diff --git a/java-dataplex/README.md b/java-dataplex/README.md
index 266ac5264ff7..06ffd8a18f1c 100644
--- a/java-dataplex/README.md
+++ b/java-dataplex/README.md
@@ -20,7 +20,7 @@ If you are using Maven with [BOM][libraries-bom], add this to your pom.xml file:
map<string, bool> dimension_passed = 3;
*/
boolean getDimensionPassedOrThrow(java.lang.String key);
+
+ /**
+ *
+ *
+ *
+ * The table-level data quality score for the data scan job. + * + * The data quality score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
float score = 4;
+ *
+ * @return The score.
+ */
+ float getScore();
+
+ /**
+ *
+ *
+ * + * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ int getDimensionScoreCount();
+ /**
+ *
+ *
+ * + * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ boolean containsDimensionScore(java.lang.String key);
+ /** Use {@link #getDimensionScoreMap()} instead. */
+ @java.lang.Deprecated
+ java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ float getDimensionScoreOrDefault(java.lang.String key, float defaultValue);
+ /**
+ *
+ *
+ * + * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ float getDimensionScoreOrThrow(java.lang.String key);
+
+ /**
+ *
+ *
+ * + * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ int getColumnScoreCount();
+ /**
+ *
+ *
+ * + * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ boolean containsColumnScore(java.lang.String key);
+ /** Use {@link #getColumnScoreMap()} instead. */
+ @java.lang.Deprecated
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ float getColumnScoreOrDefault(java.lang.String key, float defaultValue);
+ /**
+ *
+ *
+ * + * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ float getColumnScoreOrThrow(java.lang.String key);
}
/**
*
@@ -1449,6 +1623,10 @@ protected com.google.protobuf.MapField internalGetMapField(int number) {
switch (number) {
case 3:
return internalGetDimensionPassed();
+ case 5:
+ return internalGetDimensionScore();
+ case 6:
+ return internalGetColumnScore();
default:
throw new RuntimeException("Invalid map field number: " + number);
}
@@ -1615,105 +1793,412 @@ public boolean getDimensionPassedOrThrow(java.lang.String key) {
return map.get(key);
}
- private byte memoizedIsInitialized = -1;
-
+ public static final int SCORE_FIELD_NUMBER = 4;
+ private float score_ = 0F;
+ /**
+ *
+ *
+ * + * The table-level data quality score for the data scan job. + * + * The data quality score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
float score = 4;
+ *
+ * @return The score.
+ */
@java.lang.Override
- public final boolean isInitialized() {
- byte isInitialized = memoizedIsInitialized;
- if (isInitialized == 1) return true;
- if (isInitialized == 0) return false;
-
- memoizedIsInitialized = 1;
- return true;
+ public float getScore() {
+ return score_;
}
- @java.lang.Override
- public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io.IOException {
- if (rowCount_ != 0L) {
- output.writeInt64(1, rowCount_);
- }
- if (passed_ != false) {
- output.writeBool(2, passed_);
- }
- com.google.protobuf.GeneratedMessageV3.serializeStringMapTo(
- output, internalGetDimensionPassed(), DimensionPassedDefaultEntryHolder.defaultEntry, 3);
- getUnknownFields().writeTo(output);
+ public static final int DIMENSION_SCORE_FIELD_NUMBER = 5;
+
+ private static final class DimensionScoreDefaultEntryHolder {
+ static final com.google.protobuf.MapEntry+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
@java.lang.Override
- public boolean equals(final java.lang.Object obj) {
- if (obj == this) {
- return true;
+ public boolean containsDimensionScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
}
- if (!(obj instanceof com.google.cloud.dataplex.v1.DataScanEvent.DataQualityResult)) {
- return super.equals(obj);
+ return internalGetDimensionScore().getMap().containsKey(key);
+ }
+ /** Use {@link #getDimensionScoreMap()} instead. */
+ @java.lang.Override
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public float getDimensionScoreOrDefault(java.lang.String key, float defaultValue) {
+ if (key == null) {
+ throw new NullPointerException("map key");
}
- com.google.cloud.dataplex.v1.DataScanEvent.DataQualityResult other =
- (com.google.cloud.dataplex.v1.DataScanEvent.DataQualityResult) obj;
-
- if (getRowCount() != other.getRowCount()) return false;
- if (getPassed() != other.getPassed()) return false;
- if (!internalGetDimensionPassed().equals(other.internalGetDimensionPassed())) return false;
- if (!getUnknownFields().equals(other.getUnknownFields())) return false;
- return true;
+ java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
@java.lang.Override
- public int hashCode() {
- if (memoizedHashCode != 0) {
- return memoizedHashCode;
+ public float getDimensionScoreOrThrow(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
}
- int hash = 41;
- hash = (19 * hash) + getDescriptor().hashCode();
- hash = (37 * hash) + ROW_COUNT_FIELD_NUMBER;
- hash = (53 * hash) + com.google.protobuf.Internal.hashLong(getRowCount());
- hash = (37 * hash) + PASSED_FIELD_NUMBER;
- hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(getPassed());
- if (!internalGetDimensionPassed().getMap().isEmpty()) {
- hash = (37 * hash) + DIMENSION_PASSED_FIELD_NUMBER;
- hash = (53 * hash) + internalGetDimensionPassed().hashCode();
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public boolean containsColumnScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ return internalGetColumnScore().getMap().containsKey(key);
+ }
+ /** Use {@link #getColumnScoreMap()} instead. */
+ @java.lang.Override
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public float getColumnScoreOrDefault(java.lang.String key, float defaultValue) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public float getColumnScoreOrThrow(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The table-level data quality score for the data scan job. + * + * The data quality score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
float score = 4;
+ *
+ * @return The score.
+ */
+ @java.lang.Override
+ public float getScore() {
+ return score_;
+ }
+ /**
+ *
+ *
+ * + * The table-level data quality score for the data scan job. + * + * The data quality score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
float score = 4;
+ *
+ * @param value The score to set.
+ * @return This builder for chaining.
+ */
+ public Builder setScore(float value) {
+
+ score_ = value;
+ bitField0_ |= 0x00000008;
+ onChanged();
+ return this;
+ }
+ /**
+ *
+ *
+ * + * The table-level data quality score for the data scan job. + * + * The data quality score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
float score = 4;
+ *
+ * @return This builder for chaining.
+ */
+ public Builder clearScore() {
+ bitField0_ = (bitField0_ & ~0x00000008);
+ score_ = 0F;
+ onChanged();
+ return this;
+ }
+
+ private com.google.protobuf.MapField+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public boolean containsDimensionScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ return internalGetDimensionScore().getMap().containsKey(key);
+ }
+ /** Use {@link #getDimensionScoreMap()} instead. */
+ @java.lang.Override
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public float getDimensionScoreOrDefault(java.lang.String key, float defaultValue) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ @java.lang.Override
+ public float getDimensionScoreOrThrow(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ public Builder removeDimensionScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ internalGetMutableDimensionScore().getMutableMap().remove(key);
+ return this;
+ }
+ /** Use alternate mutation accessors instead. */
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ public Builder putDimensionScore(java.lang.String key, float value) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+
+ internalGetMutableDimensionScore().getMutableMap().put(key, value);
+ bitField0_ |= 0x00000010;
+ return this;
+ }
+ /**
+ *
+ *
+ * + * The score of each dimension for data quality result. + * The key of the map is the name of the dimension. + * The value is the data quality score for the dimension. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> dimension_score = 5;
+ */
+ public Builder putAllDimensionScore(java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public boolean containsColumnScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ return internalGetColumnScore().getMap().containsKey(key);
+ }
+ /** Use {@link #getColumnScoreMap()} instead. */
+ @java.lang.Override
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public float getColumnScoreOrDefault(java.lang.String key, float defaultValue) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ @java.lang.Override
+ public float getColumnScoreOrThrow(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ public Builder removeColumnScore(java.lang.String key) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+ internalGetMutableColumnScore().getMutableMap().remove(key);
+ return this;
+ }
+ /** Use alternate mutation accessors instead. */
+ @java.lang.Deprecated
+ public java.util.Map+ * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ public Builder putColumnScore(java.lang.String key, float value) {
+ if (key == null) {
+ throw new NullPointerException("map key");
+ }
+
+ internalGetMutableColumnScore().getMutableMap().put(key, value);
+ bitField0_ |= 0x00000020;
+ return this;
+ }
+ /**
+ *
+ *
+ * + * The score of each column scanned in the data scan job. + * The key of the map is the name of the column. + * The value is the data quality score for the column. + * + * The score ranges between [0, 100] (up to two decimal + * points). + *+ * + *
map<string, float> column_score = 6;
+ */
+ public Builder putAllColumnScore(java.util.MapACCESS_POLICY_UPDATE = 14;
*/
ACCESS_POLICY_UPDATE(14),
+ /**
+ *
+ *
+ * + * Number of resources matched with particular Query. + *+ * + *
GOVERNANCE_RULE_MATCHED_RESOURCES = 15;
+ */
+ GOVERNANCE_RULE_MATCHED_RESOURCES(15),
+ /**
+ *
+ *
+ * + * Rule processing exceeds the allowed limit. + *+ * + *
GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS = 16;
+ */
+ GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS(16),
+ /**
+ *
+ *
+ * + * Rule processing errors. + *+ * + *
GOVERNANCE_RULE_ERRORS = 17;
+ */
+ GOVERNANCE_RULE_ERRORS(17),
UNRECOGNIZED(-1),
;
@@ -336,6 +366,36 @@ public enum EventType implements com.google.protobuf.ProtocolMessageEnum {
* ACCESS_POLICY_UPDATE = 14;
*/
public static final int ACCESS_POLICY_UPDATE_VALUE = 14;
+ /**
+ *
+ *
+ * + * Number of resources matched with particular Query. + *+ * + *
GOVERNANCE_RULE_MATCHED_RESOURCES = 15;
+ */
+ public static final int GOVERNANCE_RULE_MATCHED_RESOURCES_VALUE = 15;
+ /**
+ *
+ *
+ * + * Rule processing exceeds the allowed limit. + *+ * + *
GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS = 16;
+ */
+ public static final int GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS_VALUE = 16;
+ /**
+ *
+ *
+ * + * Rule processing errors. + *+ * + *
GOVERNANCE_RULE_ERRORS = 17;
+ */
+ public static final int GOVERNANCE_RULE_ERRORS_VALUE = 17;
public final int getNumber() {
if (this == UNRECOGNIZED) {
@@ -387,6 +447,12 @@ public static EventType forNumber(int value) {
return BIGQUERY_POLICY_TAG_SET_IAM_POLICY;
case 14:
return ACCESS_POLICY_UPDATE;
+ case 15:
+ return GOVERNANCE_RULE_MATCHED_RESOURCES;
+ case 16:
+ return GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS;
+ case 17:
+ return GOVERNANCE_RULE_ERRORS;
default:
return null;
}
diff --git a/java-dataplex/proto-google-cloud-dataplex-v1/src/main/java/com/google/cloud/dataplex/v1/LogsProto.java b/java-dataplex/proto-google-cloud-dataplex-v1/src/main/java/com/google/cloud/dataplex/v1/LogsProto.java
index bfa5f54b3d9a..6d4595261eae 100644
--- a/java-dataplex/proto-google-cloud-dataplex-v1/src/main/java/com/google/cloud/dataplex/v1/LogsProto.java
+++ b/java-dataplex/proto-google-cloud-dataplex-v1/src/main/java/com/google/cloud/dataplex/v1/LogsProto.java
@@ -87,6 +87,14 @@ public static void registerAllExtensions(com.google.protobuf.ExtensionRegistry r
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionPassedEntry_descriptor;
static final com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionPassedEntry_fieldAccessorTable;
+ static final com.google.protobuf.Descriptors.Descriptor
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionScoreEntry_descriptor;
+ static final com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionScoreEntry_fieldAccessorTable;
+ static final com.google.protobuf.Descriptors.Descriptor
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_ColumnScoreEntry_descriptor;
+ static final com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_ColumnScoreEntry_fieldAccessorTable;
static final com.google.protobuf.Descriptors.Descriptor
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataProfileAppliedConfigs_descriptor;
static final com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
@@ -184,8 +192,8 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
+ "\"=\n\006Engine\022\026\n\022ENGINE_UNSPECIFIED\020\000\022\r\n\tSP"
+ "ARK_SQL\020\001\022\014\n\010BIGQUERY\020\002\"S\n\tEventType\022\032\n\026"
+ "EVENT_TYPE_UNSPECIFIED\020\000\022\t\n\005START\020\001\022\010\n\004S"
- + "TOP\020\002\022\t\n\005QUERY\020\003\022\n\n\006CREATE\020\004B\010\n\006detail\"\255"
- + "\006\n\017GovernanceEvent\022\017\n\007message\030\001 \001(\t\022G\n\ne"
+ + "TOP\020\002\022\t\n\005QUERY\020\003\022\n\n\006CREATE\020\004B\010\n\006detail\"\232"
+ + "\007\n\017GovernanceEvent\022\017\n\007message\030\001 \001(\t\022G\n\ne"
+ "vent_type\030\002 \001(\01623.google.cloud.dataplex."
+ "v1.GovernanceEvent.EventType\022E\n\006entity\030\003"
+ " \001(\01320.google.cloud.dataplex.v1.Governan"
@@ -194,7 +202,7 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
+ "ity\022P\n\013entity_type\030\002 \001(\0162;.google.cloud."
+ "dataplex.v1.GovernanceEvent.Entity.Entit"
+ "yType\"A\n\nEntityType\022\033\n\027ENTITY_TYPE_UNSPE"
- + "CIFIED\020\000\022\t\n\005TABLE\020\001\022\013\n\007FILESET\020\002\"\230\003\n\tEve"
+ + "CIFIED\020\000\022\t\n\005TABLE\020\001\022\013\n\007FILESET\020\002\"\205\004\n\tEve"
+ "ntType\022\032\n\026EVENT_TYPE_UNSPECIFIED\020\000\022\036\n\032RE"
+ "SOURCE_IAM_POLICY_UPDATE\020\001\022\031\n\025BIGQUERY_T"
+ "ABLE_CREATE\020\002\022\031\n\025BIGQUERY_TABLE_UPDATE\020\003"
@@ -205,84 +213,95 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
+ "QUERY_POLICY_TAG_CREATE\020\013\022\036\n\032BIGQUERY_PO"
+ "LICY_TAG_DELETE\020\014\022&\n\"BIGQUERY_POLICY_TAG"
+ "_SET_IAM_POLICY\020\r\022\030\n\024ACCESS_POLICY_UPDAT"
- + "E\020\016B\t\n\007_entity\"\257\020\n\rDataScanEvent\022\023\n\013data"
- + "_source\030\001 \001(\t\022\016\n\006job_id\030\002 \001(\t\022/\n\013create_"
- + "time\030\014 \001(\0132\032.google.protobuf.Timestamp\022."
- + "\n\nstart_time\030\003 \001(\0132\032.google.protobuf.Tim"
- + "estamp\022,\n\010end_time\030\004 \001(\0132\032.google.protob"
- + "uf.Timestamp\022>\n\004type\030\005 \001(\01620.google.clou"
- + "d.dataplex.v1.DataScanEvent.ScanType\022<\n\005"
- + "state\030\006 \001(\0162-.google.cloud.dataplex.v1.D"
- + "ataScanEvent.State\022\017\n\007message\030\007 \001(\t\022\024\n\014s"
- + "pec_version\030\010 \001(\t\022@\n\007trigger\030\t \001(\0162/.goo"
- + "gle.cloud.dataplex.v1.DataScanEvent.Trig"
- + "ger\022<\n\005scope\030\n \001(\0162-.google.cloud.datapl"
- + "ex.v1.DataScanEvent.Scope\022Q\n\014data_profil"
- + "e\030e \001(\01329.google.cloud.dataplex.v1.DataS"
- + "canEvent.DataProfileResultH\000\022Q\n\014data_qua"
- + "lity\030f \001(\01329.google.cloud.dataplex.v1.Da"
- + "taScanEvent.DataQualityResultH\000\022b\n\024data_"
- + "profile_configs\030\311\001 \001(\0132A.google.cloud.da"
- + "taplex.v1.DataScanEvent.DataProfileAppli"
- + "edConfigsH\001\022b\n\024data_quality_configs\030\312\001 \001"
- + "(\0132A.google.cloud.dataplex.v1.DataScanEv"
- + "ent.DataQualityAppliedConfigsH\001\022_\n\030post_"
- + "scan_actions_result\030\013 \001(\0132=.google.cloud"
- + ".dataplex.v1.DataScanEvent.PostScanActio"
- + "nsResult\032&\n\021DataProfileResult\022\021\n\trow_cou"
- + "nt\030\001 \001(\003\032\330\001\n\021DataQualityResult\022\021\n\trow_co"
- + "unt\030\001 \001(\003\022\016\n\006passed\030\002 \001(\010\022h\n\020dimension_p"
- + "assed\030\003 \003(\0132N.google.cloud.dataplex.v1.D"
- + "ataScanEvent.DataQualityResult.Dimension"
- + "PassedEntry\0326\n\024DimensionPassedEntry\022\013\n\003k"
- + "ey\030\001 \001(\t\022\r\n\005value\030\002 \001(\010:\0028\001\032p\n\031DataProfi"
- + "leAppliedConfigs\022\030\n\020sampling_percent\030\001 \001"
- + "(\002\022\032\n\022row_filter_applied\030\002 \001(\010\022\035\n\025column"
- + "_filter_applied\030\003 \001(\010\032Q\n\031DataQualityAppl"
- + "iedConfigs\022\030\n\020sampling_percent\030\001 \001(\002\022\032\n\022"
- + "row_filter_applied\030\002 \001(\010\032\346\002\n\025PostScanAct"
- + "ionsResult\022r\n\026bigquery_export_result\030\001 \001"
- + "(\0132R.google.cloud.dataplex.v1.DataScanEv"
- + "ent.PostScanActionsResult.BigQueryExport"
- + "Result\032\330\001\n\024BigQueryExportResult\022g\n\005state"
- + "\030\001 \001(\0162X.google.cloud.dataplex.v1.DataSc"
- + "anEvent.PostScanActionsResult.BigQueryEx"
- + "portResult.State\022\017\n\007message\030\002 \001(\t\"F\n\005Sta"
- + "te\022\025\n\021STATE_UNSPECIFIED\020\000\022\r\n\tSUCCEEDED\020\001"
- + "\022\n\n\006FAILED\020\002\022\013\n\007SKIPPED\020\003\"I\n\010ScanType\022\031\n"
- + "\025SCAN_TYPE_UNSPECIFIED\020\000\022\020\n\014DATA_PROFILE"
- + "\020\001\022\020\n\014DATA_QUALITY\020\002\"b\n\005State\022\025\n\021STATE_U"
- + "NSPECIFIED\020\000\022\013\n\007STARTED\020\001\022\r\n\tSUCCEEDED\020\002"
- + "\022\n\n\006FAILED\020\003\022\r\n\tCANCELLED\020\004\022\013\n\007CREATED\020\005"
- + "\"?\n\007Trigger\022\027\n\023TRIGGER_UNSPECIFIED\020\000\022\r\n\t"
- + "ON_DEMAND\020\001\022\014\n\010SCHEDULE\020\002\"9\n\005Scope\022\025\n\021SC"
- + "OPE_UNSPECIFIED\020\000\022\010\n\004FULL\020\001\022\017\n\013INCREMENT"
- + "AL\020\002B\010\n\006resultB\020\n\016appliedConfigs\"\351\006\n\031Dat"
- + "aQualityScanRuleResult\022\016\n\006job_id\030\001 \001(\t\022\023"
- + "\n\013data_source\030\002 \001(\t\022\016\n\006column\030\003 \001(\t\022\021\n\tr"
- + "ule_name\030\004 \001(\t\022O\n\trule_type\030\005 \001(\0162<.goog"
- + "le.cloud.dataplex.v1.DataQualityScanRule"
- + "Result.RuleType\022Z\n\016evalution_type\030\006 \001(\0162"
- + "B.google.cloud.dataplex.v1.DataQualitySc"
- + "anRuleResult.EvaluationType\022\026\n\016rule_dime"
- + "nsion\030\007 \001(\t\022\031\n\021threshold_percent\030\010 \001(\001\022J"
- + "\n\006result\030\t \001(\0162:.google.cloud.dataplex.v"
- + "1.DataQualityScanRuleResult.Result\022\033\n\023ev"
- + "aluated_row_count\030\n \001(\003\022\030\n\020passed_row_co"
- + "unt\030\013 \001(\003\022\026\n\016null_row_count\030\014 \001(\003\"\377\001\n\010Ru"
- + "leType\022\031\n\025RULE_TYPE_UNSPECIFIED\020\000\022\030\n\024NON"
- + "_NULL_EXPECTATION\020\001\022\025\n\021RANGE_EXPECTATION"
- + "\020\002\022\025\n\021REGEX_EXPECTATION\020\003\022\035\n\031ROW_CONDITI"
- + "ON_EXPECTATION\020\004\022\023\n\017SET_EXPECTATION\020\005\022\037\n"
- + "\033STATISTIC_RANGE_EXPECTATION\020\006\022\037\n\033TABLE_"
- + "CONDITION_EXPECTATION\020\007\022\032\n\026UNIQUENESS_EX"
- + "PECTATION\020\010\"M\n\016EvaluationType\022\037\n\033EVALUAT"
- + "ION_TYPE_UNSPECIFIED\020\000\022\013\n\007PER_ROW\020\001\022\r\n\tA"
- + "GGREGATE\020\002\"8\n\006Result\022\026\n\022RESULT_UNSPECIFI"
- + "ED\020\000\022\n\n\006PASSED\020\001\022\n\n\006FAILED\020\002Be\n\034com.goog"
- + "le.cloud.dataplex.v1B\tLogsProtoP\001Z8cloud"
- + ".google.com/go/dataplex/apiv1/dataplexpb"
- + ";dataplexpbb\006proto3"
+ + "E\020\016\022%\n!GOVERNANCE_RULE_MATCHED_RESOURCES"
+ + "\020\017\022(\n$GOVERNANCE_RULE_SEARCH_LIMIT_EXCEE"
+ + "DS\020\020\022\032\n\026GOVERNANCE_RULE_ERRORS\020\021B\t\n\007_ent"
+ + "ity\"\363\022\n\rDataScanEvent\022\023\n\013data_source\030\001 \001"
+ + "(\t\022\016\n\006job_id\030\002 \001(\t\022/\n\013create_time\030\014 \001(\0132"
+ + "\032.google.protobuf.Timestamp\022.\n\nstart_tim"
+ + "e\030\003 \001(\0132\032.google.protobuf.Timestamp\022,\n\010e"
+ + "nd_time\030\004 \001(\0132\032.google.protobuf.Timestam"
+ + "p\022>\n\004type\030\005 \001(\01620.google.cloud.dataplex."
+ + "v1.DataScanEvent.ScanType\022<\n\005state\030\006 \001(\016"
+ + "2-.google.cloud.dataplex.v1.DataScanEven"
+ + "t.State\022\017\n\007message\030\007 \001(\t\022\024\n\014spec_version"
+ + "\030\010 \001(\t\022@\n\007trigger\030\t \001(\0162/.google.cloud.d"
+ + "ataplex.v1.DataScanEvent.Trigger\022<\n\005scop"
+ + "e\030\n \001(\0162-.google.cloud.dataplex.v1.DataS"
+ + "canEvent.Scope\022Q\n\014data_profile\030e \001(\01329.g"
+ + "oogle.cloud.dataplex.v1.DataScanEvent.Da"
+ + "taProfileResultH\000\022Q\n\014data_quality\030f \001(\0132"
+ + "9.google.cloud.dataplex.v1.DataScanEvent"
+ + ".DataQualityResultH\000\022b\n\024data_profile_con"
+ + "figs\030\311\001 \001(\0132A.google.cloud.dataplex.v1.D"
+ + "ataScanEvent.DataProfileAppliedConfigsH\001"
+ + "\022b\n\024data_quality_configs\030\312\001 \001(\0132A.google"
+ + ".cloud.dataplex.v1.DataScanEvent.DataQua"
+ + "lityAppliedConfigsH\001\022_\n\030post_scan_action"
+ + "s_result\030\013 \001(\0132=.google.cloud.dataplex.v"
+ + "1.DataScanEvent.PostScanActionsResult\032&\n"
+ + "\021DataProfileResult\022\021\n\trow_count\030\001 \001(\003\032\234\004"
+ + "\n\021DataQualityResult\022\021\n\trow_count\030\001 \001(\003\022\016"
+ + "\n\006passed\030\002 \001(\010\022h\n\020dimension_passed\030\003 \003(\013"
+ + "2N.google.cloud.dataplex.v1.DataScanEven"
+ + "t.DataQualityResult.DimensionPassedEntry"
+ + "\022\r\n\005score\030\004 \001(\002\022f\n\017dimension_score\030\005 \003(\013"
+ + "2M.google.cloud.dataplex.v1.DataScanEven"
+ + "t.DataQualityResult.DimensionScoreEntry\022"
+ + "`\n\014column_score\030\006 \003(\0132J.google.cloud.dat"
+ + "aplex.v1.DataScanEvent.DataQualityResult"
+ + ".ColumnScoreEntry\0326\n\024DimensionPassedEntr"
+ + "y\022\013\n\003key\030\001 \001(\t\022\r\n\005value\030\002 \001(\010:\0028\001\0325\n\023Dim"
+ + "ensionScoreEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005value\030\002"
+ + " \001(\002:\0028\001\0322\n\020ColumnScoreEntry\022\013\n\003key\030\001 \001("
+ + "\t\022\r\n\005value\030\002 \001(\002:\0028\001\032p\n\031DataProfileAppli"
+ + "edConfigs\022\030\n\020sampling_percent\030\001 \001(\002\022\032\n\022r"
+ + "ow_filter_applied\030\002 \001(\010\022\035\n\025column_filter"
+ + "_applied\030\003 \001(\010\032Q\n\031DataQualityAppliedConf"
+ + "igs\022\030\n\020sampling_percent\030\001 \001(\002\022\032\n\022row_fil"
+ + "ter_applied\030\002 \001(\010\032\346\002\n\025PostScanActionsRes"
+ + "ult\022r\n\026bigquery_export_result\030\001 \001(\0132R.go"
+ + "ogle.cloud.dataplex.v1.DataScanEvent.Pos"
+ + "tScanActionsResult.BigQueryExportResult\032"
+ + "\330\001\n\024BigQueryExportResult\022g\n\005state\030\001 \001(\0162"
+ + "X.google.cloud.dataplex.v1.DataScanEvent"
+ + ".PostScanActionsResult.BigQueryExportRes"
+ + "ult.State\022\017\n\007message\030\002 \001(\t\"F\n\005State\022\025\n\021S"
+ + "TATE_UNSPECIFIED\020\000\022\r\n\tSUCCEEDED\020\001\022\n\n\006FAI"
+ + "LED\020\002\022\013\n\007SKIPPED\020\003\"I\n\010ScanType\022\031\n\025SCAN_T"
+ + "YPE_UNSPECIFIED\020\000\022\020\n\014DATA_PROFILE\020\001\022\020\n\014D"
+ + "ATA_QUALITY\020\002\"b\n\005State\022\025\n\021STATE_UNSPECIF"
+ + "IED\020\000\022\013\n\007STARTED\020\001\022\r\n\tSUCCEEDED\020\002\022\n\n\006FAI"
+ + "LED\020\003\022\r\n\tCANCELLED\020\004\022\013\n\007CREATED\020\005\"?\n\007Tri"
+ + "gger\022\027\n\023TRIGGER_UNSPECIFIED\020\000\022\r\n\tON_DEMA"
+ + "ND\020\001\022\014\n\010SCHEDULE\020\002\"9\n\005Scope\022\025\n\021SCOPE_UNS"
+ + "PECIFIED\020\000\022\010\n\004FULL\020\001\022\017\n\013INCREMENTAL\020\002B\010\n"
+ + "\006resultB\020\n\016appliedConfigs\"\351\006\n\031DataQualit"
+ + "yScanRuleResult\022\016\n\006job_id\030\001 \001(\t\022\023\n\013data_"
+ + "source\030\002 \001(\t\022\016\n\006column\030\003 \001(\t\022\021\n\trule_nam"
+ + "e\030\004 \001(\t\022O\n\trule_type\030\005 \001(\0162<.google.clou"
+ + "d.dataplex.v1.DataQualityScanRuleResult."
+ + "RuleType\022Z\n\016evalution_type\030\006 \001(\0162B.googl"
+ + "e.cloud.dataplex.v1.DataQualityScanRuleR"
+ + "esult.EvaluationType\022\026\n\016rule_dimension\030\007"
+ + " \001(\t\022\031\n\021threshold_percent\030\010 \001(\001\022J\n\006resul"
+ + "t\030\t \001(\0162:.google.cloud.dataplex.v1.DataQ"
+ + "ualityScanRuleResult.Result\022\033\n\023evaluated"
+ + "_row_count\030\n \001(\003\022\030\n\020passed_row_count\030\013 \001"
+ + "(\003\022\026\n\016null_row_count\030\014 \001(\003\"\377\001\n\010RuleType\022"
+ + "\031\n\025RULE_TYPE_UNSPECIFIED\020\000\022\030\n\024NON_NULL_E"
+ + "XPECTATION\020\001\022\025\n\021RANGE_EXPECTATION\020\002\022\025\n\021R"
+ + "EGEX_EXPECTATION\020\003\022\035\n\031ROW_CONDITION_EXPE"
+ + "CTATION\020\004\022\023\n\017SET_EXPECTATION\020\005\022\037\n\033STATIS"
+ + "TIC_RANGE_EXPECTATION\020\006\022\037\n\033TABLE_CONDITI"
+ + "ON_EXPECTATION\020\007\022\032\n\026UNIQUENESS_EXPECTATI"
+ + "ON\020\010\"M\n\016EvaluationType\022\037\n\033EVALUATION_TYP"
+ + "E_UNSPECIFIED\020\000\022\013\n\007PER_ROW\020\001\022\r\n\tAGGREGAT"
+ + "E\020\002\"8\n\006Result\022\026\n\022RESULT_UNSPECIFIED\020\000\022\n\n"
+ + "\006PASSED\020\001\022\n\n\006FAILED\020\002Be\n\034com.google.clou"
+ + "d.dataplex.v1B\tLogsProtoP\001Z8cloud.google"
+ + ".com/go/dataplex/apiv1/dataplexpb;datapl"
+ + "expbb\006proto3"
};
descriptor =
com.google.protobuf.Descriptors.FileDescriptor.internalBuildGeneratedFileFrom(
@@ -448,7 +467,7 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
new com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_descriptor,
new java.lang.String[] {
- "RowCount", "Passed", "DimensionPassed",
+ "RowCount", "Passed", "DimensionPassed", "Score", "DimensionScore", "ColumnScore",
});
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionPassedEntry_descriptor =
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_descriptor
@@ -460,6 +479,26 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
new java.lang.String[] {
"Key", "Value",
});
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionScoreEntry_descriptor =
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_descriptor
+ .getNestedTypes()
+ .get(1);
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionScoreEntry_fieldAccessorTable =
+ new com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_DimensionScoreEntry_descriptor,
+ new java.lang.String[] {
+ "Key", "Value",
+ });
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_ColumnScoreEntry_descriptor =
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_descriptor
+ .getNestedTypes()
+ .get(2);
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_ColumnScoreEntry_fieldAccessorTable =
+ new com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
+ internal_static_google_cloud_dataplex_v1_DataScanEvent_DataQualityResult_ColumnScoreEntry_descriptor,
+ new java.lang.String[] {
+ "Key", "Value",
+ });
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataProfileAppliedConfigs_descriptor =
internal_static_google_cloud_dataplex_v1_DataScanEvent_descriptor.getNestedTypes().get(2);
internal_static_google_cloud_dataplex_v1_DataScanEvent_DataProfileAppliedConfigs_fieldAccessorTable =
diff --git a/java-dataplex/proto-google-cloud-dataplex-v1/src/main/proto/google/cloud/dataplex/v1/logs.proto b/java-dataplex/proto-google-cloud-dataplex-v1/src/main/proto/google/cloud/dataplex/v1/logs.proto
index 0691afbbbafd..768d79b6e89f 100644
--- a/java-dataplex/proto-google-cloud-dataplex-v1/src/main/proto/google/cloud/dataplex/v1/logs.proto
+++ b/java-dataplex/proto-google-cloud-dataplex-v1/src/main/proto/google/cloud/dataplex/v1/logs.proto
@@ -382,6 +382,15 @@ message GovernanceEvent {
// Access policy update event.
ACCESS_POLICY_UPDATE = 14;
+
+ // Number of resources matched with particular Query.
+ GOVERNANCE_RULE_MATCHED_RESOURCES = 15;
+
+ // Rule processing exceeds the allowed limit.
+ GOVERNANCE_RULE_SEARCH_LIMIT_EXCEEDS = 16;
+
+ // Rule processing errors.
+ GOVERNANCE_RULE_ERRORS = 17;
}
// The log message.
@@ -475,6 +484,28 @@ message DataScanEvent {
// The value is the bool value depicting whether the dimension result was
// `pass` or not.
map