The following examples demonstrate using the Cloud Data Loss Prevention API to scan a 1000-row subset of a BigQuery table. The scan starts from a random row.
Explore further
For detailed documentation that includes this code sample, see the following:
Code sample
C#
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
using
Google.Api.Gax.ResourceNames
;
using
Google.Cloud.Dlp.V2
;
using
Google.Cloud.PubSub.V1
;
using
System.Collections.Generic
;
using
System.Threading
;
using
System.Threading.Tasks
;
using
static
Google
.
Cloud
.
Dlp
.
V2
.
InspectConfig
.
Types
;
public
class
InspectBigQueryWithSampling
{
public
static
async
Task<DlpJob>
InspectAsync
(
string
projectId
,
int
maxFindings
,
bool
includeQuote
,
string
topicId
,
string
subId
,
Likelihood
minLikelihood
=
Likelihood
.
Possible
,
IEnumerable<FieldId>
identifyingFields
=
null
,
IEnumerable<InfoType>
infoTypes
=
null
)
{
// Instantiate the dlp client.
var
dlp
=
DlpServiceClient
.
Create
();
// Construct Storage config.
var
storageConfig
=
new
StorageConfig
{
BigQueryOptions
=
new
BigQueryOptions
{
TableReference
=
new
BigQueryTable
{
ProjectId
=
"bigquery-public-data"
,
DatasetId
=
"usa_names"
,
TableId
=
"usa_1910_current"
,
},
IdentifyingFields
=
{
identifyingFields
??
new
FieldId
[]
{
new
FieldId
{
Name
=
"name"
}
}
},
RowsLimit
=
100
,
SampleMethod
=
BigQueryOptions
.
Types
.
SampleMethod
.
RandomStart
}
};
// Construct the inspect config.
var
inspectConfig
=
new
InspectConfig
{
InfoTypes
=
{
infoTypes
??
new
InfoType
[]
{
new
InfoType
{
Name
=
"PERSON_NAME"
}
}
},
Limits
=
new
FindingLimits
{
MaxFindingsPerRequest
=
maxFindings
,
},
IncludeQuote
=
includeQuote
,
MinLikelihood
=
minLikelihood
};
// Construct the pubsub action.
var
actions
=
new
Action
[]
{
new
Action
{
PubSub
=
new
Action
.
Types
.
PublishToPubSub
{
Topic
=
$"projects/{projectId}/topics/{topicId}"
}
}
};
// Construct the inspect job config using the actions.
var
inspectJob
=
new
InspectJobConfig
{
StorageConfig
=
storageConfig
,
InspectConfig
=
inspectConfig
,
Actions
=
{
actions
}
};
// Issue Create Dlp Job Request.
var
request
=
new
CreateDlpJobRequest
{
InspectJob
=
inspectJob
,
ParentAsLocationName
=
new
LocationName
(
projectId
,
"global"
),
};
// We keep the name of the job that we just created.
var
dlpJob
=
dlp
.
CreateDlpJob
(
request
);
var
jobName
=
dlpJob
.
Name
;
// Listen to pub/sub for the job.
var
subscriptionName
=
new
SubscriptionName
(
projectId
,
subId
);
var
subscriber
=
await
SubscriberClient
.
CreateAsync
(
subscriptionName
);
// SimpleSubscriber runs your message handle function on multiple threads to maximize throughput.
await
subscriber
.
StartAsync
((
PubsubMessage
message
,
CancellationToken
cancel
)
=
>
{
if
(
message
.
Attributes
[
"DlpJobName"
]
==
jobName
)
{
subscriber
.
StopAsync
(
cancel
);
return
Task
.
FromResult
(
SubscriberClient
.
Reply
.
Ack
);
}
else
{
return
Task
.
FromResult
(
SubscriberClient
.
Reply
.
Nack
);
}
});
// Get the latest state of the job from the service.
var
resultJob
=
dlp
.
GetDlpJob
(
new
GetDlpJobRequest
{
DlpJobName
=
DlpJobName
.
Parse
(
jobName
)
});
// Parse the response and process results.
System
.
Console
.
WriteLine
(
$"Job status: {resultJob.State}"
);
System
.
Console
.
WriteLine
(
$"Job Name: {resultJob.Name}"
);
var
result
=
resultJob
.
InspectDetails
.
Result
;
foreach
(
var
infoType
in
result
.
InfoTypeStats
)
{
System
.
Console
.
WriteLine
(
$"Info Type: {infoType. InfoType
.Name}"
);
System
.
Console
.
WriteLine
(
$"Count: {infoType.Count}"
);
}
return
resultJob
;
}
}
Go
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
(
"context"
"fmt"
"io"
"time"
dlp
"cloud.google.com/go/dlp/apiv2"
"cloud.google.com/go/dlp/apiv2/dlppb"
"cloud.google.com/go/pubsub"
)
// inspectBigQueryTableWithSampling inspect bigQueries for sensitive data with sampling
func
inspectBigQueryTableWithSampling
(
w
io
.
Writer
,
projectID
,
topicID
,
subscriptionID
string
)
error
{
// projectId := "your-project-id"
// topicID := "your-pubsub-topic-id"
// or provide a topicID name to create one
// subscriptionID := "your-pubsub-subscription-id"
// or provide a subscription name to create one
ctx
:=
context
.
Background
()
// Initialize a client once and reuse it to send multiple requests. Clients
// are safe to use across goroutines. When the client is no longer needed,
// call the Close method to cleanup its resources.
client
,
err
:=
dlp
.
NewClient
(
ctx
)
if
err
!=
nil
{
return
err
}
// Closing the client safely cleans up background resources.
defer
client
.
Close
()
// Specify the BigQuery table to be inspected.
tableReference
:=
& dlppb
.
BigQueryTable
{
ProjectId
:
"bigquery-public-data"
,
DatasetId
:
"usa_names"
,
TableId
:
"usa_1910_current"
,
}
bigQueryOptions
:=
& dlppb
.
BigQueryOptions
{
TableReference
:
tableReference
,
RowsLimit
:
int64
(
10000
),
SampleMethod
:
dlppb
.
BigQueryOptions_RANDOM_START
,
IdentifyingFields
:
[]
*
dlppb
.
FieldId
{
{
Name
:
"name"
},
},
}
// Provide storage config with BigqueryOptions
storageConfig
:=
& dlppb
.
StorageConfig
{
Type
:
& dlppb
.
StorageConfig_BigQueryOptions
{
BigQueryOptions
:
bigQueryOptions
,
},
}
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
infoTypes
:=
[]
*
dlppb
.
InfoType
{
{
Name
:
"PERSON_NAME"
},
}
// Specify how the content should be inspected.
inspectConfig
:=
& dlppb
.
InspectConfig
{
InfoTypes
:
infoTypes
,
IncludeQuote
:
true
,
}
// Create a PubSub Client used to listen for when the inspect job finishes.
pubsubClient
,
err
:=
pubsub
.
NewClient
(
ctx
,
projectID
)
if
err
!=
nil
{
return
err
}
defer
pubsubClient
.
Close
()
// Create a PubSub subscription we can use to listen for messages.
// Create the Topic if it doesn't exist.
t
:=
pubsubClient
.
Topic
(
topicID
)
if
exists
,
err
:=
t
.
Exists
(
ctx
);
err
!=
nil
{
return
err
}
else
if
!
exists
{
if
t
,
err
=
pubsubClient
.
CreateTopic
(
ctx
,
topicID
);
err
!=
nil
{
return
err
}
}
// Create the Subscription if it doesn't exist.
s
:=
pubsubClient
.
Subscription
(
subscriptionID
)
if
exists
,
err
:=
s
.
Exists
(
ctx
);
err
!=
nil
{
return
err
}
else
if
!
exists
{
if
s
,
err
=
pubsubClient
.
CreateSubscription
(
ctx
,
subscriptionID
,
pubsub
.
SubscriptionConfig
{
Topic
:
t
});
err
!=
nil
{
return
err
}
}
// topic is the PubSub topic string where messages should be sent.
topic
:=
fmt
.
Sprintf
(
"projects/%s/topics/%s"
,
projectID
,
topicID
)
action
:=
& dlppb
.
Action
{
Action
:
& dlppb
.
Action_PubSub
{
PubSub
:
& dlppb
.
Action_PublishToPubSub
{
Topic
:
topic
,
},
},
}
// Configure the long running job we want the service to perform.
inspectJobConfig
:=
& dlppb
.
InspectJobConfig
{
StorageConfig
:
storageConfig
,
InspectConfig
:
inspectConfig
,
Actions
:
[]
*
dlppb
.
Action
{
action
,
},
}
// Create the request for the job configured above.
req
:=
& dlppb
.
CreateDlpJobRequest
{
Parent
:
fmt
.
Sprintf
(
"projects/%s/locations/global"
,
projectID
),
Job
:
& dlppb
.
CreateDlpJobRequest_InspectJob
{
InspectJob
:
inspectJobConfig
,
},
}
// Use the client to send the request.
j
,
err
:=
client
.
CreateDlpJob
(
ctx
,
req
)
if
err
!=
nil
{
return
err
}
fmt
.
Fprintf
(
w
,
"Job Created: %v"
,
j
.
GetName
())
// Wait for the inspect job to finish by waiting for a PubSub message.
// This only waits for 10 minutes. For long jobs, consider using a truly
// asynchronous execution model such as Cloud Functions.
c
,
cancel
:=
context
.
WithTimeout
(
ctx
,
10
*
time
.
Minute
)
defer
cancel
()
err
=
s
.
Receive
(
c
,
func
(
ctx
context
.
Context
,
msg
*
pubsub
.
Message
)
{
// If this is the wrong job, do not process the result.
if
msg
.
Attributes
[
"DlpJobName"
]
!=
j
.
GetName
()
{
msg
.
Nack
()
return
}
msg
.
Ack
()
// Stop listening for more messages.
defer
cancel
()
})
if
err
!=
nil
{
return
err
}
resp
,
err
:=
client
.
GetDlpJob
(
ctx
,
& dlppb
.
GetDlpJobRequest
{
Name
:
j
.
GetName
(),
})
if
err
!=
nil
{
return
err
}
r
:=
resp
.
GetInspectDetails
().
GetResult
().
GetInfoTypeStats
()
if
len
(
r
)
==
0
{
fmt
.
Fprintf
(
w
,
"No results"
)
return
err
}
for
_
,
s
:=
range
r
{
fmt
.
Fprintf
(
w
,
"\nFound %v instances of infoType %v\n"
,
s
.
GetCount
(),
s
.
GetInfoType
().
GetName
())
}
return
nil
}
Java
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
com.google.api.core. SettableApiFuture
;
import
com.google.cloud.dlp.v2. DlpServiceClient
;
import
com.google.cloud.pubsub.v1. AckReplyConsumer
;
import
com.google.cloud.pubsub.v1. MessageReceiver
;
import
com.google.cloud.pubsub.v1. Subscriber
;
import
com.google.privacy.dlp.v2. Action
;
import
com.google.privacy.dlp.v2. BigQueryOptions
;
import
com.google.privacy.dlp.v2. BigQueryOptions
.SampleMethod
;
import
com.google.privacy.dlp.v2. BigQueryTable
;
import
com.google.privacy.dlp.v2. CreateDlpJobRequest
;
import
com.google.privacy.dlp.v2. DlpJob
;
import
com.google.privacy.dlp.v2. FieldId
;
import
com.google.privacy.dlp.v2. GetDlpJobRequest
;
import
com.google.privacy.dlp.v2. InfoType
;
import
com.google.privacy.dlp.v2. InfoTypeStats
;
import
com.google.privacy.dlp.v2. InspectConfig
;
import
com.google.privacy.dlp.v2. InspectDataSourceDetails
;
import
com.google.privacy.dlp.v2. InspectJobConfig
;
import
com.google.privacy.dlp.v2. LocationName
;
import
com.google.privacy.dlp.v2. StorageConfig
;
import
com.google.pubsub.v1. ProjectSubscriptionName
;
import
com.google.pubsub.v1. PubsubMessage
;
import
java.io.IOException
;
import
java.util.concurrent.ExecutionException
;
import
java.util.concurrent.TimeUnit
;
import
java.util.concurrent.TimeoutException
;
public
class
InspectBigQueryTableWithSampling
{
public
static
void
main
(
String
[]
args
)
throws
Exception
{
// TODO(developer): Replace these variables before running the sample.
String
projectId
=
"your-project-id"
;
String
topicId
=
"your-pubsub-topic-id"
;
String
subscriptionId
=
"your-pubsub-subscription-id"
;
inspectBigQueryTableWithSampling
(
projectId
,
topicId
,
subscriptionId
);
}
// Inspects a BigQuery Table
public
static
void
inspectBigQueryTableWithSampling
(
String
projectId
,
String
topicId
,
String
subscriptionId
)
throws
ExecutionException
,
InterruptedException
,
IOException
{
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try
(
DlpServiceClient
dlp
=
DlpServiceClient
.
create
())
{
// Specify the BigQuery table to be inspected.
BigQueryTable
tableReference
=
BigQueryTable
.
newBuilder
()
.
setProjectId
(
"bigquery-public-data"
)
.
setDatasetId
(
"usa_names"
)
.
setTableId
(
"usa_1910_current"
)
.
build
();
BigQueryOptions
bigQueryOptions
=
BigQueryOptions
.
newBuilder
()
.
setTableReference
(
tableReference
)
.
setRowsLimit
(
1000
)
.
setSampleMethod
(
SampleMethod
.
RANDOM_START
)
.
addIdentifyingFields
(
FieldId
.
newBuilder
().
setName
(
"name"
))
.
build
();
StorageConfig
storageConfig
=
StorageConfig
.
newBuilder
().
setBigQueryOptions
(
bigQueryOptions
).
build
();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
InfoType
infoType
=
InfoType
.
newBuilder
().
setName
(
"PERSON_NAME"
).
build
();
// Specify how the content should be inspected.
InspectConfig
inspectConfig
=
InspectConfig
.
newBuilder
().
addInfoTypes
(
infoType
).
setIncludeQuote
(
true
).
build
();
// Specify the action that is triggered when the job completes.
String
pubSubTopic
=
String
.
format
(
"projects/%s/topics/%s"
,
projectId
,
topicId
);
Action
.
PublishToPubSub
publishToPubSub
=
Action
.
PublishToPubSub
.
newBuilder
().
setTopic
(
pubSubTopic
).
build
();
Action
action
=
Action
.
newBuilder
().
setPubSub
(
publishToPubSub
).
build
();
// Configure the long running job we want the service to perform.
InspectJobConfig
inspectJobConfig
=
InspectJobConfig
.
newBuilder
()
.
setStorageConfig
(
storageConfig
)
.
setInspectConfig
(
inspectConfig
)
.
addActions
(
action
)
.
build
();
// Create the request for the job configured above.
CreateDlpJobRequest
createDlpJobRequest
=
CreateDlpJobRequest
.
newBuilder
()
.
setParent
(
LocationName
.
of
(
projectId
,
"global"
).
toString
())
.
setInspectJob
(
inspectJobConfig
)
.
build
();
// Use the client to send the request.
final
DlpJob
dlpJob
=
dlp
.
createDlpJob
(
createDlpJobRequest
);
System
.
out
.
println
(
"Job created: "
+
dlpJob
.
getName
());
// Set up a Pub/Sub subscriber to listen on the job completion status
final
SettableApiFuture<Boolean>
done
=
SettableApiFuture
.
create
();
ProjectSubscriptionName
subscriptionName
=
ProjectSubscriptionName
.
of
(
projectId
,
subscriptionId
);
MessageReceiver
messageHandler
=
(
PubsubMessage
pubsubMessage
,
AckReplyConsumer
ackReplyConsumer
)
-
>
{
handleMessage
(
dlpJob
,
done
,
pubsubMessage
,
ackReplyConsumer
);
};
Subscriber
subscriber
=
Subscriber
.
newBuilder
(
subscriptionName
,
messageHandler
).
build
();
subscriber
.
startAsync
();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try
{
done
.
get
(
15
,
TimeUnit
.
MINUTES
);
}
catch
(
TimeoutException
e
)
{
System
.
out
.
println
(
"Job was not completed after 15 minutes."
);
return
;
}
finally
{
subscriber
.
stopAsync
();
subscriber
.
awaitTerminated
();
}
// Get the latest state of the job from the service
GetDlpJobRequest
request
=
GetDlpJobRequest
.
newBuilder
().
setName
(
dlpJob
.
getName
()).
build
();
DlpJob
completedJob
=
dlp
.
getDlpJob
(
request
);
// Parse the response and process results.
System
.
out
.
println
(
"Job status: "
+
completedJob
.
getState
());
System
.
out
.
println
(
"Job name: "
+
dlpJob
.
getName
());
InspectDataSourceDetails
.
Result
result
=
completedJob
.
getInspectDetails
().
getResult
();
System
.
out
.
println
(
"Findings: "
);
for
(
InfoTypeStats
infoTypeStat
:
result
.
getInfoTypeStatsList
())
{
System
.
out
.
print
(
"\tInfo type: "
+
infoTypeStat
.
getInfoType
().
getName
());
System
.
out
.
println
(
"\tCount: "
+
infoTypeStat
.
getCount
());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private
static
void
handleMessage
(
DlpJob
job
,
SettableApiFuture<Boolean>
done
,
PubsubMessage
pubsubMessage
,
AckReplyConsumer
ackReplyConsumer
)
{
String
messageAttribute
=
pubsubMessage
.
getAttributesMap
().
get
(
"DlpJobName"
);
if
(
job
.
getName
().
equals
(
messageAttribute
))
{
done
.
set
(
true
);
ack
ReplyConsumer .
ack
();
}
else
{
ackReplyConsumer
.
nack
();
}
}
}
Node.js
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
// Import the Google Cloud client libraries
const
DLP
=
require
(
' @google-cloud/dlp
'
);
const
{
PubSub
}
=
require
(
' @google-cloud/pubsub
'
);
// Instantiates clients
const
dlp
=
new
DLP
.
DlpServiceClient
();
const
pubsub
=
new
PubSub
();
// The project ID to run the API call under
// const projectId = 'my-project';
// The project ID the table is stored under
// This may or (for public datasets) may not equal the calling project ID
// const dataProjectId = 'my-project';
// The ID of the dataset to inspect, e.g. 'my_dataset'
// const datasetId = 'my_dataset';
// The ID of the table to inspect, e.g. 'my_table'
// const tableId = 'my_table';
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
// DLP Job max time (in milliseconds)
const
DLP_JOB_WAIT_TIME
=
15
*
1000
*
60
;
async
function
inspectBigqueryWithSampling
()
{
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
const
infoTypes
=
[{
name
:
'PERSON_NAME'
}];
// Specify the BigQuery options required for inspection.
const
storageItem
=
{
bigQueryOptions
:
{
tableReference
:
{
projectId
:
dataProjectId
,
datasetId
:
datasetId
,
tableId
:
tableId
,
},
rowsLimit
:
1000
,
sampleMethod
:
DLP
.
protos
.
google
.
privacy
.
dlp
.
v2
.
BigQueryOptions
.
SampleMethod
.
RANDOM_START
,
includedFields
:
[{
name
:
'name'
}],
},
};
// Specify the action that is triggered when the job completes.
const
actions
=
[
{
pubSub
:
{
topic
:
`projects/
${
projectId
}
/topics/
${
topicId
}
`
,
},
},
];
// Construct request for creating an inspect job
const
request
=
{
parent
:
`projects/
${
projectId
}
/locations/global`
,
inspectJob
:
{
inspectConfig
:
{
infoTypes
:
infoTypes
,
includeQuote
:
true
,
},
storageConfig
:
storageItem
,
actions
:
actions
,
},
};
// Use the client to send the request.
const
[
topicResponse
]
=
await
pubsub
.
topic
(
topicId
).
get
();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const
subscription
=
await
topicResponse
.
subscription
(
subscriptionId
);
const
[
jobsResponse
]
=
await
dlp
.
createDlpJob
(
request
);
const
jobName
=
jobsResponse
.
name
;
// Watch the Pub/Sub topic until the DLP job finishes
await
new
Promise
((
resolve
,
reject
)
=
>
{
// Set up the timeout
const
timer
=
setTimeout
(()
=
>
{
reject
(
new
Error
(
'Timeout'
));
},
DLP_JOB_WAIT_TIME
);
const
messageHandler
=
message
=
>
{
if
(
message
.
attributes
&&
message
.
attributes
.
DlpJobName
===
jobName
)
{
message
.
ack
();
subscription
.
removeListener
(
'message'
,
messageHandler
);
subscription
.
removeListener
(
'error'
,
errorHandler
);
clearTimeout
(
timer
);
resolve
(
jobName
);
}
else
{
message
.
nack
();
}
};
const
errorHandler
=
err
=
>
{
subscription
.
removeListener
(
'message'
,
messageHandler
);
subscription
.
removeListener
(
'error'
,
errorHandler
);
clearTimeout
(
timer
);
reject
(
err
);
};
subscription
.
on
(
'message'
,
messageHandler
);
subscription
.
on
(
'error'
,
errorHandler
);
});
const
[
job
]
=
await
dlp
.
getDlpJob
({
name
:
jobName
});
console
.
log
(
`Job
${
job
.
name
}
status:
${
job
.
state
}
`
);
const
infoTypeStats
=
job
.
inspectDetails
.
result
.
infoTypeStats
;
if
(
infoTypeStats
.
length
>
0
)
{
infoTypeStats
.
forEach
(
infoTypeStat
=
>
{
console
.
log
(
` Found
${
infoTypeStat
.
count
}
instance(s) of infoType
${
infoTypeStat
.
infoType
.
name
}
.`
);
});
}
else
{
console
.
log
(
'No findings.'
);
}
}
await
inspectBigqueryWithSampling
();
PHP
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\BigQueryOptions;
use Google\Cloud\Dlp\V2\BigQueryOptions\SampleMethod;
use Google\Cloud\Dlp\V2\BigQueryTable;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\CreateDlpJobRequest;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\GetDlpJobRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect BigQuery for sensitive data with sampling.
* The following examples demonstrate using the Cloud Data Loss Prevention
* API to scan a 1000-row subset of a BigQuery table. The scan starts from
* a random row.
*
* @param string $callingProjectId The project ID to run the API call under.
* @param string $topicId The Pub/Sub topic ID to notify once the job is completed.
* @param string $subscriptionId The Pub/Sub subscription ID to use when listening for job.
* @param string $projectId The Google Cloud Project ID.
* @param string $datasetId The BigQuery Dataset ID.
* @param string $tableId The BigQuery Table ID to be inspected.
*/
function inspect_bigquery_with_sampling(
string $callingProjectId,
string $topicId,
string $subscriptionId,
string $projectId,
string $datasetId,
string $tableId
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// Specify the BigQuery table to be inspected.
$bigqueryTable = (new BigQueryTable())
->setProjectId($projectId)
->setDatasetId($datasetId)
->setTableId($tableId);
$bigQueryOptions = (new BigQueryOptions())
->setTableReference($bigqueryTable)
->setRowsLimit(1000)
->setSampleMethod(SampleMethod::RANDOM_START)
->setIdentifyingFields([
(new FieldId())
->setName('name')
]);
$storageConfig = (new StorageConfig())
->setBigQueryOptions($bigQueryOptions);
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
$infoTypes = [$personNameInfoType];
// Specify how the content should be inspected.
$inspectConfig = (new InspectConfig())
->setInfoTypes($infoTypes)
->setIncludeQuote(true);
// Specify the action that is triggered when the job completes.
$pubSubAction = (new PublishToPubSub())
->setTopic($topic->name());
$action = (new Action())
->setPubSub($pubSubAction);
// Configure the long running job we want the service to perform.
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request
$parent = "projects/$callingProjectId/locations/global";
$createDlpJobRequest = (new CreateDlpJobRequest())
->setParent($parent)
->setInspectJob($inspectJob);
$job = $dlp->createDlpJob($createDlpJobRequest);
// Poll Pub/Sub using exponential backoff until job finishes
// Consider using an asynchronous execution model such as Cloud Functions
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (
isset($message->attributes()['DlpJobName'])
&& $message->attributes()['DlpJobName'] === $job->getName()
) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$getDlpJobRequest = (new GetDlpJobRequest())
->setName($job->getName());
$job = $dlp->getDlpJob($getDlpJobRequest);
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while
}
}
printf('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout
// Print finding counts
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
printf('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(
' Found %s instance(s) of infoType %s' . PHP_EOL,
$infoTypeStat->getCount(),
$infoTypeStat->getInfoType()->getName()
);
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
printf('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
printf('Unexpected job state. Most likely, the job is either running or has not yet started.');
}
}
Python
To learn how to install and use the client library for Sensitive Data Protection, see Sensitive Data Protection client libraries .
To authenticate to Sensitive Data Protection, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
threading
import
google.cloud.dlp
import
google.cloud.pubsub
def
inspect_bigquery_table_with_sampling
(
project
:
str
,
topic_id
:
str
,
subscription_id
:
str
,
min_likelihood
:
str
=
None
,
max_findings
:
str
=
None
,
timeout
:
int
=
300
,
)
-
> None
:
"""Uses the Data Loss Prevention API to analyze BigQuery data by limiting
the amount of data to be scanned.
Args:
project: The Google Cloud project id to use as a parent resource.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
"""
# Instantiate a client.
dlp
=
google
.
cloud
.
dlp_v2
.
DlpServiceClient
()
# Specify how the content should be inspected. Keys which are None may
# optionally be omitted entirely.
inspect_config
=
{
"info_types"
:
[{
"name"
:
"PERSON_NAME"
}],
"min_likelihood"
:
min_likelihood
,
"limits"
:
{
"max_findings_per_request"
:
max_findings
},
"include_quote"
:
True
,
}
# Specify the BigQuery table to be inspected.
# Here we are using public bigquery table.
table_reference
=
{
"project_id"
:
"bigquery-public-data"
,
"dataset_id"
:
"usa_names"
,
"table_id"
:
"usa_1910_current"
,
}
# Construct a storage_config containing the target BigQuery info.
storage_config
=
{
"big_query_options"
:
{
"table_reference"
:
table_reference
,
"rows_limit"
:
1000
,
"sample_method"
:
"RANDOM_START"
,
"identifying_fields"
:
[{
"name"
:
"name"
}],
}
}
# Tell the API where to send a notification when the job is complete.
topic
=
google
.
cloud
.
pubsub
.
PublisherClient
.
topic_path
(
project
,
topic_id
)
actions
=
[{
"pub_sub"
:
{
"topic"
:
topic
}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job
=
{
"inspect_config"
:
inspect_config
,
"storage_config"
:
storage_config
,
"actions"
:
actions
,
}
# Convert the project id into full resource ids.
parent
=
f
"projects/
{
project
}
/locations/global"
# Call the API
operation
=
dlp
.
create_dlp_job
(
request
=
{
"parent"
:
parent
,
"inspect_job"
:
inspect_job
}
)
print
(
f
"Inspection operation started:
{
operation
.
name
}
"
)
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber
=
google
.
cloud
.
pubsub
.
SubscriberClient
()
subscription_path
=
subscriber
.
subscription_path
(
project
,
subscription_id
)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done
=
threading
.
Event
()
def
callback
(
message
:
google
.
cloud
.
pubsub_v1
.
subscriber
.
message
.
Message
)
-
> None
:
try
:
if
message
.
attributes
[
"DlpJobName"
]
==
operation
.
name
:
# This is the message we're looking for, so acknowledge it.
message
.
ack
()
# Now that the job is done, fetch the results and print them.
job
=
dlp
.
get_dlp_job
(
request
=
{
"name"
:
operation
.
name
})
print
(
f
"Job name:
{
job
.
name
}
"
)
if
job
.
inspect_details
.
result
.
info_type_stats
:
for
finding
in
job
.
inspect_details
.
result
.
info_type_stats
:
print
(
f
"Info type:
{
finding
.
info_type
.
name
}
; Count:
{
finding
.
count
}
"
)
else
:
print
(
"No findings."
)
# Signal to the main thread that we can exit.
job_done
.
set
()
else
:
# This is not the message we're looking for.
message
.
drop
()
except
Exception
as
e
:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print
(
e
)
raise
# Register the callback and wait on the event.
subscribe
r .
subscribe
(
subscription_path
,
callback
=
callback
)
finished
=
job_done
.
wait
(
timeout
=
timeout
)
if
not
finished
:
print
(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
What's next
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