- Resource: DlpJob
- JSON representation
- DlpJobType
- JobState
- AnalyzeDataSourceRiskDetails
- PrivacyMetric
- NumericalStatsConfig
- CategoricalStatsConfig
- KAnonymityConfig
- EntityId
- LDiversityConfig
- KMapEstimationConfig
- TaggedField
- AuxiliaryTable
- QuasiIdField
- DeltaPresenceEstimationConfig
- QuasiId
- StatisticalTable
- QuasiIdentifierField
- NumericalStatsResult
- CategoricalStatsResult
- CategoricalStatsHistogramBucket
- ValueFrequency
- KAnonymityResult
- KAnonymityHistogramBucket
- KAnonymityEquivalenceClass
- LDiversityResult
- LDiversityHistogramBucket
- LDiversityEquivalenceClass
- KMapEstimationResult
- KMapEstimationHistogramBucket
- KMapEstimationQuasiIdValues
- DeltaPresenceEstimationResult
- DeltaPresenceEstimationHistogramBucket
- DeltaPresenceEstimationQuasiIdValues
- RequestedRiskAnalysisOptions
- RiskAnalysisJobConfig
- InspectDataSourceDetails
- RequestedOptions
- Result
- InfoTypeStats
- HybridInspectStatistics
- ActionDetails
- DeidentifyDataSourceDetails
- RequestedDeidentifyOptions
- DeidentifyDataSourceStats
- Methods
Resource: DlpJob
Combines all of the information about a DLP job.
JSON representation |
---|
{ "name": string, "type": enum ( |
Fields | |
---|---|
name |
The server-assigned name. |
type |
The type of job. |
state |
State of a job. |
createTime |
Time when the job was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
startTime |
Time when the job started. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
endTime |
Time when the job finished. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
lastModified |
Time when the job was last modified by the system. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: |
jobTriggerName |
If created by a job trigger, the resource name of the trigger that instantiated the job. |
errors[] |
A stream of errors encountered running the job. |
actionDetails[] |
Events that should occur after the job has completed. |
Union field details . Job details. details can be only one of the following: |
|
riskDetails |
Results from analyzing risk of a data source. |
inspectDetails |
Results from inspecting a data source. |
DlpJobType
An enum to represent the various types of DLP jobs.
Enums | |
---|---|
DLP_JOB_TYPE_UNSPECIFIED |
Defaults to INSPECT_JOB. |
INSPECT_JOB |
The job inspected Google Cloud for sensitive data. |
RISK_ANALYSIS_JOB |
The job executed a Risk Analysis computation. |
JobState
Possible states of a job. New items may be added.
Enums | |
---|---|
JOB_STATE_UNSPECIFIED |
Unused. |
PENDING |
The job has not yet started. |
RUNNING |
The job is currently running. Once a job has finished it will transition to FAILED or DONE. |
DONE |
The job is no longer running. |
CANCELED |
The job was canceled before it could be completed. |
FAILED |
The job had an error and did not complete. |
ACTIVE |
The job is currently accepting findings via hybridInspect. A hybrid job in ACTIVE state may continue to have findings added to it through the calling of hybridInspect. After the job has finished no more calls to hybridInspect may be made. ACTIVE jobs can transition to DONE. |
AnalyzeDataSourceRiskDetails
Result of a risk analysis operation request.
JSON representation |
---|
{ "requestedPrivacyMetric": { object ( |
Fields | |
---|---|
requestedPrivacyMetric |
Privacy metric to compute. |
requestedSourceTable |
Input dataset to compute metrics over. |
requestedOptions |
The configuration used for this job. |
Union field result . Values associated with this metric. result can be only one of the following: |
|
numericalStatsResult |
Numerical stats result |
categoricalStatsResult |
Categorical stats result |
kAnonymityResult |
K-anonymity result |
lDiversityResult |
L-divesity result |
kMapEstimationResult |
K-map result |
deltaPresenceEstimationResult |
Delta-presence result |
PrivacyMetric
Privacy metric to compute for reidentification risk analysis.
JSON representation |
---|
{ // Union field |
Fields | |
---|---|
Union field type . Types of analysis. type can be only one of the following: |
|
numericalStatsConfig |
Numerical stats |
categoricalStatsConfig |
Categorical stats |
kAnonymityConfig |
K-anonymity |
lDiversityConfig |
l-diversity |
kMapEstimationConfig |
k-map |
deltaPresenceEstimationConfig |
delta-presence |
NumericalStatsConfig
Compute numerical stats over an individual column, including min, max, and quantiles.
JSON representation |
---|
{
"field": {
object ( |
Fields | |
---|---|
field |
Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time. |
CategoricalStatsConfig
Compute numerical stats over an individual column, including number of distinct values and value count distribution.
JSON representation |
---|
{
"field": {
object ( |
Fields | |
---|---|
field |
Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data. |
KAnonymityConfig
k-anonymity metric, used for analysis of reidentification risk.
JSON representation |
---|
{ "quasiIds": [ { object ( |
Fields | |
---|---|
quasiIds[] |
Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field. |
entityId |
Message indicating that multiple rows might be associated to a single individual. If the same entityId is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored. |
EntityId
An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the EntityId
might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity.
JSON representation |
---|
{
"field": {
object ( |
Fields | |
---|---|
field |
Composite key indicating which field contains the entity identifier. |
LDiversityConfig
l-diversity metric, used for analysis of reidentification risk.
JSON representation |
---|
{ "quasiIds": [ { object ( |
Fields | |
---|---|
quasiIds[] |
Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key. |
sensitiveAttribute |
Sensitive field for computing the l-value. |
KMapEstimationConfig
Reidentifiability metric. This corresponds to a risk model similar to what is called "journalist risk" in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset.
JSON representation |
---|
{ "quasiIds": [ { object ( |
Fields | |
---|---|
quasiIds[] |
Required. Fields considered to be quasi-identifiers. No two columns can have the same tag. |
regionCode |
ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code. |
auxiliaryTables[] |
Several auxiliary tables can be used in the analysis. Each customTag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table. |
TaggedField
A column with a semantic tag attached.
JSON representation |
---|
{ "field": { object ( |
Fields | |
---|---|
field |
Required. Identifies the column. |
Union field tag . Semantic tag that identifies what a column contains, to determine which statistical model to use to estimate the reidentifiability of each value. [required] tag can be only one of the following: |
|
infoType |
A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use infoTypes.list with the supportedBy=RISK_ANALYSIS filter. |
customTag |
A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below). |
inferred |
If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data |
AuxiliaryTable
An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
JSON representation |
---|
{ "table": { object ( |
Fields | |
---|---|
table |
Required. Auxiliary table location. |
quasiIds[] |
Required. Quasi-identifier columns. |
relativeFrequency |
Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero. |
QuasiIdField
A quasi-identifier column has a customTag, used to know which column in the data corresponds to which column in the statistical model.
JSON representation |
---|
{
"field": {
object ( |
Fields | |
---|---|
field |
Identifies the column. |
customTag |
A auxiliary field. |
DeltaPresenceEstimationConfig
δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead.
JSON representation |
---|
{ "quasiIds": [ { object ( |
Fields | |
---|---|
quasiIds[] |
Required. Fields considered to be quasi-identifiers. No two fields can have the same tag. |
regionCode |
ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code. |
auxiliaryTables[] |
Several auxiliary tables can be used in the analysis. Each customTag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table. |
QuasiId
A column with a semantic tag attached.
JSON representation |
---|
{ "field": { object ( |
Fields | |
---|---|
field |
Required. Identifies the column. |
Union field tag . Semantic tag that identifies what a column contains, to determine which statistical model to use to estimate the reidentifiability of each value. [required] tag can be only one of the following: |
|
infoType |
A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use infoTypes.list with the supportedBy=RISK_ANALYSIS filter. |
customTag |
A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below). |
inferred |
If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data |
StatisticalTable
An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
JSON representation |
---|
{ "table": { object ( |
Fields | |
---|---|
table |
Required. Auxiliary table location. |
quasiIds[] |
Required. Quasi-identifier columns. |
relativeFrequency |
Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero. |
QuasiIdentifierField
A quasi-identifier column has a customTag, used to know which column in the data corresponds to which column in the statistical model.
JSON representation |
---|
{
"field": {
object ( |
Fields | |
---|---|
field |
Identifies the column. |
customTag |
A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below). |
NumericalStatsResult
Result of the numerical stats computation.
JSON representation |
---|
{ "minValue": { object ( |
Fields | |
---|---|
minValue |
Minimum value appearing in the column. |
maxValue |
Maximum value appearing in the column. |
quantileValues[] |
List of 99 values that partition the set of field values into 100 equal sized buckets. |
CategoricalStatsResult
Result of the categorical stats computation.
JSON representation |
---|
{
"valueFrequencyHistogramBuckets": [
{
object ( |
Fields | |
---|---|
valueFrequencyHistogramBuckets[] |
Histogram of value frequencies in the column. |
CategoricalStatsHistogramBucket
Histogram of value frequencies in the column.
JSON representation |
---|
{
"valueFrequencyLowerBound": string,
"valueFrequencyUpperBound": string,
"bucketSize": string,
"bucketValues": [
{
object ( |
Fields | |
---|---|
valueFrequencyLowerBound |
Lower bound on the value frequency of the values in this bucket. |
valueFrequencyUpperBound |
Upper bound on the value frequency of the values in this bucket. |
bucketSize |
Total number of values in this bucket. |
bucketValues[] |
Sample of value frequencies in this bucket. The total number of values returned per bucket is capped at 20. |
bucketValueCount |
Total number of distinct values in this bucket. |
ValueFrequency
A value of a field, including its frequency.
JSON representation |
---|
{
"value": {
object ( |
Fields | |
---|---|
value |
A value contained in the field in question. |
count |
How many times the value is contained in the field. |
KAnonymityResult
Result of the k-anonymity computation.
JSON representation |
---|
{
"equivalenceClassHistogramBuckets": [
{
object ( |
Fields | |
---|---|
equivalenceClassHistogramBuckets[] |
Histogram of k-anonymity equivalence classes. |
KAnonymityHistogramBucket
Histogram of k-anonymity equivalence classes.
JSON representation |
---|
{
"equivalenceClassSizeLowerBound": string,
"equivalenceClassSizeUpperBound": string,
"bucketSize": string,
"bucketValues": [
{
object ( |
Fields | |
---|---|
equivalenceClassSizeLowerBound |
Lower bound on the size of the equivalence classes in this bucket. |
equivalenceClassSizeUpperBound |
Upper bound on the size of the equivalence classes in this bucket. |
bucketSize |
Total number of equivalence classes in this bucket. |
bucketValues[] |
Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20. |
bucketValueCount |
Total number of distinct equivalence classes in this bucket. |
KAnonymityEquivalenceClass
The set of columns' values that share the same ldiversity value
JSON representation |
---|
{
"quasiIdsValues": [
{
object ( |
Fields | |
---|---|
quasiIdsValues[] |
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. |
equivalenceClassSize |
Size of the equivalence class, for example number of rows with the above set of values. |
LDiversityResult
Result of the l-diversity computation.
JSON representation |
---|
{
"sensitiveValueFrequencyHistogramBuckets": [
{
object ( |
Fields | |
---|---|
sensitiveValueFrequencyHistogramBuckets[] |
Histogram of l-diversity equivalence class sensitive value frequencies. |
LDiversityHistogramBucket
Histogram of l-diversity equivalence class sensitive value frequencies.
JSON representation |
---|
{
"sensitiveValueFrequencyLowerBound": string,
"sensitiveValueFrequencyUpperBound": string,
"bucketSize": string,
"bucketValues": [
{
object ( |
Fields | |
---|---|
sensitiveValueFrequencyLowerBound |
Lower bound on the sensitive value frequencies of the equivalence classes in this bucket. |
sensitiveValueFrequencyUpperBound |
Upper bound on the sensitive value frequencies of the equivalence classes in this bucket. |
bucketSize |
Total number of equivalence classes in this bucket. |
bucketValues[] |
Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20. |
bucketValueCount |
Total number of distinct equivalence classes in this bucket. |
LDiversityEquivalenceClass
The set of columns' values that share the same ldiversity value.
JSON representation |
---|
{ "quasiIdsValues": [ { object ( |
Fields | |
---|---|
quasiIdsValues[] |
Quasi-identifier values defining the k-anonymity equivalence class. The order is always the same as the original request. |
equivalenceClassSize |
Size of the k-anonymity equivalence class. |
numDistinctSensitiveValues |
Number of distinct sensitive values in this equivalence class. |
topSensitiveValues[] |
Estimated frequencies of top sensitive values. |
KMapEstimationResult
Result of the reidentifiability analysis. Note that these results are an estimation, not exact values.
JSON representation |
---|
{
"kMapEstimationHistogram": [
{
object ( |
Fields | |
---|---|
kMapEstimationHistogram[] |
The intervals [minAnonymity, maxAnonymity] do not overlap. If a value doesn't correspond to any such interval, the associated frequency is zero. For example, the following records: {minAnonymity: 1, maxAnonymity: 1, frequency: 17} {minAnonymity: 2, maxAnonymity: 3, frequency: 42} {minAnonymity: 5, maxAnonymity: 10, frequency: 99} mean that there are no record with an estimated anonymity of 4, 5, or larger than 10. |
KMapEstimationHistogramBucket
A KMapEstimationHistogramBucket message with the following values: minAnonymity: 3 maxAnonymity: 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 minAnonymity = maxAnonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.
JSON representation |
---|
{
"minAnonymity": string,
"maxAnonymity": string,
"bucketSize": string,
"bucketValues": [
{
object ( |
Fields | |
---|---|
minAnonymity |
Always positive. |
maxAnonymity |
Always greater than or equal to minAnonymity. |
bucketSize |
Number of records within these anonymity bounds. |
bucketValues[] |
Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20. |
bucketValueCount |
Total number of distinct quasi-identifier tuple values in this bucket. |
KMapEstimationQuasiIdValues
A tuple of values for the quasi-identifier columns.
JSON representation |
---|
{
"quasiIdsValues": [
{
object ( |
Fields | |
---|---|
quasiIdsValues[] |
The quasi-identifier values. |
estimatedAnonymity |
The estimated anonymity for these quasi-identifier values. |
DeltaPresenceEstimationResult
Result of the δ-presence computation. Note that these results are an estimation, not exact values.
JSON representation |
---|
{
"deltaPresenceEstimationHistogram": [
{
object ( |
Fields | |
---|---|
deltaPresenceEstimationHistogram[] |
The intervals [minProbability, maxProbability) do not overlap. If a value doesn't correspond to any such interval, the associated frequency is zero. For example, the following records: {minProbability: 0, maxProbability: 0.1, frequency: 17} {minProbability: 0.2, maxProbability: 0.3, frequency: 42} {minProbability: 0.3, maxProbability: 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. |
DeltaPresenceEstimationHistogramBucket
A DeltaPresenceEstimationHistogramBucket message with the following values: minProbability: 0.1 maxProbability: 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 minProbability = maxProbability = 1: then, every individual who shares this quasi-identifier combination is in the dataset.
JSON representation |
---|
{
"minProbability": number,
"maxProbability": number,
"bucketSize": string,
"bucketValues": [
{
object ( |
Fields | |
---|---|
minProbability |
Between 0 and 1. |
maxProbability |
Always greater than or equal to minProbability. |
bucketSize |
Number of records within these probability bounds. |
bucketValues[] |
Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20. |
bucketValueCount |
Total number of distinct quasi-identifier tuple values in this bucket. |
DeltaPresenceEstimationQuasiIdValues
A tuple of values for the quasi-identifier columns.
JSON representation |
---|
{
"quasiIdsValues": [
{
object ( |
Fields | |
---|---|
quasiIdsValues[] |
The quasi-identifier values. |
estimatedProbability |
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. |
RequestedRiskAnalysisOptions
Risk analysis options.
JSON representation |
---|
{
"jobConfig": {
object ( |
Fields | |
---|---|
jobConfig |
The job config for the risk job. |
RiskAnalysisJobConfig
Configuration for a risk analysis job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-risk-analysis to learn more.
JSON representation |
---|
{ "privacyMetric": { object ( |
Fields | |
---|---|
privacyMetric |
Privacy metric to compute. |
sourceTable |
Input dataset to compute metrics over. |
actions[] |
Actions to execute at the completion of the job. Are executed in the order provided. |
InspectDataSourceDetails
The results of an inspect DataSource job.
JSON representation |
---|
{ "requestedOptions": { object ( |
Fields | |
---|---|
requestedOptions |
The configuration used for this job. |
result |
A summary of the outcome of this inspection job. |
RequestedOptions
Snapshot of the inspection configuration.
JSON representation |
---|
{ "snapshotInspectTemplate": { object ( |
Fields | |
---|---|
snapshotInspectTemplate |
If run with an InspectTemplate, a snapshot of its state at the time of this run. |
jobConfig |
Inspect config. |
Result
All result fields mentioned below are updated while the job is processing.
JSON representation |
---|
{ "processedBytes": string, "totalEstimatedBytes": string, "infoTypeStats": [ { object ( |
Fields | |
---|---|
processedBytes |
Total size in bytes that were processed. |
totalEstimatedBytes |
Estimate of the number of bytes to process. |
infoTypeStats[] |
Statistics of how many instances of each info type were found during inspect job. |
numRowsProcessed |
Number of rows scanned after sampling and time filtering (applicable for row based stores such as BigQuery). |
hybridStats |
Statistics related to the processing of hybrid inspect. |
InfoTypeStats
Statistics regarding a specific InfoType.
JSON representation |
---|
{
"infoType": {
object ( |
Fields | |
---|---|
infoType |
The type of finding this stat is for. |
count |
Number of findings for this infoType. |
HybridInspectStatistics
Statistics related to processing hybrid inspect requests.
JSON representation |
---|
{ "processedCount": string, "abortedCount": string, "pendingCount": string } |
Fields | |
---|---|
processedCount |
The number of hybrid inspection requests processed within this job. |
abortedCount |
The number of hybrid inspection requests aborted because the job ran out of quota or was ended before they could be processed. |
pendingCount |
The number of hybrid requests currently being processed. Only populated when called via method |
ActionDetails
The results of an Action
.
JSON representation |
---|
{ // Union field |
Fields | |
---|---|
Union field details . Summary of what occurred in the actions. details can be only one of the following: |
|
deidentifyDetails |
Outcome of a de-identification action. |
DeidentifyDataSourceDetails
The results of a Deidentify
action from an inspect job.
JSON representation |
---|
{ "requestedOptions": { object ( |
Fields | |
---|---|
requestedOptions |
De-identification config used for the request. |
deidentifyStats |
Stats about the de-identification operation. |
RequestedDeidentifyOptions
De-identification options.
JSON representation |
---|
{ "snapshotDeidentifyTemplate": { object ( |
Fields | |
---|---|
snapshotDeidentifyTemplate |
Snapshot of the state of the |
snapshotStructuredDeidentifyTemplate |
Snapshot of the state of the structured |
snapshotImageRedactTemplate |
Snapshot of the state of the image transformation |
DeidentifyDataSourceStats
Summary of what was modified during a transformation.
JSON representation |
---|
{ "transformedBytes": string, "transformationCount": string, "transformationErrorCount": string } |
Fields | |
---|---|
transformedBytes |
Total size in bytes that were transformed in some way. |
transformationCount |
Number of successfully applied transformations. |
transformationErrorCount |
Number of errors encountered while trying to apply transformations. |
Methods |
|
---|---|
|
Starts asynchronous cancellation on a long-running DlpJob. |
|
Creates a new job to inspect storage or calculate risk metrics. |
|
Deletes a long-running DlpJob. |
|
Gets the latest state of a long-running DlpJob. |
|
Lists DlpJobs that match the specified filter in the request. |