Documentation
Academy
Join the Academy
Benefit from guided learning opportunities →
Quick Starts
Learning Paths
New Features
Certifications
Academy Discussions
Community
Explore the Community
Discover, share, and contribute →
Learn About Us
Ask A Question
What's New?
Discuss Dataiku
Using Dataiku
Setup And Configuration
General Discussion
Plugins & Extending Dataiku
Product Ideas
Programs
Frontrunner Awards
Dataiku Neurons
Community Resources
Community Feedback
User Research
Documentation
Reference Documentation
Comprehensive specifications of Dataiku →
User's Guide
Specific Data Processing
Automation & Deployment
APIs
Installation & Administration
Other Topics
Knowledge
Knowledge Base
Articles and tutorials on Dataiku features →
User Guide
Admin Guide
Dataiku Solutions
Dataiku Cloud
Developer
Developer Guide
Tutorials and articles for developers and coder users →
Getting Started
Concepts and Examples
Tutorials
API Reference
User's Guide
DSS concepts
Connecting to data
Exploring your data
Schemas, storage types and meanings
Data preparation
Charts
Interactive statistics
Machine learning
The Flow
Visual recipes
Recipes based on code
Code notebooks
MLOps
Webapps
Code Studios
Code reports
Dashboards
Workspaces
Data Catalog
Dataiku Applications
Working with partitions
DSS and SQL
DSS and Python
DSS and R
DSS and Spark
Code environments
Collaboration
Specific Data Processing
Time Series
Geographic data
Generative AI and LLM Mesh
Text & Natural Language Processing
Images
Audio
Video
Automation & Deployment
Metrics, checks and Data Quality
Automation scenarios
Production deployments and bundles
API Node & API Deployer: Real-time APIs
Governance
APIs
Python APIs
R API
Public REST API
Additional APIs
Installation & Administration
Installing and setting up
Elastic AI computation
DSS in the cloud
DSS and Hadoop
Metastore catalog
Operating DSS
Security
User Isolation
Other topics
Plugins
Streaming data
Formula language
Custom variables expansion
Sampling methods
Accessibility
Troubleshooting
Diagnosing and debugging issues
Obtaining support
Support tiers
Common issues
Error codes
ERR_ACTIVITY_DIRECTORY_SIZE_LIMIT_REACHED: Job activity directory size limit reached
ERR_BUNDLE_ACTIVATE_BAD_CONNECTION_PERMISSIONS: Connection is not freely usable
ERR_BUNDLE_ACTIVATE_BAD_CONNECTION_TYPE: Connection is the wrong type
ERR_BUNDLE_ACTIVATE_CONNECTION_NOT_WRITABLE: Connection is not writable
ERR_BUNDLE_ACTIVATE_MISSING_CONNECTION: Connection is missing
ERR_CLUSTERS_INVALID_SELECTED: Selected cluster does not exist
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_DEEPHUB_ENV: Code environment for deep learning does not exist
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_NOT_USING_LATEST_DEEPHUB_ENV: Not using latest version of code environment for deep learning
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_DASHBOARD_EXPORT_SAND_BOXING_ERROR: Chrome cannot start in the “sandbox” mode
ERR_DATASET_ACTION_NOT_SUPPORTED: Action not supported for this kind of dataset
ERR_DATASET_CSV_ROW_TOO_LARGE: Error in CSV file: Dataset row is too long to be processed
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_EXPORT_OUTPUT_TOO_LARGE: Export file size limit reached
ERR_FOLDER_INVALID_CONFIG: Invalid managed folder configuration
ERR_FOLDER_INVALID_PARTITIONING_CONFIG: Invalid folder partitioning configuration
ERR_FORMAT_BOUNDING_BOXES: Invalid format of column representing bounding boxes
ERR_FORMAT_LINE_TOO_LARGE: Line is too long to be processed
ERR_FORMAT_TYPE_MISSING: Dataset is missing a format type
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_FSPROVIDER_TOO_MANY_FILES: Attempted to enumerate too many files
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_JOB_INPUT_DATASET_NOT_READY_NO_FILES: Input dataset is not ready (no files found)
ERR_LICENSING_TRIAL_INTERNAL_ERROR: Internal error trying to get a trial token
ERR_LICENSING_TRIAL_STATUS_ERROR: Internal error trying to get a trial status
Remediation
ERR_METRIC_DATASET_COMPUTATION_FAILED: Metrics computation completely failed
ERR_METRIC_ENGINE_RUN_FAILED: One of the metrics engine failed to run
ERR_MISC_DISK_FULL: Disk is almost full
ERR_MISC_EIDB: Missing, locked, unreachable or corrupted internal database
ERR_MISC_ENOSPC: Out of disk space
ERR_MISC_EOPENF: Too many open files
ERR_ML_MODEL_DETAILS_OVERFLOW: Model details exceed size limit
ERR_ML_VERTICA_NOT_SUPPORTED: Vertica ML backend is no longer supported
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_MISSING_IN_CONTAINER_IMAGE: Plugin is missing in container image
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
ERR_RECIPE_CANNOT_CHECK_SCHEMA_CONSISTENCY_NEEDS_BUILD: Cannot compute output schema with an empty input dataset. Build the input dataset first.
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 dependency 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_DECRYPTION_FAILED: Decryption failed due to invalid HMAC
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_SYNAPSE_CSV_DELIMITER: Bad delimiter setup
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
INFO_RECIPE_POTENTIAL_FAST_PATH: Potential fast path configuration
INFO_RECIPE_IMPALA_POTENTIAL_FAST_PATH: Potential Impala fast path configuration
WARN_ACTIVITY_WAITING_K8S_CONTAINERSTARTING_CLOUD: Execution container is initializing
WARN_ACTIVITY_WAITING_K8S_POD_PENDING_CLOUD: Container will start soon
WARN_ACTIVITY_WAITING_K8S_QUOTA_EXCEEDED_CLOUD: You have exceeded your RAM and CPU quotas
WARN_ACTIVITY_WAITING_QUEUED_CLOUD: Your activity is queued
WARN_CLUSTERS_NONE_SELECTED_GLOBAL: No default cluster selected
WARN_CLUSTERS_NONE_SELECTED_PROJECT: No cluster selected in project
WARN_CONNECTION_HDFS_ACL_SUBDIRECTORY: subdirectory ACL synchronization mode
WARN_CONNECTION_NO_HADOOP_INTERFACE: no Hadoop interface set
WARN_CONNECTION_DATABRICKS_NO_AUTOFASTWRITE: automatic fast-write disabled
WARN_CONNECTION_SNOWFLAKE_NO_AUTOFASTWRITE: automatic fast-write disabled
WARN_CONNECTION_SPARK_NO_GROUP_WITH_DETAILS_READ_ACCESS: no groups allowed to read connection details
WARN_FOLDER_CONNECTION_TYPE_ERROR: Invalid connection linked to a managed folder
WARN_JOBS_MAX_OVER_MAX_ACTIVITIES: Jobs - Max jobs is over max activities
WARN_JOBS_MAX_TOO_HIGH: Jobs - Max value too high
WARN_JOBS_NO_LIMIT: Jobs - No limits set
WARN_JVM_CONFIG_XMX_IN_RED_ZONE: Sub optimal Xmx value
WARN_JVM_CONFIG_KERNEL_XMX_OVER_THRESHOLD: Xmx value for kernel over threshold
WARN_MISC_AUDIT_NO_LOG4J_LOCAL_TARGET: No Log4j local target
WARN_MISC_CODE_ENV_BUILTIN_MODIFIED: Built-in code env modified
WARN_MISC_CODE_ENV_DEPRECATED_INTERPRETER: Deprecated Python interpreter
WARN_MISC_CODE_ENV_USES_PYSPARK: pyspark installed in a code environment
WARN_MISC_DISK_MOUNT_TYPE: non recommended filesystem type
WARN_MISC_DISK_NOEXEC_FLAG: noexec flag
WARN_MISC_DISK_ROTATIONAL: Rotational hard drives
WARN_MISC_ENVVAR_SPECIAL_CHAR: Environment variables with special characters
WARN_MISC_EVENT_SERVER_NO_TARGET: No target
WARN_MISC_JDBC_JARS_CONFLICT: JDBC drivers - some JARs are prone to version conflicts
WARN_MISC_LARGE_INTERNAL_DB: internal runtime database is too large
WARN_PROJECT_LARGE_JOB_HISTORY: Projects - Too old or too many job logs
WARN_PROJECT_LARGE_SCENARIO_HISTORY: Projects - Too old or too many scenario run logs
WARN_PROJECT_LARGE_STREAMING_HISTORY: Projects - Too old or too many continuous activities logs
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
WARN_SPARK_NON_DISTRIBUTED_READ: Input dataset is read in a non-distributed way
WARN_SPARK_NON_DISTRIBUTED_WRITE: Output dataset is written in a non-distributed way
WARN_SPARK_UDFS_MAY_BE_BROKEN: Python UDFs may fail
WARN_SPARK_TASK_OOM: Some Spark tasks encountered out of memory
WARN_SPARK_TASK_DISKFULL: Some Spark tasks encountered disk space issues
WARN_SPARK_K8S_KILLED_EXECUTORS: Some Kubernetes executors were killed
WARN_SPARK_MISSING_DRIVER_TO_EXECUTOR_CONNECTIVITY: The Spark driver cannot call into the executors
WARN_SPARK_WITH_DATABRICKS_DATASET: Not leveraging Databricks compute
WARN_SECURITY_NO_CGROUPS: cgroups for resource control are not enabled
WARN_SECURITY_UIF_NOT_ENABLED: User Isolation Framework is not enabled
Undocumented error
Release notes
Other Documentation
Third-party acknowledgements
Dataiku DSS
You are viewing the documentation for version
13
of DSS.
»
Troubleshooting
»
Error codes
»
ERR_LICENSING_TRIAL_STATUS_ERROR: Internal error trying to get a trial status
Open page in a new tab
ERR_LICENSING_TRIAL_STATUS_ERROR: Internal error trying to get a trial status
¶
Dataiku failed to fetch the trial status of the instance.
Remediation
¶
Please contact Dataiku.