between the current position to the Transaction 1 start time. ![]() The stream returns the change data capture records. The stream position advances to the transaction start time if the transaction commits otherwise it stays at the same position. The delta records returned by streams in a transaction is the range from the current position of the stream until the transaction start This differs from the read committed mode supported for tables, in which statements see any changes made by previous statementsĮxecuted within the same transaction, even though those changes are not yet committed. In repeatable read mode, multiple SQL statements within a transaction see the same set of records Streams support repeatable read isolation. Transactions are tracked by the change tracking system but do not update the stream until the explicit transaction statement is committedĪnd the existing change data is consumed. DML updates to the source object in parallel ToĮnsure multiple statements access the same change records in the stream, surround them with an explicit transaction statement SELECT (CTAS) statements that populate a new table with rows from an existing stream.Ī DML statement that selects from a stream consumes all of the change data in the stream as long as the transaction commits successfully. This behavior pertains both to DML statements and CREATE TABLE … AS When the transaction began rather than when the statement was run. When a SQL statement queries a stream within an explicit transaction, the stream is queried at the stream advance point (i.e. In the INSERT statement, query the stream but include a WHERE clause thatįilters out all of the change data (e.g. ![]() Insert the current change data into a temporary table. Recreate the stream (using the CREATE OR REPLACE STREAM syntax). To advance the offset of a stream to the current table version without consuming the change data in a DML operation, complete either of One example of a consumer of CDC records is a data pipeline, in which only the data in staging tables that hasĬhanged since the last extraction is transformed and copied into other tables. Travel) to consume the change records for an object at the same or different offsets. So too, a stream can be dropped and other streamsĬreated at the same or different points of time (either by creating the streams consecutively at different times or by using Time Aīookmark can be thrown away and other bookmarks inserted in different places in a book. It might be useful to think of a stream as a bookmark, which indicates a point in time in the pages of a book (i.e. Note that for streams on views, change tracking must be enabled explicitly for the view and underlying tables to add the hidden Returned when querying a stream rely on a combination of the offset stored in the stream and the change tracking metadata stored in the ![]() These columns consume a small amount of storage. When the first stream for a table is created, several hidden columnsĪre added to the source table and begin storing change tracking metadata. Records by leveraging the versioning history for the source object. A stream only stores an offset for the source object and returns CDC Note that a stream itself does not contain any table data. Change information mirrors the column structure of the tracked source object and includesĪdditional metadata columns that describe each change event. The state of a row before and after the change. ![]() Tracking system utilized by the stream then records information about the DML changes after this snapshot was taken. Tables for a view) by initializing a point in time (called an offset) as the current transactional version of the object. When created, a stream logically takes an initial snapshot of every row in the source object (e.g.
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