Class: Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails
- Inherits:
-
Object
- Object
- Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails
- Extended by:
- Protobuf::MessageExts::ClassMethods
- Includes:
- Protobuf::MessageExts
- Defined in:
- proto_docs/google/privacy/dlp/v2/dlp.rb
Overview
Result of a risk analysis operation request.
Defined Under Namespace
Classes: CategoricalStatsResult, DeltaPresenceEstimationResult, KAnonymityResult, KMapEstimationResult, LDiversityResult, NumericalStatsResult, RequestedRiskAnalysisOptions
Instance Attribute Summary collapse
-
#categorical_stats_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult
Categorical stats result.
-
#delta_presence_estimation_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult
Delta-presence result.
-
#k_anonymity_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult
K-anonymity result.
-
#k_map_estimation_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult
K-map result.
-
#l_diversity_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult
L-divesity result.
-
#numerical_stats_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::NumericalStatsResult
Numerical stats result.
-
#requested_options ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::RequestedRiskAnalysisOptions
The configuration used for this job.
-
#requested_privacy_metric ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric
Privacy metric to compute.
-
#requested_source_table ⇒ ::Google::Cloud::Dlp::V2::BigQueryTable
Input dataset to compute metrics over.
Instance Attribute Details
#categorical_stats_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult
Returns Categorical stats result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#delta_presence_estimation_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult
Returns Delta-presence result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#k_anonymity_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult
Returns K-anonymity result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#k_map_estimation_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult
Returns K-map result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#l_diversity_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult
Returns L-divesity result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#numerical_stats_result ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::NumericalStatsResult
Returns Numerical stats result.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#requested_options ⇒ ::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::RequestedRiskAnalysisOptions
Returns The configuration used for this job.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#requested_privacy_metric ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric
Returns Privacy metric to compute.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |
#requested_source_table ⇒ ::Google::Cloud::Dlp::V2::BigQueryTable
Returns Input dataset to compute metrics over.
1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 |
# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 1771 class AnalyzeDataSourceRiskDetails include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Result of the numerical stats computation. # @!attribute [rw] min_value # @return [::Google::Cloud::Dlp::V2::Value] # Minimum value appearing in the column. # @!attribute [rw] max_value # @return [::Google::Cloud::Dlp::V2::Value] # Maximum value appearing in the column. # @!attribute [rw] quantile_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # List of 99 values that partition the set of field values into 100 equal # sized buckets. class NumericalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Result of the categorical stats computation. # @!attribute [rw] value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::CategoricalStatsResult::CategoricalStatsHistogramBucket>] # Histogram of value frequencies in the column. class CategoricalStatsResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # Histogram of value frequencies in the column. # @!attribute [rw] value_frequency_lower_bound # @return [::Integer] # Lower bound on the value frequency of the values in this bucket. # @!attribute [rw] value_frequency_upper_bound # @return [::Integer] # Upper bound on the value frequency of the values in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of values in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Sample of value frequencies in this bucket. The total number of # values returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct values in this bucket. class CategoricalStatsHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the k-anonymity computation. # @!attribute [rw] equivalence_class_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityHistogramBucket>] # Histogram of k-anonymity equivalence classes. class KAnonymityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Set of values defining the equivalence class. One value per # quasi-identifier column in the original KAnonymity metric message. # The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the equivalence class, for example number of rows with the # above set of values. class KAnonymityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of k-anonymity equivalence classes. # @!attribute [rw] equivalence_class_size_lower_bound # @return [::Integer] # Lower bound on the size of the equivalence classes in this bucket. # @!attribute [rw] equivalence_class_size_upper_bound # @return [::Integer] # Upper bound on the size of the equivalence classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KAnonymityResult::KAnonymityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class KAnonymityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the l-diversity computation. # @!attribute [rw] sensitive_value_frequency_histogram_buckets # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityHistogramBucket>] # Histogram of l-diversity equivalence class sensitive value frequencies. class LDiversityResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # The set of columns' values that share the same ldiversity value. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # Quasi-identifier values defining the k-anonymity equivalence # class. The order is always the same as the original request. # @!attribute [rw] equivalence_class_size # @return [::Integer] # Size of the k-anonymity equivalence class. # @!attribute [rw] num_distinct_sensitive_values # @return [::Integer] # Number of distinct sensitive values in this equivalence class. # @!attribute [rw] top_sensitive_values # @return [::Array<::Google::Cloud::Dlp::V2::ValueFrequency>] # Estimated frequencies of top sensitive values. class LDiversityEquivalenceClass include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # Histogram of l-diversity equivalence class sensitive value frequencies. # @!attribute [rw] sensitive_value_frequency_lower_bound # @return [::Integer] # Lower bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] sensitive_value_frequency_upper_bound # @return [::Integer] # Upper bound on the sensitive value frequencies of the equivalence # classes in this bucket. # @!attribute [rw] bucket_size # @return [::Integer] # Total number of equivalence classes in this bucket. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::LDiversityResult::LDiversityEquivalenceClass>] # Sample of equivalence classes in this bucket. The total number of # classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct equivalence classes in this bucket. class LDiversityHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the reidentifiability analysis. Note that these results are an # estimation, not exact values. # @!attribute [rw] k_map_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationHistogramBucket>] # The intervals [min_anonymity, max_anonymity] do not overlap. If a value # doesn't correspond to any such interval, the associated frequency is # zero. For example, the following records: # \\{min_anonymity: 1, max_anonymity: 1, frequency: 17} # \\{min_anonymity: 2, max_anonymity: 3, frequency: 42} # \\{min_anonymity: 5, max_anonymity: 10, frequency: 99} # mean that there are no record with an estimated anonymity of 4, 5, or # larger than 10. class KMapEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_anonymity # @return [::Integer] # The estimated anonymity for these quasi-identifier values. class KMapEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A KMapEstimationHistogramBucket message with the following values: # min_anonymity: 3 # max_anonymity: 5 # frequency: 42 # means that there are 42 records whose quasi-identifier values correspond # to 3, 4 or 5 people in the overlying population. An important particular # case is when min_anonymity = max_anonymity = 1: the frequency field then # corresponds to the number of uniquely identifiable records. # @!attribute [rw] min_anonymity # @return [::Integer] # Always positive. # @!attribute [rw] max_anonymity # @return [::Integer] # Always greater than or equal to min_anonymity. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these anonymity bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::KMapEstimationResult::KMapEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class KMapEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Result of the δ-presence computation. Note that these results are an # estimation, not exact values. # @!attribute [rw] delta_presence_estimation_histogram # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationHistogramBucket>] # The intervals [min_probability, max_probability) do not overlap. If a # value doesn't correspond to any such interval, the associated frequency # is zero. For example, the following records: # \\{min_probability: 0, max_probability: 0.1, frequency: 17} # \\{min_probability: 0.2, max_probability: 0.3, frequency: 42} # \\{min_probability: 0.3, max_probability: 0.4, frequency: 99} # mean that there are no record with an estimated probability in [0.1, 0.2) # nor larger or equal to 0.4. class DeltaPresenceEstimationResult include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods # A tuple of values for the quasi-identifier columns. # @!attribute [rw] quasi_ids_values # @return [::Array<::Google::Cloud::Dlp::V2::Value>] # The quasi-identifier values. # @!attribute [rw] estimated_probability # @return [::Float] # The estimated probability that a given individual sharing these # quasi-identifier values is in the dataset. This value, typically # called δ, is the ratio between the number of records in the dataset # with these quasi-identifier values, and the total number of individuals # (inside *and* outside the dataset) with these quasi-identifier values. # For example, if there are 15 individuals in the dataset who share the # same quasi-identifier values, and an estimated 100 people in the entire # population with these values, then δ is 0.15. class DeltaPresenceEstimationQuasiIdValues include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end # A DeltaPresenceEstimationHistogramBucket message with the following # values: # min_probability: 0.1 # max_probability: 0.2 # frequency: 42 # means that there are 42 records for which δ is in [0.1, 0.2). An # important particular case is when min_probability = max_probability = 1: # then, every individual who shares this quasi-identifier combination is in # the dataset. # @!attribute [rw] min_probability # @return [::Float] # Between 0 and 1. # @!attribute [rw] max_probability # @return [::Float] # Always greater than or equal to min_probability. # @!attribute [rw] bucket_size # @return [::Integer] # Number of records within these probability bounds. # @!attribute [rw] bucket_values # @return [::Array<::Google::Cloud::Dlp::V2::AnalyzeDataSourceRiskDetails::DeltaPresenceEstimationResult::DeltaPresenceEstimationQuasiIdValues>] # Sample of quasi-identifier tuple values in this bucket. The total # number of classes returned per bucket is capped at 20. # @!attribute [rw] bucket_value_count # @return [::Integer] # Total number of distinct quasi-identifier tuple values in this bucket. class DeltaPresenceEstimationHistogramBucket include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end # Risk analysis options. # @!attribute [rw] job_config # @return [::Google::Cloud::Dlp::V2::RiskAnalysisJobConfig] # The job config for the risk job. class RequestedRiskAnalysisOptions include ::Google::Protobuf::MessageExts extend ::Google::Protobuf::MessageExts::ClassMethods end end |