Stream data using the Storage Write API
This document describes how to use the
BigQuery Storage Write API to stream data
into BigQuery.
In streaming scenarios, data arrives continuously and should be available for
reads with minimal latency. When using the BigQuery Storage Write API for streaming
workloads, consider what guarantees you need:
- If your application only needs at-least-once semantics, then use the default
stream.
- If you need exactly-once semantics, then create one or more streams in
committed type and use stream offsets to guarantee exactly-once writes.
In committed type, data written to the stream is available for query as soon as
the server acknowledges the write request. The default stream also uses
committed type, but does not provide exactly-once guarantees.
Use the default stream for at-least-once semantics
If your application can accept the possibility of duplicate records
appearing in the destination table, then we recommend using the
default stream for streaming
scenarios.
The following code shows how to write data to the default stream:
Java
To learn how to install and use the client library for BigQuery, see
BigQuery client libraries.
For more information, see the
BigQuery Java API
reference documentation.
To authenticate to BigQuery, set up Application Default Credentials.
For more information, see
Set up authentication for client libraries.
import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.core.FixedExecutorProvider;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.QueryJobConfiguration;
import com.google.cloud.bigquery.TableResult;
import com.google.cloud.bigquery.storage.v1.AppendRowsRequest;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteSettings;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.AppendSerializationError;
import com.google.cloud.bigquery.storage.v1.Exceptions.MaximumRequestCallbackWaitTimeExceededException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.Exceptions.StreamWriterClosedException;
import com.google.cloud.bigquery.storage.v1.JsonStreamWriter;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.ByteString;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.Map;
import java.util.concurrent.Executors;
import java.util.concurrent.Phaser;
import java.util.concurrent.atomic.AtomicInteger;
import javax.annotation.concurrent.GuardedBy;
import org.json.JSONArray;
import org.json.JSONObject;
import org.threeten.bp.Duration;
public class WriteToDefaultStream {
public static void runWriteToDefaultStream()
throws DescriptorValidationException, InterruptedException, IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "MY_PROJECT_ID";
String datasetName = "MY_DATASET_NAME";
String tableName = "MY_TABLE_NAME";
writeToDefaultStream(projectId, datasetName, tableName);
}
private static ByteString buildByteString() {
byte[] bytes = new byte[] {1, 2, 3, 4, 5};
return ByteString.copyFrom(bytes);
}
// Create a JSON object that is compatible with the table schema.
private static JSONObject buildRecord(int i, int j) {
JSONObject record = new JSONObject();
StringBuilder sbSuffix = new StringBuilder();
for (int k = 0; k < j; k++) {
sbSuffix.append(k);
}
record.put("test_string", String.format("record %03d-%03d %s", i, j, sbSuffix.toString()));
ByteString byteString = buildByteString();
record.put("test_bytes", byteString);
record.put(
"test_geo",
"POLYGON((-124.49 47.35,-124.49 40.73,-116.49 40.73,-116.49 47.35,-124.49 47.35))");
return record;
}
public static void writeToDefaultStream(String projectId, String datasetName, String tableName)
throws DescriptorValidationException, InterruptedException, IOException {
TableName parentTable = TableName.of(projectId, datasetName, tableName);
DataWriter writer = new DataWriter();
// One time initialization for the worker.
writer.initialize(parentTable);
// Write two batches of fake data to the stream, each with 10 JSON records. Data may be
// batched up to the maximum request size:
// https://cloud.google.com/bigquery/quotas#write-api-limits
for (int i = 0; i < 2; i++) {
JSONArray jsonArr = new JSONArray();
for (int j = 0; j < 10; j++) {
JSONObject record = buildRecord(i, j);
jsonArr.put(record);
}
writer.append(new AppendContext(jsonArr));
}
// Final cleanup for the stream during worker teardown.
writer.cleanup();
verifyExpectedRowCount(parentTable, 12);
System.out.println("Appended records successfully.");
}
private static void verifyExpectedRowCount(TableName parentTable, int expectedRowCount)
throws InterruptedException {
String queryRowCount =
"SELECT COUNT(*) FROM `"
+ parentTable.getProject()
+ "."
+ parentTable.getDataset()
+ "."
+ parentTable.getTable()
+ "`";
QueryJobConfiguration queryConfig = QueryJobConfiguration.newBuilder(queryRowCount).build();
BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();
TableResult results = bigquery.query(queryConfig);
int countRowsActual =
Integer.parseInt(results.getValues().iterator().next().get("f0_").getStringValue());
if (countRowsActual != expectedRowCount) {
throw new RuntimeException(
"Unexpected row count. Expected: " + expectedRowCount + ". Actual: " + countRowsActual);
}
}
private static class AppendContext {
JSONArray data;
AppendContext(JSONArray data) {
this.data = data;
}
}
private static class DataWriter {
private static final int MAX_RECREATE_COUNT = 3;
private BigQueryWriteClient client;
// Track the number of in-flight requests to wait for all responses before shutting down.
private final Phaser inflightRequestCount = new Phaser(1);
private final Object lock = new Object();
private JsonStreamWriter streamWriter;
@GuardedBy("lock")
private RuntimeException error = null;
private AtomicInteger recreateCount = new AtomicInteger(0);
private JsonStreamWriter createStreamWriter(String tableName)
throws DescriptorValidationException, IOException, InterruptedException {
// Configure in-stream automatic retry settings.
// Error codes that are immediately retried:
// * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
// Error codes that are retried with exponential backoff:
// * RESOURCE_EXHAUSTED
RetrySettings retrySettings =
RetrySettings.newBuilder()
.setInitialRetryDelay(Duration.ofMillis(500))
.setRetryDelayMultiplier(1.1)
.setMaxAttempts(5)
.setMaxRetryDelay(Duration.ofMinutes(1))
.build();
// Use the JSON stream writer to send records in JSON format. Specify the table name to write
// to the default stream.
// For more information about JsonStreamWriter, see:
// https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/JsonStreamWriter.html
return JsonStreamWriter.newBuilder(tableName, client)
.setExecutorProvider(FixedExecutorProvider.create(Executors.newScheduledThreadPool(100)))
.setChannelProvider(
BigQueryWriteSettings.defaultGrpcTransportProviderBuilder()
.setKeepAliveTime(org.threeten.bp.Duration.ofMinutes(1))
.setKeepAliveTimeout(org.threeten.bp.Duration.ofMinutes(1))
.setKeepAliveWithoutCalls(true)
.setChannelsPerCpu(2)
.build())
.setEnableConnectionPool(true)
// If value is missing in json and there is a default value configured on bigquery
// column, apply the default value to the missing value field.
.setDefaultMissingValueInterpretation(
AppendRowsRequest.MissingValueInterpretation.DEFAULT_VALUE)
.setRetrySettings(retrySettings)
.build();
}
public void initialize(TableName parentTable)
throws DescriptorValidationException, IOException, InterruptedException {
// Initialize client without settings, internally within stream writer a new client will be
// created with full settings.
client = BigQueryWriteClient.create();
streamWriter = createStreamWriter(parentTable.toString());
}
public void append(AppendContext appendContext)
throws DescriptorValidationException, IOException, InterruptedException {
synchronized (this.lock) {
if (!streamWriter.isUserClosed()
&& streamWriter.isClosed()
&& recreateCount.getAndIncrement() < MAX_RECREATE_COUNT) {
streamWriter = createStreamWriter(streamWriter.getStreamName());
this.error = null;
}
// If earlier appends have failed, we need to reset before continuing.
if (this.error != null) {
throw this.error;
}
}
// Append asynchronously for increased throughput.
ApiFuture<AppendRowsResponse> future = streamWriter.append(appendContext.data);
ApiFutures.addCallback(
future, new AppendCompleteCallback(this, appendContext), MoreExecutors.directExecutor());
// Increase the count of in-flight requests.
inflightRequestCount.register();
}
public void cleanup() {
// Wait for all in-flight requests to complete.
inflightRequestCount.arriveAndAwaitAdvance();
client.close();
// Close the connection to the server.
streamWriter.close();
// Verify that no error occurred in the stream.
synchronized (this.lock) {
if (this.error != null) {
throw this.error;
}
}
}
static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {
private final DataWriter parent;
private final AppendContext appendContext;
public AppendCompleteCallback(DataWriter parent, AppendContext appendContext) {
this.parent = parent;
this.appendContext = appendContext;
}
public void onSuccess(AppendRowsResponse response) {
System.out.format("Append success\n");
this.parent.recreateCount.set(0);
done();
}
public void onFailure(Throwable throwable) {
if (throwable instanceof AppendSerializationError) {
AppendSerializationError ase = (AppendSerializationError) throwable;
Map<Integer, String> rowIndexToErrorMessage = ase.getRowIndexToErrorMessage();
if (rowIndexToErrorMessage.size() > 0) {
// Omit the faulty rows
JSONArray dataNew = new JSONArray();
for (int i = 0; i < appendContext.data.length(); i++) {
if (!rowIndexToErrorMessage.containsKey(i)) {
dataNew.put(appendContext.data.get(i));
} else {
// process faulty rows by placing them on a dead-letter-queue, for instance
}
}
// Retry the remaining valid rows, but using a separate thread to
// avoid potentially blocking while we are in a callback.
if (dataNew.length() > 0) {
try {
this.parent.append(new AppendContext(dataNew));
} catch (DescriptorValidationException e) {
throw new RuntimeException(e);
} catch (IOException e) {
throw new RuntimeException(e);
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
}
// Mark the existing attempt as done since we got a response for it
done();
return;
}
}
boolean resendRequest = false;
if (throwable instanceof MaximumRequestCallbackWaitTimeExceededException) {
resendRequest = true;
} else if (throwable instanceof StreamWriterClosedException) {
if (!parent.streamWriter.isUserClosed()) {
resendRequest = true;
}
}
if (resendRequest) {
// Retry this request.
try {
this.parent.append(new AppendContext(appendContext.data));
} catch (DescriptorValidationException e) {
throw new RuntimeException(e);
} catch (IOException e) {
throw new RuntimeException(e);
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
// Mark the existing attempt as done since we got a response for it
done();
return;
}
synchronized (this.parent.lock) {
if (this.parent.error == null) {
StorageException storageException = Exceptions.toStorageException(throwable);
this.parent.error =
(storageException != null) ? storageException : new RuntimeException(throwable);
}
}
done();
}
private void done() {
// Reduce the count of in-flight requests.
this.parent.inflightRequestCount.arriveAndDeregister();
}
}
}
}
Python
This example shows how to insert a record with two fields using the default stream:
from google.cloud import bigquery_storage_v1
from google.cloud.bigquery_storage_v1 import types
from google.cloud.bigquery_storage_v1 import writer
from google.protobuf import descriptor_pb2
import logging
import json
import sample_data_pb2
# The list of columns from the table's schema to search in the given data to write to BigQuery.
TABLE_COLUMNS_TO_CHECK = [
"name",
"age"
]
# Function to create a batch of row data to be serialized.
def create_row_data(data):
row = sample_data_pb2.SampleData()
for field in TABLE_COLUMNS_TO_CHECK:
# Optional fields will be passed as null if not provided
if field in data:
setattr(row, field, data[field])
return row.SerializeToString()
class BigQueryStorageWriteAppend(object):
# The stream name is: projects/{project}/datasets/{dataset}/tables/{table}/_default
def append_rows_proto2(
project_id: str, dataset_id: str, table_id: str, data: dict
):
write_client = bigquery_storage_v1.BigQueryWriteClient()
parent = write_client.table_path(project_id, dataset_id, table_id)
stream_name = f'{parent}/_default'
write_stream = types.WriteStream()
# Create a template with fields needed for the first request.
request_template = types.AppendRowsRequest()
# The request must contain the stream name.
request_template.write_stream = stream_name
# Generating the protocol buffer representation of the message descriptor.
proto_schema = types.ProtoSchema()
proto_descriptor = descriptor_pb2.DescriptorProto()
sample_data_pb2.SampleData.DESCRIPTOR.CopyToProto(proto_descriptor)
proto_schema.proto_descriptor = proto_descriptor
proto_data = types.AppendRowsRequest.ProtoData()
proto_data.writer_schema = proto_schema
request_template.proto_rows = proto_data
# Construct an AppendRowsStream to send an arbitrary number of requests to a stream.
append_rows_stream = writer.AppendRowsStream(write_client, request_template)
# Append proto2 serialized bytes to the serialized_rows repeated field using create_row_data.
proto_rows = types.ProtoRows()
for row in data:
proto_rows.serialized_rows.append(create_row_data(row))
# Appends data to the given stream.
request = types.AppendRowsRequest()
proto_data = types.AppendRowsRequest.ProtoData()
proto_data.rows = proto_rows
request.proto_rows = proto_data
append_rows_stream.send(request)
print(f"Rows to table: '{parent}' have been written.")
if __name__ == "__main__":
###### Uncomment the below block to provide additional logging capabilities ######
#logging.basicConfig(
# level=logging.DEBUG,
# format="%(asctime)s [%(levelname)s] %(message)s",
# handlers=[
# logging.StreamHandler()
# ]
#)
###### Uncomment the above block to provide additional logging capabilities ######
with open('entries.json', 'r') as json_file:
data = json.load(json_file)
# Change this to your specific BigQuery project, dataset, table details
BigQueryStorageWriteAppend.append_rows_proto2("PROJECT_ID","DATASET_ID", "TABLE_ID ",data=data)
This code example depends on the compiled protocol module sample_data_pb2.py
. To create the compiled module, execute the
protoc --python_out=. sample_data.proto
command, where protoc
is the
protocol buffer compiler. The sample_data.proto
file defines the format
of the messages used in the Python example. To install the protoc
compiler, follow the instructions in Protocol Buffers - Google's data interchange format.
Here are the contents of the sample_data.proto
file:
message SampleData {
required string name = 1;
required int64 age = 2;
}
This script consumes the entities.json
file, which contains sample row data to be inserted into the BigQuery table:
{"name": "Jim", "age": 35}
{"name": "Jane", "age": 27}
Use multiplexing
You enable
multiplexing
at the stream writer level for default stream only. To enable multiplexing in
Java, call the setEnableConnectionPool
method when you construct a
StreamWriter
or JsonStreamWriter
object:
// One possible way for constructing StreamWriter
StreamWriter.newBuilder(streamName)
.setWriterSchema(protoSchema)
.setEnableConnectionPool(true)
.build();
// One possible way for constructing JsonStreamWriter
JsonStreamWriter.newBuilder(tableName, bigqueryClient)
.setEnableConnectionPool(true)
.build();
To enable multiplexing in Go, see
Connection Sharing (Multiplexing).
Use committed type for exactly-once semantics
If you need exactly-once write semantics, create a write stream in committed
type. In committed type, records are available for query as soon as the client
receives acknowledgement from the back end.
Committed type provides exactly-once delivery within a stream through the use of
record offsets. By using record offsets, the application specifies the next
append offset in each call to AppendRows
. The write operation is
only performed if the offset value matches the next append offset. For more
information, see
Manage stream offsets to achieve exactly-once semantics.
If you don't provide an offset, then records are appended to the current end of
the stream. In that case, if an append request returns an error, retrying it
could result in the record appearing more than once in the stream.
To use committed type, perform the following steps:
Java
- Call
CreateWriteStream
to create one or more streams in committed type.
- For each stream, call
AppendRows
in a loop to write batches of records.
- Call
FinalizeWriteStream
for each stream to release the stream. After you
call this method, you cannot write any more rows to the stream. This step is
optional in committed type, but helps to prevent exceeding the limit on
active streams. For more information, see
Limit the rate of stream creation.
Node.js
- Call
createWriteStreamFullResponse
to create one or more streams in committed type.
- For each stream, call
appendRows
in a loop to write batches of records.
- Call
finalize
for each stream to release the stream. After you
call this method, you cannot write any more rows to the stream. This step is
optional in committed type, but helps to prevent exceeding the limit on
active streams. For more information, see
Limit the rate of stream creation.
You cannot delete a stream explicitly. Streams follow the system-defined time to live (TTL):
- A committed stream has a TTL of three days if there is no traffic on the stream.
- A buffered stream by default has a TTL of seven days if there is no traffic on the stream.
The following code shows how to use committed type:
Java
To learn how to install and use the client library for BigQuery, see
BigQuery client libraries.
For more information, see the
BigQuery Java API
reference documentation.
To authenticate to BigQuery, set up Application Default Credentials.
For more information, see
Set up authentication for client libraries.
import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutureCallback;
import com.google.api.core.ApiFutures;
import com.google.api.gax.retrying.RetrySettings;
import com.google.cloud.bigquery.storage.v1.AppendRowsResponse;
import com.google.cloud.bigquery.storage.v1.BigQueryWriteClient;
import com.google.cloud.bigquery.storage.v1.CreateWriteStreamRequest;
import com.google.cloud.bigquery.storage.v1.Exceptions;
import com.google.cloud.bigquery.storage.v1.Exceptions.StorageException;
import com.google.cloud.bigquery.storage.v1.FinalizeWriteStreamResponse;
import com.google.cloud.bigquery.storage.v1.JsonStreamWriter;
import com.google.cloud.bigquery.storage.v1.TableName;
import com.google.cloud.bigquery.storage.v1.WriteStream;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.Descriptors.DescriptorValidationException;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Phaser;
import javax.annotation.concurrent.GuardedBy;
import org.json.JSONArray;
import org.json.JSONObject;
import org.threeten.bp.Duration;
public class WriteCommittedStream {
public static void runWriteCommittedStream()
throws DescriptorValidationException, InterruptedException, IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "MY_PROJECT_ID";
String datasetName = "MY_DATASET_NAME";
String tableName = "MY_TABLE_NAME";
writeCommittedStream(projectId, datasetName, tableName);
}
public static void writeCommittedStream(String projectId, String datasetName, String tableName)
throws DescriptorValidationException, InterruptedException, IOException {
BigQueryWriteClient client = BigQueryWriteClient.create();
TableName parentTable = TableName.of(projectId, datasetName, tableName);
DataWriter writer = new DataWriter();
// One time initialization.
writer.initialize(parentTable, client);
try {
// Write two batches of fake data to the stream, each with 10 JSON records. Data may be
// batched up to the maximum request size:
// https://cloud.google.com/bigquery/quotas#write-api-limits
long offset = 0;
for (int i = 0; i < 2; i++) {
// Create a JSON object that is compatible with the table schema.
JSONArray jsonArr = new JSONArray();
for (int j = 0; j < 10; j++) {
JSONObject record = new JSONObject();
record.put("col1", String.format("batch-record %03d-%03d", i, j));
jsonArr.put(record);
}
writer.append(jsonArr, offset);
offset += jsonArr.length();
}
} catch (ExecutionException e) {
// If the wrapped exception is a StatusRuntimeException, check the state of the operation.
// If the state is INTERNAL, CANCELLED, or ABORTED, you can retry. For more information, see:
// https://grpc.github.io/grpc-java/javadoc/io/grpc/StatusRuntimeException.html
System.out.println("Failed to append records. \n" + e);
}
// Final cleanup for the stream.
writer.cleanup(client);
System.out.println("Appended records successfully.");
}
// A simple wrapper object showing how the stateful stream writer should be used.
private static class DataWriter {
private JsonStreamWriter streamWriter;
// Track the number of in-flight requests to wait for all responses before shutting down.
private final Phaser inflightRequestCount = new Phaser(1);
private final Object lock = new Object();
@GuardedBy("lock")
private RuntimeException error = null;
void initialize(TableName parentTable, BigQueryWriteClient client)
throws IOException, DescriptorValidationException, InterruptedException {
// Initialize a write stream for the specified table.
// For more information on WriteStream.Type, see:
// https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/WriteStream.Type.html
WriteStream stream = WriteStream.newBuilder().setType(WriteStream.Type.COMMITTED).build();
CreateWriteStreamRequest createWriteStreamRequest =
CreateWriteStreamRequest.newBuilder()
.setParent(parentTable.toString())
.setWriteStream(stream)
.build();
WriteStream writeStream = client.createWriteStream(createWriteStreamRequest);
// Configure in-stream automatic retry settings.
// Error codes that are immediately retried:
// * ABORTED, UNAVAILABLE, CANCELLED, INTERNAL, DEADLINE_EXCEEDED
// Error codes that are retried with exponential backoff:
// * RESOURCE_EXHAUSTED
RetrySettings retrySettings =
RetrySettings.newBuilder()
.setInitialRetryDelay(Duration.ofMillis(500))
.setRetryDelayMultiplier(1.1)
.setMaxAttempts(5)
.setMaxRetryDelay(Duration.ofMinutes(1))
.build();
// Use the JSON stream writer to send records in JSON format.
// For more information about JsonStreamWriter, see:
// https://googleapis.dev/java/google-cloud-bigquerystorage/latest/com/google/cloud/bigquery/storage/v1/JsonStreamWriter.html
streamWriter =
JsonStreamWriter.newBuilder(writeStream.getName(), writeStream.getTableSchema(), client)
.setRetrySettings(retrySettings)
.build();
}
public void append(JSONArray data, long offset)
throws DescriptorValidationException, IOException, ExecutionException {
synchronized (this.lock) {
// If earlier appends have failed, we need to reset before continuing.
if (this.error != null) {
throw this.error;
}
}
// Append asynchronously for increased throughput.
ApiFuture<AppendRowsResponse> future = streamWriter.append(data, offset);
ApiFutures.addCallback(
future, new DataWriter.AppendCompleteCallback(this), MoreExecutors.directExecutor());
// Increase the count of in-flight requests.
inflightRequestCount.register();
}
public void cleanup(BigQueryWriteClient client) {
// Wait for all in-flight requests to complete.
inflightRequestCount.arriveAndAwaitAdvance();
// Close the connection to the server.
streamWriter.close();
// Verify that no error occurred in the stream.
synchronized (this.lock) {
if (this.error != null) {
throw this.error;
}
}
// Finalize the stream.
FinalizeWriteStreamResponse finalizeResponse =
client.finalizeWriteStream(streamWriter.getStreamName());
System.out.println("Rows written: " + finalizeResponse.getRowCount());
}
public String getStreamName() {
return streamWriter.getStreamName();
}
static class AppendCompleteCallback implements ApiFutureCallback<AppendRowsResponse> {
private final DataWriter parent;
public AppendCompleteCallback(DataWriter parent) {
this.parent = parent;
}
public void onSuccess(AppendRowsResponse response) {
System.out.format("Append %d success\n", response.getAppendResult().getOffset().getValue());
done();
}
public void onFailure(Throwable throwable) {
synchronized (this.parent.lock) {
if (this.parent.error == null) {
StorageException storageException = Exceptions.toStorageException(throwable);
this.parent.error =
(storageException != null) ? storageException : new RuntimeException(throwable);
}
}
System.out.format("Error: %s\n", throwable.toString());
done();
}
private void done() {
// Reduce the count of in-flight requests.
this.parent.inflightRequestCount.arriveAndDeregister();
}
}
}
}