From 59e643d178fb925138e47949766a5e2b2d58968d Mon Sep 17 00:00:00 2001 From: Yoshi Automation Date: Tue, 2 Apr 2024 07:08:24 +0000 Subject: [PATCH] feat(dataplex): update the api #### dataplex:v1 The following keys were added: - schemas.GoogleCloudDataplexV1DataQualityRule.properties.sqlAssertion.$ref (Total Keys: 1) - schemas.GoogleCloudDataplexV1DataQualityRuleResult.properties.assertionRowCount (Total Keys: 3) - schemas.GoogleCloudDataplexV1DataQualityRuleSqlAssertion (Total Keys: 3) --- ...aplex_v1.projects.locations.dataScans.html | 38 +++++++++++++++++++ ..._v1.projects.locations.dataScans.jobs.html | 17 +++++++++ ...rojects.locations.entryGroups.entries.html | 2 +- .../documents/dataplex.v1.json | 25 +++++++++++- 4 files changed, 79 insertions(+), 3 deletions(-) diff --git a/docs/dyn/dataplex_v1.projects.locations.dataScans.html b/docs/dyn/dataplex_v1.projects.locations.dataScans.html index ba09700ffe..2b31d365b9 100644 --- a/docs/dyn/dataplex_v1.projects.locations.dataScans.html +++ b/docs/dyn/dataplex_v1.projects.locations.dataScans.html @@ -240,6 +240,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -271,6 +272,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -343,6 +347,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -499,6 +506,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -646,6 +656,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -677,6 +688,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -749,6 +763,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -971,6 +988,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -1002,6 +1020,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -1074,6 +1095,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -1257,6 +1281,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -1288,6 +1313,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -1360,6 +1388,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -1560,6 +1591,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -1591,6 +1623,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -1663,6 +1698,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. diff --git a/docs/dyn/dataplex_v1.projects.locations.dataScans.jobs.html b/docs/dyn/dataplex_v1.projects.locations.dataScans.jobs.html index c3828b61ae..df3fe99afd 100644 --- a/docs/dyn/dataplex_v1.projects.locations.dataScans.jobs.html +++ b/docs/dyn/dataplex_v1.projects.locations.dataScans.jobs.html @@ -142,6 +142,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -284,6 +287,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -315,6 +319,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -387,6 +394,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -538,6 +548,7 @@

Method Details

"rowCount": "A String", # The count of rows processed. "rules": [ # A list of all the rules in a job, and their results. { # DataQualityRuleResult provides a more detailed, per-rule view of the results. + "assertionRowCount": "A String", # Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules. "evaluatedCount": "A String", # The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true. "failingRowsQuery": "A String", # The query to find rows that did not pass this rule.This field is only valid for row-level type rules. "nullCount": "A String", # The number of rows with null values in the specified column. @@ -569,6 +580,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. @@ -641,6 +655,9 @@

Method Details

"A String", ], }, + "sqlAssertion": { # Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0 # Aggregate rule which evaluates the number of rows returned for the provided statement. + "sqlStatement": "A String", # Optional. The SQL statement. + }, "statisticRangeExpectation": { # Evaluates whether the column aggregate statistic lies between a specified range. # Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range. "maxValue": "A String", # Optional. The maximum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. "minValue": "A String", # Optional. The minimum column statistic value allowed for a row to pass this validation.At least one of min_value and max_value need to be provided. diff --git a/docs/dyn/dataplex_v1.projects.locations.entryGroups.entries.html b/docs/dyn/dataplex_v1.projects.locations.entryGroups.entries.html index 9e3cb7dbad..3a3675a0e4 100644 --- a/docs/dyn/dataplex_v1.projects.locations.entryGroups.entries.html +++ b/docs/dyn/dataplex_v1.projects.locations.entryGroups.entries.html @@ -333,7 +333,7 @@

Method Details

Args: parent: string, Required. The resource name of the parent Entry Group: projects/{project}/locations/{location}/entryGroups/{entry_group}. (required) - filter: string, Optional. A filter on the entries to return. Filters are case-sensitive. The request can be filtered by the following fields: entry_type, display_name. The comparison operators are =, !=, <, >, <=, >= (strings are compared according to lexical order) The logical operators AND, OR, NOT can be used in the filter. Example filter expressions: "display_name=AnExampleDisplayName" "entry_type=projects/example-project/locations/global/entryTypes/example-entry_type" "entry_type=projects/a* OR "entry_type=projects/k*" "NOT display_name=AnotherExampleDisplayName" + filter: string, Optional. A filter on the entries to return. Filters are case-sensitive. The request can be filtered by the following fields: entry_type, entry_source.display_name. The comparison operators are =, !=, <, >, <=, >= (strings are compared according to lexical order) The logical operators AND, OR, NOT can be used in the filter. Wildcard "*" can be used, but for entry_type the full project id or number needs to be provided. Example filter expressions: "entry_source.display_name=AnExampleDisplayName" "entry_type=projects/example-project/locations/global/entryTypes/example-entry_type" "entry_type=projects/example-project/locations/us/entryTypes/a* OR entry_type=projects/another-project/locations/*" "NOT entry_source.display_name=AnotherExampleDisplayName" pageSize: integer, A parameter pageToken: string, Optional. The pagination token returned by a previous request. x__xgafv: string, V1 error format. diff --git a/googleapiclient/discovery_cache/documents/dataplex.v1.json b/googleapiclient/discovery_cache/documents/dataplex.v1.json index 07dab71de5..ad6f01c05f 100644 --- a/googleapiclient/discovery_cache/documents/dataplex.v1.json +++ b/googleapiclient/discovery_cache/documents/dataplex.v1.json @@ -2211,7 +2211,7 @@ ], "parameters": { "filter": { -"description": "Optional. A filter on the entries to return. Filters are case-sensitive. The request can be filtered by the following fields: entry_type, display_name. The comparison operators are =, !=, <, >, <=, >= (strings are compared according to lexical order) The logical operators AND, OR, NOT can be used in the filter. Example filter expressions: \"display_name=AnExampleDisplayName\" \"entry_type=projects/example-project/locations/global/entryTypes/example-entry_type\" \"entry_type=projects/a* OR \"entry_type=projects/k*\" \"NOT display_name=AnotherExampleDisplayName\"", +"description": "Optional. A filter on the entries to return. Filters are case-sensitive. The request can be filtered by the following fields: entry_type, entry_source.display_name. The comparison operators are =, !=, <, >, <=, >= (strings are compared according to lexical order) The logical operators AND, OR, NOT can be used in the filter. Wildcard \"*\" can be used, but for entry_type the full project id or number needs to be provided. Example filter expressions: \"entry_source.display_name=AnExampleDisplayName\" \"entry_type=projects/example-project/locations/global/entryTypes/example-entry_type\" \"entry_type=projects/example-project/locations/us/entryTypes/a* OR entry_type=projects/another-project/locations/*\" \"NOT entry_source.display_name=AnotherExampleDisplayName\"", "location": "query", "type": "string" }, @@ -5271,7 +5271,7 @@ } } }, -"revision": "20240317", +"revision": "20240325", "rootUrl": "https://dataplex.googleapis.com/", "schemas": { "Empty": { @@ -6886,6 +6886,10 @@ "$ref": "GoogleCloudDataplexV1DataQualityRuleSetExpectation", "description": "Row-level rule which evaluates whether each column value is contained by a specified set." }, +"sqlAssertion": { +"$ref": "GoogleCloudDataplexV1DataQualityRuleSqlAssertion", +"description": "Aggregate rule which evaluates the number of rows returned for the provided statement." +}, "statisticRangeExpectation": { "$ref": "GoogleCloudDataplexV1DataQualityRuleStatisticRangeExpectation", "description": "Aggregate rule which evaluates whether the column aggregate statistic lies between a specified range." @@ -6950,6 +6954,12 @@ "description": "DataQualityRuleResult provides a more detailed, per-rule view of the results.", "id": "GoogleCloudDataplexV1DataQualityRuleResult", "properties": { +"assertionRowCount": { +"description": "Output only. The number of rows returned by the sql statement in the SqlAssertion rule.This field is only valid for SqlAssertion rules.", +"format": "int64", +"readOnly": true, +"type": "string" +}, "evaluatedCount": { "description": "The number of rows a rule was evaluated against.This field is only valid for row-level type rules.Evaluated count can be configured to either include all rows (default) - with null rows automatically failing rule evaluation, or exclude null rows from the evaluated_count, by setting ignore_nulls = true.", "format": "int64", @@ -7010,6 +7020,17 @@ }, "type": "object" }, +"GoogleCloudDataplexV1DataQualityRuleSqlAssertion": { +"description": "Queries for rows returned by the provided SQL statement. If any rows are are returned, this rule fails.The SQL statement needs to use BigQuery standard SQL syntax, and must not contain any semicolons.${data()} can be used to reference the rows being evaluated, i.e. the table after all additional filters (row filters, incremental data filters, sampling) are applied.Example: SELECT * FROM ${data()} WHERE price < 0", +"id": "GoogleCloudDataplexV1DataQualityRuleSqlAssertion", +"properties": { +"sqlStatement": { +"description": "Optional. The SQL statement.", +"type": "string" +} +}, +"type": "object" +}, "GoogleCloudDataplexV1DataQualityRuleStatisticRangeExpectation": { "description": "Evaluates whether the column aggregate statistic lies between a specified range.", "id": "GoogleCloudDataplexV1DataQualityRuleStatisticRangeExpectation",