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Iceberg","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides/snowflake-confluent-tableflow-iceberg","currentPage":true},{"title":"Guides","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides","currentPage":false},{"title":"Snowflake for Developers","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers","currentPage":false}],"quickstartHeroTitle":{"lines":["Stream Kafka Data to Snowflake via Confluent Tableflow and Iceberg"],"type":"heading2",":type":"snowflake-site/components/title-v2"},"quickstartHeroAuthor":"Jeremy Ber, Sean 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Repo"}},"flexible_column_cont":{"id":"flexible-column-container-0db483de50","propertiesId":"quickstart-template-main-flexible-container","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"id":"container-620b5cd6d4","layout":"SIMPLE",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"contentfragment":{"id":"contentfragment-e65e05d928","paragraphs":["\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Cp\u003EIn this quickstart, you&rsquo;ll build a real-time data pipeline that connects Apache Kafka with Snowflake, without writing a single custom connector or ETL job. Using Confluent Cloud, Kafka, and Tableflow, you&rsquo;ll stream simulated data into Kafka topics, automatically materialize that data into Apache Iceberg tables on Amazon S3, and expose those tables directly to Snowflake&rsquo;s Open Data Catalog.\u003C/p\u003E\n","\u003Cp\u003EImagine you're building a modern trading platform or a customer-facing analytics dashboard. You're capturing user activity and stock trades as they happen, and you want your data teams and downstream systems to react in near real-time, whether it's for fraud detection, personalized recommendations, or operational intelligence.\u003C/p\u003E\n","\u003Cp\u003ETraditionally, this would require stitching together multiple systems: Kafka for ingestion, Spark or Flink for transformation, cloud storage for persistence, and finally Snowflake for analytics, plus a ton of glue code and scheduling overhead.\u003C/p\u003E\n","\u003Cp\u003EThis quickstart shows how to streamline that entire process:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EKafka\u003C/strong\u003E ingests and transports the data in real time.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ETableflow\u003C/strong\u003E continuously materializes that data into Iceberg tables on \u003Cstrong\u003EAmazon S3\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESnowflake Open Catalog\u003C/strong\u003E connects directly to those tables, giving analysts and apps live access to fresh data using simple SQL.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThis architecture supports use cases like:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EReal-time dashboards\u003C/strong\u003E for trading activity or user behavior\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EFeeding machine learning pipelines\u003C/strong\u003E with live, structured data\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EStreaming feature stores\u003C/strong\u003E for AI/ML applications\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ETechnologies at a Glance\u003C/h3\u003E\n","\u003Ch4\u003EApache Kafka\u003C/h4\u003E\n","\u003Cp\u003EKafka is a distributed event streaming platform used to capture and route real-time data. In this lab, Kafka will act as the backbone for ingesting live event streams like user registrations and stock trades.\u003C/p\u003E\n","\u003Ch4\u003EConfluent Cloud\u003C/h4\u003E\n","\u003Cp\u003EConfluent is a fully managed data streaming platform built on Apache Kafka. It handles the heavy lifting of provisioning, scaling, and securing Kafka in the cloud so you can focus on your data flow, not the infrastructure.\u003C/p\u003E\n","\u003Ch4\u003ETableflow\u003C/h4\u003E\n","\u003Cp\u003ETableflow is a new Confluent-native service that simplifies getting data out of Kafka and into data lake and warehouse formats. It automatically handles schema evolution, file compaction, and catalog registration bridging the world of real-time streaming and batch analytics. Think of it as the glue between Kafka and your Iceberg or Delta Lake tables.\u003C/p\u003E\n","\u003Ch4\u003EApache Iceberg\u003C/h4\u003E\n","\u003Cp\u003EIceberg is an open table format designed for large-scale analytic datasets. It brings reliability and performance to data lakes with features like ACID transactions, schema evolution, and partitioning, making it easy to work with both streaming and batch data as if it were a traditional database table.\u003C/p\u003E\n","\u003Ch3\u003EAssumptions and Prerequisites\u003C/h3\u003E\n","\u003Cp\u003EBefore you begin, make sure you have the following:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://www.confluent.io/get-started\"\u003E\u003Cstrong\u003EConfluent Cloud Account\u003C/strong\u003E\u003C/a\u003E: You&rsquo;ve created (or have access to) a Confluent Cloud account where you can provision Kafka clusters and use Tableflow.\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.aws.amazon.com/AmazonS3/latest/userguide/create-bucket-overview.html\"\u003E\u003Cstrong\u003EAWS Account with S3 Access\u003C/strong\u003E\u003C/a\u003E: You can create or access an Amazon S3 bucket and configure IAM roles and policies.\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://app.snowflake.com/\"\u003E\u003Cstrong\u003ESnowflake Account with OrgAdmin Permissions\u003C/strong\u003E\u003C/a\u003E: You have a Snowflake account with \u003Cstrong\u003EOrganization Administrator\u003C/strong\u003E privileges, required to create an Open Data Catalog and configure external integrations.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You&rsquo;ll Learn in the Lab\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to set up Apache Kafka and streaming data pipelines in Confluent Cloud.\u003C/li\u003E\u003Cli\u003EHow to generate synthetic data using Datagen connectors.\u003C/li\u003E\u003Cli\u003EHow to use Tableflow to write Kafka topics to Apache Iceberg tables stored in Amazon S3.\u003C/li\u003E\u003Cli\u003EHow to configure secure access between AWS, Confluent, and Snowflake using IAM roles and trust policies.\u003C/li\u003E\u003Cli\u003EHow to expose Iceberg tables in Snowflake&rsquo;s Open Data Catalog and run live queries on continuously updated data.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n","\u003Cp\u003EBy the end of this quickstart, you&rsquo;ll have:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EA fully functional \u003Cstrong\u003EConfluent Cloud\u003C/strong\u003E environment with Kafka topics for user and stock trading events.\u003C/li\u003E\u003Cli\u003EReal-time \u003Cstrong\u003EDatagen\u003C/strong\u003E connectors simulating events into Kafka.\u003C/li\u003E\u003Cli\u003EA \u003Cstrong\u003ETableflow pipeline\u003C/strong\u003E writing those topics as Iceberg tables into S3.\u003C/li\u003E\u003Cli\u003EA \u003Cstrong\u003ESnowflake Open Catalog\u003C/strong\u003E integration that makes those Iceberg tables queryable with standard SQL.\u003C/li\u003E\u003C/ul\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003ECreate an environment and Kafka cluster within your Confluent Cloud Account\u003C/h2\u003E\n","\u003Cp\u003EIn Confluent Cloud, we need to create a Kafka cluster to run our Tableflow examples. This Kakfa cluster will be automatically sized and provisioned with a few clicks. This will allow us to stream our datasets for further work with Tableflow.\u003C/p\u003E\n","\u003Cp\u003EIn order to create a Kafka cluster, we need to first create an environment which will house all of the cloud resources we will create in this quickstart guide.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAccess the Environments console by clicking \u003Cstrong\u003EEnvironments\u003C/strong\u003E left-hand side of the Confluent Cloud menu or by clicking \u003Cstrong\u003EEnvironments\u003C/strong\u003E under \u003Cstrong\u003EYour resource overview.\u003C/strong\u003E\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image25.png\" alt=\"\"\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cem\u003EIf you already have an environment created, feel free to skip this section and use your existing environment for the remainder of the quickstart.\u003C/em\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EFrom the Environments console, you will see an option to \u003Cstrong\u003E+ Add cloud environment\u003C/strong\u003E. Click this to begin creating a new environment.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image34.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELet&rsquo;s give our environment a name, \u003Cstrong\u003ESnowflakeTableflowDemo\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELeave the default &ldquo;Essentials&rdquo; governance package selected and click \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image55.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EYou now have a Confluent environment and we can proceed to create our Kafka cluster within the environment.\u003C/li\u003E\u003Cli\u003EOn the next screen, you will be presented with options on which Kakfa cluster to create. Select the Basic option, and click \u003Cstrong\u003EBegin Configuration\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image42.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EOn the next screen, choose \u003Cstrong\u003EAWS\u003C/strong\u003E as the cloud provider, and choose \u003Ccode\u003Eus-east-1\u003C/code\u003E as the region. Then click \u003Cstrong\u003EContinue.\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image24.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EGive your cluster a name, \u003Cstrong\u003Emy-kafka-cluster\u003C/strong\u003E, leave the configurations as default and \u003Cstrong\u003ELaunch cluster.\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image53.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EYou will then see a success banner &ldquo;Cluster created&rdquo;, and be taken to the Cluster Overview page. We are now ready to get started with Tableflow.\u003C/li\u003E\u003C/ul\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003EGetting Started with Tableflow\u003C/h2\u003E\n","\u003Cp\u003ETableflow simplifies the traditionally complex process of moving data from Kafka topics to data lakes or warehouses. It allows users to materialize Kafka topics and schemas into Apache Iceberg or Delta Lake tables within a few clicks, leveraging Confluent&rsquo;s Schema Registry for schema management and evolution. This eliminates manual data mappings and streamlines the data ingestion pipeline. Tableflow also continuously compacts Parquet files for improved read performance and offers integrations with popular catalog services. By unifying streaming and batch processing, Tableflow enables real-time data availability in the data lakehouse and simplifies stream processing jobs.\u003C/p\u003E\n","\u003Ch3\u003ECreate Datagen Connectors for Users and Stock_Trades\u003C/h3\u003E\n","\u003Cp\u003ETo demonstrate how Tableflow moves data from Kafka into Apache Iceberg tables, we&rsquo;ll start by generating sample data into our Kafka topics. These data generators simulate user activity and stock trading data, generating example events that Tableflow will use to hydrate the data lake.\u003C/p\u003E\n","\u003Cp\u003EHere is a sample of the user data topic:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003E{\n  &quot;registertime&quot;: 1491981791331,\n  &quot;userid&quot;: &quot;User_2&quot;,\n  &quot;regionid&quot;: &quot;Region_8&quot;,\n  &quot;gender&quot;: &quot;MALE&quot;\n}\n\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThe stock_trades topic will look like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003E{\n  &quot;side&quot;: &quot;BUY&quot;,\n  &quot;quantity&quot;: 1934,\n  &quot;symbol&quot;: &quot;ZBZX&quot;,\n  &quot;price&quot;: 974,\n  &quot;account&quot;: &quot;XYZ789&quot;,\n  &quot;userid&quot;: &quot;User_9&quot;\n}\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIn this quickstart, we will write the sample data to both the users and stock_trade topic in order to demonstrate how Tableflow works, write to Amazon S3 and reference these tables in Snowflake&rsquo;s Open Data Catalog.\u003C/p\u003E\n","\u003Cp\u003ELet&rsquo;s get started.\u003C/p\u003E\n\u003Chr\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EFrom the Confluent Cloud console, navigate to your environment either via the left-hand side portal or in the middle of the page under \u003Cstrong\u003EYour resource overview.\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFind the environment you created and select it from the list of Environments\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EYou should now see your \u003Cstrong\u003EEnvironment Overview\u003C/strong\u003E screen that shows your Kafka Cluster. \u003Cstrong\u003EClick into your Kafka cluster.\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOn the Cluster Overview screen, you will see Connectors on the left hand screen. Click on Connectors and then search for \u003Cstrong\u003EDatagen Source\u003C/strong\u003E or click the datagen source, it is usually one of the first connectors on the page.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image29.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EChoose the \u003Ccode\u003EUsers\u003C/code\u003E Sample Data.\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003ELaunch\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EThis will start a \u003Cstrong\u003EDatagen Source\u003C/strong\u003E Kafka connector that writes User data to a Kafka topic called \u003Ccode\u003Esample_data_users\u003C/code\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image27.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EYou will then see the connector you created from the Connector Screen, transitioning from Provisioning state to Running.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ERepeat this process to create another Datagen Source using the \u003Cstrong\u003EStock Trades\u003C/strong\u003E sample dataset. Once you have a connector, you should see the option to + \u003Cstrong\u003EAdd Connector\u003C/strong\u003E at the top right. Use this button to create a new datagen connector.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image19.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EUse the \u003Cstrong\u003EStock trades\u003C/strong\u003E dataset this time. Click \u003Cstrong\u003ELaunch.\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image38.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOnce finished, you should have two Datagen sources, \u003Cstrong\u003Esample_data\u003C/strong\u003E and \u003Cstrong\u003Esample_data_1\u003C/strong\u003E in running state on the Connectors screen.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image23.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EVerify that the subsequent Kafka topics have been created by navigating to the \u003Cstrong\u003ETopics\u003C/strong\u003E menu on the left-hand navigation bar. You should see one topic called \u003Ccode\u003Esample_data_users\u003C/code\u003E, and another called \u003Ccode\u003Esample_data_stock_trades\u003C/code\u003E, each with 6 partitions.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image37.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EWe are now in position to start configuring our Tableflow sync process into our Data Lake.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EConfigure your Amazon S3 Bucket and Provider Integration\u003C/h3\u003E\n","\u003Cp\u003EOnce you have your Kafka topics created, you can now get started with Tableflow to sync your data from your Kafka topics into Snowflake Data Cloud.\u003C/p\u003E\n","\u003Cp\u003EBut first, we need an Amazon S3 Bucket to write our Apache Iceberg data to.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIf you already have an Amazon S3 bucket, feel free to skip to the next section\u003C/li\u003E\u003Cli\u003EIn a new tab, navigate to the Amazon S3 console or click \u003Ca href=\"https://us-east-1.console.aws.amazon.com/s3/home?region=us-east-1#\"\u003Ehere\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EClick on \u003Cstrong\u003ECreate Bucket\u003C/strong\u003E on the top right.\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image9.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003ELeave everything default and give your bucket a name. The name of the bucket must be unique so let&rsquo;s name it \u003Cstrong\u003E\u003Ccode\u003Etableflow-bucket-&lt;&lt;Account-ID&gt;&gt;\u003C/code\u003E\u003C/strong\u003E, using your account ID which can be retrieved from the dropdown at the top right of the screen.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image59.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ELeave the rest of the options as default, scroll down and click \u003Cstrong\u003ECreate Bucket\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EConfigure Storage Provider\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EBack on Confluent Cloud, navigate to the \u003Cstrong\u003ETableflow\u003C/strong\u003E page by clicking on Tableflow on the left-hand side of the menu bar within your Confluent Environment.\u003C/li\u003E\u003Cli\u003EIn the center of the page, you&rsquo;ll see an option to configure a Storage Connection. Click on \u003Cstrong\u003EGo to Provider Integrations\u003C/strong\u003E in order to configure the connection to Amazon S3.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image60.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EFrom Provider Integrations, click on  \u003Cstrong\u003E+ Add Integration.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EYou can either create or use an existing role. For the sake of this example, we will create a \u003Cstrong\u003Enew role\u003C/strong\u003E. Click \u003Cstrong\u003EContinue.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EOn the \u003Cstrong\u003ECreate Permission Policy in AWS\u003C/strong\u003E page, select \u003Cstrong\u003ETableflow S3 Bucket\u003C/strong\u003E in the dropdown.\u003C/li\u003E\u003Cli\u003EYou will need to copy this permissions-policy.json for use in the next step\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate a new permissions policy on AWS\u003C/h3\u003E\n","\u003Cp\u003EWe need to create a permissions policy for Amazon S3 Access. In this section, we will create a permissions policy to be later used with an AWS Identity Access Management (IAM) Role.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn a new tab, open your Amazon Web Services (AWS) account and navigate to IAM Policies or \u003Ca href=\"https://us-east-1.console.aws.amazon.com/iam/home?region=us-east-1#/policies\"\u003Eclick this link\u003C/a\u003E.\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate Policy\u003C/strong\u003E\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image22.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003EFrom the Create Policy screen, \u003Cstrong\u003Eswitch to the JSON editor\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003ECopy the permissions-policy.json from the Confluent Provider Create Wizard into your policy editor on AWS. Ensure to replace the values for the Amazon S3 bucket we created above (\u003Cstrong\u003Etableflow-bucket-&lt;&lt;account-number&gt;&gt;)\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003E{\n    &quot;Version&quot;: &quot;2012-10-17&quot;,\n    &quot;Statement&quot;: [\n        {\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Action&quot;: [\n                &quot;s3:GetBucketLocation&quot;,\n                &quot;s3:ListBucketMultipartUploads&quot;,\n                &quot;s3:ListBucket&quot;\n            ],\n            &quot;Resource&quot;: [\n                &quot;arn:aws:s3:::tableflow-bucket-123456789101&quot;\n            ]\n        },\n        {\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Action&quot;: [\n                &quot;s3:PutObject&quot;,\n                &quot;s3:PutObjectTagging&quot;,\n                &quot;s3:GetObject&quot;,\n                &quot;s3:DeleteObject&quot;,\n                &quot;s3:AbortMultipartUpload&quot;,\n                &quot;s3:ListMultipartUploadParts&quot;\n            ],\n            &quot;Resource&quot;: [\n                &quot;arn:aws:s3:::tableflow-bucket-123456789101/*&quot;\n            ]\n        }\n    ]\n}\n\n\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image15.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ENext\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EGive the policy the name \u003Ccode\u003Etableflow-s3-access-policy\u003C/code\u003E and click \u003Cstrong\u003ECreate Policy\u003C/strong\u003E.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image14.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003EOnce the policy has been created, you can click \u003Cstrong\u003EContinue\u003C/strong\u003E on Confluent Cloud.\u003C/li\u003E\u003Cli\u003EThe next page, \u003Cstrong\u003ECreate role in AWS and map to Confluent\u003C/strong\u003E will present a \u003Cstrong\u003Etrust-policy.json\u003C/strong\u003E that we will leverage for the next section of these instructions. Copy this down for later use.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate role in AWS and map to Confluent\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003ENext, we are going to create a role in AWS that will leverage the policy we just created, plus a \u003Ccode\u003Etrust-policy.json\u003C/code\u003E to allow Confluent to assume this role.\u003C/li\u003E\u003Cli\u003EClick \u003Ca href=\"https://us-east-1.console.aws.amazon.com/iam/home#/roles\"\u003Ehere\u003C/a\u003E or navigate to the \u003Cstrong\u003ERoles\u003C/strong\u003E sub-menu under the IAM service on AWS\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image5.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\n","\u003Cp\u003EOnce on the Roles sub-menu, on the top right of the screen, click \u003Cstrong\u003ECreate role\u003C/strong\u003E in order to begin creating the role for Tableflow to assume.\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image30.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003ECustom Trust Policy\u003C/strong\u003E and paste in the \u003Cstrong\u003Etrust-policy.json\u003C/strong\u003E from Confluent.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image7.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003EScroll down and click \u003Cstrong\u003ENext\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EIn the next page, Add Permissions, search for the policy you created in the previous step, named \u003Ccode\u003Etableflow-s3-access-policy\u003C/code\u003E and attach it to the role. Click \u003Ccode\u003ENext\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image49.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"7\"\u003E\u003Cli\u003E\n","\u003Cp\u003EGive the role a name, \u003Ccode\u003Equickstart-tableflow-assume-role\u003C/code\u003E, scroll down and click \u003Cstrong\u003ECreate Role\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOnce the role is created,you should see a green banner at the top of the console stating that the role was created. Click \u003Cstrong\u003EView Role\u003C/strong\u003E to see the role details.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image10.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECopy the AWS ARN of the role and paste it in the Mapping component on the Provider Integration wizard on Confluent Cloud\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EGive the Provider integration the name s3-provider-integration and click \u003Cstrong\u003EContinue\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image57.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"11\"\u003E\u003Cli\u003EYou will now copy the updated Trust Policy from Confluent which contains the Confluent External ID and role. Copy the \u003Ccode\u003Etrust-policy.json\u003C/code\u003E from Confluent to your clipboard.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image20.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"12\"\u003E\u003Cli\u003ENavigate back to your Role on AWS and switch to the \u003Cstrong\u003ETrust Relationships\u003C/strong\u003E tab\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003EEdit Trust Policy\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image16.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Col start=\"14\"\u003E\u003Cli\u003EPaste in the updated Trust Policy from Confluent Cloud and \u003Cstrong\u003Eupdate policy\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ENavigate back to Confluent Cloud and click Continue on Confluent Cloud once the role trust policy has been updated. You have now successfully created a Provider Integration.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image33.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EEnable Tableflow on Users and Stock Trades Topics\u003C/h3\u003E\n","\u003Cp\u003EReturn to the Topics Confluent menu (Environments &gt; Your Environment &gt; Your Kafka Cluster &gt; Topics). We can now enable Tableflow from this menu.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EFind the \u003Ccode\u003Esample_data_stock_trades\u003C/code\u003E topic in the list of topics.\u003C/li\u003E\u003Cli\u003EOn the right-hand side of the topic table, you will see the option to \u003Cstrong\u003EEnable Tableflow\u003C/strong\u003E for the \u003Ccode\u003Esample_data_stock_trades\u003C/code\u003E topic. Select \u003Cstrong\u003EEnable Tableflow.\u003C/strong\u003E\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image51.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003EYou will be presented with two options: Configure Custom Storage or Use Confluent Storage. \u003Cstrong\u003EChoose Configure custom storage.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EIn the next menu, you will be able to choose the Provider Integration we created in the previous section. You can identify it by either the name of the provider integration or the IAM Role you created.\u003C/li\u003E\u003Cli\u003EProvide the AWS S3 bucket name (\u003Ccode\u003Etableflow-bucket-&lt;&lt;account-id&gt;&gt;\u003C/code\u003E)\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image47.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the next screen, review the details and then click \u003Cstrong\u003ELaunch.\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EYou will now see \u003Cem\u003ETableflow sync pending\u003C/em\u003E at the top of your topic information. This should transition to the \u003Cem\u003ESyncing\u003C/em\u003E status shortly.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ERepeat this process for the \u003Ccode\u003Esample_data_users\u003C/code\u003E topic, navigating back to the Topics menu, clicking on Enable Tableflow, and provide the same provider integration and Amazon S3 Bucket. Finally, click \u003Cstrong\u003ELaunch.\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOnce you have done this for both topics, your Topic list should look like this:\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image35.png\" alt=\"\"\u003E\u003C/p\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003ECreate an Open Catalog Account on Snowflake\u003C/h2\u003E\n","\u003Cp\u003EIf you do not already have Open Catalog Account set up on Snowflake, you can create one from the Snowflake homepage:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EOpen the Snowflake main screen by visiting \u003Ca href=\"https://app.snowflake.com/\"\u003Ehttps://app.snowflake.com/\u003C/a\u003E, which should redirect you to your organization&rsquo;s Snowflake account.\u003C/li\u003E\u003Cli\u003EIf you have the ORGADMIN permissions, you should see an option on the left-hand menu called \u003Ccode\u003EAdmin\u003C/code\u003E. Under the \u003Ccode\u003EAdmin\u003C/code\u003E menu, you should see an option for \u003Ccode\u003EAccounts\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EClick on \u003Ccode\u003EAccounts\u003C/code\u003E and look to the top-right side of the screen where you will see a blue Accounts action button. Select the arrow pointing down to expose the \u003Ccode\u003ECreate Snowflake Open Catalog Account\u003C/code\u003E option.\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image54.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003EGo through the create wizard to create the Open Catalog account, and log in.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ESet up Open Catalog Connection on Snowflake\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EWhen you first log in to the Snowflake Open Catalog account, you should see a screen that looks like this:\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image17.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFrom here, we will create a Connection:\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003EOn the left-hand menu, click on Connections &gt; + Connection (on top right side of screen).\n\u003Col\u003E\u003Cli\u003EName: \u003Ccode\u003Emy-service-connection\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EQuery Engine: &lt; leave blank&gt;\u003C/li\u003E\u003Cli\u003ECheck the option to \u003Ccode\u003ECreate new principal role\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EGive the principal role a name and click \u003Ccode\u003ECreate\u003C/code\u003E\u003C/li\u003E\u003C/ol\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image8.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EAfter clicking \u003Ccode\u003ECreate\u003C/code\u003E, you will see your \u003Ccode\u003EClient ID\u003C/code\u003E and \u003Ccode\u003EClient Secret\u003C/code\u003E presented on screen. Make sure to copy these down as they will be required later for setting up the External Catalog Integration on Confluent Cloud and Snowflake.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EOnce you created the connection and principal role, you are now ready to create your Open\u003Cbr\u003E\nData Catalog in Snowflake.\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003ENavigate to the Catalogs menu on the left hand side of the Snowflake Open Catalog menu and Click on the \u003Ccode\u003E+ Catalog\u003C/code\u003E wizard.\u003C/li\u003E\u003Cli\u003EYou will now enter the details of your new Open Data Catalog:\n\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003EName\u003C/strong\u003E: \u003Ccode\u003Emy-snowflake-catalog\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EIMPORTANT:\u003C/strong\u003E Check the box which says \u003Ccode\u003EExternal\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EStorage Provider\u003C/strong\u003E: S3\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EDefault Base Location:\u003C/strong\u003E \u003Ccode\u003Es3://tableflow-bucket-&lt;&lt;account-id&gt;&gt;\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAdditional Locations:\u003C/strong\u003E &lt; Leave Blank &gt;\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ES3 Role Arn\u003C/strong\u003E: The ARN of the S3 Role you created earlier (\u003Ccode\u003Earn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/quickstart-tableflow-assume-role\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EExternal ID: \u003Ccode\u003Esnowflake-external-id\u003C/code\u003E\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image39.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"6\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003ENote down the external ID assigned to the newly created catalog.\u003C/li\u003E\u003Cli\u003EIn the Catalog page, you&rsquo;ll see a tab called Roles. Create a Catalog role by clicking the button  \u003Cstrong\u003E+ Catalog Role\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image58.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"9\"\u003E\u003Cli\u003EGive the role a name (\u003Ccode\u003Emy_role\u003C/code\u003E) and Select \u003Cstrong\u003ECATALOG_MANAGE_CONTENT\u003C/strong\u003E under Privileges.\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image28.png\" alt=\"\"\u003E\u003C/li\u003E\u003Cli\u003EFrom here, we need to assign this role to a principal role. Click on the button \u003Cstrong\u003EGrant to Principal Role\u003C/strong\u003E at the top right and select the catalog role you just created under \u003Cstrong\u003ECatalog role to grant\u003C/strong\u003E and the principal role you created in the Connection Creation phase above for \u003Cstrong\u003EPrincipal role to receive grant.\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image61.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Col start=\"12\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EGrant.\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image44.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EModify Role and Trust Policy for Snowflake\u003C/h3\u003E\n","\u003Cp\u003ENow that we&rsquo;ve created the Open Data Catalog, we can allow Snowflake access to the storage provider (Amazon S3) through a trust policy.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EFind the role you provided in the previous section (\u003Cstrong\u003ES3 Role ARN)\u003C/strong\u003E in the AWS Management Console by searching for IAM in the top search bar.\u003C/li\u003E\u003Cli\u003EFrom the IAM Dashboard, you can click on the left hand side under Access Management &gt; Roles to open the Roles menu.\u003C/li\u003E\u003Cli\u003EFrom here, we can search for the role you previously created (\u003Ccode\u003Equickstart-tableflow-assume-role\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003EClick on the role name and find the tab in the middle of the page which reads \u003Cstrong\u003ETrust Relationships.\u003C/strong\u003E This is where you will add the trust policy for Snowflake.\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003EEdit trust policy\u003C/strong\u003E and add the following to your \u003Cstrong\u003EStatement\u003C/strong\u003E section within the brackets:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003E        ,{\n            &quot;Sid&quot;: &quot;&quot;,\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Principal&quot;: {\n                &quot;AWS&quot;: &quot;&lt;&lt; Get this value from your snowflake catalog under IAM user arn &gt;&gt;&quot;\n            },\n            &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n            &quot;Condition&quot;: {\n                &quot;StringEquals&quot;: {\n                    &quot;sts:ExternalId&quot;: &quot;&lt;&lt; external ID from snowflake catalog &gt;&gt;&quot;\n                }\n            }\n        }\n\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"6\"\u003E\u003Cli\u003EYou will need to replace the values for \u003Ccode\u003EAWS\u003C/code\u003E and \u003Ccode\u003Ests:ExternalId\u003C/code\u003E. These can be found in your snowflake Catalog Details section.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image18.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"7\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EUpdate Policy\u003C/strong\u003E to save it.\u003C/li\u003E\u003Cli\u003EYour updated AWS Role Trust Policy should look like this:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003E{\n  &quot;Version&quot;: &quot;2012-10-17&quot;,\n  &quot;Statement&quot;: [\n    {\n      &quot;Effect&quot;: &quot;Allow&quot;,\n      &quot;Principal&quot;: {\n        // from Confluent\n        &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n      },\n      &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n      &quot;Condition&quot;: {\n        &quot;StringEquals&quot;: {\n          // from Confluent\n          &quot;sts:ExternalId&quot;: &quot;&lt;&lt;external-id&gt;&gt;&quot;\n        }\n      }\n    },\n    {\n      &quot;Effect&quot;: &quot;Allow&quot;,\n      &quot;Principal&quot;: {\n        // from Confluent\n        &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n      },\n      &quot;Action&quot;: &quot;sts:TagSession&quot;\n    },\n    {\n            &quot;Sid&quot;: &quot;&quot;,\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Principal&quot;: {\n       // from Snowflake\n                &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n\n            },\n            &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n            &quot;Condition&quot;: {\n                &quot;StringEquals&quot;: {\n      // from Snowflake\n                    &quot;sts:ExternalId&quot;: &quot;snowflake-external-id&quot;\n                }\n            }\n        }\n  ]\n}\n\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou are now ready to add your External Provider to Tableflow.\u003C/p\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003EAdd Snowflake as External Provider to Tableflow\u003C/h2\u003E\n\u003Cul\u003E\u003Cli\u003ENavigate back to your Tableflow console on Confluent Cloud\u003C/li\u003E\u003Cli\u003EOn the bottom of the page, you will see the External Catalog Integration. Within this sub-menu, click \u003Cstrong\u003E+ Add Integration\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image11.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EOn the next page, select Snowflake Open Catalog as your integration type\u003C/li\u003E\u003Cli\u003EIn the name column, type \u003Ccode\u003Emy-polaris-catalog-integration\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image26.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EClick \u003Cstrong\u003EContinue.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003EContinue\u003C/strong\u003E again.\u003C/li\u003E\u003Cli\u003EOn the launch page, we will provide the following information:\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ESnowflake Open Catalog URL\u003C/strong\u003E: \u003Ccode\u003Ehttps://&lt;locatorID&gt;.&lt;region&gt;.snowflakecomputing.com\u003C/code\u003E\n\u003Cul\u003E\u003Cli\u003EYou can retrieve the locatorID from your open catalog URL bar. It will be the ID after the domain name/region like so:\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://app.snowflake.com/us-east-1/\"\u003Ehttps://app.snowflake.com/us-east-1/\u003C/a\u003E&lt;LOCATOR ID&gt;/#/\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EWarehouse name:\u003C/strong\u003E my-snowflake-catalog\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EClient ID:\u003C/strong\u003E Retrieve this from the Client Connection credentials you generated in step two of Set Up Open Catalog Connection on Snowflake\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EClient secret:\u003C/strong\u003E Retrieve this from the Client Connection credentials you generated in step two of Set Up Open Catalog Connection on Snowflake\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAllowed scope:\u003C/strong\u003E \u003Ccode\u003EPRINCIPAL_ROLE:my-snowflake-principal-role\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image43.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EClick continue\u003C/strong\u003E and then \u003Cstrong\u003Eclick launch.\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EAfter a few moments, you should see the External Catalog integration you have just set up transitioning from Pending to Connected.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image50.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ENavigate back to the Snowflake Open Data Catalog\u003C/li\u003E\u003Cli\u003EUnder the Catalogs sub-menu, click on your catalog name (\u003Ccode\u003Emy-snowflake-catalog\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003EYou should see the Kafka cluster ID appear here\u003C/li\u003E\u003Cli\u003EUnder the Kafka cluster ID, you will see the tables you enabled Tableflow on successfully materialized in Snowflake.\u003C/li\u003E\u003Cli\u003EYou should also see the topics materialized under your cluster ID\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image52.png\" alt=\"\"\u003E\u003C/h2\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003EQuery Iceberg Tables via Snowflake\u003C/h2\u003E\n","\u003Cp\u003ENow that we&rsquo;ve got our Snowflake Open Catalog set up receiving data from our Kafka topics, we can now see the full end-to-end integration by referencing our Snowflake Open Catalog within our Snowflake environment.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EStart by navigating back to your Snowflake environment. You can click \u003Ca href=\"https://app.snowflake.com/\"\u003Ethis link\u003C/a\u003E in order to open your Snowsight UI.\u003C/li\u003E\u003Cli\u003ECreate a new SQL Worksheet by clicking \u003Cstrong\u003E+ Create\u003C/strong\u003E at the top left hand corner, and select \u003Cstrong\u003ESQL Worksheet\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image31.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EThis will open up a new SQL Worksheet named the current date and time. Feel free to rename this as \u003Ccode\u003EOpen Data Catalog Setup\u003C/code\u003E by clicking the three dots ⠇to the right of the worksheet tab.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image46.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ECreate an External Volume\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EEnsure you have \u003Ccode\u003EAccountAdmin\u003C/code\u003E Privileges granted to your account in order to create an external volume\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image2.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EWe will now create an external volume referencing our Amazon S3 bucket. Enter the following SQL statement, replacing the Amazon S3 bucket with the one you created earlier (\u003Ccode\u003Es3://tableflow-bucket-&lt;&lt;account-id&gt;&gt;\u003C/code\u003E), the IAM role you created earlier (\u003Ccode\u003Earn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/quickstart-tableflow-assume-role\u003C/code\u003E), and leave the rest.\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE EXTERNAL VOLUME iceberg_external_volume\n   STORAGE_LOCATIONS =\n      (\n         (\n            NAME = 'my-iceberg-external-volume'\n            STORAGE_PROVIDER = 'S3'\n            STORAGE_BASE_URL = 's3://tableflow-bucket-&lt;&lt;account-id&gt;&gt;'\n            STORAGE_AWS_ROLE_ARN = 'arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/quickstart-tableflow-assume-role'\n            STORAGE_AWS_EXTERNAL_ID = 'snowflake-external-id'\n         )\n      );\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003EExecute this statement by highlighting the text and clicking the Play button  ▶️ to the top-right.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image36.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EYou will see the success message appear at the bottom of the page, showing that the external volume was successfully created.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EWe need to get the \u003Ccode\u003ESTORAGE_AWS_IAM_USER_ARN\u003C/code\u003E to provide to our IAM Role trust policy. We can do so by running a describe query on the external volume we just created.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003EDESC EXTERNAL VOLUME iceberg_external_volume;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003ERun this command like we did with the first command by highlighting the text and clicking on the Play button  ▶️to the top right.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image6.gif\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EThe output of this command will appear at the bottom of the page. Under the results for \u003Ccode\u003ESTORAGE_LOCATIONS\u003C/code\u003E there will be a \u003Ccode\u003Eproperty_value\u003C/code\u003E, click this value to see the results on the right hand side.\u003C/li\u003E\u003Cli\u003EFrom the value of the \u003Ccode\u003Eproperty_value\u003C/code\u003E column, copy the value of \u003Ccode\u003ESTORAGE_AWS_IAM_USER_ARN\u003C/code\u003E which should look like an IAM ARN\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image21.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EUpdate Trust Policy for Snowflake\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ELet&rsquo;s now navigate back to our AWS IAM Role that we created previously (\u003Cstrong\u003Equickstart-tableflow-assume-role\u003C/strong\u003E) and update the trust policy again:\n\u003Cul\u003E\u003Cli\u003ENavigate back to your Role on AWS and switch to the \u003Cstrong\u003ETrust Relationships\u003C/strong\u003E tab\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003EEdit Trust Policy\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image16.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EWe will again be adding another entry to our trust policy under the Statement block that will look like this:\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003E    {\n      &quot;Sid&quot;: &quot;&quot;,\n      &quot;Effect&quot;: &quot;Allow&quot;,\n      &quot;Principal&quot;: {\n        &quot;AWS&quot;: &quot;&lt;&lt;STORAGE_AWS_IAM_USER_ARN&gt;&gt;&quot;\n      },\n      &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n      &quot;Condition&quot;: {\n        &quot;StringEquals&quot;: {\n          &quot;sts:ExternalId&quot;: &quot;snowflake-external-id&quot;\n        }\n      }\n\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EUnder the AWS key, paste your \u003Ccode\u003ESTORAGE_AWS_IAM_USER_ARN\u003C/code\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EKeep the external ID as \u003Ccode\u003Esnowflake-external-id\u003C/code\u003E as that&rsquo;s the external ID we created in the external volume\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOnce you add the extra trust policy, your full trust policy should look like this:\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003E        \n{\n  &quot;Version&quot;: &quot;2012-10-17&quot;,\n  &quot;Statement&quot;: [\n    {\n      &quot;Effect&quot;: &quot;Allow&quot;,\n      &quot;Principal&quot;: {\n        // from Confluent\n        &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n      },\n      &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n      &quot;Condition&quot;: {\n        &quot;StringEquals&quot;: {\n          // from Confluent\n          &quot;sts:ExternalId&quot;: &quot;&lt;&lt;external-id&gt;&gt;&quot;\n        }\n      }\n    },\n    {\n      &quot;Effect&quot;: &quot;Allow&quot;,\n      &quot;Principal&quot;: {\n        // from Confluent\n        &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n      },\n      &quot;Action&quot;: &quot;sts:TagSession&quot;\n    },\n    {\n            &quot;Sid&quot;: &quot;&quot;,\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Principal&quot;: {\n       // from Snowflake Open Catalog\n                &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n\n            },\n            &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n            &quot;Condition&quot;: {\n                &quot;StringEquals&quot;: {\n       // from Snowflake Open Catalog\n                    &quot;sts:ExternalId&quot;: &quot;snowflake-external-id&quot;\n                }\n            }\n        },\n{\n            &quot;Sid&quot;: &quot;&quot;,\n            &quot;Effect&quot;: &quot;Allow&quot;,\n            &quot;Principal&quot;: {\n       // from Snowflake \n                &quot;AWS&quot;: &quot;arn:aws:iam::&lt;&lt;account-id&gt;&gt;:role/&lt;&lt;role-id&gt;&gt;&quot;\n            },\n            &quot;Action&quot;: &quot;sts:AssumeRole&quot;,\n            &quot;Condition&quot;: {\n                &quot;StringEquals&quot;: {\n       // from Snowflake\n                    &quot;sts:ExternalId&quot;: &quot;snowflake-external-id&quot;\n                }\n            }\n        }\n  ]\n}\n\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003EThe next step is verifying that we can actually access the external volume via Snowflake. Execute this command:\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT SYSTEM$VERIFY_EXTERNAL_VOLUME('iceberg_external_volume');\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003EWhen this runs, you should see the keywords &ldquo;success&rdquo;:&rdquo;true&rdquo; and &ldquo;PASSED&rdquo; in the results set. This means the trust policy update took effect.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ECreate Catalog Integration\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EWe can now create our catalog integration, to link Snowflake to our Snowflake Open Data Catalog. For this SQL statement you will need to retrieve some information in the placeholders. Start by pasting in this placeholder create statement into your SQL worksheet.\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE CATALOG INTEGRATION my_snowflake_open_catalog_int\n  CATALOG_SOURCE = POLARIS\n  TABLE_FORMAT = ICEBERG\n    CATALOG_NAMESPACE='&lt;&lt; KAFKA CLUSTER ID&gt;&gt;'\n  REST_CONFIG = (\n     CATALOG_URI ='https://&lt;&lt;organization-name&gt;&gt;-&lt;&lt;open-data-catalog-account-name&gt;&gt;.snowflakecomputing.com/polaris/api/catalog'\n     WAREHOUSE = 'my-snowflake-catalog'\n  )\n  REST_AUTHENTICATION = (\n     TYPE=OAUTH\n    OAUTH_CLIENT_ID='&lt;&lt;client-id&gt;&gt;'\n    OAUTH_CLIENT_SECRET='&lt;&lt;client-secret&gt;&gt;'\n     OAUTH_ALLOWED_SCOPES=('PRINCIPAL_ROLE:my-snowflake-principal-role')\n  )\n  REFRESH_INTERVAL_SECONDS = 60\n  ENABLED=true;\n\n\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cul\u003E\u003Cli\u003EThe first placeholder, \u003Ccode\u003ECATALOG_NAMESPACE\u003C/code\u003E should be your Kafka cluster ID. This can be found by navigating to your Confluent Cloud Kafka cluster and checking the cluster details on the right hand menu. \u003Cstrong\u003ECopy this value and paste it in the value for CATALOG_NAMESPACE.\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image4.png\" alt=\"\"\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EThe next placeholder, \u003Ccode\u003ECATALOG_URI\u003C/code\u003E will require your Snowflake Organization name and your open data catalog \u003Cstrong\u003Eaccount name\u003C/strong\u003E. The Snowflake Organization name can be found in your Snowflake homepage by clicking on your profile at the bottom left of the screen, hovering over your account and clicking on account details.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image41.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003ECopy the value of your \u003Cstrong\u003EOrganization Name\u003C/strong\u003E as the first part of your \u003Ccode\u003ECATALOG_URI\u003C/code\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EThe second part of your \u003Ccode\u003ECATALOG_URI\u003C/code\u003E is the \u003Cstrong\u003Eaccount name\u003C/strong\u003E for your open data catalog account. This can be found under the same profile menu when you switch accounts. Just copy the account name and put it into the second part of your catalog URI for the placeholders.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EThe final result should look like:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ccode\u003ECATALOG_URI=\u003C/code\u003E&rsquo;\u003Ccode\u003Ehttps://organizationname-opendatacatalogaccountname.snowflakecomputing.com/polaris/api/catalog&rsquo;\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFor the OATH client id and client secret, these were the values you copied down when creating your open data catalog connection. Copy and paste these values as appropriate.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EYou are now ready to create your catalog integration. Highlight the command and click the Play ▶️button just as before.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image12.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAfter running the command, you should see that the catalog integration was successfully created.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ECreating the Iceberg Table and Querying\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EOnce we have the catalog integration set up, you can now create an Iceberg table to query your snowflake open data catalog data.\u003C/li\u003E\u003Cli\u003EExecute the following command, ensuring that all variables match exactly. If you named your external volume, catalog or kafka topic something different, this query will not work:\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE ICEBERG TABLE snowflake_stock_trades\n    EXTERNAL_VOLUME = 'iceberg_external_volume'\n    CATALOG = 'my_snowflake_open_catalog_int'\n    CATALOG_TABLE_NAME = sample_data_stock_trades\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image13.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EFinally we are ready to query the table. Here are some queries you can try and evaluate the results.\u003C/li\u003E\u003C/ul\u003E\n\u003Cpre\u003E\u003Ccode\u003E-- count the number of records\nSELECT COUNT(*) from snowflake_stock_trades;\n\n-- see one record in the table\nselect * from snowflake_stock_trades limit 1;\n\n-- see all records in the table\nSELECT * FROM snowflake_stock_trades;\n\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThese query results should update periodically when run again, showcasing that we are continuously writing data to our Iceberg tables. You should expect to see updated results every 15 minutes or so depending on data volume and refresh frequency.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image56.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image48.png\" alt=\"\"\u003E\u003C/p\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003EOptional: Automatic Anomaly Detection with Apache Flink\u003C/h2\u003E\n","\u003Cp\u003EWhile your data is flowing from Kafka to Snowflake via Tableflow, you may want to enrich or flag certain records \u003Cem\u003Ebefore\u003C/em\u003E they land in the data lake. This is where \u003Cstrong\u003EApache Flink\u003C/strong\u003E comes in.\u003C/p\u003E\n","\u003Cp\u003EIn this optional step, you'll use Flink SQL in Confluent Cloud to detect basic anomalies in the stock trading stream. This can be useful for spotting potential fraud, pricing glitches, or unusually large trades as they happen.\u003C/p\u003E\n","\u003Cp\u003EWe'll create a lightweight streaming job using Flink SQL that watches for simple anomalies based on rules:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ETrades with \u003Cstrong\u003Eunusually large quantities\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003ETrades with a \u003Cstrong\u003Enegative price\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003ETrades that exceed a configurable threshold\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThese flagged records will be tagged with an \u003Ccode\u003Eanomaly_flag\u003C/code\u003E field and written to a new Kafka topic called \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E. You could later route this to a separate Iceberg table, alerting system, or ML pipeline.\u003C/p\u003E\n","\u003Ch3\u003ECreate the Anomaly Detection Flink Job\u003C/h3\u003E\n","\u003Ch4\u003E1. Open Flink SQL in Confluent Cloud\u003C/h4\u003E\n\u003Cul\u003E\u003Cli\u003EIn your Confluent Cloud console, navigate to your cloud environment.\u003C/li\u003E\u003Cli\u003EIn the left-hand menu, click \u003Cstrong\u003EFlink\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image40.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EClick \u003Cstrong\u003E+ Add compute pool\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EOn the next screen, choose \u003Cstrong\u003EAWS\u003C/strong\u003E as the cloud provider, and choose \u003Ccode\u003Eus-east-1\u003C/code\u003E as the region. Then click \u003Cstrong\u003EContinue.\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EFinally, click \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EOnce the compute pool is created, click \u003Cstrong\u003EOpen SQL workspace\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003EDefine a Cleaned and Flagged Version of \u003Ccode\u003Estock_trades\u003C/code\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EPaste the following SQL into the editor. This will read from the \u003Ccode\u003Esample_data_stock_trades\u003C/code\u003E topic, apply simple anomaly rules, and write the results to a new topic.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE TABLE flagged_stock_trades\nAS SELECT\n  side,\n  quantity,\n  symbol,\n  price,\n  account,\n  userid,\n  CASE\n    WHEN price &lt; 0 THEN 'NEGATIVE_PRICE'\n    WHEN quantity &gt; 4000 THEN 'LARGE_TRADE'\n    WHEN price &gt; 900 THEN 'UNUSUAL_PRICE'\n    ELSE 'NORMAL'\n  END AS anomaly_flag\nFROM sample_data_stock_trades;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image45.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003ELaunch the Flink Job\u003C/li\u003E\u003C/ol\u003E\n\u003Cul\u003E\u003Cli\u003EClick \u003Cstrong\u003ERun\u003C/strong\u003E to execute the job.\u003C/li\u003E\u003Cli\u003EOnce deployed, it will continuously process new \u003Ccode\u003Estock_trades\u003C/code\u003E events and write flagged records to \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch4\u003E4. Inspect the Flagged Trade Messages\u003C/h4\u003E\n","\u003Cp\u003EOnce your Flink job is running, you can verify that it&rsquo;s working by looking at the \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E topic and checking for the \u003Ccode\u003Eanomaly_flag\u003C/code\u003E field in the messages or by creating and running another Flink job with the SQL below.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT * FROM flagged_stock_trades;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou should see live messages coming through that look something like this:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image32.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETip: Filter by Anomaly\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ETo narrow in on only anomalous records, you can modify the Flink SQL to exclude \u003Ccode\u003E&quot;NORMAL&quot;\u003C/code\u003E entries, or filter them later downstream when querying from Iceberg or Snowflake.\u003C/p\u003E\n","\u003Ch4\u003E5. (Optional) Enable Tableflow on \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E\u003C/h4\u003E\n","\u003Cp\u003EYou can repeat the same Tableflow steps you followed earlier to sync \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E into your Iceberg tables and expose it to Snowflake.\u003C/p\u003E\n","\u003Ch3\u003EWhy This Matters\u003C/h3\u003E\n","\u003Cp\u003EBy adding a lightweight Flink layer, you can inspect, clean, or augment your data \u003Cem\u003Ein motion\u003C/em\u003E, before it ever hits storage or analytics layers. This pattern is useful for:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EPre-processing for machine learning\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EReal-time monitoring and alerting\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EReducing noise or garbage in your data lake\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EWhile this was a simple rule-based example, Flink also supports more sophisticated anomaly detection techniques such as applying ML models or calculating dynamic thresholds using moving averages over time windows. All of this can be expressed declaratively in Flink SQL.\u003C/p\u003E\n","\u003Cp\u003EThis optional step shows how real-time intelligence fits naturally into a streaming lakehouse architecture with no batch jobs, no glue code, and no waiting.\u003C/p\u003E\n&lt;!-- ------------------------ --&gt;\n","\u003Ch2\u003EConclusion and Resources\u003C/h2\u003E\n","\u003Cp\u003EYou&rsquo;ve now built a complete real-time data pipeline, from ingestion to insight, using Confluent Cloud, Tableflow, Apache Flink, and Snowflake.\u003C/p\u003E\n","\u003Cp\u003EAlong the way, you:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ESet up a Kafka-based streaming architecture with simulated user and stock trade data.\u003C/li\u003E\u003Cli\u003EMaterialized Kafka topics directly into Iceberg tables using Tableflow.\u003C/li\u003E\u003Cli\u003EQueried fresh, continuously updated data from Snowflake&rsquo;s Open Data Catalog.\u003C/li\u003E\u003Cli\u003E(Optionally) Enriched and flagged anomalies in-flight using Flink SQL.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThis architecture is modular, cloud-native, and scalable giving you a flexible foundation for powering analytics, AI, and operational decision-making in real time.\u003C/p\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://docs.confluent.io/cloud/current/topics/tableflow/overview.html\"\u003ETableflow in Confluent Cloud\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.confluent.io/cloud/current/flink/overview.html\"\u003EStream Processing with Confluent Cloud for Apache Flink\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.confluent.io/cloud/current/ai/overview.html\"\u003EBuild AI with Flink SQL and Confluent Cloud for Apache Flink\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/tables-iceberg\"\u003EApache Iceberg tables\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003ECleanup\u003C/h2\u003E\n","\u003Cp\u003EOnce you&rsquo;ve completed the lab (or if you&rsquo;re done experimenting), it&rsquo;s a good idea to clean up the cloud resources to avoid incurring unnecessary costs and to keep your environment tidy.\u003C/p\u003E\n","\u003Ch3\u003ESnowflake Cleanup\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003ERemove the Iceberg Table(s)\u003C/strong\u003E\u003Cbr\u003E\nIn your Snowflake SQL Worksheet, drop any Iceberg tables you created:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003EDROP TABLE IF EXISTS snowflake_stock_trades;\nDROP TABLE IF EXISTS flagged_stock_trades;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003ERemove the Catalog Integration\u003C/strong\u003E\u003Cbr\u003E\nRemove the integration between Snowflake and the Open Data Catalog:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003EDROP CATALOG INTEGRATION IF EXISTS my_snowflake_open_catalog_int;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003E\u003Cstrong\u003ERemove External Volume\u003C/strong\u003E\u003Cbr\u003E\nDelete the external volume referencing your S3 bucket:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003EDROP EXTERNAL VOLUME IF EXISTS iceberg_external_volume;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\u003Cstrong\u003EDelete Catalog Roles and Catalog\u003C/strong\u003E\u003Cbr\u003E\nIn the Snowflake Open Data Catalog interface:\n\u003Cul\u003E\u003Cli\u003EGo to \u003Cstrong\u003ECatalogs &gt; your catalog &gt; Roles\u003C/strong\u003E and delete any catalog roles you created.\u003C/li\u003E\u003Cli\u003EReturn to the \u003Cstrong\u003ECatalogs\u003C/strong\u003E tab and delete the entire catalog (e.g., \u003Ccode\u003Emy-snowflake-catalog\u003C/code\u003E).\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EDelete Connection and Principal Role\u003C/strong\u003E\u003Cbr\u003E\nIn the \u003Cstrong\u003EConnections\u003C/strong\u003E tab:\n\u003Cul\u003E\u003Cli\u003EDelete the connection (\u003Ccode\u003Emy-service-connection\u003C/code\u003E).\u003C/li\u003E\u003Cli\u003EDelete the associated principal role.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EConfluent Cloud Cleanup\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete Tableflow Syncs\u003C/strong\u003E\u003Cbr\u003E\nGo to the \u003Cstrong\u003ETopics\u003C/strong\u003E section, select each topic with Tableflow enabled, and disable or delete the Tableflow sync.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete Kafka Topics\u003C/strong\u003E\u003Cbr\u003E\nDelete the \u003Ccode\u003Esample_data_users\u003C/code\u003E, \u003Ccode\u003Esample_data_stock_trades\u003C/code\u003E, and \u003Ccode\u003Eflagged_stock_trades\u003C/code\u003E topics.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete Connectors\u003C/strong\u003E\u003Cbr\u003E\nGo to the \u003Cstrong\u003EConnectors\u003C/strong\u003E tab and delete both Datagen connectors you created.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete Flink SQL Statements\u003C/strong\u003E\u003Cbr\u003E\nNavigate to the \u003Cstrong\u003EFlink SQL\u003C/strong\u003E section and delete the statement that was used for anomaly detection.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete the Kafka Cluster and Environment\u003C/strong\u003E (optional)\u003Cbr\u003E\nIf you don&rsquo;t plan to reuse the cluster or environment:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EGo to the \u003Cstrong\u003ECluster Settings\u003C/strong\u003E and delete your Kafka cluster.\u003C/li\u003E\u003Cli\u003ENavigate back to \u003Cstrong\u003EEnvironments\u003C/strong\u003E and delete the environment you created.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EAWS Cleanup\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDelete the S3 Bucket\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EGo to the \u003Cstrong\u003EAmazon S3 Console\u003C/strong\u003E, find the bucket you created (\u003Ccode\u003Etableflow-bucket-&lt;&lt;account-id&gt;&gt;\u003C/code\u003E), and delete it. Be sure to empty the bucket first if required.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERemove IAM Role and Policy\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ENavigate to the \u003Cstrong\u003EIAM Console\u003C/strong\u003E, locate the \u003Ccode\u003Equickstart-tableflow-assume-role\u003C/code\u003E, and delete it.\u003C/li\u003E\u003Cli\u003EAlso delete the custom IAM policy (\u003Ccode\u003Etableflow-s3-access-policy\u003C/code\u003E) if it was created for this demo.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E"],"description":"","title":"Stream Kafka Data to Snowflake via Confluent Tableflow and Iceberg",":type":"snowflake-site/components/contentfragment","isDeveloperGuidesPage":false,":items":{},":itemsOrder":[],"elements":{"quickstartArticleBody":{"dataType":"string","value":"## Overview\r\n\r\n\r\nIn this quickstart, you’ll build a real-time data pipeline that connects Apache Kafka with Snowflake, without writing a single custom connector or ETL job. Using Confluent Cloud, Kafka, and Tableflow, you’ll stream simulated data into Kafka topics, automatically materialize that data into Apache Iceberg tables on Amazon S3, and expose those tables directly to Snowflake’s Open Data Catalog.\r\n\r\nImagine you're building a modern trading platform or a customer-facing analytics dashboard. You're capturing user activity and stock trades as they happen, and you want your data teams and downstream systems to react in near real-time, whether it's for fraud detection, personalized recommendations, or operational intelligence.\r\n\r\nTraditionally, this would require stitching together multiple systems: Kafka for ingestion, Spark or Flink for transformation, cloud storage for persistence, and finally Snowflake for analytics, plus a ton of glue code and scheduling overhead.\r\n\r\nThis quickstart shows how to streamline that entire process:\r\n\r\n* **Kafka** ingests and transports the data in real time.  \r\n* **Tableflow** continuously materializes that data into Iceberg tables on **Amazon S3**.  \r\n* **Snowflake Open Catalog** connects directly to those tables, giving analysts and apps live access to fresh data using simple SQL.\r\n\r\nThis architecture supports use cases like:\r\n\r\n* **Real-time dashboards** for trading activity or user behavior  \r\n* **Feeding machine learning pipelines** with live, structured data  \r\n* **Streaming feature stores** for AI/ML applications\r\n\r\n### Technologies at a Glance\r\n\r\n#### Apache Kafka \r\n\r\nKafka is a distributed event streaming platform used to capture and route real-time data. In this lab, Kafka will act as the backbone for ingesting live event streams like user registrations and stock trades.\r\n\r\n#### Confluent Cloud\r\n\r\nConfluent is a fully managed data streaming platform built on Apache Kafka. It handles the heavy lifting of provisioning, scaling, and securing Kafka in the cloud so you can focus on your data flow, not the infrastructure.\r\n\r\n#### Tableflow\r\n\r\nTableflow is a new Confluent-native service that simplifies getting data out of Kafka and into data lake and warehouse formats. It automatically handles schema evolution, file compaction, and catalog registration bridging the world of real-time streaming and batch analytics. Think of it as the glue between Kafka and your Iceberg or Delta Lake tables.\r\n\r\n#### Apache Iceberg\r\n\r\nIceberg is an open table format designed for large-scale analytic datasets. It brings reliability and performance to data lakes with features like ACID transactions, schema evolution, and partitioning, making it easy to work with both streaming and batch data as if it were a traditional database table.\r\n\r\n### Assumptions and Prerequisites\r\n\r\nBefore you begin, make sure you have the following:\r\n\r\n- [**Confluent Cloud Account**](https://www.confluent.io/get-started): You’ve created (or have access to) a Confluent Cloud account where you can provision Kafka clusters and use Tableflow.  \r\n- [**AWS Account with S3 Access**](https://docs.aws.amazon.com/AmazonS3/latest/userguide/create-bucket-overview.html): You can create or access an Amazon S3 bucket and configure IAM roles and policies.  \r\n- [**Snowflake Account with OrgAdmin Permissions**](https://app.snowflake.com/): You have a Snowflake account with **Organization Administrator** privileges, required to create an Open Data Catalog and configure external integrations.\r\n\r\n### What You’ll Learn in the Lab\r\n\r\n* How to set up Apache Kafka and streaming data pipelines in Confluent Cloud.  \r\n* How to generate synthetic data using Datagen connectors.  \r\n* How to use Tableflow to write Kafka topics to Apache Iceberg tables stored in Amazon S3.  \r\n* How to configure secure access between AWS, Confluent, and Snowflake using IAM roles and trust policies.  \r\n* How to expose Iceberg tables in Snowflake’s Open Data Catalog and run live queries on continuously updated data.\r\n\r\n### What You'll Build\r\n\r\nBy the end of this quickstart, you’ll have:\r\n\r\n* A fully functional **Confluent Cloud** environment with Kafka topics for user and stock trading events.  \r\n* Real-time **Datagen** connectors simulating events into Kafka.  \r\n* A **Tableflow pipeline** writing those topics as Iceberg tables into S3.  \r\n* A **Snowflake Open Catalog** integration that makes those Iceberg tables queryable with standard SQL.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Create an environment and Kafka cluster within your Confluent Cloud Account\r\n\r\nIn Confluent Cloud, we need to create a Kafka cluster to run our Tableflow examples. This Kakfa cluster will be automatically sized and provisioned with a few clicks. This will allow us to stream our datasets for further work with Tableflow. \r\n\r\nIn order to create a Kafka cluster, we need to first create an environment which will house all of the cloud resources we will create in this quickstart guide.\r\n\r\n* Access the Environments console by clicking **Environments** left-hand side of the Confluent Cloud menu or by clicking **Environments** under **Your resource overview.**  \r\n  ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image25.png)\r\n\r\n*If you already have an environment created, feel free to skip this section and use your existing environment for the remainder of the quickstart.*\r\n\r\n* From the Environments console, you will see an option to **+ Add cloud environment**. Click this to begin creating a new environment.  \r\n    \r\n  ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image34.png)\r\n    \r\n* Let’s give our environment a name, **SnowflakeTableflowDemo**  \r\n* Leave the default “Essentials” governance package selected and click **Create**. \r\n\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image55.png)\r\n\r\n* You now have a Confluent environment and we can proceed to create our Kafka cluster within the environment.  \r\n* On the next screen, you will be presented with options on which Kakfa cluster to create. Select the Basic option, and click **Begin Configuration**\r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image42.png)**\r\n\r\n* On the next screen, choose **AWS** as the cloud provider, and choose `us-east-1` as the region. Then click **Continue.**\r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image24.png)**\r\n\r\n* Give your cluster a name, **my-kafka-cluster**, leave the configurations as default and **Launch cluster.**\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image53.png)\r\n\r\n* You will then see a success banner “Cluster created”, and be taken to the Cluster Overview page. We are now ready to get started with Tableflow.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Getting Started with Tableflow\r\n\r\n\r\nTableflow simplifies the traditionally complex process of moving data from Kafka topics to data lakes or warehouses. It allows users to materialize Kafka topics and schemas into Apache Iceberg or Delta Lake tables within a few clicks, leveraging Confluent’s Schema Registry for schema management and evolution. This eliminates manual data mappings and streamlines the data ingestion pipeline. Tableflow also continuously compacts Parquet files for improved read performance and offers integrations with popular catalog services. By unifying streaming and batch processing, Tableflow enables real-time data availability in the data lakehouse and simplifies stream processing jobs.\r\n\r\n### Create Datagen Connectors for Users and Stock_Trades\r\n\r\nTo demonstrate how Tableflow moves data from Kafka into Apache Iceberg tables, we’ll start by generating sample data into our Kafka topics. These data generators simulate user activity and stock trading data, generating example events that Tableflow will use to hydrate the data lake.\r\n\r\nHere is a sample of the user data topic:\r\n\r\n```\r\n{\r\n  \"registertime\": 1491981791331,\r\n  \"userid\": \"User_2\",\r\n  \"regionid\": \"Region_8\",\r\n  \"gender\": \"MALE\"\r\n}\r\n\r\n```\r\n\r\nThe stock_trades topic will look like this:\r\n\r\n```\r\n{\r\n  \"side\": \"BUY\",\r\n  \"quantity\": 1934,\r\n  \"symbol\": \"ZBZX\",\r\n  \"price\": 974,\r\n  \"account\": \"XYZ789\",\r\n  \"userid\": \"User_9\"\r\n}\r\n```\r\n\r\nIn this quickstart, we will write the sample data to both the users and stock_trade topic in order to demonstrate how Tableflow works, write to Amazon S3 and reference these tables in Snowflake’s Open Data Catalog. \r\n\r\nLet’s get started.\r\n\r\n---\r\n\r\n- From the Confluent Cloud console, navigate to your environment either via the left-hand side portal or in the middle of the page under **Your resource overview.**  \r\n- Find the environment you created and select it from the list of Environments  \r\n    \r\n- You should now see your **Environment Overview** screen that shows your Kafka Cluster. **Click into your Kafka cluster.**\r\n\r\n- On the Cluster Overview screen, you will see Connectors on the left hand screen. Click on Connectors and then search for **Datagen Source** or click the datagen source, it is usually one of the first connectors on the page.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image29.png)\r\n\r\n- Choose the `Users` Sample Data.   \r\n- Click **Launch**  \r\n- This will start a **Datagen Source** Kafka connector that writes User data to a Kafka topic called `sample_data_users`. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image27.png)\r\n\r\n- You will then see the connector you created from the Connector Screen, transitioning from Provisioning state to Running. \r\n\r\n- Repeat this process to create another Datagen Source using the **Stock Trades** sample dataset. Once you have a connector, you should see the option to + **Add Connector** at the top right. Use this button to create a new datagen connector. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image19.png)\r\n\r\n- Use the **Stock trades** dataset this time. Click **Launch.**\r\n\r\n  **![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image38.png)**\r\n\r\n- Once finished, you should have two Datagen sources, **sample_data** and **sample_data_1** in running state on the Connectors screen.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image23.png)\r\n\r\n- Verify that the subsequent Kafka topics have been created by navigating to the **Topics** menu on the left-hand navigation bar. You should see one topic called `sample_data_users`, and another called `sample_data_stock_trades`, each with 6 partitions.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image37.png)\r\n\r\n- We are now in position to start configuring our Tableflow sync process into our Data Lake. \r\n\r\n### Configure your Amazon S3 Bucket and Provider Integration\r\n\r\nOnce you have your Kafka topics created, you can now get started with Tableflow to sync your data from your Kafka topics into Snowflake Data Cloud.\r\n\r\nBut first, we need an Amazon S3 Bucket to write our Apache Iceberg data to. \r\n\r\n1. If you already have an Amazon S3 bucket, feel free to skip to the next section  \r\n2. In a new tab, navigate to the Amazon S3 console or click [here](https://us-east-1.console.aws.amazon.com/s3/home?region=us-east-1#)  \r\n3. Click on **Create Bucket** on the top right.  \r\n   ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image9.png)\r\n4. Leave everything default and give your bucket a name. The name of the bucket must be unique so let’s name it **`tableflow-bucket-\u003C\u003CAccount-ID\u003E\u003E`**, using your account ID which can be retrieved from the dropdown at the top right of the screen.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image59.png)\r\n\r\n- Leave the rest of the options as default, scroll down and click **Create Bucket**. \r\n\r\n### Configure Storage Provider\r\n\r\n1. Back on Confluent Cloud, navigate to the **Tableflow** page by clicking on Tableflow on the left-hand side of the menu bar within your Confluent Environment.  \r\n2. In the center of the page, you’ll see an option to configure a Storage Connection. Click on **Go to Provider Integrations** in order to configure the connection to Amazon S3.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image60.png)\r\n\r\n3. From Provider Integrations, click on  **+ Add Integration.**   \r\n4. You can either create or use an existing role. For the sake of this example, we will create a **new role**. Click **Continue.**  \r\n5. On the **Create Permission Policy in AWS** page, select **Tableflow S3 Bucket** in the dropdown.  \r\n6. You will need to copy this permissions-policy.json for use in the next step\r\n\r\n### Create a new permissions policy on AWS\r\n\r\nWe need to create a permissions policy for Amazon S3 Access. In this section, we will create a permissions policy to be later used with an AWS Identity Access Management (IAM) Role.\r\n\r\n1. In a new tab, open your Amazon Web Services (AWS) account and navigate to IAM Policies or [click this link](https://us-east-1.console.aws.amazon.com/iam/home?region=us-east-1#/policies).  \r\n2. Click **Create Policy**  \r\n   ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image22.png)\r\n3. From the Create Policy screen, **switch to the JSON editor**  \r\n4. Copy the permissions-policy.json from the Confluent Provider Create Wizard into your policy editor on AWS. Ensure to replace the values for the Amazon S3 bucket we created above (**tableflow-bucket-\u003C\u003Caccount-number\u003E\u003E)**.\r\n\r\nExample: \r\n\r\n```\r\n{\r\n    \"Version\": \"2012-10-17\",\r\n    \"Statement\": [\r\n        {\r\n            \"Effect\": \"Allow\",\r\n            \"Action\": [\r\n                \"s3:GetBucketLocation\",\r\n                \"s3:ListBucketMultipartUploads\",\r\n                \"s3:ListBucket\"\r\n            ],\r\n            \"Resource\": [\r\n                \"arn:aws:s3:::tableflow-bucket-123456789101\"\r\n            ]\r\n        },\r\n        {\r\n            \"Effect\": \"Allow\",\r\n            \"Action\": [\r\n                \"s3:PutObject\",\r\n                \"s3:PutObjectTagging\",\r\n                \"s3:GetObject\",\r\n                \"s3:DeleteObject\",\r\n                \"s3:AbortMultipartUpload\",\r\n                \"s3:ListMultipartUploadParts\"\r\n            ],\r\n            \"Resource\": [\r\n                \"arn:aws:s3:::tableflow-bucket-123456789101/*\"\r\n            ]\r\n        }\r\n    ]\r\n}\r\n\r\n\r\n```\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image15.png)\r\n\r\n5. Click **Next**  \r\n6. Give the policy the name `tableflow-s3-access-policy` and click **Create Policy**.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image14.png)\r\n7. Once the policy has been created, you can click **Continue** on Confluent Cloud.  \r\n8. The next page, **Create role in AWS and map to Confluent** will present a **trust-policy.json** that we will leverage for the next section of these instructions. Copy this down for later use.\r\n\r\n### Create role in AWS and map to Confluent\r\n\r\n1. Next, we are going to create a role in AWS that will leverage the policy we just created, plus a `trust-policy.json` to allow Confluent to assume this role.   \r\n2. Click [here](https://us-east-1.console.aws.amazon.com/iam/home#/roles) or navigate to the **Roles** sub-menu under the IAM service on AWS\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image5.png)\r\n\r\n3. Once on the Roles sub-menu, on the top right of the screen, click **Create role** in order to begin creating the role for Tableflow to assume.  \r\n   ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image30.png)\r\n     \r\n4. Select **Custom Trust Policy** and paste in the **trust-policy.json** from Confluent. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image7.png)\r\n\r\n5. Scroll down and click **Next**  \r\n6. In the next page, Add Permissions, search for the policy you created in the previous step, named `tableflow-s3-access-policy` and attach it to the role. Click `Next`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image49.png)\r\n\r\n7. Give the role a name, `quickstart-tableflow-assume-role`, scroll down and click **Create Role**  \r\n8. Once the role is created,you should see a green banner at the top of the console stating that the role was created. Click **View Role** to see the role details.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image10.png)\r\n\r\n9. Copy the AWS ARN of the role and paste it in the Mapping component on the Provider Integration wizard on Confluent Cloud  \r\n10. Give the Provider integration the name s3-provider-integration and click **Continue**.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image57.png)\r\n\r\n11. You will now copy the updated Trust Policy from Confluent which contains the Confluent External ID and role. Copy the `trust-policy.json` from Confluent to your clipboard.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image20.png)\r\n\r\n12. Navigate back to your Role on AWS and switch to the **Trust Relationships** tab  \r\n13. Click **Edit Trust Policy** \r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image16.png)**\r\n\r\n14. Paste in the updated Trust Policy from Confluent Cloud and **update policy**.  \r\n15. Navigate back to Confluent Cloud and click Continue on Confluent Cloud once the role trust policy has been updated. You have now successfully created a Provider Integration.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image33.png)\r\n\r\n\r\n### Enable Tableflow on Users and Stock Trades Topics\r\n\r\nReturn to the Topics Confluent menu (Environments \u003E Your Environment \u003E Your Kafka Cluster \u003E Topics). We can now enable Tableflow from this menu.\r\n\r\n- Find the `sample_data_stock_trades` topic in the list of topics.  \r\n- On the right-hand side of the topic table, you will see the option to **Enable Tableflow** for the `sample_data_stock_trades` topic. Select **Enable Tableflow.**  \r\n  ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image51.png)\r\n- You will be presented with two options: Configure Custom Storage or Use Confluent Storage. **Choose Configure custom storage.**  \r\n- In the next menu, you will be able to choose the Provider Integration we created in the previous section. You can identify it by either the name of the provider integration or the IAM Role you created.  \r\n- Provide the AWS S3 bucket name (`tableflow-bucket-\u003C\u003Caccount-id\u003E\u003E`)\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image47.png)\r\n\r\n- In the next screen, review the details and then click **Launch.**  \r\n- You will now see *Tableflow sync pending* at the top of your topic information. This should transition to the *Syncing* status shortly.\r\n\r\n- Repeat this process for the `sample_data_users` topic, navigating back to the Topics menu, clicking on Enable Tableflow, and provide the same provider integration and Amazon S3 Bucket. Finally, click **Launch.**\r\n\r\n- Once you have done this for both topics, your Topic list should look like this:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image35.png)\r\n    \r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Create an Open Catalog Account on Snowflake\r\n\r\nIf you do not already have Open Catalog Account set up on Snowflake, you can create one from the Snowflake homepage:\r\n\r\n1. Open the Snowflake main screen by visiting [https://app.snowflake.com/](https://app.snowflake.com/), which should redirect you to your organization’s Snowflake account.  \r\n2. If you have the ORGADMIN permissions, you should see an option on the left-hand menu called `Admin`. Under the `Admin` menu, you should see an option for `Accounts`.   \r\n3. Click on `Accounts` and look to the top-right side of the screen where you will see a blue Accounts action button. Select the arrow pointing down to expose the `Create Snowflake Open Catalog Account` option.  \r\n   ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image54.png)\r\n4. Go through the create wizard to create the Open Catalog account, and log in.\r\n\r\n### Set up Open Catalog Connection on Snowflake\r\n\r\n1. When you first log in to the Snowflake Open Catalog account, you should see a screen that looks like this:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image17.png)\r\n\r\nFrom here, we will create a Connection:\r\n\r\n2. On the left-hand menu, click on Connections \u003E + Connection (on top right side of screen).  \r\n   1. Name: `my-service-connection`  \r\n   2. Query Engine: \u003C leave blank\u003E  \r\n   3. Check the option to `Create new principal role`  \r\n   4. Give the principal role a name and click `Create`\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image8.png)\r\n  \r\n\r\n3. After clicking `Create`, you will see your `Client ID` and `Client Secret` presented on screen. Make sure to copy these down as they will be required later for setting up the External Catalog Integration on Confluent Cloud and Snowflake.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image1.png)\r\n\r\nOnce you created the connection and principal role, you are now ready to create your Open   \r\nData Catalog in Snowflake. \r\n\r\n4. Navigate to the Catalogs menu on the left hand side of the Snowflake Open Catalog menu and Click on the `+ Catalog` wizard.   \r\n5. You will now enter the details of your new Open Data Catalog:  \r\n   1. **Name**: `my-snowflake-catalog`  \r\n   2. **IMPORTANT:** Check the box which says `External`  \r\n   3. **Storage Provider**: S3  \r\n   4. **Default Base Location:** `s3://tableflow-bucket-\u003C\u003Caccount-id\u003E\u003E`  \r\n   5. **Additional Locations:** \u003C Leave Blank \u003E  \r\n   6. **S3 Role Arn**: The ARN of the S3 Role you created earlier (`arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/quickstart-tableflow-assume-role`)  \r\n   7. **External ID: `snowflake-external-id`**\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image39.png)\r\n\r\n6. Click **Create**  \r\n7. Note down the external ID assigned to the newly created catalog.  \r\n8. In the Catalog page, you’ll see a tab called Roles. Create a Catalog role by clicking the button  **+ Catalog Role**. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image58.png)\r\n\r\n9. Give the role a name (`my_role`) and Select **CATALOG_MANAGE_CONTENT** under Privileges.  \r\n10. Click **Create**.  \r\n    ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image28.png)\r\n11. From here, we need to assign this role to a principal role. Click on the button **Grant to Principal Role** at the top right and select the catalog role you just created under **Catalog role to grant** and the principal role you created in the Connection Creation phase above for **Principal role to receive grant.** \r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image61.png)**\r\n\r\n12. Click **Grant.** \r\n\r\n ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image44.png)\r\n\r\n### Modify Role and Trust Policy for Snowflake\r\n\r\nNow that we’ve created the Open Data Catalog, we can allow Snowflake access to the storage provider (Amazon S3) through a trust policy.\r\n\r\n1. Find the role you provided in the previous section (**S3 Role ARN)** in the AWS Management Console by searching for IAM in the top search bar.  \r\n2. From the IAM Dashboard, you can click on the left hand side under Access Management \u003E Roles to open the Roles menu.  \r\n3. From here, we can search for the role you previously created (`quickstart-tableflow-assume-role`)  \r\n4. Click on the role name and find the tab in the middle of the page which reads **Trust Relationships.** This is where you will add the trust policy for Snowflake.  \r\n5. Click **Edit trust policy** and add the following to your **Statement** section within the brackets:\r\n\r\n```\r\n        ,{\r\n            \"Sid\": \"\",\r\n            \"Effect\": \"Allow\",\r\n            \"Principal\": {\r\n                \"AWS\": \"\u003C\u003C Get this value from your snowflake catalog under IAM user arn \u003E\u003E\"\r\n            },\r\n            \"Action\": \"sts:AssumeRole\",\r\n            \"Condition\": {\r\n                \"StringEquals\": {\r\n                    \"sts:ExternalId\": \"\u003C\u003C external ID from snowflake catalog \u003E\u003E\"\r\n                }\r\n            }\r\n        }\r\n\r\n```\r\n\r\n6. You will need to replace the values for `AWS` and `sts:ExternalId`. These can be found in your snowflake Catalog Details section.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image18.png)\r\n\r\n7. Click **Update Policy** to save it.  \r\n8. Your updated AWS Role Trust Policy should look like this:\r\n\r\n```\r\n{\r\n  \"Version\": \"2012-10-17\",\r\n  \"Statement\": [\r\n    {\r\n      \"Effect\": \"Allow\",\r\n      \"Principal\": {\r\n        // from Confluent\r\n        \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n      },\r\n      \"Action\": \"sts:AssumeRole\",\r\n      \"Condition\": {\r\n        \"StringEquals\": {\r\n          // from Confluent\r\n          \"sts:ExternalId\": \"\u003C\u003Cexternal-id\u003E\u003E\"\r\n        }\r\n      }\r\n    },\r\n    {\r\n      \"Effect\": \"Allow\",\r\n      \"Principal\": {\r\n        // from Confluent\r\n        \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n      },\r\n      \"Action\": \"sts:TagSession\"\r\n    },\r\n    {\r\n            \"Sid\": \"\",\r\n            \"Effect\": \"Allow\",\r\n            \"Principal\": {\r\n       // from Snowflake\r\n                \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n\r\n            },\r\n            \"Action\": \"sts:AssumeRole\",\r\n            \"Condition\": {\r\n                \"StringEquals\": {\r\n      // from Snowflake\r\n                    \"sts:ExternalId\": \"snowflake-external-id\"\r\n                }\r\n            }\r\n        }\r\n  ]\r\n}\r\n\r\n```\r\n\r\nYou are now ready to add your External Provider to Tableflow.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Add Snowflake as External Provider to Tableflow\r\n\r\n- Navigate back to your Tableflow console on Confluent Cloud  \r\n- On the bottom of the page, you will see the External Catalog Integration. Within this sub-menu, click **+ Add Integration**. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image11.png)\r\n\r\n- On the next page, select Snowflake Open Catalog as your integration type  \r\n- In the name column, type `my-polaris-catalog-integration`\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image26.png)\r\n\r\n- Click **Continue.**  \r\n- Click **Continue** again.  \r\n- On the launch page, we will provide the following information:  \r\n  - **Snowflake Open Catalog URL**: `https://\u003ClocatorID\u003E.\u003Cregion\u003E.snowflakecomputing.com`  \r\n    - You can retrieve the locatorID from your open catalog URL bar. It will be the ID after the domain name/region like so:  \r\n    - [https://app.snowflake.com/us-east-1/](https://app.snowflake.com/us-east-1/)\u003CLOCATOR ID\u003E/#/  \r\n  - **Warehouse name:** my-snowflake-catalog  \r\n  - **Client ID:** Retrieve this from the Client Connection credentials you generated in step two of Set Up Open Catalog Connection on Snowflake   \r\n  - **Client secret:** Retrieve this from the Client Connection credentials you generated in step two of Set Up Open Catalog Connection on Snowflake   \r\n  - **Allowed scope:** `PRINCIPAL_ROLE:my-snowflake-principal-role`\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image43.png)\r\n\r\n- **Click continue** and then **click launch.**\r\n\r\nAfter a few moments, you should see the External Catalog integration you have just set up transitioning from Pending to Connected.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image50.png)\r\n\r\n- Navigate back to the Snowflake Open Data Catalog  \r\n- Under the Catalogs sub-menu, click on your catalog name (`my-snowflake-catalog`)  \r\n- You should see the Kafka cluster ID appear here  \r\n- Under the Kafka cluster ID, you will see the tables you enabled Tableflow on successfully materialized in Snowflake.  \r\n- You should also see the topics materialized under your cluster ID\r\n\r\n## ![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image52.png)\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Query Iceberg Tables via Snowflake\r\n\r\n\r\nNow that we’ve got our Snowflake Open Catalog set up receiving data from our Kafka topics, we can now see the full end-to-end integration by referencing our Snowflake Open Catalog within our Snowflake environment.\r\n\r\n- Start by navigating back to your Snowflake environment. You can click [this link](https://app.snowflake.com/) in order to open your Snowsight UI.  \r\n- Create a new SQL Worksheet by clicking **+ Create** at the top left hand corner, and select **SQL Worksheet**\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image31.png)\r\n\r\n- This will open up a new SQL Worksheet named the current date and time. Feel free to rename this as `Open Data Catalog Setup` by clicking the three dots ⠇to the right of the worksheet tab.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image46.png)\r\n\r\n### Create an External Volume\r\n\r\n- Ensure you have `AccountAdmin` Privileges granted to your account in order to create an external volume\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image2.png)\r\n\r\n- We will now create an external volume referencing our Amazon S3 bucket. Enter the following SQL statement, replacing the Amazon S3 bucket with the one you created earlier (`s3://tableflow-bucket-\u003C\u003Caccount-id\u003E\u003E`), the IAM role you created earlier (`arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/quickstart-tableflow-assume-role`), and leave the rest.\r\n\r\n\r\n```\r\nCREATE OR REPLACE EXTERNAL VOLUME iceberg_external_volume\r\n   STORAGE_LOCATIONS =\r\n      (\r\n         (\r\n            NAME = 'my-iceberg-external-volume'\r\n            STORAGE_PROVIDER = 'S3'\r\n            STORAGE_BASE_URL = 's3://tableflow-bucket-\u003C\u003Caccount-id\u003E\u003E'\r\n            STORAGE_AWS_ROLE_ARN = 'arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/quickstart-tableflow-assume-role'\r\n            STORAGE_AWS_EXTERNAL_ID = 'snowflake-external-id'\r\n         )\r\n      );\r\n```\r\n\r\n- Execute this statement by highlighting the text and clicking the Play button  ▶️ to the top-right.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image36.png)\r\n\r\n- You will see the success message appear at the bottom of the page, showing that the external volume was successfully created.\r\n\r\n- We need to get the `STORAGE_AWS_IAM_USER_ARN` to provide to our IAM Role trust policy. We can do so by running a describe query on the external volume we just created.\r\n\r\n```\r\nDESC EXTERNAL VOLUME iceberg_external_volume;\r\n```\r\n\r\n- Run this command like we did with the first command by highlighting the text and clicking on the Play button  ▶️to the top right.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image6.gif)\r\n\r\n- The output of this command will appear at the bottom of the page. Under the results for `STORAGE_LOCATIONS` there will be a `property_value`, click this value to see the results on the right hand side.  \r\n- From the value of the `property_value` column, copy the value of `STORAGE_AWS_IAM_USER_ARN` which should look like an IAM ARN\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image21.png)\r\n\r\n### Update Trust Policy for Snowflake\r\n\r\n- Let’s now navigate back to our AWS IAM Role that we created previously (**quickstart-tableflow-assume-role**) and update the trust policy again:  \r\n  - Navigate back to your Role on AWS and switch to the **Trust Relationships** tab  \r\n  - Click **Edit Trust Policy** \r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image16.png)**\r\n\r\n- We will again be adding another entry to our trust policy under the Statement block that will look like this:\r\n\r\n```\r\n    {\r\n      \"Sid\": \"\",\r\n      \"Effect\": \"Allow\",\r\n      \"Principal\": {\r\n        \"AWS\": \"\u003C\u003CSTORAGE_AWS_IAM_USER_ARN\u003E\u003E\"\r\n      },\r\n      \"Action\": \"sts:AssumeRole\",\r\n      \"Condition\": {\r\n        \"StringEquals\": {\r\n          \"sts:ExternalId\": \"snowflake-external-id\"\r\n        }\r\n      }\r\n\r\n```\r\n\r\n- Under the AWS key, paste your `STORAGE_AWS_IAM_USER_ARN`  \r\n- Keep the external ID as `snowflake-external-id` as that’s the external ID we created in the external volume\r\n\r\n- Once you add the extra trust policy, your full trust policy should look like this:\r\n\r\n```\r\n        \r\n{\r\n  \"Version\": \"2012-10-17\",\r\n  \"Statement\": [\r\n    {\r\n      \"Effect\": \"Allow\",\r\n      \"Principal\": {\r\n        // from Confluent\r\n        \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n      },\r\n      \"Action\": \"sts:AssumeRole\",\r\n      \"Condition\": {\r\n        \"StringEquals\": {\r\n          // from Confluent\r\n          \"sts:ExternalId\": \"\u003C\u003Cexternal-id\u003E\u003E\"\r\n        }\r\n      }\r\n    },\r\n    {\r\n      \"Effect\": \"Allow\",\r\n      \"Principal\": {\r\n        // from Confluent\r\n        \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n      },\r\n      \"Action\": \"sts:TagSession\"\r\n    },\r\n    {\r\n            \"Sid\": \"\",\r\n            \"Effect\": \"Allow\",\r\n            \"Principal\": {\r\n       // from Snowflake Open Catalog\r\n                \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n\r\n            },\r\n            \"Action\": \"sts:AssumeRole\",\r\n            \"Condition\": {\r\n                \"StringEquals\": {\r\n       // from Snowflake Open Catalog\r\n                    \"sts:ExternalId\": \"snowflake-external-id\"\r\n                }\r\n            }\r\n        },\r\n{\r\n            \"Sid\": \"\",\r\n            \"Effect\": \"Allow\",\r\n            \"Principal\": {\r\n       // from Snowflake \r\n                \"AWS\": \"arn:aws:iam::\u003C\u003Caccount-id\u003E\u003E:role/\u003C\u003Crole-id\u003E\u003E\"\r\n            },\r\n            \"Action\": \"sts:AssumeRole\",\r\n            \"Condition\": {\r\n                \"StringEquals\": {\r\n       // from Snowflake\r\n                    \"sts:ExternalId\": \"snowflake-external-id\"\r\n                }\r\n            }\r\n        }\r\n  ]\r\n}\r\n\r\n```\r\n\r\n- The next step is verifying that we can actually access the external volume via Snowflake. Execute this command:\r\n\r\n```\r\nSELECT SYSTEM$VERIFY_EXTERNAL_VOLUME('iceberg_external_volume');\r\n```\r\n\r\n- When this runs, you should see the keywords “success”:”true” and “PASSED” in the results set. This means the trust policy update took effect.\r\n\r\n### Create Catalog Integration\r\n\r\n- We can now create our catalog integration, to link Snowflake to our Snowflake Open Data Catalog. For this SQL statement you will need to retrieve some information in the placeholders. Start by pasting in this placeholder create statement into your SQL worksheet.\r\n\r\n```\r\nCREATE OR REPLACE CATALOG INTEGRATION my_snowflake_open_catalog_int\r\n  CATALOG_SOURCE = POLARIS\r\n  TABLE_FORMAT = ICEBERG\r\n    CATALOG_NAMESPACE='\u003C\u003C KAFKA CLUSTER ID\u003E\u003E'\r\n  REST_CONFIG = (\r\n     CATALOG_URI ='https://\u003C\u003Corganization-name\u003E\u003E-\u003C\u003Copen-data-catalog-account-name\u003E\u003E.snowflakecomputing.com/polaris/api/catalog'\r\n     WAREHOUSE = 'my-snowflake-catalog'\r\n  )\r\n  REST_AUTHENTICATION = (\r\n     TYPE=OAUTH\r\n    OAUTH_CLIENT_ID='\u003C\u003Cclient-id\u003E\u003E'\r\n    OAUTH_CLIENT_SECRET='\u003C\u003Cclient-secret\u003E\u003E'\r\n     OAUTH_ALLOWED_SCOPES=('PRINCIPAL_ROLE:my-snowflake-principal-role')\r\n  )\r\n  REFRESH_INTERVAL_SECONDS = 60\r\n  ENABLED=true;\r\n\r\n\r\n```\r\n\r\n- The first placeholder, `CATALOG_NAMESPACE` should be your Kafka cluster ID. This can be found by navigating to your Confluent Cloud Kafka cluster and checking the cluster details on the right hand menu. **Copy this value and paste it in the value for CATALOG_NAMESPACE.**\r\n\r\n**![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image4.png)**\r\n\r\n- The next placeholder, `CATALOG_URI` will require your Snowflake Organization name and your open data catalog **account name**. The Snowflake Organization name can be found in your Snowflake homepage by clicking on your profile at the bottom left of the screen, hovering over your account and clicking on account details.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image41.png)\r\n\r\n- Copy the value of your **Organization Name** as the first part of your `CATALOG_URI`.   \r\n- The second part of your `CATALOG_URI` is the **account name** for your open data catalog account. This can be found under the same profile menu when you switch accounts. Just copy the account name and put it into the second part of your catalog URI for the placeholders.  \r\n- The final result should look like:  \r\n  - `CATALOG_URI=`’`https://organizationname-opendatacatalogaccountname.snowflakecomputing.com/polaris/api/catalog’`\r\n\r\n- For the OATH client id and client secret, these were the values you copied down when creating your open data catalog connection. Copy and paste these values as appropriate.\r\n\r\n- You are now ready to create your catalog integration. Highlight the command and click the Play ▶️button just as before. \r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image12.png)\r\n\r\n- After running the command, you should see that the catalog integration was successfully created.\r\n\r\n### Creating the Iceberg Table and Querying\r\n\r\n- Once we have the catalog integration set up, you can now create an Iceberg table to query your snowflake open data catalog data.  \r\n- Execute the following command, ensuring that all variables match exactly. If you named your external volume, catalog or kafka topic something different, this query will not work:\r\n\r\n```\r\nCREATE OR REPLACE ICEBERG TABLE snowflake_stock_trades\r\n    EXTERNAL_VOLUME = 'iceberg_external_volume'\r\n    CATALOG = 'my_snowflake_open_catalog_int'\r\n    CATALOG_TABLE_NAME = sample_data_stock_trades\r\n```\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image13.png)\r\n\r\n- Finally we are ready to query the table. Here are some queries you can try and evaluate the results.\r\n\r\n```\r\n-- count the number of records\r\nSELECT COUNT(*) from snowflake_stock_trades;\r\n\r\n-- see one record in the table\r\nselect * from snowflake_stock_trades limit 1;\r\n\r\n-- see all records in the table\r\nSELECT * FROM snowflake_stock_trades;\r\n\r\n```\r\n\r\nThese query results should update periodically when run again, showcasing that we are continuously writing data to our Iceberg tables. You should expect to see updated results every 15 minutes or so depending on data volume and refresh frequency.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image56.png)\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image48.png)\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n\r\n## Optional: Automatic Anomaly Detection with Apache Flink\r\n\r\nWhile your data is flowing from Kafka to Snowflake via Tableflow, you may want to enrich or flag certain records *before* they land in the data lake. This is where **Apache Flink** comes in.\r\n\r\nIn this optional step, you'll use Flink SQL in Confluent Cloud to detect basic anomalies in the stock trading stream. This can be useful for spotting potential fraud, pricing glitches, or unusually large trades as they happen.\r\n\r\nWe'll create a lightweight streaming job using Flink SQL that watches for simple anomalies based on rules:\r\n\r\n* Trades with **unusually large quantities**  \r\n* Trades with a **negative price**  \r\n* Trades that exceed a configurable threshold\r\n\r\nThese flagged records will be tagged with an `anomaly_flag` field and written to a new Kafka topic called `flagged_stock_trades`. You could later route this to a separate Iceberg table, alerting system, or ML pipeline.\r\n\r\n### Create the Anomaly Detection Flink Job\r\n\r\n#### 1. Open Flink SQL in Confluent Cloud\r\n\r\n* In your Confluent Cloud console, navigate to your cloud environment.  \r\n* In the left-hand menu, click **Flink**.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image40.png)\r\n\r\n* Click **+ Add compute pool**  \r\n* On the next screen, choose **AWS** as the cloud provider, and choose `us-east-1` as the region. Then click **Continue.**  \r\n* Finally, click **Create**.  \r\n* Once the compute pool is created, click **Open SQL workspace**.\r\n\r\n2. Define a Cleaned and Flagged Version of `stock_trades`\r\n\r\nPaste the following SQL into the editor. This will read from the `sample_data_stock_trades` topic, apply simple anomaly rules, and write the results to a new topic.\r\n\r\n```sql\r\nCREATE TABLE flagged_stock_trades\r\nAS SELECT\r\n  side,\r\n  quantity,\r\n  symbol,\r\n  price,\r\n  account,\r\n  userid,\r\n  CASE\r\n    WHEN price \u003C 0 THEN 'NEGATIVE_PRICE'\r\n    WHEN quantity \u003E 4000 THEN 'LARGE_TRADE'\r\n    WHEN price \u003E 900 THEN 'UNUSUAL_PRICE'\r\n    ELSE 'NORMAL'\r\n  END AS anomaly_flag\r\nFROM sample_data_stock_trades;\r\n```\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image45.png)\r\n\r\n3. Launch the Flink Job\r\n\r\n* Click **Run** to execute the job.  \r\n* Once deployed, it will continuously process new `stock_trades` events and write flagged records to `flagged_stock_trades`.\r\n\r\n#### 4. Inspect the Flagged Trade Messages\r\n\r\nOnce your Flink job is running, you can verify that it’s working by looking at the `flagged_stock_trades` topic and checking for the `anomaly_flag` field in the messages or by creating and running another Flink job with the SQL below.\r\n\r\n```sql\r\nSELECT * FROM flagged_stock_trades;\r\n```\r\n\r\nYou should see live messages coming through that look something like this:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/snowflake-confluent-tableflow-iceberg/image32.png)\r\n\r\n**Tip: Filter by Anomaly**\r\n\r\nTo narrow in on only anomalous records, you can modify the Flink SQL to exclude `\"NORMAL\"` entries, or filter them later downstream when querying from Iceberg or Snowflake.\r\n\r\n#### 5. (Optional) Enable Tableflow on `flagged_stock_trades`\r\n\r\nYou can repeat the same Tableflow steps you followed earlier to sync `flagged_stock_trades` into your Iceberg tables and expose it to Snowflake.\r\n\r\n### Why This Matters\r\n\r\nBy adding a lightweight Flink layer, you can inspect, clean, or augment your data *in motion*, before it ever hits storage or analytics layers. This pattern is useful for:\r\n\r\n* **Pre-processing for machine learning**  \r\n* **Real-time monitoring and alerting**  \r\n* **Reducing noise or garbage in your data lake**\r\n\r\nWhile this was a simple rule-based example, Flink also supports more sophisticated anomaly detection techniques such as applying ML models or calculating dynamic thresholds using moving averages over time windows. All of this can be expressed declaratively in Flink SQL.\r\n\r\nThis optional step shows how real-time intelligence fits naturally into a streaming lakehouse architecture with no batch jobs, no glue code, and no waiting.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Conclusion and Resources\r\n\r\nYou’ve now built a complete real-time data pipeline, from ingestion to insight, using Confluent Cloud, Tableflow, Apache Flink, and Snowflake.\r\n\r\nAlong the way, you:\r\n\r\n* Set up a Kafka-based streaming architecture with simulated user and stock trade data.  \r\n* Materialized Kafka topics directly into Iceberg tables using Tableflow.  \r\n* Queried fresh, continuously updated data from Snowflake’s Open Data Catalog.  \r\n* (Optionally) Enriched and flagged anomalies in-flight using Flink SQL.\r\n\r\nThis architecture is modular, cloud-native, and scalable giving you a flexible foundation for powering analytics, AI, and operational decision-making in real time.\r\n\r\n### Related Resources\r\n\r\n* [Tableflow in Confluent Cloud](https://docs.confluent.io/cloud/current/topics/tableflow/overview.html)  \r\n* [Stream Processing with Confluent Cloud for Apache Flink](https://docs.confluent.io/cloud/current/flink/overview.html)  \r\n* [Build AI with Flink SQL and Confluent Cloud for Apache Flink](https://docs.confluent.io/cloud/current/ai/overview.html)  \r\n* [Apache Iceberg tables](https://docs.snowflake.com/en/user-guide/tables-iceberg)\r\n\r\n## Cleanup\r\n\r\nOnce you’ve completed the lab (or if you’re done experimenting), it’s a good idea to clean up the cloud resources to avoid incurring unnecessary costs and to keep your environment tidy.\r\n\r\n### Snowflake Cleanup\r\n\r\n1. **Remove the Iceberg Table(s)**   \r\n   In your Snowflake SQL Worksheet, drop any Iceberg tables you created:\r\n\r\n```\r\nDROP TABLE IF EXISTS snowflake_stock_trades;\r\nDROP TABLE IF EXISTS flagged_stock_trades;\r\n```\r\n\r\n1. **Remove the Catalog Integration**  \r\n   Remove the integration between Snowflake and the Open Data Catalog:\r\n\r\n```\r\nDROP CATALOG INTEGRATION IF EXISTS my_snowflake_open_catalog_int;\r\n```\r\n\r\n2. **Remove External Volume**  \r\n   Delete the external volume referencing your S3 bucket:\r\n\r\n```\r\nDROP EXTERNAL VOLUME IF EXISTS iceberg_external_volume;\r\n```\r\n\r\n3. **Delete Catalog Roles and Catalog**  \r\n   In the Snowflake Open Data Catalog interface:  \r\n   * Go to **Catalogs \u003E your catalog \u003E Roles** and delete any catalog roles you created.  \r\n   * Return to the **Catalogs** tab and delete the entire catalog (e.g., `my-snowflake-catalog`).  \r\n4. **Delete Connection and Principal Role**  \r\n   In the **Connections** tab:  \r\n   * Delete the connection (`my-service-connection`).  \r\n   * Delete the associated principal role.\r\n\r\n### Confluent Cloud Cleanup\r\n\r\n1. **Delete Tableflow Syncs**  \r\n   Go to the **Topics** section, select each topic with Tableflow enabled, and disable or delete the Tableflow sync.\r\n\r\n2. **Delete Kafka Topics**  \r\n   Delete the `sample_data_users`, `sample_data_stock_trades`, and `flagged_stock_trades` topics.\r\n\r\n3. **Delete Connectors**  \r\n   Go to the **Connectors** tab and delete both Datagen connectors you created.\r\n\r\n4. **Delete Flink SQL Statements**  \r\n   Navigate to the **Flink SQL** section and delete the statement that was used for anomaly detection.\r\n\r\n5. **Delete the Kafka Cluster and Environment** (optional)  \r\n   If you don’t plan to reuse the cluster or environment:  \r\n   * Go to the **Cluster Settings** and delete your Kafka cluster.  \r\n   * Navigate back to **Environments** and delete the environment you created.\r\n\r\n### AWS Cleanup\r\n\r\n1. **Delete the S3 Bucket**  \r\n   * Go to the **Amazon S3 Console**, find the bucket you created (`tableflow-bucket-\u003C\u003Caccount-id\u003E\u003E`), and delete it. 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