Gets a batch prediction job using the get_batch_prediction_job method.
Code sample
Java
Before trying this sample, follow the Java setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Java API reference documentation .
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
import
com.google.cloud.aiplatform.v1. BatchPredictionJob
;
import
com.google.cloud.aiplatform.v1. BatchPredictionJob
. InputConfig
;
import
com.google.cloud.aiplatform.v1. BatchPredictionJob
.OutputConfig
;
import
com.google.cloud.aiplatform.v1. BatchPredictionJob
.OutputInfo
;
import
com.google.cloud.aiplatform.v1. BatchPredictionJobName
;
import
com.google.cloud.aiplatform.v1. BigQueryDestination
;
import
com.google.cloud.aiplatform.v1. BigQuerySource
;
import
com.google.cloud.aiplatform.v1. CompletionStats
;
import
com.google.cloud.aiplatform.v1. GcsDestination
;
import
com.google.cloud.aiplatform.v1. GcsSource
;
import
com.google.cloud.aiplatform.v1. JobServiceClient
;
import
com.google.cloud.aiplatform.v1. JobServiceSettings
;
import
com.google.cloud.aiplatform.v1. ResourcesConsumed
;
import
com.google.protobuf. Any
;
import
com.google.rpc. Status
;
import
java.io.IOException
;
import
java.util.List
;
public
class
GetBatchPredictionJobSample
{
public
static
void
main
(
String
[]
args
)
throws
IOException
{
// TODO(developer): Replace these variables before running the sample.
String
project
=
"YOUR_PROJECT_ID"
;
String
batchPredictionJobId
=
"YOUR_BATCH_PREDICTION_JOB_ID"
;
getBatchPredictionJobSample
(
project
,
batchPredictionJobId
);
}
static
void
getBatchPredictionJobSample
(
String
project
,
String
batchPredictionJobId
)
throws
IOException
{
JobServiceSettings
jobServiceSettings
=
JobServiceSettings
.
newBuilder
()
.
setEndpoint
(
"us-central1-aiplatform.googleapis.com:443"
)
.
build
();
// 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
(
JobServiceClient
jobServiceClient
=
JobServiceClient
.
create
(
jobServiceSettings
))
{
String
location
=
"us-central1"
;
BatchPredictionJobName
batchPredictionJobName
=
BatchPredictionJobName
.
of
(
project
,
location
,
batchPredictionJobId
);
BatchPredictionJob
batchPredictionJob
=
jobServiceClient
.
getBatchPredictionJob
(
batchPredictionJobName
);
System
.
out
.
println
(
"Get Batch Prediction Job Response"
);
System
.
out
.
format
(
"\tName: %s\n"
,
batchPredictionJob
.
getName
());
System
.
out
.
format
(
"\tDisplay Name: %s\n"
,
batchPredictionJob
.
getDisplayName
());
System
.
out
.
format
(
"\tModel: %s\n"
,
batchPredictionJob
.
getModel
());
System
.
out
.
format
(
"\tModel Parameters: %s\n"
,
batchPredictionJob
.
getModelParameters
());
System
.
out
.
format
(
"\tState: %s\n"
,
batchPredictionJob
.
getState
());
System
.
out
.
format
(
"\tCreate Time: %s\n"
,
batchPredictionJob
.
getCreateTime
());
System
.
out
.
format
(
"\tStart Time: %s\n"
,
batchPredictionJob
.
getStartTime
());
System
.
out
.
format
(
"\tEnd Time: %s\n"
,
batchPredictionJob
.
getEndTime
());
System
.
out
.
format
(
"\tUpdate Time: %s\n"
,
batchPredictionJob
.
getUpdateTime
());
System
.
out
.
format
(
"\tLabels: %s\n"
,
batchPredictionJob
.
getLabelsMap
());
InputConfig
inputConfig
=
batchPredictionJob
.
getInputConfig
();
System
.
out
.
println
(
"\tInput Config"
);
System
.
out
.
format
(
"\t\tInstances Format: %s\n"
,
inputConfig
.
getInstancesFormat
());
GcsSource
gcsSource
=
inputConfig
.
getGcsSource
();
System
.
out
.
println
(
"\t\tGcs Source"
);
System
.
out
.
format
(
"\t\t\tUris: %s\n"
,
gcsSource
.
getUrisList
());
BigQuerySource
bigquerySource
=
inputConfig
.
getBigquerySource
();
System
.
out
.
println
(
"\t\tBigquery Source"
);
System
.
out
.
format
(
"\t\t\tInput Uri: %s\n"
,
bigquerySource
.
getInputUri
());
OutputConfig
outputConfig
=
batchPredictionJob
.
getOutputConfig
();
System
.
out
.
println
(
"\tOutput Config"
);
System
.
out
.
format
(
"\t\tPredictions Format: %s\n"
,
outputConfig
.
getPredictionsFormat
());
GcsDestination
gcsDestination
=
outputConfig
.
getGcsDestination
();
System
.
out
.
println
(
"\t\tGcs Destination"
);
System
.
out
.
format
(
"\t\t\tOutput Uri Prefix: %s\n"
,
gcsDestination
.
getOutputUriPrefix
());
BigQueryDestination
bigqueryDestination
=
outputConfig
.
getBigqueryDestination
();
System
.
out
.
println
(
"\t\tBigquery Destination"
);
System
.
out
.
format
(
"\t\t\tOutput Uri: %s\n"
,
bigqueryDestination
.
getOutputUri
());
OutputInfo
outputInfo
=
batchPredictionJob
.
getOutputInfo
();
System
.
out
.
println
(
"\tOutput Info"
);
System
.
out
.
format
(
"\t\tGcs Output Directory: %s\n"
,
outputInfo
.
getGcsOutputDirectory
());
System
.
out
.
format
(
"\t\tBigquery Output Dataset: %s\n"
,
outputInfo
.
getBigqueryOutputDataset
());
Status
status
=
batchPredictionJob
.
getError
();
System
.
out
.
println
(
"\tError"
);
System
.
out
.
format
(
"\t\tCode: %s\n"
,
status
.
getCode
());
System
.
out
.
format
(
"\t\tMessage: %s\n"
,
status
.
getMessage
());
List<Any>
detailsList
=
status
.
getDetailsList
();
for
(
Status
partialFailure
:
batchPredictionJob
.
getPartialFailuresList
())
{
System
.
out
.
println
(
"\tPartial Failure"
);
System
.
out
.
format
(
"\t\tCode: %s\n"
,
partialFailure
.
getCode
());
System
.
out
.
format
(
"\t\tMessage: %s\n"
,
partialFailure
.
getMessage
());
List<Any>
details
=
partialFailure
.
getDetailsList
();
}
ResourcesConsumed
resourcesConsumed
=
batchPredictionJob
.
getResourcesConsumed
();
System
.
out
.
println
(
"\tResources Consumed"
);
System
.
out
.
format
(
"\t\tReplica Hours: %s\n"
,
resourcesConsumed
.
getReplicaHours
());
CompletionStats
completionStats
=
batchPredictionJob
.
getCompletionStats
();
System
.
out
.
println
(
"\tCompletion Stats"
);
System
.
out
.
format
(
"\t\tSuccessful Count: %s\n"
,
completionStats
.
getSuccessfulCount
());
System
.
out
.
format
(
"\t\tFailed Count: %s\n"
,
completionStats
.
getFailedCount
());
System
.
out
.
format
(
"\t\tIncomplete Count: %s\n"
,
completionStats
.
getIncompleteCount
());
}
}
}
Python
Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Python API reference documentation .
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
from
google.cloud
import
aiplatform
def
get_batch_prediction_job_sample
(
project
:
str
,
batch_prediction_job_id
:
str
,
location
:
str
=
"us-central1"
,
api_endpoint
:
str
=
"us-central1-aiplatform.googleapis.com"
,
):
# The AI Platform services require regional API endpoints.
client_options
=
{
"api_endpoint"
:
api_endpoint
}
# Initialize client that will be used to create and send requests.
# This client only needs to be created once, and can be reused for multiple requests.
client
=
aiplatform
.
gapic
.
JobServiceClient
(
client_options
=
client_options
)
name
=
client
.
batch_prediction_job_path
(
project
=
project
,
location
=
location
,
batch_prediction_job
=
batch_prediction_job_id
)
response
=
client
.
get_batch_prediction_job
(
name
=
name
)
print
(
"response:"
,
response
)
What's next
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