Overview
The data hierarchy in Datastream is:
- A stream, which is comprised of a data source and a destination.
- An object, which is a portion of a stream, such as a table from a specific database.
- An event, which is a single change generated by a specific object, such as a database insert.
Streams, objects, and events have data and metadata associated with them. This data and metadata can be used for different purposes.
About events
Each event consists of three types of data:
- Event data: This represents the change to the data itself from the object originating from the stream source. Every event contains the entirety of the row that changed.
- Generic metadata: This metadata appears on every event generated by Datastream which is used for actions, such as removing duplicate data in the destination.
- Source-specific metadata: This metadata appears on every event generated by a specific stream source. This metadata varies by source.
Event data
Event data is the payload of every change from a given object originating from a stream source.
Events are in either the Avro or JSON format.
When working with the Avro format, for each column, the event contains the column index and value. Using the column index, the column name and unified type can be retrieved from the schema in the Avro header.
When working with the JSON format, for each column, the event will contain the column name and value.
Event metadata can be used to collect information about the event's origin, as well as to remove duplicate data in the destination and order events by the downstream consumer.
The following tables list and describe the fields and data types for generic and source-specific event metadata.
Generic metadata
This metadata is consistent across streams of all types.
Field | Avro type | JSON type | Description |
---|---|---|---|
stream_name |
string | string | The unique stream name as defined at creation time. |
read_method |
string | string | Indicates if the data was read from the source using a change data capture (CDC) method, as part of historical backfill, or as part of a supplementation task that's created when a transaction is rolled back during CDC replication. Possible values include:
|
object |
string | string | The name used to group different types of events, typically the name of the table or object in the source. |
schema_key |
string | string | The unique identifier for the unified schema of the event. |
uuid |
string | string | A unique identifier for the event generated by Datastream. |
read_timestamp |
timestamp-millis | string | The timestamp (UTC) when the record was read by Datastream (the epoch timestamp in milliseconds). |
source_timestamp |
timestamp-millis | string | The timestamp (UTC) when the record changed on the source (the epoch timestamp in milliseconds). |
sort_keys |
{"type": "array", "items": ["string", "long"]} |
array | An array of values that can be used to sort events in the order in which they occurred. |
Source-specific metadata
This metadata is associated with CDC and backfill events from a source database. To view this metadata, select a source from the drop-down menu below.
Source | Field | Avro type | JSON type | Description |
---|---|---|---|---|
MySQL | log_file |
string | string | The log file that Datastream pulls events from in CDC replication. |
MySQL | log_position |
long | long | The log position (offset) in the MySQL binary log. |
MySQL | primary_keys |
string array | string array | The list of (one or more) column names that make up the tables primary key. If the table doesn't have a primary key, then this field is empty. |
MySQL | is_deleted |
boolean | boolean |
|
MySQL | database |
string | string | The database associated with the event. |
MySQL | table |
string | string | The table associated with the event. |
MySQL | change_type |
string | string | The type of change ( |
Oracle | log_file |
string | string | The log file that Datastream pulls events from in CDC replication. |
Oracle | scn |
long | long | The log position (offset) in the Oracle transaction log. |
Oracle | row_id |
string | string | Oracle's row_id. |
Oracle | is_deleted |
boolean | boolean |
|
Oracle | database |
string | string | The database associated with the event. |
Oracle | schema |
string | string | The schema associated with the table from the event. |
Oracle | table |
string | string | The table associated with the event. |
Oracle | change_type |
string | string | The type of change ( |
Oracle | tx_id |
string | string | The transaction ID to which the event belongs. |
Oracle | rs_id |
string | string | The record set ID. The coupling of rs_id and ssn uniquely identifies a row in V$LOGMNR_CONTENTS . rs_id uniquely identifies the redo record that generated the row. |
Oracle | ssn |
long | long | A SQL sequence number. This number is used with rs_id and uniquely identifies a row in V$LOGMNR_CONTENTS . |
PostgreSQL | schema |
string | string | The schema associated with the table from the event. |
PostgreSQL | table |
string | string | The table associated with the event. |
PostgreSQL | is_deleted |
boolean | boolean |
|
PostgreSQL | change_type |
string | string | The type of change (INSERT , UPDATE , DELETE ) that the event represents.
|
PostgreSQL | tx_id |
string | string | The transaction ID to which the event belongs. |
PostgreSQL | lsn |
string | string | The log sequence number for the current entry. |
PostgreSQL | primary_keys |
string array | string array | The list of (one or more) column names that make up the tables primary key. If the table doesn't have a primary key, then this field is empty. |
SQL Server | table |
string | string | The table associated with the event. |
SQL Server | database |
long | long | The database associated with the event. |
SQL Server | schema |
string array | string array | The schema associated with the table from the event. |
SQL Server | is_deleted |
boolean | boolean |
|
SQL Server | lsn |
string | string | The log sequence number for the event. |
SQL Server | tx_id |
string | string | The transaction ID to which the event belongs. | SQL Server | physical_location |
Integer array | Integer array | The physical location of the log record described by three integers: file ID, page ID and slot ID of the record. |
SQL Server | replication_index |
String array | String array | The list of column names of an index that can uniquely identify a row in the table. |
SQL Server | change_type |
String | String | The type of change (`INSERT`, UPDATE, `DELETE`) that the event represents. |
Example of an event flow
This flow illustrates the events generated by three consecutive operations:
INSERT
, UPDATE
, and DELETE
, on a single row in a SAMPLE
table for a source database.
TIME | THIS_IS_MY_PK (int) | FIELD1 (nchar nullable) | FIELD2 (nchar non-null)> |
---|---|---|---|
0 | 1231535353 | foo | TLV |
1 | 1231535353 | NULL | TLV |
INSERT (T0)
The message payload consists of the entirety of the new row.
{
"stream_name": "projects/myProj/locations/myLoc/streams/Oracle-to-Source",
"read_method": "oracle-cdc-logminer",
"object": "SAMPLE.TBL",
"uuid": "d7989206-380f-0e81-8056-240501101100",
"read_timestamp": "2019-11-07T07:37:16.808Z",
"source_timestamp": "2019-11-07T02:15:39",
"source_metadata": {
"log_file": ""
"scn": 15869116216871,
"row_id": "AAAPwRAALAAMzMBABD",
"is_deleted": false,
"database": "DB1",
"schema": "ROOT",
"table": "SAMPLE"
"change_type": "INSERT",
"tx_id":
"rs_id": "0x0073c9.000a4e4c.01d0",
"ssn": 67,
},
"payload": {
"THIS_IS_MY_PK": "1231535353",
"FIELD1": "foo",
"FIELD2": "TLV",
}
}
UPDATE (T1)
The message payload consists of the entirety of the new row. It doesn't include previous values.
{
"stream_name": "projects/myProj/locations/myLoc/streams/Oracle-to-Source",
"read_method": "oracle-cdc-logminer",
"object": "SAMPLE.TBL",
"uuid": "e6067366-1efc-0a10-a084-0d8701101101",
"read_timestamp": "2019-11-07T07:37:18.808Z",
"source_timestamp": "2019-11-07T02:17:39",
"source_metadata": {
"log_file":
"scn": 15869150473224,
"row_id": "AAAGYPAATAAPIC5AAB",
"is_deleted": false,
"database":
"schema": "ROOT",
"table": "SAMPLE"
"change_type": "UPDATE",
"tx_id":
"rs_id": "0x006cf4.00056b26.0010",
"ssn": 0,
},
"payload": {
"THIS_IS_MY_PK": "1231535353",
"FIELD1": null,
"FIELD2": "TLV",
}
}
DELETE (T2)
The message payload consists of the entirety of the new row.
{
"stream_name": "projects/myProj/locations/myLoc/streams/Oracle-to-Source",
"read_method": "oracle-cdc-logminer",
"object": "SAMPLE.TBL",
"uuid": "c504f4bc-0ffc-4a1a-84df-6aba382fa651",
"read_timestamp": "2019-11-07T07:37:20.808Z",
"source_timestamp": "2019-11-07T02:19:39",
"source_metadata": {
"log_file":
"scn": 158691504732555,
"row_id": "AAAGYPAATAAPIC5AAC",
"is_deleted": true,
"database":
"schema": "ROOT",
"table": "SAMPLE"
"change_type": "DELETE",
"tx_id":
"rs_id": "0x006cf4.00056b26.0011",
"ssn": 0,
},
"payload": {
"THIS_IS_MY_PK": "1231535353",
"FIELD1": null,
"FIELD2": "TLV",
}
}
Ordering and consistency
This section covers how Datastream handles ordering and consistency.
Ordering
Datastream doesn't guarantee ordering, but each event contains the full row of data and the timestamp of when the data was written to the source. In BigQuery, out-of-order events will be merged in the correct sequence automatically. BigQuery uses the event metadata and an internal change sequence number (CSN) to apply the events to the table in the correct order. In Cloud Storage, events from the same time can span more than one file.
Events that are generated out of order happen by design when events are backfilled for the initial backfill of data that's created when the stream is initiated.
Ordering can be inferred on a source-by-source basis.
Source | Description |
---|---|
MySQL | Events that are part of the initial backfill have the Events that are part of the ongoing replication have the The order can be inferred by the combination of the |
Oracle | Events that are part of the initial backfill have the Events that are part of the ongoing replication have the The order can be inferred by the combination of the |
PostgreSQL | Events that are part of the initial backfill have the Events that are part of the ongoing replication have the The order can be inferred by the combination of the |
SQL Server |
Events that are part of the initial backfill have the Events that are part of the ongoing replication have the The order can be inferred by the combination of the |
Consistency
Datastream guarantees that the data from the source database will be delivered to the destination at least once. No event will be missed, but there's a possibility of duplicate events in the stream. The window for duplicate events should be on the order of minutes, and the universally unique identifier (UUID) of the event in the event metadata can be used to detect duplicates.
When database log files contain uncommitted transactions, if any transactions are rolled back, then the database reflects this in the log files as "reverse" data manipulation language (DML) operations. For example, a rolled-back INSERT
operation will have a corresponding DELETE
operation. Datastream reads these operations from the log files.
About streams
Every stream has metadata that describes both the stream and the source from which it pulls data. This metadata includes information such as the stream name, the source and destination connection profiles, and so on.
To view the complete definition of the Stream object, see the API Reference documentation.
Stream state and status
A stream can be in one of the following states:
Not started
Starting
Running
Draining
Paused
Failed
Failed permanently
You can use the logs to find additional status information, such as the tables backfilling, number of rows processed, and so on. You can also use the FetchStreamErrors
API to retrieve errors.
Object metadata available using the discover API
The discover API returns objects which represent the structure of the objects defined in the data source or destination that's represented by the connection profile. Each object has metadata on the object itself, as well as for every field of data that it pulls. This metadata is available via the discover API.
What's next
- To learn more about streams, see Stream lifecycle.
- To learn how to create a stream, see Create a stream.