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Trino

There are 2 sources that provide integration with Trino

Source ModuleDocumentation

trino

This plugin extracts the following:

  • Metadata for databases, schemas, and tables

  • Column types and schema associated with each table

  • Table, row, and column statistics via optional SQL profiling

    Read more...

starburst-trino-usage

If you are using Starburst Trino you can collect usage stats the following way.

Prerequsities

  1. You need to setup Event Logger which saves audit logs into a Postgres db and setup this db as a catalog in Trino Here you can find more info about how to setup: https://docs.starburst.io/354-e/security/event-logger.html#security-event-logger--page-root https://docs.starburst.io/354-e/security/event-logger.html#analyzing-the-event-log

  2. Install starbust-trino-usage plugin Run pip install 'acryl-datahub[starburst-trino-usage]'.

    Read more...

Module trino

Certified

Important Capabilities

CapabilityStatusNotes
Data ProfilingOptionally enabled via configuration
DomainsSupported via the domain config field

This plugin extracts the following:

  • Metadata for databases, schemas, and tables
  • Column types and schema associated with each table
  • Table, row, and column statistics via optional SQL profiling

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[trino]'

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: trino
config:
# Coordinates
host_port: localhost:5300
database: dbname

# Credentials
username: foo
password: datahub

# If you need to connect to Trino over http and not https, uncomment this section.
# options:
# connect_args:
# http_scheme: http

sink:
# sink configs

Config Details

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

Field [Required]TypeDescriptionDefaultNotes
host_port []stringhost URL
databasestringdatabase (catalog)
database_aliasstring[Deprecated] Alias to apply to database when ingesting.
include_table_location_lineagebooleanIf the source supports it, include table lineage to the underlying storage location.True
include_tablesbooleanWhether tables should be ingested.True
include_viewsbooleanWhether views should be ingested.True
optionsobjectAny 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.
passwordstring(password)password
platform_instancestringThe instance of the platform that all assets produced by this recipe belong to
sqlalchemy_uristringURI of database to connect to. See https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls. Takes precedence over other connection parameters.
usernamestringusername
envstringThe environment that all assets produced by this connector belong toPROD
domainmap(str,AllowDenyPattern)A class to store allow deny regexes
domain.key.allowarray(string)
domain.key.denyarray(string)
domain.key.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
profile_patternAllowDenyPatternRegex 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.allowarray(string)
profile_pattern.denyarray(string)
profile_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
schema_patternAllowDenyPatternRegex patterns for schemas to filter in ingestion. Specify regex to only match the schema name. e.g. to match all tables in schema analytics, use the regex 'analytics'{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
schema_pattern.allowarray(string)
schema_pattern.denyarray(string)
schema_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
table_patternAllowDenyPatternRegex 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.allowarray(string)
table_pattern.denyarray(string)
table_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
view_patternAllowDenyPatternRegex 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.allowarray(string)
view_pattern.denyarray(string)
view_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
profilingGEProfilingConfig{'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': 20, 'query_combiner_enabled': True, 'catch_exceptions': True, 'partition_profiling_enabled': True, 'partition_datetime': None}
profiling.catch_exceptionsbooleanTrue
profiling.enabledbooleanWhether profiling should be done.False
profiling.field_sample_values_limitintegerUpper limit for number of sample values to collect for all columns.20
profiling.include_field_distinct_countbooleanWhether to profile for the number of distinct values for each column.True
profiling.include_field_distinct_value_frequenciesbooleanWhether to profile for distinct value frequencies.False
profiling.include_field_histogrambooleanWhether to profile for the histogram for numeric fields.False
profiling.include_field_max_valuebooleanWhether to profile for the max value of numeric columns.True
profiling.include_field_mean_valuebooleanWhether to profile for the mean value of numeric columns.True
profiling.include_field_median_valuebooleanWhether to profile for the median value of numeric columns.True
profiling.include_field_min_valuebooleanWhether to profile for the min value of numeric columns.True
profiling.include_field_null_countbooleanWhether to profile for the number of nulls for each column.True
profiling.include_field_quantilesbooleanWhether to profile for the quantiles of numeric columns.False
profiling.include_field_sample_valuesbooleanWhether to profile for the sample values for all columns.True
profiling.include_field_stddev_valuebooleanWhether to profile for the standard deviation of numeric columns.True
profiling.limitintegerMax number of documents to profile. By default, profiles all documents.
profiling.max_number_of_fields_to_profileintegerA 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_workersintegerNumber of worker threads to use for profiling. Set to 1 to disable.20
profiling.offsetintegerOffset in documents to profile. By default, uses no offset.
profiling.partition_datetimestring(date-time)For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this.
profiling.partition_profiling_enabledbooleanTrue
profiling.profile_if_updated_since_daysnumberProfile 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_onlybooleanWhether to perform profiling at table-level only, or include column-level profiling as well.False
profiling.profile_table_row_count_estimate_onlybooleanUse an approximate query for row count. This will be much faster but slightly less accurate. Only supported for Postgres.False
profiling.profile_table_row_limitintegerProfile 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 BigQuery5000000
profiling.profile_table_size_limitintegerProfile 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 BigQuery5
profiling.query_combiner_enabledbooleanThis feature is still experimental and can be disabled if it causes issues. Reduces the total number of queries issued and speeds up profiling by dynamically combining SQL queries where possible.True
profiling.report_dropped_profilesbooleanWhether to report datasets or dataset columns which were not profiled. Set to True for debugging purposes.False
profiling.turn_off_expensive_profiling_metricsbooleanWhether 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
stateful_ingestionStatefulStaleMetadataRemovalConfigBase specialized config for Stateful Ingestion with stale metadata removal capability.
stateful_ingestion.enabledbooleanThe type of the ingestion state provider registered with datahub.False
stateful_ingestion.ignore_new_statebooleanIf set to True, ignores the current checkpoint state.False
stateful_ingestion.ignore_old_statebooleanIf set to True, ignores the previous checkpoint state.False
stateful_ingestion.remove_stale_metadatabooleanSoft-deletes the entities present in the last successful run but missing in the current run with stateful_ingestion enabled.True

Code Coordinates

  • Class Name: datahub.ingestion.source.sql.trino.TrinoSource
  • Browse on GitHub

Module starburst-trino-usage

Certified

If you are using Starburst Trino you can collect usage stats the following way.

Prerequsities

  1. You need to setup Event Logger which saves audit logs into a Postgres db and setup this db as a catalog in Trino Here you can find more info about how to setup: https://docs.starburst.io/354-e/security/event-logger.html#security-event-logger--page-root https://docs.starburst.io/354-e/security/event-logger.html#analyzing-the-event-log

  2. Install starbust-trino-usage plugin Run pip install 'acryl-datahub[starburst-trino-usage]'.

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[starburst-trino-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: starburst-trino-usage
config:
# Coordinates
host_port: yourtrinohost:port
# The name of the catalog from getting the usage
database: hive
# Credentials
username: trino_username
password: trino_password
email_domain: test.com
audit_catalog: audit
audit_schema: audit_schema

sink:
type: "datahub-rest"
config:
server: "http://localhost:8080"

Config Details

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

Field [Required]TypeDescriptionDefaultNotes
audit_catalog []stringThe catalog name where the audit table can be found
audit_schema []stringThe schema name where the audit table can be found
database []stringThe name of the catalog from getting the usage
email_domain []stringThe email domain which will be appended to the users
host_port []stringhost URL
bucket_durationEnumSize of the time window to aggregate usage stats.DAY
database_aliasstring[Deprecated] Alias to apply to database when ingesting.
end_timestring(date-time)Latest date of usage to consider. Default: Current time in UTC
format_sql_queriesbooleanWhether to format sql queriesFalse
include_operational_statsbooleanWhether to display operational stats.True
include_read_operational_statsbooleanWhether to report read operational stats. Experimental.False
include_table_location_lineagebooleanIf the source supports it, include table lineage to the underlying storage location.True
include_tablesbooleanWhether tables should be ingested.True
include_top_n_queriesbooleanWhether to ingest the top_n_queries.True
include_viewsbooleanWhether views should be ingested.True
optionsobject{}
passwordstring(password)password
platform_instancestringThe instance of the platform that all assets produced by this recipe belong to
sqlalchemy_uristringURI of database to connect to. See https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls. Takes precedence over other connection parameters.
start_timestring(date-time)Earliest date of usage to consider. Default: Last full day in UTC (or hour, depending on bucket_duration)
top_n_queriesintegerNumber of top queries to save to each table.10
usernamestringusername
envstringThe environment that all assets produced by this connector belong toPROD
domainmap(str,AllowDenyPattern)A class to store allow deny regexes
domain.key.allowarray(string)
domain.key.denyarray(string)
domain.key.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
profile_patternAllowDenyPatternRegex 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.allowarray(string)
profile_pattern.denyarray(string)
profile_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
schema_patternAllowDenyPatternRegex patterns for schemas to filter in ingestion. Specify regex to only match the schema name. e.g. to match all tables in schema analytics, use the regex 'analytics'{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
schema_pattern.allowarray(string)
schema_pattern.denyarray(string)
schema_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
table_patternAllowDenyPatternRegex 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.allowarray(string)
table_pattern.denyarray(string)
table_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
user_email_patternAllowDenyPatternregex patterns for user emails to filter in usage.{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
user_email_pattern.allowarray(string)
user_email_pattern.denyarray(string)
user_email_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
view_patternAllowDenyPatternRegex 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.allowarray(string)
view_pattern.denyarray(string)
view_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
profilingGEProfilingConfig{'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': 20, 'query_combiner_enabled': True, 'catch_exceptions': True, 'partition_profiling_enabled': True, 'partition_datetime': None}
profiling.catch_exceptionsbooleanTrue
profiling.enabledbooleanWhether profiling should be done.False
profiling.field_sample_values_limitintegerUpper limit for number of sample values to collect for all columns.20
profiling.include_field_distinct_countbooleanWhether to profile for the number of distinct values for each column.True
profiling.include_field_distinct_value_frequenciesbooleanWhether to profile for distinct value frequencies.False
profiling.include_field_histogrambooleanWhether to profile for the histogram for numeric fields.False
profiling.include_field_max_valuebooleanWhether to profile for the max value of numeric columns.True
profiling.include_field_mean_valuebooleanWhether to profile for the mean value of numeric columns.True
profiling.include_field_median_valuebooleanWhether to profile for the median value of numeric columns.True
profiling.include_field_min_valuebooleanWhether to profile for the min value of numeric columns.True
profiling.include_field_null_countbooleanWhether to profile for the number of nulls for each column.True
profiling.include_field_quantilesbooleanWhether to profile for the quantiles of numeric columns.False
profiling.include_field_sample_valuesbooleanWhether to profile for the sample values for all columns.True
profiling.include_field_stddev_valuebooleanWhether to profile for the standard deviation of numeric columns.True
profiling.limitintegerMax number of documents to profile. By default, profiles all documents.
profiling.max_number_of_fields_to_profileintegerA 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_workersintegerNumber of worker threads to use for profiling. Set to 1 to disable.20
profiling.offsetintegerOffset in documents to profile. By default, uses no offset.
profiling.partition_datetimestring(date-time)For partitioned datasets profile only the partition which matches the datetime or profile the latest one if not set. Only Bigquery supports this.
profiling.partition_profiling_enabledbooleanTrue
profiling.profile_if_updated_since_daysnumberProfile 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_onlybooleanWhether to perform profiling at table-level only, or include column-level profiling as well.False
profiling.profile_table_row_count_estimate_onlybooleanUse an approximate query for row count. This will be much faster but slightly less accurate. Only supported for Postgres.False
profiling.profile_table_row_limitintegerProfile 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 BigQuery5000000
profiling.profile_table_size_limitintegerProfile 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 BigQuery5
profiling.query_combiner_enabledbooleanThis feature is still experimental and can be disabled if it causes issues. Reduces the total number of queries issued and speeds up profiling by dynamically combining SQL queries where possible.True
profiling.report_dropped_profilesbooleanWhether to report datasets or dataset columns which were not profiled. Set to True for debugging purposes.False
profiling.turn_off_expensive_profiling_metricsbooleanWhether 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
stateful_ingestionStatefulStaleMetadataRemovalConfigBase specialized config for Stateful Ingestion with stale metadata removal capability.
stateful_ingestion.enabledbooleanThe type of the ingestion state provider registered with datahub.False
stateful_ingestion.ignore_new_statebooleanIf set to True, ignores the current checkpoint state.False
stateful_ingestion.ignore_old_statebooleanIf set to True, ignores the previous checkpoint state.False
stateful_ingestion.remove_stale_metadatabooleanSoft-deletes the entities present in the last successful run but missing in the current run with stateful_ingestion enabled.True

Code Coordinates

  • Class Name: datahub.ingestion.source.usage.starburst_trino_usage.TrinoUsageSource
  • Browse on GitHub

Questions

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