BigQuery subscriptions

This document provides an overview of a BigQuery subscription, its workflow, and associated properties.

A BigQuery subscription is a type of export subscription that writes messages to an existing BigQuery table as they are received. You don't need to configure a separate subscriber client. Use the Google Cloud console, the Google Cloud CLI, the client libraries, or the Pub/Sub API to create, update, list, detach, or delete a BigQuery subscription.

Without the BigQuery subscription type, you need a pull or push subscription and a subscriber (such as Dataflow) that reads messages and writes them to a BigQuery table. The overhead of running a Dataflow job is not necessary when messages don't require additional processing before storing them in a BigQuery table; you can use a BigQuery subscription instead.

However, a Dataflow pipeline is still recommended for Pub/Sub systems where some data transformation is required before the data is stored in a BigQuery table. To learn how to stream data from Pub/Sub to BigQuery with transformation by using Dataflow, see Stream from Pub/Sub to BigQuery.

The Pub/Sub subscription to BigQuery template from Dataflow enforces exactly once delivery by default. This is typically achieved through deduplication mechanisms within the Dataflow pipeline. However, the BigQuery subscription only supports at least once delivery. If exact deduplication is critical for your use case, consider downstream processes in BigQuery to handle potential duplicates.

Before you begin

Before reading this document, ensure that you're familiar with the following:

  • How Pub/Sub works and the different Pub/Sub terms.

  • The different kinds of subscriptions that Pub/Sub supports and why you might want to use a BigQuery subscription.

  • How BigQuery works and how to configure and manage BigQuery tables.

BigQuery subscription workflow

The following image shows the workflow between a BigQuery subscription and BigQuery.

Flow of messages for a BigQuery subscription
Figure 1. Workflow for a BigQuery subscription

Here is a brief description of the workflow that references Figure 1:

  1. Pub/Sub uses the BigQuery storage write API to send data to the BigQuery table.
  2. The messages are sent in batches to the BigQuery table.
  3. After a successful completion of a write operation, the API returns an OK response.
  4. If there are any failures in the write operation, the Pub/Sub message itself is negatively acknowledged. The message is then re-sent. If the message fails enough times and there's a dead letter topic configured on the subscription, then the message is moved to the dead letter topic.

Properties of a BigQuery subscription

The properties that you configure for a BigQuery subscription determine the BigQuery table to which Pub/Sub writes messages and the type of schema of that table.

For more information, see BigQuery properties.

Schema compatibility

This section is only applicable if you select the option Use topic schema when you create a BigQuery subscription.

Pub/Sub and BigQuery use different ways to define their schemas. Pub/Sub schemas are defined in Apache Avro or Protocol Buffer format while BigQuery schemas are defined using a variety of formats.

The following is a list of important information regarding the schema compatibility between a Pub/Sub topic and a BigQuery table.

  • Any message that contains an improperly formatted field is not written to BigQuery.

  • In the BigQuery schema, INT, SMALLINT, INTEGER, BIGINT, TINYINT, and BYTEINT are aliases for INTEGER; DECIMAL is an alias for NUMERIC; and BIGDECIMAL is an alias for BIGNUMERIC.

  • When the type in the topic schema is a string and the type in the BigQuery table is JSON, TIMESTAMP, DATETIME, DATE, TIME, NUMERIC, or BIGNUMERIC, then any value for this field in a Pub/Sub message must adhere to the format specified for the BigQuery data type.

  • Some Avro logical types are supported, as specified in the following table. Any logical types not listed only match the equivalent Avro type that they annotate, as detailed in the Avro specification.

The following is a collection of mapping of different schema formats to BigQuery data types.

Avro types

Avro Type BigQuery Data Type
null Any NULLABLE
boolean BOOLEAN
int INTEGER, NUMERIC, or BIGNUMERIC
long INTEGER, NUMERIC, or BIGNUMERIC
float FLOAT64, NUMERIC, or BIGNUMERIC
double FLOAT64, NUMERIC, or BIGNUMERIC
bytes BYTES, NUMERIC, or BIGNUMERIC
string STRING, JSON, TIMESTAMP, DATETIME, DATE, TIME, NUMERIC, or BIGNUMERIC
record RECORD/STRUCT
array of Type REPEATED Type
map with value type ValueType REPEATED STRUCT <key STRING, value ValueType>
union with two types, one that is null and the other Type NULLABLE Type
other unions Unmappable
fixed BYTES, NUMERIC, or BIGNUMERIC
enum INTEGER

Avro logical types

Avro Logical Type BigQuery Data Type
timestamp-micros TIMESTAMP
date DATE
time-micros TIME
duration INTERVAL
decimal NUMERIC or BIGNUMERIC

Protocol Buffer types

Protocol Buffer Type BigQuery Data Type
double FLOAT64, NUMERIC, or BIGNUMERIC
float FLOAT64, NUMERIC, or BIGNUMERIC
int32 INTEGER, NUMERIC, BIGNUMERIC, or DATE
int64 INTEGER, NUMERIC, BIGNUMERIC, DATE, DATETIME, or TIMESTAMP
uint32 INTEGER, NUMERIC, BIGNUMERIC, or DATE
uint64 NUMERIC or BIGNUMERIC
sint32 INTEGER, NUMERIC, or BIGNUMERIC
sint64 INTEGER, NUMERIC, BIGNUMERIC, DATE, DATETIME, or TIMESTAMP
fixed32 INTEGER, NUMERIC, BIGNUMERIC, or DATE
fixed64 NUMERIC or BIGNUMERIC
sfixed32 INTEGER, NUMERIC, BIGNUMERIC, or DATE
sfixed64 INTEGER, NUMERIC, BIGNUMERIC, DATE, DATETIME, or TIMESTAMP
bool BOOLEAN
string STRING, JSON, TIMESTAMP, DATETIME, DATE, TIME, NUMERIC, or BIGNUMERIC
bytes BYTES, NUMERIC, or BIGNUMERIC
enum INTEGER
message RECORD/STRUCT
oneof Unmappable
map<KeyType, ValueType> REPEATED RECORD<key KeyType, value ValueType>
enum INTEGER
repeated/array of Type REPEATED Type

Date and time integer representation

When mapping from an integer to one of the date or time types, the number must represent the correct value. The following is the mapping from BigQuery data types to the integer that represents them.

BigQuery Data Type Integer Representation
DATE The number of days since the Unix epoch, January 1, 1970
DATETIME The date and time in microseconds expressed as civil time using the CivilTimeEncoder
TIME The time in microseconds expressed as civil time using the CivilTimeEncoder
TIMESTAMP The number of microseconds since the Unix epoch, January 1, 1970 00:00:00 UTC

BigQuery change data capture

BigQuery subscriptions support change data capture (CDC) updates when use_topic_schema or use_table_schema is set to true in the subscription properties. To use the feature with use_topic_schema, set the schema of the topic with the following fields:

  • _CHANGE_TYPE (required): A string field set to UPSERT or DELETE.

    • If a Pub/Sub message written to the BigQuery table has _CHANGE_TYPE set to UPSERT, then BigQuery updates the row with the same key if it exists or inserts a new row if it does not.

    • If a Pub/Sub message written to the BigQuery table has _CHANGE_TYPE set to DELETE, then BigQuery deletes the row in the table with the same key if it exists.

  • _CHANGE_SEQUENCE_NUMBER (optional): An int64 (long) field set to ensure that updates and deletes made to the BigQuery table are processed in order. Messages for the same row key must contain a monotonically increasing value for _CHANGE_SEQUENCE_NUMBER. Messages with sequence numbers that are lesser than the highest sequence number processed for a row don't have any effect on the row in the BigQuery table. Note that Pub/Sub requires an integer-based value as opposed to the string-based value used when interacting with BigQuery directly.

To use the feature with use_table_schema, include the preceding fields in the JSON message.

For information about CDC pricing, see CDC pricing.

Pub/Sub service account permissions

To create a BigQuery subscription, the Pub/Sub service account must have permission to write to the specific BigQuery table and to read the table metadata. For more information, see Assign BigQuery roles to the Pub/Sub service account.

Handle message failures

When a Pub/Sub message cannot be written to BigQuery, the message cannot be acknowledged. To forward such undeliverable messages, configure a dead-letter topic on the BigQuery subscription. The Pub/Sub message forwarded to the dead-letter topic contains an attribute CloudPubSubDeadLetterSourceDeliveryErrorMessage that has the reason that the Pub/Sub message couldn't be written to BigQuery.

If Pub/Sub cannot write messages to BigQuery, then Pub/Sub backs off delivery of messages in a way similar to push backoff behavior. However, if the subscription has a dead-letter topic attached to it, Pub/Sub does not back off delivery when message failures are due to schema compatibility errors.

Quotas and limits

There are quota limitations on the BigQuery subscriber throughput per region. For more information, see Pub/Sub quotas and limits.

BigQuery subscriptions write data by using the BigQuery Storage Write API. For information about the quotas and limits for the Storage Write API, see BigQuery Storage Write API requests. BigQuery subscriptions only consume the throughput quota for the Storage Write API. You can ignore the other Storage Write API quota considerations in this instance.

Pricing

For the pricing for BigQuery subscriptions, see the Pub/Sub pricing page.

What's next