SCHEMA TASTY_PIPELINE_QS_DB.PIPELINE."\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EYour Snowsight role was ACCOUNTADMIN when you created the pipeline\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESwitch your Snowsight role to \u003Cstrong\u003ETASTY_PIPELINE_QS_ROLE\u003C/strong\u003E, and create the pipeline again\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EDeployment fails on \u003Ccode\u003ECREATE NOTEBOOK PROJECT\u003C/code\u003E or \u003Ccode\u003ECREATE TASK\u003C/code\u003E, and the error names ACCOUNTADMIN\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThe pipeline's \u003Ccode\u003Eproject_owner\u003C/code\u003E in \u003Cstrong\u003Emanifest.yml\u003C/strong\u003E is \u003Ccode\u003EACCOUNTADMIN\u003C/code\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EChange the target's owner to \u003Ccode\u003ETASTY_PIPELINE_QS_ROLE\u003C/code\u003E: open the DCM project controls in the bottom pane, open the target menu, and select the pencil icon. Or delete the pipeline folder and create it again as the guide role.\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Cstrong\u003EReview planned changes\u003C/strong\u003E shows an \u003Cstrong\u003EALTER\u003C/strong\u003E on \u003Cstrong\u003EACCOUNTADMIN\u003C/strong\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESame as above\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESame as above\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ERunning the graph fails with "Cannot execute task, USAGE privilege on the task's schema and database must be granted to owner role."\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThe tasks are owned by a role, such as ACCOUNTADMIN, that has no usage on the guide database\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EFix the owner role as above and redeploy, so the guide role owns the tasks\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ECreating the API integration in the \u003Cstrong\u003ECreate API Integration\u003C/strong\u003E dialog fails\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EYour Snowsight role can't create integrations\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESwitch your Snowsight role to ACCOUNTADMIN, or ask your admin to create the integration for you\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EClean Up\u003C/h2\u003E\n","\u003Cp\u003ELet's remove everything this Quickstart created. \u003Cstrong\u003Ecleanup.sql\u003C/strong\u003E in the companion repo does it in order. Start with the DCM project, because it knows every object it manages.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EOpen \u003Cstrong\u003Ecleanup.sql\u003C/strong\u003E. If you deployed the CoCo pipeline, uncomment its two lines.\u003C/li\u003E\u003Cli\u003ERun the first part as the guide role. \u003Ccode\u003EPURGE\u003C/code\u003E runs a deployment with no definitions, so it drops every task, task graph, and Code Bundle the project manages, and records the purge in the project's deployment history. Purge doesn't drop the project object itself, so the script drops it next.\u003C/li\u003E\u003Cli\u003ERun the second part as ACCOUNTADMIN. It drops the database, compute pool, warehouse, Git API integration, and role. Dropping the database also removes the sample data and the tables your notebooks created, which the DCM project didn't manage.\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImportant:\u003C/strong\u003E Purge before you drop. Dropping a DCM project without purging it first leaves its tasks and task graphs in your account as unmanaged objects.\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E If your DCM project names differ, check them with \u003Ccode\u003ESHOW DCM PROJECTS IN SCHEMA TASTY_PIPELINE_QS_DB.PIPELINE;\u003C/code\u003E.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EFinally, delete the workspace you created from the companion repo.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003ETasty Bytes' daily sales table no longer depends on someone remembering to run two notebooks. You turned them into a scheduled task graph on a canvas, reviewed a plan before anything changed, and deployed it, without writing a \u003Ccode\u003ECREATE TASK\u003C/code\u003E statement.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EDragging notebooks onto the Pipeline Builder canvas creates tasks and the Code Bundles that package your code\u003C/li\u003E\u003Cli\u003EConnecting tasks creates a task graph that holds the schedule and the defaults its tasks share\u003C/li\u003E\u003Cli\u003EEvery deployment is planned first, and the declarative model creates, alters, and drops objects to match your project\u003C/li\u003E\u003Cli\u003EHow to run and monitor a task graph from Snowsight or with \u003Ccode\u003EEXECUTE TASK GRAPH\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EHow to have CoCo draft a pipeline for you to review\u003C/li\u003E\u003Cli\u003EHow to purge a DCM project to clean up everything it manages\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EResources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder\"\u003ECompanion repo\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-overview\"\u003EPipeline Builder\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-build\"\u003EBuild and configure pipelines with Pipeline Builder\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-conditions\"\u003ERun tasks conditionally\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-deploy\"\u003EDeploy, run, and monitor pipelines\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/code-bundles/code-bundles\"\u003ECode Bundles\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/developers/guides/dcm-projects-for-tasks/\"\u003EDCM Projects for Tasks\u003C/a\u003E: build a similar task graph code-first with DCM definition files\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/developers/guides/getting-started-with-task-graphs/\"\u003EGetting Started with Task Graphs\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"title":"Getting Started with Pipeline Builder",":items":{},":itemsOrder":[],"isDeveloperGuidesPage":false,"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!-- ------------------------ --\u003E\n## Overview\n\nTasty Bytes is a fictional global food truck company. Every morning its data engineering team receives the previous day's raw orders, and analysts expect a clean daily sales-by-truck table to be ready by 6:00 AM. Today, a teammate opens two notebooks and runs them by hand. One cleans the raw orders, and the other builds the daily sales table.\n\nIn this Quickstart, you'll turn those two notebooks into a scheduled pipeline with Pipeline Builder, a visual designer in Snowflake Workspaces. You drag notebooks onto a canvas, connect them to set the order they run in, and deploy. Pipeline Builder creates the tasks, the task graph, and the Code Bundles that package your code. You don't write `CREATE TASK` statements by hand.\n\nEach pipeline is also a DCM project. Before anything changes in your account, you see a plan of every object a deployment will create, alter, or drop.\n\n\u003E **Note:** Pipeline Builder is in public preview.\n\n### Prerequisites\n- A Snowflake account (or [free trial](https://signup.snowflake.com/)) in a region where Pipeline Builder and Snowpark Container Services are available\n- Familiarity with SQL and basic Python\n\n### What You'll Learn\n- How to turn notebooks into tasks by dragging them onto the Pipeline Builder canvas\n- How connecting tasks creates a task graph, and how to schedule the graph as one unit\n- How to plan and deploy a pipeline as a DCM project, and how the declarative model creates, alters, and drops objects\n- How to run and monitor a deployed task graph in Snowsight\n- How to generate a pipeline draft with CoCo\n\n### What You'll Need\n- The ACCOUNTADMIN role, or an admin who can run the role and grants block in the next step. Creating the warehouse, compute pool, and database requires ACCOUNTADMIN.\n- Access to Workspaces in Snowsight\n- The [companion repo](https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder), which you clone into a workspace in the next step. It's public, so you don't need a GitHub account.\n\n### What You'll Build\n- A Tasty Bytes daily sales pipeline: a task graph that cleans raw food truck orders, then builds a daily sales table per truck, on a 6:00 AM schedule\n\n```console\nRAW.ORDERS ──\u003E clean_orders_task (notebook) ──\u003E STAGING.ORDERS_CLEAN\n                     │\n                     v\n               daily_sales_task (notebook) ──\u003E ANALYTICS.DAILY_TRUCK_SALES\n```\n\n\u003C!-- ------------------------ --\u003E\n## Setup\n\nIn this step, you clone the companion repo into a workspace, then run its setup script to create the role, warehouse, compute pool, database, and sample data this Quickstart uses. Do this step as ACCOUNTADMIN: make sure ACCOUNTADMIN is selected in your Snowsight user menu in the lower-left corner.\n\n\u003E **Note:** If you don't have ACCOUNTADMIN access, ask your Snowflake admin to create an API integration named `TASTY_PIPELINE_QS_GIT_INT` that allows `https://github.com/Snowflake-Labs`, grant your role `USAGE` on it, and run [setup.sql](https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder/blob/main/setup.sql) with your user name. Then clone the repo with the steps below and skip to Switch to the guide role.\n\n### Get the companion repo\n\n1. In Snowsight, click **Workspaces**.\n2. In the workspaces UI, click **Create new Git workspace**.\n3. For **Repository URL**, enter `https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder`.\n4. Next to **API integration**, select **+ API Integration**, and fill in the **Create API Integration** dialog:\n   - For **Name**, enter `TASTY_PIPELINE_QS_GIT_INT`. Use this exact name, so **cleanup.sql** can drop it at the end.\n   - For **Allowed prefixes**, enter `https://github.com/Snowflake-Labs`.\n   - For **Allowed authentication secrets**, select **None**. The repo is public, so it doesn't need a secret.\n   - Leave **Enable OAuth authentication** cleared, and select **Create**.\n\n   ![Create API Integration dialog](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-api-integration.png?v=d0fdcebc)\n\n5. Back in the **Create workspace from Git repository** dialog, select **Public repository**. You can't push changes back to the repo with public authentication, and this Quickstart doesn't need to. Leave **Workspace name** as it fills in from the URL.\n\n   ![Create workspace from Git repository dialog](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-workspace-from-git.png?v=d0fdcebc)\n\n6. Select **Create**.\n\nThe workspace opens with **setup.sql**, **cleanup.sql**, **01_clean_orders.ipynb**, and **02_daily_sales.ipynb**.\n\n\u003E **Important:** The repo gets fixes over time, so pull the latest changes now, before you start. Once you move the notebooks into your pipeline's folder later in this Quickstart, your workspace has local changes, and pulling again can conflict with them.\n\n### Run the setup script\n\nOpen **setup.sql**, replace `\u003Cyour_username\u003E` with your Snowflake user name, and run the whole file as ACCOUNTADMIN.\n\nHere's what the script does:\n\n- Creates the `TASTY_PIPELINE_QS_ROLE` role and grants it to you and to `SYSADMIN`\n- Creates the `TASTY_PIPELINE_QS_WH` warehouse and the `TASTY_PIPELINE_QS_POOL` compute pool. Notebooks in Pipeline Builder run on a compute pool.\n- Creates the `TASTY_PIPELINE_QS_DB` database and makes the guide role its owner, so the role can create the schemas, tables, tasks, task graphs, Code Bundles, and DCM project the pipeline needs\n- Grants the guide role `EXECUTE TASK` on the account\n- Creates a RAW, STAGING, ANALYTICS, and PIPELINE schema. The PIPELINE schema holds the pipeline's tasks, task graph, Code Bundle, and DCM project.\n- Seeds about 5,000 Tasty Bytes orders, plus 200 duplicate orders and 50 invalid orders for the pipeline to clean up\n- Creates a `RUN_LOG` table that the optional Advanced modules write to\n\nThe last statement returns `raw_rows` = `5250`.\n\n### Switch to the guide role\n\nYou create the pipeline in the next step, and it has to be created with the guide role. If you create it as ACCOUNTADMIN, deployments and runs fail with privilege errors.\n\n1. In the lower-left corner of Snowsight, select your name.\n2. Select **Switch role**.\n3. Select **TASTY_PIPELINE_QS_ROLE**.\n4. Confirm that your name in the lower-left corner now shows **TASTY_PIPELINE_QS_ROLE**.\n\nChanging the role selector inside a SQL file doesn't count. Pipeline Builder uses the role in your user menu.\n\n\u003C!-- ------------------------ --\u003E\n## Create the Pipeline\n\nA Pipeline Builder pipeline lives in a project folder in your workspace. Let's create one.\n\n1. In Snowsight, open your workspace.\n2. In the file explorer, select **Add new**, and then select **Pipeline Builder**.\n3. In the **Create Pipeline Builder** dialog, enter `Pipeline_builder_quickstart` for the **Name**. Pipeline Builder creates a folder with this name for the pipeline.\n4. Select **Select database and schema**, and select `TASTY_PIPELINE_QS_DB.PIPELINE`. This is where the pipeline's DCM project object is created.\n5. Select **Create**.\n\n![Create Pipeline Builder dialog](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/create-pipeline-dialog.png?v=d0fdcebc)\n\nPipeline Builder creates a **Pipeline_builder_quickstart** project folder and opens an empty canvas. The folder contains:\n\n- **manifest.yml**: the DCM project's manifest, including its deployment target\n- **sources/**: a folder for DCM definition files\n\nWhen you add your first task, Pipeline Builder also creates **pipeline.yml**, which holds the tasks, task graphs, and Code Bundles you build on the canvas. You won't edit these files in this Quickstart. Pipeline Builder writes to them for you.\n\nOpen **manifest.yml** and confirm that the target's `project_owner` is `TASTY_PIPELINE_QS_ROLE`. If it shows another role, such as `ACCOUNTADMIN`, see Troubleshooting before you continue.\n\n![Pipeline_builder_quickstart project folder](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/project-folder.png?v=d0fdcebc)\n\n### Move the notebooks into the pipeline\n\nNow add the two notebooks your teammate has been running by hand. They came with the companion repo, at the root of your workspace. Pipeline Builder can only turn files inside the pipeline's project folder into tasks, so move them there first.\n\nIn the file explorer, drag **01_clean_orders.ipynb** and **02_daily_sales.ipynb** into the **Pipeline_builder_quickstart** folder. Drop them at the root of the folder, not in **sources/** or **out/**. Pipeline Builder can't turn files in those two folders into tasks.\n\nHere's what the notebooks do:\n\n- **01_clean_orders.ipynb** drops the invalid rows, removes the duplicates, and writes `STAGING.ORDERS_CLEAN`\n- **02_daily_sales.ipynb** aggregates the clean orders into one row per day, truck, and city in `ANALYTICS.DAILY_TRUCK_SALES`\n- Both use fully qualified table names, because a notebook that runs as a task doesn't have a current database or schema\n\n\u003E **Note:** You can open each notebook and run its cell to check it works. Running it now also creates the tables early, which is fine: the pipeline replaces them on every run.\n\n![Notebook with a single SQL cell](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/notebook-sql-cell.png?v=d0fdcebc)\n\n\u003C!-- ------------------------ --\u003E\n## Turn Notebooks into Tasks\n\nThis is where Pipeline Builder starts saving you work. You drag your notebooks onto the canvas, without publishing them or uploading files to a stage.\n\nIf the canvas isn't open, go back to it: select the **Pipeline Builder** tab for **Pipeline_builder_quickstart** at the top of the editor, or, in the file explorer, hover over the **Pipeline_builder_quickstart** folder and select the **Open pipeline builder** icon. Keep the file explorer visible next to the canvas, then drag **01_clean_orders.ipynb** from the file explorer and drop it anywhere on the canvas.\n\nPipeline Builder adds a card with a **Notebook** badge and opens the task's settings drawer. Behind the scenes, it also creates a Code Bundle that packages the project's code so Snowflake can run it, and fills in a default runtime, compute pool, and warehouse.\n\nIn the drawer, on the **General** tab:\n\n1. Confirm that **Name** is `TASTY_PIPELINE_QS_DB.PIPELINE.clean_orders_task`. Pipeline Builder names the task after the file and the project's database and schema. Names in Pipeline Builder are always fully qualified.\n2. Confirm that **Entrypoint** points at **01_clean_orders.ipynb**.\n3. Under **Execution**, for **Warehouse**, set to `TASTY_PIPELINE_QS_WH`.\n\n![Task drawer for clean_orders_task](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/first-task-drawer.png?v=d0fdcebc)\n\nOn the **Specification** tab:\n\n1. For **Compute pool**, set to `TASTY_PIPELINE_QS_POOL`.\n2. For **Query warehouse**, set to `TASTY_PIPELINE_QS_WH`. This warehouse runs the SQL that the notebook issues.\n3. Leave **Runtime version** at its default.\n\n\u003E **Note:** If a field shows an error with a **Fix** action, the value is close to an existing object, for example a name with the wrong case. Select **Fix** to correct it.\n\n![Specification tab](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/specification-tab.png?v=d0fdcebc)\n\n### Add the second task\n\nNow drag **02_daily_sales.ipynb** onto the right side of the **clean_orders_task** card. When the **Run After** hint appears, drop the file.\n\nPipeline Builder adds a second task, connects the two cards, and makes the new task run after **clean_orders_task**. The new task reuses the same Code Bundle.\n\nIn its drawer, confirm that **Name** is `TASTY_PIPELINE_QS_DB.PIPELINE.daily_sales_task`, and under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`. On the **Specification** tab, select the same compute pool and query warehouse as the first task.\n\nThen select the **clean_orders_task** card and check its **Warehouse** again. Connecting the tasks can clear it. If it's empty, set it to `TASTY_PIPELINE_QS_WH`.\n\nYou now have two connected cards on the canvas. You can also connect cards by dragging from the outgoing connector on the right of one card to the incoming connector on the left of another.\n\n![Two connected tasks on the canvas](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/two-tasks-connected.png?v=d0fdcebc)\n\n\u003C!-- ------------------------ --\u003E\n## Schedule the Task Graph\n\nWhen you connected the two tasks, Pipeline Builder quietly did something else: it created a task graph that contains both of them. A task graph is a first-class object that holds the schedule, run policies, and the defaults its tasks inherit. **clean_orders_task** has no predecessors, so it's the graph's root.\n\nPipeline Builder also moved any values the tasks share, such as the warehouse, into the graph's task defaults. Let's look.\n\n1. Select **Objects** on the canvas toolbar, and then select **Task graphs**.\n2. Select the task graph that Pipeline Builder created.\n3. Under **Task graph object**, set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.TASTY_DAILY_SALES_GRAPH`.\n4. Under **Task graph settings**, for **Schedule**, select **Cron**. Enter `0 6 * * *`, and select your time zone (e.g., `0 6 * * * UTC`).\n5. For **Desired state**, leave **Suspended**. You'll run the graph manually for now, so it doesn't start running on a schedule and using credits before you're ready.\n6. Under **Task defaults**, confirm that **Warehouse** is `TASTY_PIPELINE_QS_WH`. Any task in the graph that doesn't set its own warehouse uses this one.\n7. Under **Tasks in this graph**, confirm both tasks are listed, with **clean_orders_task** marked **Root**.\n\nYou can open the same settings from any task: select the task, select the **Graph** tab, and then select **Edit graph settings**.\n\n![Task graph settings](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/task-graph-settings.png?v=d0fdcebc)\n\n\u003C!-- ------------------------ --\u003E\n## Plan and Deploy\n\nNothing you've built exists in your account yet. A pipeline doesn't run until you deploy it, and deploying starts with a plan that shows exactly what will change.\n\n1. Select **Deploy** in the upper-right corner of the canvas. If you don't see it, collapse the workspace's bottom pane.\n2. In the **Review planned changes** dialog, review the list. This first deployment creates the Code Bundle, the **clean_orders_task** and **daily_sales_task** tasks, and the **TASTY_DAILY_SALES_GRAPH** task graph. It also lists an **ALTER** on **TASTY_PIPELINE_QS_ROLE**. Confirm that this row names `TASTY_PIPELINE_QS_ROLE`. If it names `ACCOUNTADMIN`, the pipeline was created with the wrong role. Cancel and see Troubleshooting.\n\n   ![Review planned changes dialog](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/review-planned-changes.png?v=d0fdcebc)\n\n3. Select **Deploy**.\n\nWhile the deployment runs, the **Deploy** button changes to **Cancel**. When it finishes, a **Deployed Project** button appears next to **Deploy**.\n\nThis plan-then-deploy loop comes from DCM. The project files describe the objects you want, not the steps to create them. Each deployment compares the files with your account and creates, alters, or drops objects to match, in the right order.\n\n\u003C!-- ------------------------ --\u003E\n## Run and Monitor\n\nThe graph is deployed but suspended. Let's run it once now, ahead of its 6:00 AM schedule.\n\n1. Select **Deployed Project**. The DCM project opens in Snowsight on the **Objects** tab, which lists the tasks, task graph, and Code Bundle the project manages.\n\n   ![Deployed project objects](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/deployed-project-objects.png?v=d0fdcebc)\n\n2. Select **TASTY_DAILY_SALES_GRAPH** to open its details page.\n3. Select the **Graph** tab, and then select the **Run Task Graph** (play) icon in the toolbar above the graph.\n\n   ![Run Task Graph icon on the Graph tab](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/run-task-graph.png?v=d0fdcebc)\n\n4. To watch the run while it's in progress, open a task's details page (for example, select **clean_orders_task** on the **Objects** tab of the DCM project) and select its **Run History** tab. The task graph's **Overview** tab shows the run once it finishes.\n\nYou can also run the graph from SQL:\n\n```sql\nEXECUTE TASK GRAPH TASTY_PIPELINE_QS_DB.PIPELINE.TASTY_DAILY_SALES_GRAPH;\n```\n\nA task that belongs to a task graph runs only as part of its graph. You can't run **daily_sales_task** on its own.\n\n\u003E **Note:** The first run after the compute pool resumes can take a few minutes while the pool starts. If a notebook task fails quickly on that first run, run the graph again once the pool is active.\n\nWhen both tasks succeed, check the output:\n\n```sql\nSELECT city, SUM(orders) AS orders, SUM(revenue) AS revenue\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES\nGROUP BY city\nORDER BY revenue DESC;\n```\n\nYou should see five cities. Check the clean row count too:\n\n```sql\nSELECT COUNT(*) AS clean_orders FROM TASTY_PIPELINE_QS_DB.STAGING.ORDERS_CLEAN;\n```\n\nYou should see `clean_orders` = `5000`: the 200 duplicates and the 50 invalid orders are gone.\n\n\u003C!-- ------------------------ --\u003E\n## Change It Like Code\n\nBecause the pipeline is a DCM project, every deployment brings your account in line with the project files. Let's see what that means in practice.\n\n### Redeploy with no changes\n\nSelect **Deploy** again without changing anything. Pipeline Builder shows \"No changes to deploy.\" and doesn't deploy. Deployments are safe to repeat.\n\n![No changes to deploy](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/no-changes-to-deploy.png?v=d0fdcebc)\n\n### Add a task\n\nAnalysts have asked for a daily leaderboard of the top five trucks. Let's add a SQL task after **daily_sales_task** that rebuilds it on every run. A SQL task is also how you run stored procedures or any other Snowflake object from a pipeline.\n\n1. Hover over the **daily_sales_task** card, select **+** on its outgoing connector, and then select **SQL**. Pipeline Builder adds a new card that runs after **daily_sales_task**.\n2. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.top_trucks_task`.\n3. Under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`.\n4. In the **Source** editor, enter:\n\n```sql\nCREATE OR REPLACE TABLE TASTY_PIPELINE_QS_DB.ANALYTICS.TOP_TRUCKS AS\nSELECT truck_id, city, SUM(revenue) AS revenue\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES\nGROUP BY ALL\nORDER BY revenue DESC\nLIMIT 5;\n```\n\n5. Select **Deploy**. The plan shows **TOP_TRUCKS_TASK** as a task to create and an **ALTER** on **TASTY_PIPELINE_QS_ROLE**. Confirm the **ALTER** row still names `TASTY_PIPELINE_QS_ROLE`, and then select **Deploy**.\n\n   ![Plan for adding a task](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-add-task.png?v=d0fdcebc)\n\n### Delete a task\n\nNow suppose the analysts change their minds. On the **top_trucks_task** card, select the **⋮** menu, and then select **Delete**. Select **Deploy**.\n\nThis time, the plan shows **top_trucks_task** as a task to drop. Deleting a card removes it from the project files, and the next deployment drops the task from your account. You never write a `DROP TASK`.\n\n\u003E **Note:** The deployment drops the task, but not the `TOP_TRUCKS` table the task created if it ran. DCM manages the objects defined in the project, such as tasks, task graphs, and Code Bundles. Tables that your code creates at run time aren't part of the project.\n\n![Plan for deleting a task](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-drop-task.png?v=d0fdcebc)\n\n### Turn on the schedule (optional)\n\nTo have Tasty Bytes' sales table ready every morning, open the task graph settings: select **Objects** on the canvas toolbar, select **Task graphs**, and then select **TASTY_DAILY_SALES_GRAPH**. Set **Desired state** to **Resumed**, and deploy. The graph then runs every day at 6:00 AM. If you do this, remember to clean up at the end of the Quickstart so the graph stops running.\n\n\u003C!-- ------------------------ --\u003E\n## Build with CoCo\n\nYou've built a pipeline card by card. Now let's have CoCo draft one from a description.\n\n1. In the file explorer, select **Add new**, and then select **Pipeline Builder**.\n2. In the **Create Pipeline Builder** dialog, enter `tasty_menu_popularity` for the **Name**, and select `TASTY_PIPELINE_QS_DB.PIPELINE` for **Database and schema**.\n3. Select **Generate with Cortex**.\n4. In the **Prompt** field, enter:\n\n```console\nBuild a weekly pipeline for Tasty Bytes over TASTY_PIPELINE_QS_DB.RAW.ORDERS.\nStep 1: a SQL task that writes weekly order counts and revenue per city to\nTASTY_PIPELINE_QS_DB.ANALYTICS.WEEKLY_CITY_SALES.\nStep 2: a SQL task, after step 1, that writes the top city for each week to\nTASTY_PIPELINE_QS_DB.ANALYTICS.WEEKLY_TOP_CITY.\nPut all tasks in TASTY_PIPELINE_QS_DB.PIPELINE, use warehouse TASTY_PIPELINE_QS_WH,\nand schedule the graph every Monday at 7:00 AM America/Los_Angeles, suspended.\n```\n\n5. Select **Generate**.\n\nCoCo writes the tasks, the connection between them, and the task graph settings to the new project's definition file, so you can review its work on the canvas before anything is deployed. Select each card to check its SQL. To check the schedule, select **Objects** on the canvas toolbar, select **Task graphs**, and then select the graph CoCo created. If it looks right, select **Deploy** to plan and deploy it the same way as the first pipeline.\n\nTo change an existing pipeline with CoCo, open the CoCo chat in your workspace and use the `/pipeline-builder` skill. For example, ask it to add a task to **Pipeline_builder_quickstart**.\n\n\u003C!-- ------------------------ --\u003E\n## Advanced: Optional Modules\n\nYou've built, deployed, run, and changed a pipeline. That's the core of Pipeline Builder. The modules below go further. Each one starts from the **Pipeline_builder_quickstart** pipeline as you left it in Change It Like Code, and none depend on each other, so pick the ones that match your pipelines.\n\nEach module ends with a deployment. To compare what changed, review the **Review planned changes** dialog before you select **Deploy**.\n\nBefore you start, make sure you're back on the **Pipeline_builder_quickstart** canvas, not the pipeline CoCo generated in the previous step. Select its **Pipeline Builder** tab, or, in the file explorer, hover over the **Pipeline_builder_quickstart** folder and select the **Open pipeline builder** icon.\n\nFor every task you add in these modules, set **Warehouse** to `TASTY_PIPELINE_QS_WH` under **Execution** on the task's **General** tab, as you did for the first two tasks.\n\nSeveral modules write to `TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG`, a small log table that **setup.sql** already created. It has three columns: `logged_at`, `source`, and `message`.\n\n### A1: Branch on a Return Value\n\nTasty Bytes wants to reprocess everything when order volume is high, and take a lighter path otherwise. You'll build three tasks: one that decides, and one for each branch. To keep the focus on branching, each branch task writes a row to `RUN_LOG`. In a real pipeline, that's where the full or incremental logic would go.\n\n```console\nclean_orders_task ──\u003E CHECK_VOLUME ──\u003E FULL_PATH\n                                  └──\u003E INCREMENTAL_PATH\n```\n\n#### Step 1: Create the deciding task\n\n`CHECK_VOLUME` counts the clean orders and sets its return value to `FULL` if there are more than 4,000, or `INCREMENTAL` otherwise. Tasks that run after it can read that value.\n\n1. Hover over the **clean_orders_task** card and select **+** on its outgoing connector to add a **SQL** task.\n2. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.CHECK_VOLUME`.\n3. Under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`.\n4. In the **Source** editor, enter:\n\n```sql\nEXECUTE IMMEDIATE $$\nDECLARE\n  path STRING;\nBEGIN\n  SELECT IFF(COUNT(*) \u003E 4000, 'FULL', 'INCREMENTAL') INTO :path\n  FROM TASTY_PIPELINE_QS_DB.STAGING.ORDERS_CLEAN;\n  CALL SYSTEM$SET_RETURN_VALUE(:path);\nEND;\n$$;\n```\n\nThe block computes the path into a variable first, because `SYSTEM$SET_RETURN_VALUE` only accepts a constant or a variable, not a subquery.\n\n#### Step 2: Create the full refresh branch\n\n`FULL_PATH` stands in for a full reprocess. It logs `FULL_PATH` to `RUN_LOG`, and it runs only when `CHECK_VOLUME` returned `FULL`.\n\n1. Hover over the **CHECK_VOLUME** card and select **+** on its outgoing connector to add a **SQL** task.\n2. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.FULL_PATH`.\n3. Under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`.\n4. In the **Source** editor, enter:\n\n```sql\nINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('FULL_PATH', 'Full refresh branch ran');\n```\n\n![FULL_PATH General tab](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/full-path-general.png?v=d0fdcebc)\n\n5. Select the **Task** tab. Under **Dependencies** \u003E **Additional conditions**, enter:\n\n```sql\nSYSTEM$GET_PREDECESSOR_RETURN_VALUE('CHECK_VOLUME') = 'FULL'\n```\n\n![Branching condition on FULL_PATH](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/branching-condition.png?v=d0fdcebc)\n\n#### Step 3: Create the incremental branch\n\n`INCREMENTAL_PATH` stands in for the lighter path. It logs `INCREMENTAL_PATH` to `RUN_LOG`, and it runs only when `CHECK_VOLUME` returned `INCREMENTAL`.\n\n1. Hover over the **CHECK_VOLUME** card and select **+** on its outgoing connector again to add a second **SQL** task.\n2. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.INCREMENTAL_PATH`.\n3. Under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`.\n4. In the **Source** editor, enter:\n\n```sql\nINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('INCREMENTAL_PATH', 'Incremental branch ran');\n```\n\n5. Select the **Task** tab. Under **Dependencies** \u003E **Additional conditions**, enter:\n\n```sql\nSYSTEM$GET_PREDECESSOR_RETURN_VALUE('CHECK_VOLUME') = 'INCREMENTAL'\n```\n\n\u003E **Note:** `SYSTEM$GET_PREDECESSOR_RETURN_VALUE` takes the name of a predecessor task without its database and schema, so the condition uses `'CHECK_VOLUME'`. The name is case-sensitive.\n\n![Branching condition on INCREMENTAL_PATH](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/branching-incremental.png?v=d0fdcebc)\n\n#### Step 4: Deploy and run\n\nDeploy the pipeline, and then run the task graph.\n\n![Plan for the branching tasks](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-branching.png?v=d0fdcebc)\n\nWhen the run finishes, check which branch ran:\n\n```sql\nSELECT logged_at, source, message\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG\nORDER BY logged_at;\n```\n\n`ORDERS_CLEAN` has 5,000 rows, so you should see only `FULL_PATH`. `INCREMENTAL_PATH` doesn't write a row, because its condition isn't met.\n\n### A2: Handle Failures\n\nWhen a step fails, you want to know. A task with the **At least one failed** condition runs only when something upstream fails.\n\n1. Hover over the **daily_sales_task** card and select **+** on its outgoing connector to add a **SQL** task. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.FORCE_FAIL`, set **Warehouse** to `TASTY_PIPELINE_QS_WH` under **Execution**, and enter `SELECT 1/0;` in the **Source** editor. This stands in for a step that breaks.\n2. Hover over the **FORCE_FAIL** card and select **+** on its outgoing connector to add a **SQL** task. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.ON_FAILURE`, set **Warehouse** to `TASTY_PIPELINE_QS_WH` under **Execution**, and in the **Source** editor, enter:\n\n```sql\nINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nVALUES ('ON_FAILURE', 'A pipeline step failed');\n```\n\n3. On the **ON_FAILURE** drawer, select the **Task** tab, and under **Dependencies**, set **Predecessors condition** to **At least one failed**.\n\n![At least one failed condition on ON_FAILURE](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/failure-condition.png?v=d0fdcebc)\n\n4. Deploy and run the graph.\n\n**FORCE_FAIL** fails, and **ON_FAILURE** runs and writes to `RUN_LOG`. In production, the handler could call a stored procedure that sends an alert. When you're done, delete both cards and deploy.\n\n![Plan for the failure handler](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/plan-failure-handler.png?v=d0fdcebc)\n\n### A3: Add a Finalizer\n\nA finalizer task runs after all other tasks in the graph finish, whether they succeeded or failed. It's a good place for cleanup or a run summary. A finalizer can't also be a member of the graph, so you create it as a standalone task first and then attach it to the graph.\n\n`RUN_SUMMARY` stands in for an end-of-run report. It writes one row to `RUN_LOG` with the number of daily sales rows the run produced.\n\n1. Select **Create** on the canvas toolbar, and then select **SQL**. Don't connect the new card to anything.\n2. Set **Name** to `TASTY_PIPELINE_QS_DB.PIPELINE.RUN_SUMMARY`, and under **Execution**, set **Warehouse** to `TASTY_PIPELINE_QS_WH`.\n3. In the **Source** editor, enter:\n\n```sql\nINSERT INTO TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG (source, message)\nSELECT 'RUN_SUMMARY', COUNT(*) || ' daily sales rows'\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.DAILY_TRUCK_SALES;\n```\n\n4. Open the task graph settings: select **Objects** on the canvas toolbar, select **Task graphs**, and then select **TASTY_DAILY_SALES_GRAPH**. You can also select any task in the graph, select its **Graph** tab, and then select **Edit graph settings**.\n5. Under **Task graph settings**, for **Finalizer task**, select **RUN_SUMMARY**.\n\n   ![Finalizer task setting](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/finalizer-setting.png?v=d0fdcebc)\n\n6. Deploy, and then run the task graph.\n\nWhen the run finishes, check `RUN_LOG`:\n\n```sql\nSELECT logged_at, source, message\nFROM TASTY_PIPELINE_QS_DB.ANALYTICS.RUN_LOG\nORDER BY logged_at;\n```\n\nThe last row is from `RUN_SUMMARY`, written after every other task in the graph finished. On the graph's **Graph** tab in Snowsight, the finalizer appears with a **Finalized by** label.\n\n![Task graph with a finalizer](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-pipeline-builder/finalizer-graph.png?v=d0fdcebc)\n\n\u003C!-- ------------------------ --\u003E\n## Troubleshooting\n\nMost problems in this Quickstart come from creating the pipeline with a role other than `TASTY_PIPELINE_QS_ROLE`. The pipeline's owner role is set when you create it, so switching your Snowsight role afterward doesn't change which role deploys.\n\n| Error or symptom | Cause | Fix |\n| --- | --- | --- |\n| Creating the pipeline fails with \"ACCOUNTADMIN must have CREATE DCM PROJECT on SCHEMA TASTY_PIPELINE_QS_DB.PIPELINE.\" | Your Snowsight role was ACCOUNTADMIN when you created the pipeline | Switch your Snowsight role to **TASTY_PIPELINE_QS_ROLE**, and create the pipeline again |\n| Deployment fails on `CREATE NOTEBOOK PROJECT` or `CREATE TASK`, and the error names ACCOUNTADMIN | The pipeline's `project_owner` in **manifest.yml** is `ACCOUNTADMIN` | Change the target's owner to `TASTY_PIPELINE_QS_ROLE`: open the DCM project controls in the bottom pane, open the target menu, and select the pencil icon. Or delete the pipeline folder and create it again as the guide role. |\n| **Review planned changes** shows an **ALTER** on **ACCOUNTADMIN** | Same as above | Same as above |\n| Running the graph fails with \"Cannot execute task, USAGE privilege on the task's schema and database must be granted to owner role.\" | The tasks are owned by a role, such as ACCOUNTADMIN, that has no usage on the guide database | Fix the owner role as above and redeploy, so the guide role owns the tasks |\n| Creating the API integration in the **Create API Integration** dialog fails | Your Snowsight role can't create integrations | Switch your Snowsight role to ACCOUNTADMIN, or ask your admin to create the integration for you |\n\n\u003C!-- ------------------------ --\u003E\n## Clean Up\n\nLet's remove everything this Quickstart created. **cleanup.sql** in the companion repo does it in order. Start with the DCM project, because it knows every object it manages.\n\n1. Open **cleanup.sql**. If you deployed the CoCo pipeline, uncomment its two lines.\n2. Run the first part as the guide role. `PURGE` runs a deployment with no definitions, so it drops every task, task graph, and Code Bundle the project manages, and records the purge in the project's deployment history. Purge doesn't drop the project object itself, so the script drops it next.\n3. Run the second part as ACCOUNTADMIN. It drops the database, compute pool, warehouse, Git API integration, and role. Dropping the database also removes the sample data and the tables your notebooks created, which the DCM project didn't manage.\n\n\u003E **Important:** Purge before you drop. Dropping a DCM project without purging it first leaves its tasks and task graphs in your account as unmanaged objects.\n\n\u003E **Note:** If your DCM project names differ, check them with `SHOW DCM PROJECTS IN SCHEMA TASTY_PIPELINE_QS_DB.PIPELINE;`.\n\nFinally, delete the workspace you created from the companion repo.\n\n\u003C!-- ------------------------ --\u003E\n## Conclusion And Resources\n\nTasty Bytes' daily sales table no longer depends on someone remembering to run two notebooks. You turned them into a scheduled task graph on a canvas, reviewed a plan before anything changed, and deployed it, without writing a `CREATE TASK` statement.\n\n### What You Learned\n- Dragging notebooks onto the Pipeline Builder canvas creates tasks and the Code Bundles that package your code\n- Connecting tasks creates a task graph that holds the schedule and the defaults its tasks share\n- Every deployment is planned first, and the declarative model creates, alters, and drops objects to match your project\n- How to run and monitor a task graph from Snowsight or with `EXECUTE TASK GRAPH`\n- How to have CoCo draft a pipeline for you to review\n- How to purge a DCM project to clean up everything it manages\n\n### Resources\n- [Companion repo](https://github.com/Snowflake-Labs/sfguide-getting-started-with-pipeline-builder)\n- [Pipeline Builder](https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-overview)\n- [Build and configure pipelines with Pipeline Builder](https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-build)\n- [Run tasks conditionally](https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-conditions)\n- [Deploy, run, and monitor pipelines](https://docs.snowflake.com/en/user-guide/pipeline-builder/pipeline-builder-deploy)\n- [Code Bundles](https://docs.snowflake.com/en/developer-guide/code-bundles/code-bundles)\n- [DCM Projects for Tasks](https://www.snowflake.com/en/developers/guides/dcm-projects-for-tasks/): build a similar task graph code-first with DCM definition files\n- [Getting Started with Task Graphs](https://www.snowflake.com/en/developers/guides/getting-started-with-task-graphs/)\n","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],":type":"snowflake-site/components/contentfragment","model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-3ab46cfd39","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-1faadc36f5",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-7c2472eb6c","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-11-03",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-5cc157eea2","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake instances\u003C/span\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"}},":itemsOrder":["quickstart_last_modi","text"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-75ab4af67c",":items":{},":itemsOrder":[],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isBlogPage":false,"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container"}},":itemsOrder":["contentfragment","flexible_column_cont"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-08426162cc",":items":{"quickstart_table_of_":{"layout":"SIMPLE","id":"container-8080b1f730","isDeveloperGuidesPage":false,":items":{"quickstart_table_of_":{"id":"quickstart-table-of-content-5583b183a7","fragmentPath":"/content/dam/snowflake-site/en/content-fragments/quickstarts/getting-started-with-pipeline-builder",":type":"snowflake-site/components/quickstart/quickstart-table-of-content","headings":["\u003Ch2\u003EOverview\u003C/h2\u003E","\u003Ch2\u003ESetup\u003C/h2\u003E","\u003Ch2\u003ECreate the Pipeline\u003C/h2\u003E","\u003Ch2\u003ETurn Notebooks into Tasks\u003C/h2\u003E","\u003Ch2\u003ESchedule the Task Graph\u003C/h2\u003E","\u003Ch2\u003EPlan and Deploy\u003C/h2\u003E","\u003Ch2\u003ERun and Monitor\u003C/h2\u003E","\u003Ch2\u003EChange It Like Code\u003C/h2\u003E","\u003Ch2\u003EBuild with CoCo\u003C/h2\u003E","\u003Ch2\u003EAdvanced: Optional Modules\u003C/h2\u003E","\u003Ch2\u003ETroubleshooting\u003C/h2\u003E","\u003Ch2\u003EClean Up\u003C/h2\u003E","\u003Ch2\u003EConclusion And 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class=\"sf-footer__column-title\"\u003EProduct\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/platform/\"\u003EPlatform\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/product/snowflake-cowork/\"\u003ESnowflake CoWork\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/data-engineering/\"\u003EData Engineering\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003EAnalytics\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/ai/\"\u003EAI\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/applications-and-collaboration/\"\u003EApplications & Collaboration\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca 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