rowadddbname filter adds a new
column to every incoming row of data containing the schema name of the
table. This can used in combination with analytics replication targets
where the information is being written into a single schema, concentrating
data from multiple source databases into a single database. Optionally,
the filter can also add the information as a primary key (required for
some heterogeneous targets), and the hash of the source database name.
|Pre-configured filter name||
|tpm Option compatibility|
|Data compatibility||Row-events only|
||boolean||true||Add a hash column, computed using the Java hash value of the string for the incoming source database name|
||boolean||true||Add the information to the primary key data in the THL, in addition to the column data|
||string||dbname||The name of the database name column that will be added|
||string||dbname||The name of the database has name column that will be added|
rowadddbname filter adds a
column to every row of THL processed by the filter. This can be used when
data is being written into a single target schema within an analytics
environment, and where the source database can be used to identify a
customer, project or dataset, and therefore queried within the analytics
platform either specifically or with other datasets.
The filter is able to perform the following modifications to every row of incoming data:
Add the source database or schema name.
Add a numerical hash value of the string of the source database of schema name.
Add the database name (and hash name) to the primary key data.
For example, the source THL:
- ROW# = 0 - COL(1: id) = 12 - COL(2: msg) = Hello - COL(3: msg2) = World - KEY(1: id) = NULL
And after the filter has been applied:
- ROW# = 0 - COL(1: id) = 12 - COL(2: msg) = Hello - COL(3: msg2) = World - COL(4: dbname) = msg - COL(5: dbname_hash) = 108417 - KEY(1: id) = NULL - KEY(4: dbname) = NULL - KEY(5: dbname_hash) = NULL
This filter is a required component of deployments when replicating into a single schema within Vertica (see Concentrating Data into a Single Schema with Vertica) and Amazon Redshift (see Concentrating Data into a Single Schema with Vertica).