Presto on Hive

Module presto-on-hive

Important Capabilities

Capability	Status	Notes
Data Profiling	✅	Optionally enabled via configuration
Detect Deleted Entities	✅	Enabled via stateful ingestion

This plugin extracts the following:

• Metadata for Presto views and Hive tables (external / managed)
• Column types associated with each table / view
• Detailed table / view property info

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[presto-on-hive]'

Starter 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: presto-on-hive
  config:
    # Hive metastore DB connection
    host_port: localhost:5432
    database: metastore

    # specify the schema where metastore tables reside
    schema_pattern:
      allow:
        - "^public"

    # credentials
    username: user # optional
    password: pass # optional

    #scheme: 'postgresql+psycopg2' # set this if metastore db is using postgres
    #scheme: 'mysql+pymysql' # set this if metastore db is using mysql, default if unset

    # set this to have advanced filters on what to ingest
    #views_where_clause_suffix: AND d."name" in ('db1')
    #tables_where_clause_suffix: AND d."name" in ('db1')

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	Notes
database	string	database (catalog)	None
database_alias	string	Alias to apply to database when ingesting.	None
host_port	string	Host URL and port to connect to. Example: localhost:3306	localhost:3306
include_catalog_name_in_ids	boolean	Add the Presto catalog name (e.g. hive) to the generated dataset urns. urn:li:dataset:(urn:li:dataPlatform:hive,hive.user.logging_events,PROD) versus urn:li:dataset:(urn:li:dataPlatform:hive,user.logging_events,PROD)	None
include_table_location_lineage	boolean	If the source supports it, include table lineage to the underlying storage location.	True
include_tables	boolean	Whether tables should be ingested.	True
include_views	boolean	Whether views should be ingested.	True
ingestion_job_id	string		None
metastore_db_name	string	Name of the Hive metastore's database (usually: metastore). For backward compatibility, if this field is not provided, the database field will be used. If both the 'database' and 'metastore_db_name' fields are set then the 'database' field will be used to filter the hive/presto/trino database	None
mode	Enum	The ingested data will be stored under this platform. Valid options: ['hive', 'presto', 'presto-on-hive', 'trino']	presto-on-hive
options	object	Any options specified here will be passed to SQLAlchemy's create_engine as kwargs. See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details.	None
password	string(password)	password	None
platform_instance	string	The instance of the platform that all assets produced by this recipe belong to	None
schemas_where_clause_suffix	string	Where clause to specify what Hive schemas should be ingested.	None
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
tables_where_clause_suffix	string	Where clause to specify what Hive tables should be ingested.	None
use_catalog_subtype	boolean	Container Subtype name to be 'Database' or 'Catalog' Valid options: ['True', 'False']	True
use_dataset_pascalcase_subtype	boolean	Dataset Subtype name to be 'Table' or 'View' Valid options: ['True', 'False']	None
username	string	username	None
views_where_clause_suffix	string	Where clause to specify what Presto views should be ingested.	None
env	string	The environment that all assets produced by this connector belong to	PROD
database_pattern	AllowDenyPattern	Regex patterns for hive/presto database to filter in ingestion. Specify regex to only match the database name. e.g. to match all tables in database analytics, use the regex 'analytics'	{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
database_pattern.allow	array(string)		None
database_pattern.deny	array(string)		None
database_pattern.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
domain	map(str,AllowDenyPattern)	A class to store allow deny regexes	None
domain.key.allow	array(string)		None
domain.key.deny	array(string)		None
domain.key.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
profile_pattern	AllowDenyPattern	Regex patterns to filter tables (or specific columns) for profiling during ingestion. Note that only tables allowed by the table_pattern will be considered.	{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
profile_pattern.allow	array(string)		None
profile_pattern.deny	array(string)		None
profile_pattern.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
schema_pattern	AllowDenyPattern	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}
schema_pattern.allow	array(string)		None
schema_pattern.deny	array(string)		None
schema_pattern.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
table_pattern	AllowDenyPattern	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}
table_pattern.allow	array(string)		None
table_pattern.deny	array(string)		None
table_pattern.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
view_pattern	AllowDenyPattern	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}
view_pattern.allow	array(string)		None
view_pattern.deny	array(string)		None
view_pattern.ignoreCase	boolean	Whether to ignore case sensitivity during pattern matching.	True
profiling	GEProfilingConfig		{'enabled': False, 'limit': None, 'offset': None, 'report_dropped_profiles': False, 'turn_off_expensive_profiling_metrics': False, 'profile_table_level_only': False, 'include_field_null_count': True, 'include_field_distinct_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, 'field_sample_values_limit': 20, 'max_number_of_fields_to_profile': None, 'profile_if_updated_since_days': None, 'profile_table_size_limit': 5, 'profile_table_row_limit': 5000000, 'profile_table_row_count_estimate_only': False, 'max_workers': 10, 'query_combiner_enabled': True, 'catch_exceptions': True, 'partition_profiling_enabled': True, 'partition_datetime': None}
profiling.catch_exceptions	boolean		True
profiling.enabled	boolean	Whether profiling should be done.	None
profiling.field_sample_values_limit	integer	Upper limit for number of sample values to collect for all columns.	20
profiling.include_field_distinct_count	boolean	Whether to profile for the number of distinct values for each column.	True
profiling.include_field_distinct_value_frequencies	boolean	Whether to profile for distinct value frequencies.	None
profiling.include_field_histogram	boolean	Whether to profile for the histogram for numeric fields.	None
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_min_value	boolean	Whether to profile for the min value of numeric columns.	True
profiling.include_field_null_count	boolean	Whether to profile for the number of nulls for each column.	True
profiling.include_field_quantiles	boolean	Whether to profile for the quantiles of numeric columns.	None
profiling.include_field_sample_values	boolean	Whether to profile for the sample values for all columns.	True
profiling.include_field_stddev_value	boolean	Whether to profile for the standard deviation of numeric columns.	True
profiling.limit	integer	Max number of documents to profile. By default, profiles all documents.	None
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.max_workers	integer	Number of worker threads to use for profiling. Set to 1 to disable.	10
profiling.offset	integer	Offset in documents to profile. By default, uses no offset.	None
profiling.partition_datetime	string(date-time)	For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this.	None
profiling.partition_profiling_enabled	boolean		True
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.	None
profiling.profile_table_level_only	boolean	Whether to perform profiling at table-level only, or include column-level profiling as well.	None
profiling.profile_table_row_count_estimate_only	boolean	Use an approximate query for row count. This will be much faster but slightly less accurate. Only supported for Postgres.	None
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 snowflake and BigQuery	5000000
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 snowflake and BigQuery	5
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.report_dropped_profiles	boolean	Whether to report datasets or dataset columns which were not profiled. Set to True for debugging purposes.	None
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.	None
stateful_ingestion	StatefulStaleMetadataRemovalConfig	Base specialized config for Stateful Ingestion with stale metadata removal capability.	None
stateful_ingestion.enabled	boolean	The type of the ingestion state provider registered with datahub.	None
stateful_ingestion.ignore_new_state	boolean	If set to True, ignores the current checkpoint state.	None
stateful_ingestion.ignore_old_state	boolean	If set to True, ignores the previous checkpoint state.	None
stateful_ingestion.remove_stale_metadata	boolean	Soft-deletes the entities present in the last successful run but missing in the current run with stateful_ingestion enabled.	True

Schema

The JSONSchema for this configuration is inlined below.

{
  "title": "PrestoOnHiveConfig",
  "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_instance": {
      "title": "Platform Instance",
      "description": "The instance of the platform that all assets produced by this recipe belong to",
      "type": "string"
    },
    "stateful_ingestion": {
      "$ref": "#/definitions/StatefulStaleMetadataRemovalConfig"
    },
    "options": {
      "title": "Options",
      "description": "Any options specified here will be passed to SQLAlchemy's create_engine as kwargs. See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details.",
      "type": "object"
    },
    "schema_pattern": {
      "title": "Schema Pattern",
      "description": "Regex patterns for schemas to filter in ingestion. Specify regex to only match the schema name. e.g. to match all tables in schema analytics, use the regex 'analytics'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true
      },
      "allOf": [
        {
          "$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
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "view_pattern": {
      "title": "View Pattern",
      "description": "Regex patterns for views to filter in ingestion. Note: Defaults to table_pattern if not specified. Specify regex to match the entire view name in database.schema.view format. e.g. to match all views starting with customer in Customer database and public schema, use the regex 'Customer.public.customer.*'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "profile_pattern": {
      "title": "Profile Pattern",
      "description": "Regex patterns to filter tables (or specific columns) for profiling during ingestion. Note that only tables allowed by the `table_pattern` will be considered.",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true
      },
      "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"
    },
    "include_table_location_lineage": {
      "title": "Include Table Location Lineage",
      "description": "If the source supports it, include table lineage to the underlying storage location.",
      "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_distinct_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,
        "field_sample_values_limit": 20,
        "max_number_of_fields_to_profile": null,
        "profile_if_updated_since_days": null,
        "profile_table_size_limit": 5,
        "profile_table_row_limit": 5000000,
        "profile_table_row_count_estimate_only": false,
        "max_workers": 10,
        "query_combiner_enabled": true,
        "catch_exceptions": true,
        "partition_profiling_enabled": true,
        "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 and port to connect to. Example: localhost:3306",
      "default": "localhost:3306",
      "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"
    },
    "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"
    },
    "views_where_clause_suffix": {
      "title": "Views Where Clause Suffix",
      "description": "Where clause to specify what Presto views should be ingested.",
      "default": "",
      "type": "string"
    },
    "tables_where_clause_suffix": {
      "title": "Tables Where Clause Suffix",
      "description": "Where clause to specify what Hive tables should be ingested.",
      "default": "",
      "type": "string"
    },
    "schemas_where_clause_suffix": {
      "title": "Schemas Where Clause Suffix",
      "description": "Where clause to specify what Hive schemas should be ingested.",
      "default": "",
      "type": "string"
    },
    "ingestion_job_id": {
      "title": "Ingestion Job Id",
      "default": "",
      "type": "string"
    },
    "database_pattern": {
      "title": "Database Pattern",
      "description": "Regex patterns for hive/presto database to filter in ingestion. Specify regex to only match the database name. e.g. to match all tables in database analytics, use the regex 'analytics'",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "metastore_db_name": {
      "title": "Metastore Db Name",
      "description": "Name of the Hive metastore's database (usually: metastore). For backward compatibility, if this field is not provided, the database field will be used. If both the 'database' and 'metastore_db_name' fields are set then the 'database' field will be used to filter the hive/presto/trino database",
      "type": "string"
    },
    "mode": {
      "description": "The ingested data will be stored under this platform. Valid options: ['hive', 'presto', 'presto-on-hive', 'trino']",
      "default": "presto-on-hive",
      "allOf": [
        {
          "$ref": "#/definitions/PrestoOnHiveConfigMode"
        }
      ]
    },
    "use_catalog_subtype": {
      "title": "Use Catalog Subtype",
      "description": "Container Subtype name to be 'Database' or 'Catalog' Valid options: ['True', 'False']",
      "default": true,
      "type": "boolean"
    },
    "use_dataset_pascalcase_subtype": {
      "title": "Use Dataset Pascalcase Subtype",
      "description": "Dataset Subtype name to be 'Table' or 'View' Valid options: ['True', 'False']",
      "default": false,
      "type": "boolean"
    },
    "include_catalog_name_in_ids": {
      "title": "Include Catalog Name In Ids",
      "description": "Add the Presto catalog name (e.g. hive) to the generated dataset urns. `urn:li:dataset:(urn:li:dataPlatform:hive,hive.user.logging_events,PROD)` versus `urn:li:dataset:(urn:li:dataPlatform:hive,user.logging_events,PROD)`",
      "default": false,
      "type": "boolean"
    }
  },
  "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
    },
    "StatefulStaleMetadataRemovalConfig": {
      "title": "StatefulStaleMetadataRemovalConfig",
      "description": "Base specialized config for Stateful Ingestion with stale metadata removal capability.",
      "type": "object",
      "properties": {
        "enabled": {
          "title": "Enabled",
          "description": "The type of the ingestion state provider registered with datahub.",
          "default": false,
          "type": "boolean"
        },
        "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 entities present 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"
        }
      },
      "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": "Whether to report datasets or dataset columns which were not profiled. 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_distinct_count": {
          "title": "Include Field Distinct Count",
          "description": "Whether to profile for the number of distinct values 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"
        },
        "field_sample_values_limit": {
          "title": "Field Sample Values Limit",
          "description": "Upper limit for number of sample values to collect for all columns.",
          "default": 20,
          "type": "integer"
        },
        "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`.",
          "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 `snowflake` and `BigQuery`",
          "default": 5,
          "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 `snowflake` and `BigQuery`",
          "default": 5000000,
          "type": "integer"
        },
        "profile_table_row_count_estimate_only": {
          "title": "Profile Table Row Count Estimate Only",
          "description": "Use an approximate query for row count. This will be much faster but slightly less accurate. Only supported for Postgres. ",
          "default": false,
          "type": "boolean"
        },
        "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"
        },
        "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
    },
    "PrestoOnHiveConfigMode": {
      "title": "PrestoOnHiveConfigMode",
      "description": "An enumeration.",
      "enum": [
        "hive",
        "presto",
        "presto-on-hive",
        "trino"
      ],
      "type": "string"
    }
  }
}

Code Coordinates

• Class Name: datahub.ingestion.source.sql.presto_on_hive.PrestoOnHiveSource
• Browse on GitHub

Questions

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