Update

Description

The Update transform looks up a row in a table using one or more lookup keys and updates it if needed.

If the row can’t be found, nothing is done.

If the row is found the row in the table is updated.

Supported Engines

Hop Engine

Supported

Spark

Maybe Supported

Flink

Maybe Supported

Dataflow

Maybe Supported

Options

Option	Description
Commit size	The number of rows to update before running a commit.
Use batch updates?	Allows the use of batch updates.
Skip lookup	Skips the row lookup.
Ignore lookup failure?	Allows the transform to skip lookup failures.
Flag field (key found)	Field which contains whether the key was found or not.
Connection	The database connection to which data is written.
Key Lookup table	Allows you to specify a list of field values and comparators. You can use the following comparators: =, = ~NULL, <>, <, ⇐, >, >=, LIKE, BETWEEN, IS NULL, IS NOT NULL
SQL button	Click SQL to generate the SQL to create the table and indexes for correct operation.
Transform name	Name of the transform; this name has to be unique in a single pipeline.
Target schema	The name of the Schema for the table to which data is written. This is important for data sources that allow for table names with periods in them.
Target table	Name of the table in which you want to do the update.
Update Fields	Allows you to specify all fields in the table you want to update.

Option

Description

Commit size

The number of rows to update before running a commit.

Use batch updates?

Allows the use of batch updates.

Skip lookup

Skips the row lookup.

Ignore lookup failure?

Allows the transform to skip lookup failures.

Flag field (key found)

Field which contains whether the key was found or not.

Connection

The database connection to which data is written.

Key Lookup table

Allows you to specify a list of field values and comparators. You can use the following comparators: =, = ~NULL, <>, <, ⇐, >, >=, LIKE, BETWEEN, IS NULL, IS NOT NULL

SQL button

Click SQL to generate the SQL to create the table and indexes for correct operation.

Transform name

Name of the transform; this name has to be unique in a single pipeline.

Target schema

The name of the Schema for the table to which data is written. This is important for data sources that allow for table names with periods in them.

Target table

Name of the table in which you want to do the update.

Update Fields

Allows you to specify all fields in the table you want to update.