Redshift

There are 2 sources that provide integration with Redshift

Source Module	Documentation
redshift	This plugin extracts the following: Metadata for databases, schemas, views and tables Column types associated with each table Also supports PostGIS extensions Table, row, and column statistics via optional SQL profiling Table lineage tip You can also get fine-grained usage statistics for Redshift using the redshift-usage source described below. Prerequisites This source needs to access system tables that require extra permissions. To grant these permissions, please alter your datahub Redshift user the following way: ALTER USER datahub_user WITH SYSLOG ACCESS UNRESTRICTED; GRANT SELECT ON pg_catalog.svv_table_info to datahub_user; GRANT SELECT ON pg_catalog.svl_user_info to datahub_user; note Giving a user unrestricted access to system tables gives the user visibility to data generated by other users. For example, STL_QUERY and STL_QUERYTEXT contain the full text of INSERT, UPDATE, and DELETE statements. Lineage There are multiple lineage collector implementations as Redshift does not support table lineage out of the box. stl_scan_based The stl_scan based collector uses Redshift's stl_insert and stl_scan system tables to discover lineage between tables. Pros: Fast Reliable Cons: Does not work with Spectrum/external tables because those scans do not show up in stl_scan table. If a table is depending on a view then the view won't be listed as dependency. Instead the table will be connected with the view's dependencies. sql_based The sql_based based collector uses Redshift's stl_insert to discover all the insert queries and uses sql parsing to discover the dependecies. Pros: Works with Spectrum tables Views are connected properly if a table depends on it Cons: Slow. Less reliable as the query parser can fail on certain queries mixed Using both collector above and first applying the sql based and then the stl_scan based one. Pros: Works with Spectrum tables Views are connected properly if a table depends on it A bit more reliable than the sql_based one only Cons: Slow May be incorrect at times as the query parser can fail on certain queries note The redshift stl redshift tables which are used for getting data lineage only retain approximately two to five days of log history. This means you cannot extract lineage from queries issued outside that window. Read more...
redshift-usage	This plugin extracts usage statistics for datasets in Amazon Redshift. Note: Usage information is computed by querying the following system tables - stl_scan svv_table_info stl_query svl_user_info To grant access this plugin for all system tables, please alter your datahub Redshift user the following way: ALTER USER datahub_user WITH SYSLOG ACCESS UNRESTRICTED; This plugin has the below functionalities - For a specific dataset this plugin ingests the following statistics - top n queries. top users. Aggregation of these statistics into buckets, by day or hour granularity. note This source only does usage statistics. To get the tables, views, and schemas in your Redshift warehouse, ingest using the redshift source described above. note Redshift system tables have some latency in getting data from queries. In addition, these tables only maintain logs for 2-5 days. You can find more information from the official documentation here. Read more...

To get all metadata from Redshift you need to use two plugins redshift and redshift-usage. Both of them are described in this page. These will require 2 separate recipes. We understand this is not ideal and we plan to make this easier in the future.

Module redshift

Important Capabilities

Capability	Status	Notes
Data Profiling	✅	Optionally enabled via configuration
Dataset Usage	❌	Not provided by this module, use redshift-usage for that.
Descriptions	✅	Enabled by default
Detect Deleted Entities	✅	Enabled via stateful ingestion
Domains	✅	Supported via the domain config field
Platform Instance	✅	Enabled by default
Table-Level Lineage	✅	Optionally enabled via configuration

This plugin extracts the following:

• Metadata for databases, schemas, views and tables
• Column types associated with each table
• Also supports PostGIS extensions
• Table, row, and column statistics via optional SQL profiling
• Table lineage

tip

You can also get fine-grained usage statistics for Redshift using the redshift-usage source described below.

Prerequisites

This source needs to access system tables that require extra permissions. To grant these permissions, please alter your datahub Redshift user the following way:

ALTER USER datahub_user WITH SYSLOG ACCESS UNRESTRICTED;
GRANT SELECT ON pg_catalog.svv_table_info to datahub_user;
GRANT SELECT ON pg_catalog.svl_user_info to datahub_user;

note

Giving a user unrestricted access to system tables gives the user visibility to data generated by other users. For example, STL_QUERY and STL_QUERYTEXT contain the full text of INSERT, UPDATE, and DELETE statements.

Lineage

There are multiple lineage collector implementations as Redshift does not support table lineage out of the box.

stl_scan_based

The stl_scan based collector uses Redshift's stl_insert and stl_scan system tables to discover lineage between tables. Pros:

• Fast
• Reliable

Cons:

• Does not work with Spectrum/external tables because those scans do not show up in stl_scan table.
• If a table is depending on a view then the view won't be listed as dependency. Instead the table will be connected with the view's dependencies.

sql_based

The sql_based based collector uses Redshift's stl_insert to discover all the insert queries and uses sql parsing to discover the dependecies.

Pros:

• Works with Spectrum tables
• Views are connected properly if a table depends on it

Cons:

• Slow.
• Less reliable as the query parser can fail on certain queries

mixed

Using both collector above and first applying the sql based and then the stl_scan based one.

Pros:

• Works with Spectrum tables
• Views are connected properly if a table depends on it
• A bit more reliable than the sql_based one only

Cons:

• Slow
• May be incorrect at times as the query parser can fail on certain queries

note

The redshift stl redshift tables which are used for getting data lineage only retain approximately two to five days of log history. This means you cannot extract lineage from queries issued outside that window.

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[redshift]'

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: redshift
  config:
    # Coordinates
    host_port: example.something.us-west-2.redshift.amazonaws.com:5439
    database: DemoDatabase

    # Credentials
    username: user
    password: pass

    # Options
    options:
      # driver_option: some-option

    include_views: True # whether to include views, defaults to True
    include_tables: True # whether to include views, defaults to True

sink:
  # sink configs

#------------------------------------------------------------------------------
# Extra options when running Redshift behind a proxy</summary>
# This requires you to have already installed the Microsoft ODBC Driver for SQL Server.
# See https://docs.microsoft.com/en-us/sql/connect/python/pyodbc/step-1-configure-development-environment-for-pyodbc-python-development?view=sql-server-ver15
#------------------------------------------------------------------------------

source:
  type: redshift
  config:
    host_port: my-proxy-hostname:5439

    options:
      connect_args:
        sslmode: "prefer" # or "require" or "verify-ca"
        sslrootcert: ~ # needed to unpin the AWS Redshift certificate

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_instance_map		Dict[str,string]	A holder for platform -> platform_instance mappings to generate correct dataset urns
bucket_duration		enum(BucketDuration)	Size of the time window to aggregate usage stats.. Allowed symbols are DAY, HOUR	DAY
end_time		string	Latest date of usage to consider. Default: Current time in UTC	None
start_time		string	Earliest date of usage to consider. Default: Last full day in UTC (or hour, depending on bucket_duration)	None
platform_instance		string	The instance of the platform that all assets produced by this recipe belong to	None
options		Dict	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.
include_views		boolean	Whether views should be ingested.	True
include_tables		boolean	Whether tables should be ingested.	True
include_table_location_lineage		boolean	If the source supports it, include table lineage to the underlying storage location.	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
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
include_view_lineage		boolean	Include table lineage for views	False
default_schema		string	The default schema to use if the sql parser fails to parse the schema with sql_based lineage collector	public
include_table_lineage		boolean	Whether table lineage should be ingested.	True
include_copy_lineage		boolean	Whether lineage should be collected from copy commands	True
include_unload_lineage		boolean	Whether lineage should be collected from unload commands	True
capture_lineage_query_parser_failures		boolean	Whether to capture lineage query parser errors with dataset properties for debuggings	False
table_lineage_mode		enum(LineageMode)	Which table lineage collector mode to use. Available modes are: [stl_scan_based, sql_based, mixed]	stl_scan_based
s3_lineage_config		S3LineageProviderConfig (see below for fields)	Common config for S3 lineage generation
s3_lineage_config.path_specs	❓ (required if s3_lineage_config is set)	Array of object	List of PathSpec. See below the details about PathSpec	None
stateful_ingestion		StatefulStaleMetadataRemovalConfig (see below for fields)
stateful_ingestion.enabled		boolean	The type of the ingestion state provider registered with datahub.	False
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 entities present in the last successful run but missing in the current run with stateful_ingestion enabled.	True
schema_pattern		AllowDenyPattern (see below for fields)		{'allow': ['.*'], 'deny': ['information_schema'], 'ignoreCase': True}
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
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}
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
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}
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
profile_pattern		AllowDenyPattern (see below for fields)	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 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
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
profiling		GEProfilingConfig (see below for fields)		{'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.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	Whether to report datasets or dataset columns which were not profiled. 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_distinct_count		boolean	Whether to profile for the number of distinct values 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.field_sample_values_limit		integer	Upper limit for number of sample values to collect for all columns.	20
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.	None
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.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_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.	False
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.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": "RedshiftConfig",
  "description": "Base configuration class for stateful ingestion for source configs to inherit from.",
  "type": "object",
  "properties": {
    "s3_lineage_config": {
      "title": "S3 Lineage Config",
      "description": "Common config for S3 lineage generation",
      "allOf": [
        {
          "$ref": "#/definitions/S3LineageProviderConfig"
        }
      ]
    },
    "env": {
      "title": "Env",
      "description": "The environment that all assets produced by this connector belong to",
      "default": "PROD",
      "type": "string"
    },
    "platform_instance_map": {
      "title": "Platform Instance Map",
      "description": "A holder for platform -> platform_instance mappings to generate correct dataset urns",
      "type": "object",
      "additionalProperties": {
        "type": "string"
      }
    },
    "bucket_duration": {
      "description": "Size of the time window to aggregate usage stats.",
      "default": "DAY",
      "allOf": [
        {
          "$ref": "#/definitions/BucketDuration"
        }
      ]
    },
    "end_time": {
      "title": "End Time",
      "description": "Latest date of usage to consider. Default: Current time in UTC",
      "type": "string",
      "format": "date-time"
    },
    "start_time": {
      "title": "Start Time",
      "description": "Earliest date of usage to consider. Default: Last full day in UTC (or hour, depending on `bucket_duration`)",
      "type": "string",
      "format": "date-time"
    },
    "platform_instance": {
      "title": "Platform Instance",
      "description": "The instance of the platform that all assets produced by this recipe belong to",
      "type": "string"
    },
    "stateful_ingestion": {
      "$ref": "#/definitions/StatefulStaleMetadataRemovalConfig"
    },
    "options": {
      "title": "Options",
      "description": "Any options specified here will be passed to SQLAlchemy's create_engine as kwargs. See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details.",
      "type": "object"
    },
    "schema_pattern": {
      "title": "Schema Pattern",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [
          "information_schema"
        ],
        "ignoreCase": true
      },
      "allOf": [
        {
          "$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",
      "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"
    },
    "include_view_lineage": {
      "title": "Include View Lineage",
      "description": "Include table lineage for views",
      "default": false,
      "type": "boolean"
    },
    "default_schema": {
      "title": "Default Schema",
      "description": "The default schema to use if the sql parser fails to parse the schema with `sql_based` lineage collector",
      "default": "public",
      "type": "string"
    },
    "include_table_lineage": {
      "title": "Include Table Lineage",
      "description": "Whether table lineage should be ingested.",
      "default": true,
      "type": "boolean"
    },
    "include_copy_lineage": {
      "title": "Include Copy Lineage",
      "description": "Whether lineage should be collected from copy commands",
      "default": true,
      "type": "boolean"
    },
    "include_unload_lineage": {
      "title": "Include Unload Lineage",
      "description": "Whether lineage should be collected from unload commands",
      "default": true,
      "type": "boolean"
    },
    "capture_lineage_query_parser_failures": {
      "title": "Capture Lineage Query Parser Failures",
      "description": "Whether to capture lineage query parser errors with dataset properties for debuggings",
      "default": false,
      "type": "boolean"
    },
    "table_lineage_mode": {
      "description": "Which table lineage collector mode to use. Available modes are: [stl_scan_based, sql_based, mixed]",
      "default": "stl_scan_based",
      "allOf": [
        {
          "$ref": "#/definitions/LineageMode"
        }
      ]
    }
  },
  "required": [
    "host_port"
  ],
  "additionalProperties": false,
  "definitions": {
    "PathSpec": {
      "title": "PathSpec",
      "type": "object",
      "properties": {
        "include": {
          "title": "Include",
          "description": "Path to table (s3 or local file system). Name variable {table} is used to mark the folder with dataset. In absence of {table}, file level dataset will be created. Check below examples for more details.",
          "type": "string"
        },
        "exclude": {
          "title": "Exclude",
          "description": "list of paths in glob pattern which will be excluded while scanning for the datasets",
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "file_types": {
          "title": "File Types",
          "description": "Files with extenstions specified here (subset of default value) only will be scanned to create dataset. Other files will be omitted.",
          "default": [
            "csv",
            "tsv",
            "json",
            "parquet",
            "avro"
          ],
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "default_extension": {
          "title": "Default Extension",
          "description": "For files without extension it will assume the specified file type. If it is not set the files without extensions will be skipped.",
          "type": "string"
        },
        "table_name": {
          "title": "Table Name",
          "description": "Display name of the dataset.Combination of named variables from include path and strings",
          "type": "string"
        },
        "enable_compression": {
          "title": "Enable Compression",
          "description": "Enable or disable processing compressed files. Currently .gz and .bz files are supported.",
          "default": true,
          "type": "boolean"
        },
        "sample_files": {
          "title": "Sample Files",
          "description": "Not listing all the files but only taking a handful amount of sample file to infer the schema. File count and file size calculation will be disabled. This can affect performance significantly if enabled",
          "default": true,
          "type": "boolean"
        }
      },
      "required": [
        "include"
      ],
      "additionalProperties": false
    },
    "S3LineageProviderConfig": {
      "title": "S3LineageProviderConfig",
      "description": "Any source that produces s3 lineage from/to Datasets should inherit this class.",
      "type": "object",
      "properties": {
        "path_specs": {
          "title": "Path Specs",
          "description": "List of PathSpec. See below the details about PathSpec",
          "type": "array",
          "items": {
            "$ref": "#/definitions/PathSpec"
          }
        }
      },
      "required": [
        "path_specs"
      ],
      "additionalProperties": false
    },
    "BucketDuration": {
      "title": "BucketDuration",
      "description": "An enumeration.",
      "enum": [
        "DAY",
        "HOUR"
      ],
      "type": "string"
    },
    "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
    },
    "LineageMode": {
      "title": "LineageMode",
      "description": "An enumeration.",
      "enum": [
        "sql_based",
        "stl_scan_based",
        "mixed"
      ]
    }
  }
}

Code Coordinates

• Class Name: datahub.ingestion.source.sql.redshift.RedshiftSource
• Browse on GitHub

Module redshift-usage

Important Capabilities

Capability	Status	Notes
Platform Instance	✅	Enabled by default

This plugin extracts usage statistics for datasets in Amazon Redshift.

Note: Usage information is computed by querying the following system tables -

1. stl_scan
2. svv_table_info
3. stl_query
4. svl_user_info

To grant access this plugin for all system tables, please alter your datahub Redshift user the following way:

ALTER USER datahub_user WITH SYSLOG ACCESS UNRESTRICTED;

This plugin has the below functionalities -

1. For a specific dataset this plugin ingests the following statistics -
   1. top n queries.
   2. top users.
2. Aggregation of these statistics into buckets, by day or hour granularity.

note

This source only does usage statistics. To get the tables, views, and schemas in your Redshift warehouse, ingest using the redshift source described above.

note

Redshift system tables have some latency in getting data from queries. In addition, these tables only maintain logs for 2-5 days. You can find more information from the official documentation here.

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[redshift-usage]'

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: redshift-usage
  config:
    # Coordinates
    host_port: db_host:port
    database: dev
    email_domain: acryl.io

    # Credentials
    username: username
    password: "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
bucket_duration		enum(BucketDuration)	Size of the time window to aggregate usage stats.. Allowed symbols are DAY, HOUR	DAY
end_time		string	Latest date of usage to consider. Default: Current time in UTC	None
start_time		string	Earliest date of usage to consider. Default: Last full day in UTC (or hour, depending on bucket_duration)	None
top_n_queries		integer	Number of top queries to save to each table.	10
include_operational_stats		boolean	Whether to display operational stats.	True
include_read_operational_stats		boolean	Whether to report read operational stats. Experimental.	False
format_sql_queries		boolean	Whether to format sql queries	False
include_top_n_queries		boolean	Whether to ingest the top_n_queries.	True
platform_instance_map		Dict[str,string]	A holder for platform -> platform_instance mappings to generate correct dataset urns
platform_instance		string	The instance of the platform that all assets produced by this recipe belong to	None
options		Dict	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.	{}
include_views		boolean	Whether views should be ingested.	True
include_tables		boolean	Whether tables should be ingested.	True
include_table_location_lineage		boolean	If the source supports it, include table lineage to the underlying storage location.	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
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
include_view_lineage		boolean	Include table lineage for views	False
default_schema		string	The default schema to use if the sql parser fails to parse the schema with sql_based lineage collector	public
include_table_lineage		boolean	Whether table lineage should be ingested.	True
include_copy_lineage		boolean	Whether lineage should be collected from copy commands	True
include_unload_lineage		boolean	Whether lineage should be collected from unload commands	True
capture_lineage_query_parser_failures		boolean	Whether to capture lineage query parser errors with dataset properties for debuggings	False
table_lineage_mode		enum(LineageMode)	Which table lineage collector mode to use. Available modes are: [stl_scan_based, sql_based, mixed]	stl_scan_based
email_domain	✅	string	Email domain of your organisation so users can be displayed on UI appropriately.	None
user_email_pattern		AllowDenyPattern (see below for fields)	regex patterns for user emails to filter in usage.	{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
user_email_pattern.allow		Array of string	List of regex patterns to include in ingestion	['.*']
user_email_pattern.deny		Array of string	List of regex patterns to exclude from ingestion.	[]
user_email_pattern.ignoreCase		boolean	Whether to ignore case sensitivity during pattern matching.	True
s3_lineage_config		S3LineageProviderConfig (see below for fields)	Common config for S3 lineage generation
s3_lineage_config.path_specs	❓ (required if s3_lineage_config is set)	Array of object	List of PathSpec. See below the details about PathSpec	None
stateful_ingestion		StatefulStaleMetadataRemovalConfig (see below for fields)
stateful_ingestion.enabled		boolean	The type of the ingestion state provider registered with datahub.	False
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 entities present in the last successful run but missing in the current run with stateful_ingestion enabled.	True
schema_pattern		AllowDenyPattern (see below for fields)		{'allow': ['.*'], 'deny': ['information_schema'], 'ignoreCase': True}
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
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}
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
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}
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
profile_pattern		AllowDenyPattern (see below for fields)	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 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
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
profiling		GEProfilingConfig (see below for fields)		{'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.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	Whether to report datasets or dataset columns which were not profiled. 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_distinct_count		boolean	Whether to profile for the number of distinct values 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.field_sample_values_limit		integer	Upper limit for number of sample values to collect for all columns.	20
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.	None
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.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_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.	False
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.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": "RedshiftUsageConfig",
  "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"
    },
    "bucket_duration": {
      "description": "Size of the time window to aggregate usage stats.",
      "default": "DAY",
      "allOf": [
        {
          "$ref": "#/definitions/BucketDuration"
        }
      ]
    },
    "end_time": {
      "title": "End Time",
      "description": "Latest date of usage to consider. Default: Current time in UTC",
      "type": "string",
      "format": "date-time"
    },
    "start_time": {
      "title": "Start Time",
      "description": "Earliest date of usage to consider. Default: Last full day in UTC (or hour, depending on `bucket_duration`)",
      "type": "string",
      "format": "date-time"
    },
    "top_n_queries": {
      "title": "Top N Queries",
      "description": "Number of top queries to save to each table.",
      "default": 10,
      "exclusiveMinimum": 0,
      "type": "integer"
    },
    "user_email_pattern": {
      "title": "User Email Pattern",
      "description": "regex patterns for user emails to filter in usage.",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [],
        "ignoreCase": true
      },
      "allOf": [
        {
          "$ref": "#/definitions/AllowDenyPattern"
        }
      ]
    },
    "include_operational_stats": {
      "title": "Include Operational Stats",
      "description": "Whether to display operational stats.",
      "default": true,
      "type": "boolean"
    },
    "include_read_operational_stats": {
      "title": "Include Read Operational Stats",
      "description": "Whether to report read operational stats. Experimental.",
      "default": false,
      "type": "boolean"
    },
    "format_sql_queries": {
      "title": "Format Sql Queries",
      "description": "Whether to format sql queries",
      "default": false,
      "type": "boolean"
    },
    "include_top_n_queries": {
      "title": "Include Top N Queries",
      "description": "Whether to ingest the top_n_queries.",
      "default": true,
      "type": "boolean"
    },
    "s3_lineage_config": {
      "title": "S3 Lineage Config",
      "description": "Common config for S3 lineage generation",
      "allOf": [
        {
          "$ref": "#/definitions/S3LineageProviderConfig"
        }
      ]
    },
    "platform_instance_map": {
      "title": "Platform Instance Map",
      "description": "A holder for platform -> platform_instance mappings to generate correct dataset urns",
      "type": "object",
      "additionalProperties": {
        "type": "string"
      }
    },
    "platform_instance": {
      "title": "Platform Instance",
      "description": "The instance of the platform that all assets produced by this recipe belong to",
      "type": "string"
    },
    "stateful_ingestion": {
      "$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.",
      "default": {},
      "type": "object"
    },
    "schema_pattern": {
      "title": "Schema Pattern",
      "default": {
        "allow": [
          ".*"
        ],
        "deny": [
          "information_schema"
        ],
        "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",
      "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"
    },
    "include_view_lineage": {
      "title": "Include View Lineage",
      "description": "Include table lineage for views",
      "default": false,
      "type": "boolean"
    },
    "default_schema": {
      "title": "Default Schema",
      "description": "The default schema to use if the sql parser fails to parse the schema with `sql_based` lineage collector",
      "default": "public",
      "type": "string"
    },
    "include_table_lineage": {
      "title": "Include Table Lineage",
      "description": "Whether table lineage should be ingested.",
      "default": true,
      "type": "boolean"
    },
    "include_copy_lineage": {
      "title": "Include Copy Lineage",
      "description": "Whether lineage should be collected from copy commands",
      "default": true,
      "type": "boolean"
    },
    "include_unload_lineage": {
      "title": "Include Unload Lineage",
      "description": "Whether lineage should be collected from unload commands",
      "default": true,
      "type": "boolean"
    },
    "capture_lineage_query_parser_failures": {
      "title": "Capture Lineage Query Parser Failures",
      "description": "Whether to capture lineage query parser errors with dataset properties for debuggings",
      "default": false,
      "type": "boolean"
    },
    "table_lineage_mode": {
      "description": "Which table lineage collector mode to use. Available modes are: [stl_scan_based, sql_based, mixed]",
      "default": "stl_scan_based",
      "allOf": [
        {
          "$ref": "#/definitions/LineageMode"
        }
      ]
    },
    "email_domain": {
      "title": "Email Domain",
      "description": "Email domain of your organisation so users can be displayed on UI appropriately.",
      "type": "string"
    }
  },
  "required": [
    "host_port",
    "email_domain"
  ],
  "additionalProperties": false,
  "definitions": {
    "BucketDuration": {
      "title": "BucketDuration",
      "description": "An enumeration.",
      "enum": [
        "DAY",
        "HOUR"
      ],
      "type": "string"
    },
    "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
    },
    "PathSpec": {
      "title": "PathSpec",
      "type": "object",
      "properties": {
        "include": {
          "title": "Include",
          "description": "Path to table (s3 or local file system). Name variable {table} is used to mark the folder with dataset. In absence of {table}, file level dataset will be created. Check below examples for more details.",
          "type": "string"
        },
        "exclude": {
          "title": "Exclude",
          "description": "list of paths in glob pattern which will be excluded while scanning for the datasets",
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "file_types": {
          "title": "File Types",
          "description": "Files with extenstions specified here (subset of default value) only will be scanned to create dataset. Other files will be omitted.",
          "default": [
            "csv",
            "tsv",
            "json",
            "parquet",
            "avro"
          ],
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "default_extension": {
          "title": "Default Extension",
          "description": "For files without extension it will assume the specified file type. If it is not set the files without extensions will be skipped.",
          "type": "string"
        },
        "table_name": {
          "title": "Table Name",
          "description": "Display name of the dataset.Combination of named variables from include path and strings",
          "type": "string"
        },
        "enable_compression": {
          "title": "Enable Compression",
          "description": "Enable or disable processing compressed files. Currently .gz and .bz files are supported.",
          "default": true,
          "type": "boolean"
        },
        "sample_files": {
          "title": "Sample Files",
          "description": "Not listing all the files but only taking a handful amount of sample file to infer the schema. File count and file size calculation will be disabled. This can affect performance significantly if enabled",
          "default": true,
          "type": "boolean"
        }
      },
      "required": [
        "include"
      ],
      "additionalProperties": false
    },
    "S3LineageProviderConfig": {
      "title": "S3LineageProviderConfig",
      "description": "Any source that produces s3 lineage from/to Datasets should inherit this class.",
      "type": "object",
      "properties": {
        "path_specs": {
          "title": "Path Specs",
          "description": "List of PathSpec. See below the details about PathSpec",
          "type": "array",
          "items": {
            "$ref": "#/definitions/PathSpec"
          }
        }
      },
      "required": [
        "path_specs"
      ],
      "additionalProperties": false
    },
    "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
    },
    "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
    },
    "LineageMode": {
      "title": "LineageMode",
      "description": "An enumeration.",
      "enum": [
        "sql_based",
        "stl_scan_based",
        "mixed"
      ]
    }
  }
}

Code Coordinates

• Class Name: datahub.ingestion.source.usage.redshift_usage.RedshiftUsageSource
• Browse on GitHub

Questions

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