Vertica

Integration Details

This plugin extracts metadata for Tables and Views on Vertica.

This plugin is in beta and has only been tested on sample data on the Vertica database.

Concept Mapping

This ingestion source maps the following Source System Concepts to DataHub Concepts:

Source Concept	DataHub Concept	Notes
Vertica	Data Platform
Table	Dataset
View	Dataset

Metadata Ingestion Quickstart

For context on getting started with ingestion, check out our metadata ingestion guide.

Module vertica

Important Capabilities

Capability	Status	Notes
Domains	✅	Supported via the domain config field
Platform Instance	✅	Enabled by default

Install the Plugin

pip install 'acryl-datahub[vertica]'

Quickstart Recipe

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide

source:
  type: vertica
  config:
    # Coordinates
    host_port: localhost:5433
    database: DATABASE_NAME

    # Credentials
    username: "${VERTICA_USER}"
    password: "${VERTICA_PASSWORD}"

sink:
  # sink configs

Config Details

Options

Note that a . is used to denote nested fields in the YAML recipe.

View All Configuration Options

Field	Required	Type	Description	Default
env		string	The environment that all assets produced by this connector belong to	PROD
platform		string	The platform that this source connects to	None
platform_instance		string	The instance of the platform that all assets produced by this recipe belong to	None
options		Dict		{}
include_views		boolean	Whether views should be ingested.	True
include_tables		boolean	Whether tables should be ingested.	True
username		string	username	None
password		string	password	None
host_port	✅	string	host URL	None
database		string	database (catalog)	None
database_alias		string	Alias to apply to database when ingesting.	None
scheme		string		vertica+vertica_python
sqlalchemy_uri		string	URI of database to connect to. See https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls. Takes precedence over other connection parameters.	None
stateful_ingestion		SQLAlchemyStatefulIngestionConfig (see below for fields)
stateful_ingestion.enabled		boolean	The type of the ingestion state provider registered with datahub.	False
stateful_ingestion.max_checkpoint_state_size		integer	The maximum size of the checkpoint state in bytes. Default is 16MB	16777216
stateful_ingestion.state_provider		DynamicTypedStateProviderConfig (see below for fields)	The ingestion state provider configuration.
stateful_ingestion.state_provider.type	✅	string	The type of the state provider to use. For DataHub use datahub	None
stateful_ingestion.state_provider.config		Generic dict	The configuration required for initializing the state provider. Default: The datahub_api config if set at pipeline level. Otherwise, the default DatahubClientConfig. See the defaults (https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/src/datahub/ingestion/graph/client.py#L19).	None
stateful_ingestion.ignore_old_state		boolean	If set to True, ignores the previous checkpoint state.	False
stateful_ingestion.ignore_new_state		boolean	If set to True, ignores the current checkpoint state.	False
stateful_ingestion.remove_stale_metadata		boolean	Soft-deletes the tables and views that were found in the last successful run but missing in the current run with stateful_ingestion enabled.	True
schema_pattern		AllowDenyPattern (see below for fields)	Regex patterns for schemas to filter in ingestion. Specify regex to only match the schema name. e.g. to match all tables in schema analytics, use the regex 'analytics'	{'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 _.-]'}
schema_pattern.allow		Array of string	List of regex patterns to include in ingestion	['.*']
schema_pattern.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
schema_pattern.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
schema_pattern.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
table_pattern		AllowDenyPattern (see below for fields)	Regex patterns for tables to filter in ingestion. Specify regex to match the entire table name in database.schema.table format. e.g. to match all tables starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*'	{'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 _.-]'}
table_pattern.allow		Array of string	List of regex patterns to include in ingestion	['.*']
table_pattern.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
table_pattern.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
table_pattern.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
view_pattern		AllowDenyPattern (see below for fields)	Regex patterns for views to filter in ingestion. Note: Defaults to table_pattern if not specified. Specify regex to match the entire view name in database.schema.view format. e.g. to match all views starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*'	{'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 _.-]'}
view_pattern.allow		Array of string	List of regex patterns to include in ingestion	['.*']
view_pattern.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
view_pattern.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
view_pattern.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
profile_pattern		AllowDenyPattern (see below for fields)	Regex patterns to filter tables for profiling during ingestion. Allowed by the table_pattern.	{'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 _.-]'}
profile_pattern.allow		Array of string	List of regex patterns to include in ingestion	['.*']
profile_pattern.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
profile_pattern.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
profile_pattern.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
domain		Dict[str, AllowDenyPattern]	Attach domains to databases, schemas or tables during ingestion using regex patterns. Domain key can be a guid like urn:li:domain:ec428203-ce86-4db3-985d-5a8ee6df32ba or a string like "Marketing".) If you provide strings, then datahub will attempt to resolve this name to a guid, and will error out if this fails. There can be multiple domain keys specified.	{}
domain.key.allow		Array of string	List of regex patterns to include in ingestion	['.*']
domain.key.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
domain.key.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
domain.key.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
profiling		GEProfilingConfig (see below for fields)		{'enabled': False, 'limit': None, 'offset': None, 'reportdropped_profiles': False, 'turn_off_expensive_profiling_metrics': False, 'profile_table_level_only': False, 'include_field_null_count': True, 'include_field_min_value': True, 'include_field_max_value': True, 'include_field_mean_value': True, 'include_field_median_value': True, 'include_field_stddev_value': True, 'include_field_quantiles': False, 'include_field_distinct_value_frequencies': False, 'include_field_histogram': False, 'include_field_sample_values': True, 'allow_deny_patterns': {'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 .-]'}, 'max_number_of_fields_to_profile': None, 'profile_if_updated_since_days': 1, 'profile_table_size_limit': 1, 'profile_table_row_limit': 50000, 'max_workers': 10, 'query_combiner_enabled': True, 'catch_exceptions': True, 'partition_profiling_enabled': True, 'bigquery_temp_table_schema': None, 'partition_datetime': None}
profiling.enabled		boolean	Whether profiling should be done.	False
profiling.limit		integer	Max number of documents to profile. By default, profiles all documents.	None
profiling.offset		integer	Offset in documents to profile. By default, uses no offset.	None
profiling.report_dropped_profiles		boolean	If datasets which were not profiled are reported in source report or not. Set to True for debugging purposes.	False
profiling.turn_off_expensive_profiling_metrics		boolean	Whether to turn off expensive profiling or not. This turns off profiling for quantiles, distinct_value_frequencies, histogram & sample_values. This also limits maximum number of fields being profiled to 10.	False
profiling.profile_table_level_only		boolean	Whether to perform profiling at table-level only, or include column-level profiling as well.	False
profiling.include_field_null_count		boolean	Whether to profile for the number of nulls for each column.	True
profiling.include_field_min_value		boolean	Whether to profile for the min value of numeric columns.	True
profiling.include_field_max_value		boolean	Whether to profile for the max value of numeric columns.	True
profiling.include_field_mean_value		boolean	Whether to profile for the mean value of numeric columns.	True
profiling.include_field_median_value		boolean	Whether to profile for the median value of numeric columns.	True
profiling.include_field_stddev_value		boolean	Whether to profile for the standard deviation of numeric columns.	True
profiling.include_field_quantiles		boolean	Whether to profile for the quantiles of numeric columns.	False
profiling.include_field_distinct_value_frequencies		boolean	Whether to profile for distinct value frequencies.	False
profiling.include_field_histogram		boolean	Whether to profile for the histogram for numeric fields.	False
profiling.include_field_sample_values		boolean	Whether to profile for the sample values for all columns.	True
profiling.allow_deny_patterns		AllowDenyPattern (see below for fields)	regex patterns for filtering of tables or table columns to profile.	{'allow': ['.*'], 'deny': [], 'ignoreCase': True, 'alphabet': '[A-Za-z0-9 _.-]'}
profiling.allow_deny_patterns.allow		Array of string	List of regex patterns to include in ingestion	['.*']
profiling.allow_deny_patterns.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
profiling.allow_deny_patterns.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
profiling.allow_deny_patterns.alphabet		string	Allowed alphabets pattern	[A-Za-z0-9 _.-]
profiling.max_number_of_fields_to_profile		integer	A positive integer that specifies the maximum number of columns to profile for any table. None implies all columns. The cost of profiling goes up significantly as the number of columns to profile goes up.	None
profiling.profile_if_updated_since_days		number	Profile table only if it has been updated since these many number of days. If set to null, no constraint of last modified time for tables to profile. Supported only in Snowflake and BigQuery.	1
profiling.profile_table_size_limit		integer	Profile tables only if their size is less then specified GBs. If set to null, no limit on the size of tables to profile. Supported only in BigQuery	1
profiling.profile_table_row_limit		integer	Profile tables only if their row count is less then specified count. If set to null, no limit on the row count of tables to profile. Supported only in BigQuery	50000
profiling.max_workers		integer	Number of worker threads to use for profiling. Set to 1 to disable.	10
profiling.query_combiner_enabled		boolean	This feature is still experimental and can be disabled if it causes issues. Reduces the total number of queries issued and speeds up profiling by dynamically combining SQL queries where possible.	True
profiling.catch_exceptions		boolean		True
profiling.partition_profiling_enabled		boolean		True
profiling.bigquery_temp_table_schema		string	On bigquery for profiling partitioned tables needs to create temporary views. You have to define a dataset where these will be created. Views will be cleaned up after profiler runs. (Great expectation tech details about this (https://legacy.docs.greatexpectations.io/en/0.9.0/reference/integrations/bigquery.html#custom-queries-with-sql-datasource).	None
profiling.partition_datetime		string	For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this.	None

Schema

The JSONSchema for this configuration is inlined below.

{
  "title": "VerticaConfig",
  "description": "Base configuration class for stateful ingestion for source configs to inherit from.",
  "type": "object",
  "properties": {
    "env": {
      "title": "Env",
      "description": "The environment that all assets produced by this connector belong to",
      "default": "PROD",
      "type": "string"
    },
    "platform": {
      "title": "Platform",
      "description": "The platform that this source connects to",
      "type": "string"
    },
    "platform_instance": {
      "title": "Platform Instance",
      "description": "The instance of the platform that all assets produced by this recipe belong to",
      "type": "string"
    },
    "stateful_ingestion": {
      "$ref": "#/definitions/SQLAlchemyStatefulIngestionConfig"
    },
    "options": {
      "title": "Options",
      "default": {},
      "type": "object"
    },
    "schema_pattern": {
      "title": "Schema Pattern",
      "description": "Regex patterns for schemas to filter in ingestion. Specify regex to only match the schema name. e.g. to match all tables in schema analytics, use the regex 'analytics'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true,
        "alphabet": "[A-Za-z0-9 _.-]"
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "table_pattern": {
      "title": "Table Pattern",
      "description": "Regex patterns for tables to filter in ingestion. Specify regex to match the entire table name in database.schema.table format. e.g. to match all tables starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true,
        "alphabet": "[A-Za-z0-9 _.-]"
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "view_pattern": {
      "title": "View Pattern",
      "description": "Regex patterns for views to filter in ingestion. Note: Defaults to table_pattern if not specified. Specify regex to match the entire view name in database.schema.view format. e.g. to match all views starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true,
        "alphabet": "[A-Za-z0-9 _.-]"
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "profile_pattern": {
      "title": "Profile Pattern",
      "description": "Regex patterns to filter tables for profiling during ingestion. Allowed by the `table_pattern`.",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true,
        "alphabet": "[A-Za-z0-9 _.-]"
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "domain": {
      "title": "Domain",
      "description": "Attach domains to databases, schemas or tables during ingestion using regex patterns. Domain key can be a guid like *urn:li:domain:ec428203-ce86-4db3-985d-5a8ee6df32ba* or a string like \"Marketing\".) If you provide strings, then datahub will attempt to resolve this name to a guid, and will error out if this fails. There can be multiple domain keys specified.",
      "default": {},
      "type": "object",
      "additionalProperties": {
        "$ref": "#/definitions/AllowDenyPattern"
      }
    },
    "include_views": {
      "title": "Include Views",
      "description": "Whether views should be ingested.",
      "default": true,
      "type": "boolean"
    },
    "include_tables": {
      "title": "Include Tables",
      "description": "Whether tables should be ingested.",
      "default": true,
      "type": "boolean"
    },
    "profiling": {
      "title": "Profiling",
      "default": {
        "enabled": false,
        "limit": null,
        "offset": null,
        "report_dropped_profiles": false,
        "turn_off_expensive_profiling_metrics": false,
        "profile_table_level_only": false,
        "include_field_null_count": true,
        "include_field_min_value": true,
        "include_field_max_value": true,
        "include_field_mean_value": true,
        "include_field_median_value": true,
        "include_field_stddev_value": true,
        "include_field_quantiles": false,
        "include_field_distinct_value_frequencies": false,
        "include_field_histogram": false,
        "include_field_sample_values": true,
        "allow_deny_patterns": {
          "allow": [
            ".*"
          ],
          "deny": [],
          "ignoreCase": true,
          "alphabet": "[A-Za-z0-9 _.-]"
        },
        "max_number_of_fields_to_profile": null,
        "profile_if_updated_since_days": 1,
        "profile_table_size_limit": 1,
        "profile_table_row_limit": 50000,
        "max_workers": 10,
        "query_combiner_enabled": true,
        "catch_exceptions": true,
        "partition_profiling_enabled": true,
        "bigquery_temp_table_schema": null,
        "partition_datetime": null
      },
      "allOf": [
        {
          "$ref": "#/definitions/GEProfilingConfig"
        }
      ]
    },
    "username": {
      "title": "Username",
      "description": "username",
      "type": "string"
    },
    "password": {
      "title": "Password",
      "description": "password",
      "type": "string",
      "writeOnly": true,
      "format": "password"
    },
    "host_port": {
      "title": "Host Port",
      "description": "host URL",
      "type": "string"
    },
    "database": {
      "title": "Database",
      "description": "database (catalog)",
      "type": "string"
    },
    "database_alias": {
      "title": "Database Alias",
      "description": "Alias to apply to database when ingesting.",
      "type": "string"
    },
    "scheme": {
      "title": "Scheme",
      "default": "vertica+vertica_python",
      "type": "string"
    },
    "sqlalchemy_uri": {
      "title": "Sqlalchemy Uri",
      "description": "URI of database to connect to. See https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls. Takes precedence over other connection parameters.",
      "type": "string"
    }
  },
  "required": [
    "host_port"
  ],
  "additionalProperties": false,
  "definitions": {
    "DynamicTypedStateProviderConfig": {
      "title": "DynamicTypedStateProviderConfig",
      "type": "object",
      "properties": {
        "type": {
          "title": "Type",
          "description": "The type of the state provider to use. For DataHub use `datahub`",
          "type": "string"
        },
        "config": {
          "title": "Config",
          "description": "The configuration required for initializing the state provider. Default: The datahub_api config if set at pipeline level. Otherwise, the default DatahubClientConfig. See the defaults (https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/src/datahub/ingestion/graph/client.py#L19)."
        }
      },
      "required": [
        "type"
      ],
      "additionalProperties": false
    },
    "SQLAlchemyStatefulIngestionConfig": {
      "title": "SQLAlchemyStatefulIngestionConfig",
      "description": "Specialization of basic StatefulIngestionConfig to adding custom config.\nThis will be used to override the stateful_ingestion config param of StatefulIngestionConfigBase\nin the SQLAlchemyConfig.",
      "type": "object",
      "properties": {
        "enabled": {
          "title": "Enabled",
          "description": "The type of the ingestion state provider registered with datahub.",
          "default": false,
          "type": "boolean"
        },
        "max_checkpoint_state_size": {
          "title": "Max Checkpoint State Size",
          "description": "The maximum size of the checkpoint state in bytes. Default is 16MB",
          "default": 16777216,
          "exclusiveMinimum": 0,
          "type": "integer"
        },
        "state_provider": {
          "title": "State Provider",
          "description": "The ingestion state provider configuration.",
          "allOf": [
            {
              "$ref": "#/definitions/DynamicTypedStateProviderConfig"
            }
          ]
        },
        "ignore_old_state": {
          "title": "Ignore Old State",
          "description": "If set to True, ignores the previous checkpoint state.",
          "default": false,
          "type": "boolean"
        },
        "ignore_new_state": {
          "title": "Ignore New State",
          "description": "If set to True, ignores the current checkpoint state.",
          "default": false,
          "type": "boolean"
        },
        "remove_stale_metadata": {
          "title": "Remove Stale Metadata",
          "description": "Soft-deletes the tables and views that were found in the last successful run but missing in the current run with stateful_ingestion enabled.",
          "default": true,
          "type": "boolean"
        }
      },
      "additionalProperties": false
    },
    "AllowDenyPattern": {
      "title": "AllowDenyPattern",
      "description": "A class to store allow deny regexes",
      "type": "object",
      "properties": {
        "allow": {
          "title": "Allow",
          "description": "List of regex patterns to include in ingestion",
          "default": [
            ".*"
          ],
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "deny": {
          "title": "Deny",
          "description": "List of regex patterns to exclude from ingestion.",
          "default": [],
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "ignoreCase": {
          "title": "Ignorecase",
          "description": "Whether to ignore case sensitivity during pattern matching.",
          "default": true,
          "type": "boolean"
        },
        "alphabet": {
          "title": "Alphabet",
          "description": "Allowed alphabets pattern",
          "default": "[A-Za-z0-9 _.-]",
          "type": "string"
        }
      },
      "additionalProperties": false
    },
    "GEProfilingConfig": {
      "title": "GEProfilingConfig",
      "type": "object",
      "properties": {
        "enabled": {
          "title": "Enabled",
          "description": "Whether profiling should be done.",
          "default": false,
          "type": "boolean"
        },
        "limit": {
          "title": "Limit",
          "description": "Max number of documents to profile. By default, profiles all documents.",
          "type": "integer"
        },
        "offset": {
          "title": "Offset",
          "description": "Offset in documents to profile. By default, uses no offset.",
          "type": "integer"
        },
        "report_dropped_profiles": {
          "title": "Report Dropped Profiles",
          "description": "If datasets which were not profiled are reported in source report or not. Set to `True` for debugging purposes.",
          "default": false,
          "type": "boolean"
        },
        "turn_off_expensive_profiling_metrics": {
          "title": "Turn Off Expensive Profiling Metrics",
          "description": "Whether to turn off expensive profiling or not. This turns off profiling for quantiles, distinct_value_frequencies, histogram & sample_values. This also limits maximum number of fields being profiled to 10.",
          "default": false,
          "type": "boolean"
        },
        "profile_table_level_only": {
          "title": "Profile Table Level Only",
          "description": "Whether to perform profiling at table-level only, or include column-level profiling as well.",
          "default": false,
          "type": "boolean"
        },
        "include_field_null_count": {
          "title": "Include Field Null Count",
          "description": "Whether to profile for the number of nulls for each column.",
          "default": true,
          "type": "boolean"
        },
        "include_field_min_value": {
          "title": "Include Field Min Value",
          "description": "Whether to profile for the min value of numeric columns.",
          "default": true,
          "type": "boolean"
        },
        "include_field_max_value": {
          "title": "Include Field Max Value",
          "description": "Whether to profile for the max value of numeric columns.",
          "default": true,
          "type": "boolean"
        },
        "include_field_mean_value": {
          "title": "Include Field Mean Value",
          "description": "Whether to profile for the mean value of numeric columns.",
          "default": true,
          "type": "boolean"
        },
        "include_field_median_value": {
          "title": "Include Field Median Value",
          "description": "Whether to profile for the median value of numeric columns.",
          "default": true,
          "type": "boolean"
        },
        "include_field_stddev_value": {
          "title": "Include Field Stddev Value",
          "description": "Whether to profile for the standard deviation of numeric columns.",
          "default": true,
          "type": "boolean"
        },
        "include_field_quantiles": {
          "title": "Include Field Quantiles",
          "description": "Whether to profile for the quantiles of numeric columns.",
          "default": false,
          "type": "boolean"
        },
        "include_field_distinct_value_frequencies": {
          "title": "Include Field Distinct Value Frequencies",
          "description": "Whether to profile for distinct value frequencies.",
          "default": false,
          "type": "boolean"
        },
        "include_field_histogram": {
          "title": "Include Field Histogram",
          "description": "Whether to profile for the histogram for numeric fields.",
          "default": false,
          "type": "boolean"
        },
        "include_field_sample_values": {
          "title": "Include Field Sample Values",
          "description": "Whether to profile for the sample values for all columns.",
          "default": true,
          "type": "boolean"
        },
        "allow_deny_patterns": {
          "title": "Allow Deny Patterns",
          "description": "regex patterns for filtering of tables or table columns to profile.",
          "default": {
            "allow": [
              ".*"
            ],
            "deny": [],
            "ignoreCase": true,
            "alphabet": "[A-Za-z0-9 _.-]"
          },
          "allOf": [
            {
              "$ref": "#/definitions/AllowDenyPattern"
            }
          ]
        },
        "max_number_of_fields_to_profile": {
          "title": "Max Number Of Fields To Profile",
          "description": "A positive integer that specifies the maximum number of columns to profile for any table. `None` implies all columns. The cost of profiling goes up significantly as the number of columns to profile goes up.",
          "exclusiveMinimum": 0,
          "type": "integer"
        },
        "profile_if_updated_since_days": {
          "title": "Profile If Updated Since Days",
          "description": "Profile table only if it has been updated since these many number of days. If set to `null`, no constraint of last modified time for tables to profile. Supported only in `Snowflake` and `BigQuery`.",
          "default": 1,
          "exclusiveMinimum": 0,
          "type": "number"
        },
        "profile_table_size_limit": {
          "title": "Profile Table Size Limit",
          "description": "Profile tables only if their size is less then specified GBs. If set to `null`, no limit on the size of tables to profile. Supported only in `BigQuery`",
          "default": 1,
          "type": "integer"
        },
        "profile_table_row_limit": {
          "title": "Profile Table Row Limit",
          "description": "Profile tables only if their row count is less then specified count. If set to `null`, no limit on the row count of tables to profile. Supported only in `BigQuery`",
          "default": 50000,
          "type": "integer"
        },
        "max_workers": {
          "title": "Max Workers",
          "description": "Number of worker threads to use for profiling. Set to 1 to disable.",
          "default": 10,
          "type": "integer"
        },
        "query_combiner_enabled": {
          "title": "Query Combiner Enabled",
          "description": "*This feature is still experimental and can be disabled if it causes issues.* Reduces the total number of queries issued and speeds up profiling by dynamically combining SQL queries where possible.",
          "default": true,
          "type": "boolean"
        },
        "catch_exceptions": {
          "title": "Catch Exceptions",
          "default": true,
          "type": "boolean"
        },
        "partition_profiling_enabled": {
          "title": "Partition Profiling Enabled",
          "default": true,
          "type": "boolean"
        },
        "bigquery_temp_table_schema": {
          "title": "Bigquery Temp Table Schema",
          "description": "On bigquery for profiling partitioned tables needs to create temporary views. You have to define a dataset where these will be created. Views will be cleaned up after profiler runs. (Great expectation tech details about this (https://legacy.docs.greatexpectations.io/en/0.9.0/reference/integrations/bigquery.html#custom-queries-with-sql-datasource).",
          "type": "string"
        },
        "partition_datetime": {
          "title": "Partition Datetime",
          "description": "For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this.",
          "type": "string",
          "format": "date-time"
        }
      },
      "additionalProperties": false
    }
  }
}

Prerequisites

In order to ingest metadata from Vertica, you will need:

• Python Version 3.6+
• Vertica Server Version 10.1.1-0 and avobe. It may also work for older versions.
• Vertica Credentials (Username/Password)

Code Coordinates

• Class Name: datahub.ingestion.source.sql.vertica.VerticaSource
• Browse on GitHub

Questions

If you've got any questions on configuring ingestion for Vertica, feel free to ping us on our Slack