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Microsoft SQL Server

Certified

Important Capabilities​

CapabilityStatusNotes
Asset Containers✅Enabled by default
Classification✅Optionally enabled via classification.enabled
Data Profiling✅Optionally enabled via configuration
Descriptions✅Enabled by default
Detect Deleted Entities✅Enabled via stateful ingestion
Domains✅Supported via the domain config field
Platform Instance✅Enabled by default
Schema Metadata✅Enabled by default

This plugin extracts the following:

  • Metadata for databases, schemas, views and tables
  • Column types associated with each table/view
  • Table, row, and column statistics via optional SQL profiling We have two options for the underlying library used to connect to SQL Server: (1) python-tds and (2) pyodbc. The TDS library is pure Python and hence easier to install. If you do use pyodbc, make sure to change the source type from mssql to mssql-odbc so that we pull in the right set of dependencies. This will be needed in most cases where encryption is required, such as managed SQL Server services in Azure.

Prerequisites​

If you want to ingest MSSQL Jobs and stored procedures (with code) the user credentials needs the proper privileges.

Script for granting the privileges:

USE MSDB
GRANT SELECT ON OBJECT::msdb.dbo.sysjobsteps TO 'USERNAME'
GRANT SELECT ON OBJECT::msdb.dbo.sysjobs TO 'USERNAME'

USE 'DATA_DB_NAME'
GRANT VIEW DEFINITION TO 'USERNAME'
GRANT SELECT ON OBJECT::sys.sql_expression_dependencies TO 'USERNAME'

CLI based Ingestion​

Install the Plugin​

The mssql source works out of the box with acryl-datahub.

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: mssql
  config:
    # Coordinates
    host_port: localhost:1433
    database: DemoDatabase

    # Credentials
    username: user
    password: pass

    # Options
    # Uncomment if you need to use encryption with pytds
    # See https://python-tds.readthedocs.io/en/latest/pytds.html#pytds.connect
    # options:
    #   connect_args:
    #     cafile: server-ca.pem
    #     validate_host: true

sink:
  # sink configs

#------------------------------------------------------------------------
#Example: using ingestion with ODBC and encryption
#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: mssql-odbc
  config:
    # Coordinates
    host_port: localhost:1433
    database: DemoDatabase

    # Credentials
    username: admin
    password: password

    # Options
    use_odbc: "True"
    uri_args:
      driver: "ODBC Driver 17 for SQL Server"
      Encrypt: "yes"
      TrustServerCertificate: "Yes"
      ssl: "True"

sink:
  # sink configs

Config Details​

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

FieldDescription
convert_urns_to_lowercase
boolean
Enable to convert the SQL Server assets urns to lowercase
Default: False
database
string
database (catalog). If set to Null, all databases will be considered for ingestion.
host_port
string
MSSQL host URL.
Default: localhost:1433
include_descriptions
boolean
Include table descriptions information.
Default: True
include_jobs
boolean
Include ingest of MSSQL Jobs. Requires access to the 'msdb' and 'sys' schema.
Default: True
include_stored_procedures
boolean
Include ingest of stored procedures. Requires access to the 'sys' schema.
Default: True
include_stored_procedures_code
boolean
Include information about object code.
Default: True
include_table_location_lineage
boolean
If the source supports it, include table lineage to the underlying storage location.
Default: True
include_tables
boolean
Whether tables should be ingested.
Default: True
include_view_column_lineage
boolean
Populates column-level lineage for view->view and table->view lineage using DataHub's sql parser. Requires include_view_lineage to be enabled.
Default: True
include_view_lineage
boolean
Populates view->view and table->view lineage using DataHub's sql parser.
Default: True
include_views
boolean
Whether views should be ingested.
Default: True
incremental_lineage
boolean
When enabled, emits lineage as incremental to existing lineage already in DataHub. When disabled, re-states lineage on each run.
Default: False
options
object
Any options specified here will be passed to SQLAlchemy.create_engine as kwargs. To set connection arguments in the URL, specify them under connect_args.
password
string(password)
password
platform_instance
string
The instance of the platform that all assets produced by this recipe belong to. This should be unique within the platform. See https://datahubproject.io/docs/platform-instances/ for more details.
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.
uri_args
map(str,string)
use_file_backed_cache
boolean
Whether to use a file backed cache for the view definitions.
Default: True
use_odbc
boolean
See https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pyodbc.
Default: False
username
string
username
env
string
The environment that all assets produced by this connector belong to
Default: PROD
classification
ClassificationConfig
For details, refer Classification.
Default: {'enabled': False, 'sample_size': 100, 'max_worker...
classification.enabled
boolean
Whether classification should be used to auto-detect glossary terms
Default: False
classification.info_type_to_term
map(str,string)
classification.max_workers
integer
Number of worker processes to use for classification. Set to 1 to disable.
Default: 4
classification.sample_size
integer
Number of sample values used for classification.
Default: 100
classification.classifiers
array
Classifiers to use to auto-detect glossary terms. If more than one classifier, infotype predictions from the classifier defined later in sequence take precedance.
Default: [{'type': 'datahub', 'config': None}]
classification.classifiers.DynamicTypedClassifierConfig
DynamicTypedClassifierConfig
classification.classifiers.DynamicTypedClassifierConfig.type ❓
string
The type of the classifier to use. For DataHub, use datahub
classification.classifiers.DynamicTypedClassifierConfig.config
object
The configuration required for initializing the classifier. If not specified, uses defaults for classifer type.
classification.column_pattern
AllowDenyPattern
Regex patterns to filter columns for classification. This is used in combination with other patterns in parent config. Specify regex to match the column name in database.schema.table.column format.
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
classification.column_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
classification.column_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
classification.column_pattern.allow.string
string
classification.column_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
classification.column_pattern.deny.string
string
classification.table_pattern
AllowDenyPattern
Regex patterns to filter tables for classification. This is used in combination with other patterns in parent config. 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}
classification.table_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
classification.table_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
classification.table_pattern.allow.string
string
classification.table_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
classification.table_pattern.deny.string
string
database_pattern
AllowDenyPattern
Regex patterns for databases to filter in ingestion.
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
database_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
database_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
database_pattern.allow.string
string
database_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
database_pattern.deny.string
string
domain
map(str,AllowDenyPattern)
A class to store allow deny regexes
domain.key.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
domain.key.allow.string
string
domain.key.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
domain.key.deny
array
List of regex patterns to exclude from ingestion.
Default: []
domain.key.deny.string
string
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.
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
profile_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
profile_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
profile_pattern.allow.string
string
profile_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
profile_pattern.deny.string
string
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'
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
schema_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
schema_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
schema_pattern.allow.string
string
schema_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
schema_pattern.deny.string
string
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.*'
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
table_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
table_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
table_pattern.allow.string
string
table_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
table_pattern.deny.string
string
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.*'
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
view_pattern.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
view_pattern.allow
array
List of regex patterns to include in ingestion
Default: ['.*']
view_pattern.allow.string
string
view_pattern.deny
array
List of regex patterns to exclude from ingestion.
Default: []
view_pattern.deny.string
string
profiling
GEProfilingConfig
Default: {'enabled': False, 'operation_config': {'lower_fre...
profiling.catch_exceptions
boolean
Default: True
profiling.enabled
boolean
Whether profiling should be done.
Default: False
profiling.field_sample_values_limit
integer
Upper limit for number of sample values to collect for all columns.
Default: 20
profiling.include_field_distinct_count
boolean
Whether to profile for the number of distinct values for each column.
Default: True
profiling.include_field_distinct_value_frequencies
boolean
Whether to profile for distinct value frequencies.
Default: False
profiling.include_field_histogram
boolean
Whether to profile for the histogram for numeric fields.
Default: False
profiling.include_field_max_value
boolean
Whether to profile for the max value of numeric columns.
Default: True
profiling.include_field_mean_value
boolean
Whether to profile for the mean value of numeric columns.
Default: True
profiling.include_field_median_value
boolean
Whether to profile for the median value of numeric columns.
Default: True
profiling.include_field_min_value
boolean
Whether to profile for the min value of numeric columns.
Default: True
profiling.include_field_null_count
boolean
Whether to profile for the number of nulls for each column.
Default: True
profiling.include_field_quantiles
boolean
Whether to profile for the quantiles of numeric columns.
Default: False
profiling.include_field_sample_values
boolean
Whether to profile for the sample values for all columns.
Default: True
profiling.include_field_stddev_value
boolean
Whether to profile for the standard deviation of numeric columns.
Default: True
profiling.limit
integer
Max number of documents to profile. By default, profiles all documents.
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.
profiling.max_workers
integer
Number of worker threads to use for profiling. Set to 1 to disable.
Default: 20
profiling.offset
integer
Offset in documents to profile. By default, uses no offset.
profiling.partition_datetime
string(date-time)
If specified, profile only the partition which matches this datetime. If not specified, profile the latest partition. Only Bigquery supports this.
profiling.partition_profiling_enabled
boolean
Whether to profile partitioned tables. Only BigQuery and Aws Athena supports this. If enabled, latest partition data is used for profiling.
Default: True
profiling.profile_external_tables
boolean
Whether to profile external tables. Only Snowflake and Redshift supports this.
Default: False
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.
profiling.profile_table_level_only
boolean
Whether to perform profiling at table-level only, or include column-level profiling as well.
Default: False
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 and MySQL.
Default: False
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
Default: 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
Default: 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.
Default: True
profiling.report_dropped_profiles
boolean
Whether to report datasets or dataset columns which were not profiled. Set to True for debugging purposes.
Default: False
profiling.sample_size
integer
Number of rows to be sampled from table for column level profiling.Applicable only if use_sampling is set to True.
Default: 10000
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.
Default: False
profiling.use_sampling
boolean
Whether to profile column level stats on sample of table. Only BigQuery and Snowflake support this. If enabled, profiling is done on rows sampled from table. Sampling is not done for smaller tables.
Default: True
profiling.operation_config
OperationConfig
Experimental feature. To specify operation configs.
profiling.operation_config.lower_freq_profile_enabled
boolean
Whether to do profiling at lower freq or not. This does not do any scheduling just adds additional checks to when not to run profiling.
Default: False
profiling.operation_config.profile_date_of_month
integer
Number between 1 to 31 for date of month (both inclusive). If not specified, defaults to Nothing and this field does not take affect.
profiling.operation_config.profile_day_of_week
integer
Number between 0 to 6 for day of week (both inclusive). 0 is Monday and 6 is Sunday. If not specified, defaults to Nothing and this field does not take affect.
profiling.tags_to_ignore_sampling
array
Fixed list of tags to ignore sampling. If not specified, tables will be sampled based on use_sampling.
profiling.tags_to_ignore_sampling.string
string
stateful_ingestion
StatefulStaleMetadataRemovalConfig
Base specialized config for Stateful Ingestion with stale metadata removal capability.
stateful_ingestion.enabled
boolean
Whether or not to enable stateful ingest. Default: True if a pipeline_name is set and either a datahub-rest sink or datahub_api is specified, otherwise False
Default: 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.
Default: True

Code Coordinates​

  • Class Name: datahub.ingestion.source.sql.mssql.source.SQLServerSource
  • Browse on GitHub

Questions

If you've got any questions on configuring ingestion for Microsoft SQL Server, feel free to ping us on our Slack.