The “HDFS interface” connection parameter should be set This post introduces Dataiku's Data Science Studio on Azure HDInsight to make data science easier. Topics … DSS can be deployed on a regular EC2 instance, not part of the EMR cluster itself. With Amazon EMR 5.23.0 and later, you can launch a cluster with three master nodes to support high availability of applications like YARN Resource Manager, HDFS Name Node, Spark, Hive, and Ganglia. Follow the steps outlined above. Systems Manager gives you … When this is not allowed, Spark jobs will fall back to reading and writing the datasets through the DSS backend, Deploying Infoworks Edge Node for EMR. . In that case, you don’t require any specific additional steps, just follow Data scientist use Apache Spark cluster running on Amazon EMR to perform distributed training. Enter the DSS cluster identifier, either directly, or using a variable - the latter case is required if you setup your cluster as part of the scenario. The VPC Subnet identifier in which you want to create your EMR cluster. You are viewing the documentation for version, Setting up Dashboards and Flow export to PDF or images, Projects, Folders, Dashboards, Wikis Views, Changing the Order of Sections on the Homepage, Fuzzy join with other dataset (memory-based), Fill empty cells with previous/next value, In-memory Python (Scikit-learn / XGBoost), How to Manage Large Flows with Flow Folding, Reference architecture: managed compute on EKS with Glue and Athena, Reference architecture: manage compute on AKS and storage on ADLS gen2, Reference architecture: managed compute on GKE and storage on GCS, Hadoop filesystems connections (HDFS, S3, EMRFS, WASB, ADLS, GS), Using Amazon Elastic Kubernetes Service (EKS), Using Microsoft Azure Kubernetes Service (AKS), Using code envs with containerized execution, Importing code from Git in project libraries, Automation scenarios, metrics, and checks, Components: Custom chart palettes and map backgrounds, Authentication information and impersonation, Hadoop Impersonation (HDFS, YARN, Hive, Impala), DSS crashes / The “Disconnected” overlay appears, “Your user profile does not allow” issues, ERR_BUNDLE_ACTIVATE_CONNECTION_NOT_WRITABLE: Connection is not writable, ERR_CODEENV_CONTAINER_IMAGE_FAILED: Could not build container image for this code environment, ERR_CODEENV_CONTAINER_IMAGE_TAG_NOT_FOUND: Container image tag not found for this Code environment, ERR_CODEENV_CREATION_FAILED: Could not create this code environment, ERR_CODEENV_DELETION_FAILED: Could not delete this code environment, ERR_CODEENV_EXISTING_ENV: Code environment already exists, ERR_CODEENV_INCORRECT_ENV_TYPE: Wrong type of Code environment, ERR_CODEENV_INVALID_CODE_ENV_ARCHIVE: Invalid code environment archive, ERR_CODEENV_JUPYTER_SUPPORT_INSTALL_FAILED: Could not install Jupyter support in this code environment, ERR_CODEENV_JUPYTER_SUPPORT_REMOVAL_FAILED: Could not remove Jupyter support from this code environment, ERR_CODEENV_MISSING_ENV: Code environment does not exists, ERR_CODEENV_MISSING_ENV_VERSION: Code environment version does not exists, ERR_CODEENV_NO_CREATION_PERMISSION: User not allowed to create Code environments, ERR_CODEENV_NO_USAGE_PERMISSION: User not allowed to use this Code environment, ERR_CODEENV_UNSUPPORTED_OPERATION_FOR_ENV_TYPE: Operation not supported for this type of Code environment, ERR_CODEENV_UPDATE_FAILED: Could not update this code environment, ERR_CONNECTION_ALATION_REGISTRATION_FAILED: Failed to register Alation integration, ERR_CONNECTION_API_BAD_CONFIG: Bad configuration for connection, ERR_CONNECTION_AZURE_INVALID_CONFIG: Invalid Azure connection configuration, ERR_CONNECTION_DUMP_FAILED: Failed to dump connection tables, ERR_CONNECTION_INVALID_CONFIG: Invalid connection configuration, ERR_CONNECTION_LIST_HIVE_FAILED: Failed to list indexable Hive connections, ERR_CONNECTION_S3_INVALID_CONFIG: Invalid S3 connection configuration, ERR_CONNECTION_SQL_INVALID_CONFIG: Invalid SQL connection configuration, ERR_CONNECTION_SSH_INVALID_CONFIG: Invalid SSH connection configuration, ERR_CONTAINER_CONF_NO_USAGE_PERMISSION: User not allowed to use this containerized execution configuration, ERR_CONTAINER_CONF_NOT_FOUND: The selected container configuration was not found, ERR_CONTAINER_IMAGE_PUSH_FAILED: Container image push failed, ERR_DATASET_ACTION_NOT_SUPPORTED: Action not supported for this kind of dataset, ERR_DATASET_CSV_UNTERMINATED_QUOTE: Error in CSV file: Unterminated quote, ERR_DATASET_HIVE_INCOMPATIBLE_SCHEMA: Dataset schema not compatible with Hive, ERR_DATASET_INVALID_CONFIG: Invalid dataset configuration, ERR_DATASET_INVALID_FORMAT_CONFIG: Invalid format configuration for this dataset, ERR_DATASET_INVALID_METRIC_IDENTIFIER: Invalid metric identifier, ERR_DATASET_INVALID_PARTITIONING_CONFIG: Invalid dataset partitioning configuration, ERR_DATASET_PARTITION_EMPTY: Input partition is empty, ERR_DATASET_TRUNCATED_COMPRESSED_DATA: Error in compressed file: Unexpected end of file, ERR_ENDPOINT_INVALID_CONFIG: Invalid configuration for API Endpoint, ERR_FOLDER_INVALID_PARTITIONING_CONFIG: Invalid folder partitioning configuration, ERR_FSPROVIDER_CANNOT_CREATE_FOLDER_ON_DIRECTORY_UNAWARE_FS: Cannot create a folder on this type of file system, ERR_FSPROVIDER_DEST_PATH_ALREADY_EXISTS: Destination path already exists, ERR_FSPROVIDER_FSLIKE_REACH_OUT_OF_ROOT: Illegal attempt to access data out of connection root path, ERR_FSPROVIDER_HTTP_CONNECTION_FAILED: HTTP connection failed, ERR_FSPROVIDER_HTTP_INVALID_URI: Invalid HTTP URI, ERR_FSPROVIDER_HTTP_REQUEST_FAILED: HTTP request failed, ERR_FSPROVIDER_ILLEGAL_PATH: Illegal path for that file system, ERR_FSPROVIDER_INVALID_CONFIG: Invalid configuration, ERR_FSPROVIDER_INVALID_FILE_NAME: Invalid file name, ERR_FSPROVIDER_LOCAL_LIST_FAILED: Could not list local directory, ERR_FSPROVIDER_PATH_DOES_NOT_EXIST: Path in dataset or folder does not exist, ERR_FSPROVIDER_ROOT_PATH_DOES_NOT_EXIST: Root path of the dataset or folder does not exist, ERR_FSPROVIDER_SSH_CONNECTION_FAILED: Failed to establish SSH connection, ERR_HIVE_HS2_CONNECTION_FAILED: Failed to establish HiveServer2 connection, ERR_HIVE_LEGACY_UNION_SUPPORT: Your current Hive version doesn’t support UNION clause but only supports UNION ALL, which does not remove duplicates, ERR_METRIC_DATASET_COMPUTATION_FAILED: Metrics computation completely failed, ERR_METRIC_ENGINE_RUN_FAILED: One of the metrics engine failed to run, ERR_ML_MODEL_DETAILS_OVERFLOW: Model details exceed size limit, ERR_NOT_USABLE_FOR_USER: You may not use this connection, ERR_OBJECT_OPERATION_NOT_AVAILABLE_FOR_TYPE: Operation not supported for this kind of object, ERR_PLUGIN_CANNOT_LOAD: Plugin cannot be loaded, ERR_PLUGIN_COMPONENT_NOT_INSTALLED: Plugin component not installed or removed, ERR_PLUGIN_DEV_INVALID_COMPONENT_PARAMETER: Invalid parameter for plugin component creation, ERR_PLUGIN_DEV_INVALID_DEFINITION: The descriptor of the plugin is invalid, ERR_PLUGIN_INVALID_DEFINITION: The plugin’s definition is invalid, ERR_PLUGIN_NOT_INSTALLED: Plugin not installed or removed, ERR_PLUGIN_WITHOUT_CODEENV: The plugin has no code env specification, ERR_PLUGIN_WRONG_TYPE: Unexpected type of plugin, ERR_PROJECT_INVALID_ARCHIVE: Invalid project archive, ERR_PROJECT_INVALID_PROJECT_KEY: Invalid project key, ERR_PROJECT_UNKNOWN_PROJECT_KEY: Unknown project key, ERR_RECIPE_CANNOT_CHANGE_ENGINE: Cannot change engine, ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY: Cannot check schema consistency, ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY_EXPENSIVE: Cannot check schema consistency: expensive checks disabled. to “Amazon EMRFS”. For example, the edge weight of the link between Spider Man and Captain America is the same as the number of comics they both appear in together. ... After the user has selected DSS, DSS is installed on the edge node, which is part of the cluster. This operation is not officially documented by EMR nor officially supported by Dataiku. Hi Team, We have configured dss and connected to EMR cluster (edge node) and there I am running jobs by selecting the cluster from project level . We strongly recommend that you use our AMI “dataiku-emrclient” which contains everything required for EMR support. Note that the DSS cluster definition itself remains, allowing you to recreate the EMR cluster at a later time. The master node is no longer a potential single point of failure with this feature. At this point, your EMR cluster, edge node and remote server are all set up and running. compatible, and BUILD_DATE is its build date using format YYYYMMDD. In “Type”, select “EMR cluster (create cluster)” and give a name to your new cluster. Hi, What is the impact of changing my Hadoop distribution (MapR to CLOUDERA). In order to do that, I ran some graph clustering algorithms (e.g., the … Otherwise, you can specify S3 credentials at the connection level by defining the following properties in “Extra Hadop conf.” (refer to EMRFS documentation for details about available properties): These properties will be used by DSS whenever accessing files within this connection, and will be passed to If running different versions, some incompatibilities may occur. More visual recipes: Dataiku’s graphical interface … In that case, your server needs to have the EMR client libraries for the EMR version you will use. Go to the “Actions” tab of your cluster, and select the “Scale” action. DSS is not compatible with EMR version 6.x. It is acceptable amount of resources to the cluster, in order to be entirely available to DSS. the regular Hadoop installation steps. EMR worker nodes may not have the full client configuration installed, and may in particular be missing the contents of Deploying an edge node for an EMR cluster. You will need two steps for that. to reattach the EBS to a node of the new cluster, rerun Hadoop integration and restart DSS from here (this can be easily Connect DSS to an existing EMR cluster. You are viewing the documentation for version, Setting up Dashboards and Flow export to PDF or images, Projects, Folders, Dashboards, Wikis Views, Changing the Order of Sections on the Homepage, Fuzzy join with other dataset (memory-based), Fill empty cells with previous/next value, In-memory Python (Scikit-learn / XGBoost), How to Manage Large Flows with Flow Folding, Reference architecture: managed compute on EKS with Glue and Athena, Reference architecture: manage compute on AKS and storage on ADLS gen2, Reference architecture: managed compute on GKE and storage on GCS, Hadoop filesystems connections (HDFS, S3, EMRFS, WASB, ADLS, GS), Using Amazon Elastic Kubernetes Service (EKS), Using Microsoft Azure Kubernetes Service (AKS), Using code envs with containerized execution, Importing code from Git in project libraries, Automation scenarios, metrics, and checks, Components: Custom chart palettes and map backgrounds, Authentication information and impersonation, Hadoop Impersonation (HDFS, YARN, Hive, Impala), DSS crashes / The “Disconnected” overlay appears, “Your user profile does not allow” issues, ERR_BUNDLE_ACTIVATE_CONNECTION_NOT_WRITABLE: Connection is not writable, ERR_CODEENV_CONTAINER_IMAGE_FAILED: Could not build container image for this code environment, ERR_CODEENV_CONTAINER_IMAGE_TAG_NOT_FOUND: Container image tag not found for this Code environment, ERR_CODEENV_CREATION_FAILED: Could not create this code environment, ERR_CODEENV_DELETION_FAILED: Could not delete this code environment, ERR_CODEENV_EXISTING_ENV: Code environment already exists, ERR_CODEENV_INCORRECT_ENV_TYPE: Wrong type of Code environment, ERR_CODEENV_INVALID_CODE_ENV_ARCHIVE: Invalid code environment archive, ERR_CODEENV_JUPYTER_SUPPORT_INSTALL_FAILED: Could not install Jupyter support in this code environment, ERR_CODEENV_JUPYTER_SUPPORT_REMOVAL_FAILED: Could not remove Jupyter support from this code environment, ERR_CODEENV_MISSING_ENV: Code environment does not exists, ERR_CODEENV_MISSING_ENV_VERSION: Code environment version does not exists, ERR_CODEENV_NO_CREATION_PERMISSION: User not allowed to create Code environments, ERR_CODEENV_NO_USAGE_PERMISSION: User not allowed to use this Code environment, ERR_CODEENV_UNSUPPORTED_OPERATION_FOR_ENV_TYPE: Operation not supported for this type of Code environment, ERR_CODEENV_UPDATE_FAILED: Could not update this code environment, ERR_CONNECTION_ALATION_REGISTRATION_FAILED: Failed to register Alation integration, ERR_CONNECTION_API_BAD_CONFIG: Bad configuration for connection, ERR_CONNECTION_AZURE_INVALID_CONFIG: Invalid Azure connection configuration, ERR_CONNECTION_DUMP_FAILED: Failed to dump connection tables, ERR_CONNECTION_INVALID_CONFIG: Invalid connection configuration, ERR_CONNECTION_LIST_HIVE_FAILED: Failed to list indexable Hive connections, ERR_CONNECTION_S3_INVALID_CONFIG: Invalid S3 connection configuration, ERR_CONNECTION_SQL_INVALID_CONFIG: Invalid SQL connection configuration, ERR_CONNECTION_SSH_INVALID_CONFIG: Invalid SSH connection configuration, ERR_CONTAINER_CONF_NO_USAGE_PERMISSION: User not allowed to use this containerized execution configuration, ERR_CONTAINER_CONF_NOT_FOUND: The selected container configuration was not found, ERR_CONTAINER_IMAGE_PUSH_FAILED: Container image push failed, ERR_DATASET_ACTION_NOT_SUPPORTED: Action not supported for this kind of dataset, ERR_DATASET_CSV_UNTERMINATED_QUOTE: Error in CSV file: Unterminated quote, ERR_DATASET_HIVE_INCOMPATIBLE_SCHEMA: Dataset schema not compatible with Hive, ERR_DATASET_INVALID_CONFIG: Invalid dataset configuration, ERR_DATASET_INVALID_FORMAT_CONFIG: Invalid format configuration for this dataset, ERR_DATASET_INVALID_METRIC_IDENTIFIER: Invalid metric identifier, ERR_DATASET_INVALID_PARTITIONING_CONFIG: Invalid dataset partitioning configuration, ERR_DATASET_PARTITION_EMPTY: Input partition is empty, ERR_DATASET_TRUNCATED_COMPRESSED_DATA: Error in compressed file: Unexpected end of file, ERR_ENDPOINT_INVALID_CONFIG: Invalid configuration for API Endpoint, ERR_FOLDER_INVALID_PARTITIONING_CONFIG: Invalid folder partitioning configuration, ERR_FSPROVIDER_CANNOT_CREATE_FOLDER_ON_DIRECTORY_UNAWARE_FS: Cannot create a folder on this type of file system, ERR_FSPROVIDER_DEST_PATH_ALREADY_EXISTS: Destination path already exists, ERR_FSPROVIDER_FSLIKE_REACH_OUT_OF_ROOT: Illegal attempt to access data out of connection root path, ERR_FSPROVIDER_HTTP_CONNECTION_FAILED: HTTP connection failed, ERR_FSPROVIDER_HTTP_INVALID_URI: Invalid HTTP URI, ERR_FSPROVIDER_HTTP_REQUEST_FAILED: HTTP request failed, ERR_FSPROVIDER_ILLEGAL_PATH: Illegal path for that file system, ERR_FSPROVIDER_INVALID_CONFIG: Invalid configuration, ERR_FSPROVIDER_INVALID_FILE_NAME: Invalid file name, ERR_FSPROVIDER_LOCAL_LIST_FAILED: Could not list local directory, ERR_FSPROVIDER_PATH_DOES_NOT_EXIST: Path in dataset or folder does not exist, ERR_FSPROVIDER_ROOT_PATH_DOES_NOT_EXIST: Root path of the dataset or folder does not exist, ERR_FSPROVIDER_SSH_CONNECTION_FAILED: Failed to establish SSH connection, ERR_HIVE_HS2_CONNECTION_FAILED: Failed to establish HiveServer2 connection, ERR_HIVE_LEGACY_UNION_SUPPORT: Your current Hive version doesn’t support UNION clause but only supports UNION ALL, which does not remove duplicates, ERR_METRIC_DATASET_COMPUTATION_FAILED: Metrics computation completely failed, ERR_METRIC_ENGINE_RUN_FAILED: One of the metrics engine failed to run, ERR_ML_MODEL_DETAILS_OVERFLOW: Model details exceed size limit, ERR_NOT_USABLE_FOR_USER: You may not use this connection, ERR_OBJECT_OPERATION_NOT_AVAILABLE_FOR_TYPE: Operation not supported for this kind of object, ERR_PLUGIN_CANNOT_LOAD: Plugin cannot be loaded, ERR_PLUGIN_COMPONENT_NOT_INSTALLED: Plugin component not installed or removed, ERR_PLUGIN_DEV_INVALID_COMPONENT_PARAMETER: Invalid parameter for plugin component creation, ERR_PLUGIN_DEV_INVALID_DEFINITION: The descriptor of the plugin is invalid, ERR_PLUGIN_INVALID_DEFINITION: The plugin’s definition is invalid, ERR_PLUGIN_NOT_INSTALLED: Plugin not installed or removed, ERR_PLUGIN_WITHOUT_CODEENV: The plugin has no code env specification, ERR_PLUGIN_WRONG_TYPE: Unexpected type of plugin, ERR_PROJECT_INVALID_ARCHIVE: Invalid project archive, ERR_PROJECT_INVALID_PROJECT_KEY: Invalid project key, ERR_PROJECT_UNKNOWN_PROJECT_KEY: Unknown project key, ERR_RECIPE_CANNOT_CHANGE_ENGINE: Cannot change engine, ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY: Cannot check schema consistency, ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY_EXPENSIVE: Cannot check schema consistency: expensive checks disabled. Dataset of nodes to only keep information about the nodes (the edges are lost): one row per node and its features. DSS can be connected to an EMR cluster using the standard Hadoop integration procedure, provided the underlying host is ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY_ON_RECIPE_TYPE: Cannot check schema consistency on this kind of recipe, ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY_WITH_RECIPE_CONFIG: Cannot check schema consistency because of recipe configuration, ERR_RECIPE_CANNOT_CHANGE_ENGINE: Not compatible with Spark, ERR_RECIPE_CANNOT_USE_ENGINE: Cannot use the selected engine for this recipe, ERR_RECIPE_ENGINE_NOT_DWH: Error in recipe engine: SQLServer is not Data Warehouse edition, ERR_RECIPE_INCONSISTENT_I_O: Inconsistent recipe input or output, ERR_RECIPE_SYNC_AWS_DIFFERENT_REGIONS: Error in recipe engine: Redshift and S3 are in different AWS regions, ERR_RECIPE_PDEP_UPDATE_REQUIRED: Partition dependecy update required, ERR_RECIPE_SPLIT_INVALID_COMPUTED_COLUMNS: Invalid computed column, ERR_SCENARIO_INVALID_STEP_CONFIG: Invalid scenario step configuration, ERR_SECURITY_CRUD_INVALID_SETTINGS: The user attributes submitted for a change are invalid, ERR_SECURITY_GROUP_EXISTS: The new requested group already exists, ERR_SECURITY_INVALID_NEW_PASSWORD: The new password is invalid, ERR_SECURITY_INVALID_PASSWORD: The password hash from the database is invalid, ERR_SECURITY_MUS_USER_UNMATCHED: The DSS user is not configured to be matched onto a system user, ERR_SECURITY_PATH_ESCAPE: The requested file is not within any allowed directory, ERR_SECURITY_USER_EXISTS: The requested user for creation already exists, ERR_SECURITY_WRONG_PASSWORD: The old password provided for password change is invalid, ERR_SPARK_FAILED_DRIVER_OOM: Spark failure: out of memory in driver, ERR_SPARK_FAILED_TASK_OOM: Spark failure: out of memory in task, ERR_SPARK_FAILED_YARN_KILLED_MEMORY: Spark failure: killed by YARN (excessive memory usage), ERR_SPARK_PYSPARK_CODE_FAILED_UNSPECIFIED: Pyspark code failed, ERR_SPARK_SQL_LEGACY_UNION_SUPPORT: Your current Spark version doesn’t support UNION clause but only supports UNION ALL, which does not remove duplicates, ERR_SQL_CANNOT_LOAD_DRIVER: Failed to load database driver, ERR_SQL_DB_UNREACHABLE: Failed to reach database, ERR_SQL_IMPALA_MEMORYLIMIT: Impala memory limit exceeded, ERR_SQL_POSTGRESQL_TOOMANYSESSIONS: too many sessions open concurrently, ERR_SQL_TABLE_NOT_FOUND: SQL Table not found, ERR_SQL_VERTICA_TOOMANYROS: Error in Vertica: too many ROS, ERR_SQL_VERTICA_TOOMANYSESSIONS: Error in Vertica: too many sessions open concurrently, ERR_TRANSACTION_FAILED_ENOSPC: Out of disk space, ERR_TRANSACTION_GIT_COMMMIT_FAILED: Failed committing changes, ERR_USER_ACTION_FORBIDDEN_BY_PROFILE: Your user profile does not allow you to perform this action, WARN_RECIPE_SPARK_INDIRECT_HDFS: No direct access to read/write HDFS dataset, WARN_RECIPE_SPARK_INDIRECT_S3: No direct access to read/write S3 dataset, Let DSS dynamically manage one or several EMR clusters, Connect DSS to multiple existing EMR clusters.