Cast
The following provides usage information for the Apache Kafka® SMT org.apache.kafka.connect.transforms.Cast
Description
Cast fields (or the entire key or value) to a specific type, updating the schema
if one is present. For example, this can be used to force an integer field into
an integer of smaller width. Only simple primitive types are supported, such as
integer, float, boolean, and string.
Use the concrete transformation type designed for the record key (org.apache.kafka.connect.transforms.Cast$Key) or value (org.apache.kafka.connect.transforms.Cast$Value).
Examples
Cast can transform an entire primitive key/value or one or more fields of a
complex (Struct or Map) key or value. The two configuration snippet examples
below show how to use Cast in these two scenarios.
Cast Value
This example shows how to use Cast to transform a 64-bit floating point
value into a string.
"transforms": "Cast",
"transforms.Cast.type": "org.apache.kafka.connect.transforms.Cast$Value",
"transforms.Cast.spec": "string"
Before: 63521704.02
After: "63521704.02"
Cast Comma-Separated Values
This example shows how to use Cast with a complex key or value. It shows a
comma-separated field:type pair, where field is the name of the field to
cast and type is the type to cast the field into.
"transforms": "Cast",
"transforms.Cast.type": "org.apache.kafka.connect.transforms.Cast$Value",
"transforms.Cast.spec": "ID:string,score:float64"
The before and after example below shows a Map or Struct with an ID field of
46290 and a score field of 4761. The ID field is cast into a
string and the score field is cast into a 64-bit floating point value.
Before:
{"ID": 46920,"score": 4761}
After:
{"ID": "46290","score": 4761.0}
Properties
| Name |
Description |
Type |
Default |
Valid Values |
Importance |
|---|
spec |
A single type to cast the entire value, or for Maps and Structs the comma-separated list of field names and the type to which they should be cast, of the form field1:type1,field2:type2. Valid types are int8, int16, int32, int64, float32, float64, boolean, and string. |
list |
|
comma-separated list of colon-delimited pairs of field:type, e.g. foo:int32,bar:string |
high |
Predicates
Transformations can be configured with predicates so that the transformation
is applied only to records which satisfy a condition. You can use predicates in
a transformation chain and, when combined with the Apache Kafka® Filter, predicates can conditionally filter out specific records.
Predicates are specified in the connector configuration. The following properties are used:
predicates: A set of aliases for predicates applied to one or more transformations.predicates.$alias.type: Fully qualified class name for the predicate.predicates.$alias.$predicateSpecificConfig: Configuration properties for the predicate.
All transformations have the implicit config properties predicate and
negate. A predicular predicate is associated with a transformation by
setting the transformation’s predicate configuration to the predicate’s alias.
The predicate’s value can be reversed using the negate configuration
property.
Kafka Connect includes the following predicates:
org.apache.kafka.connect.predicates.TopicNameMatches: Matches records in a topic with a name matching a particular Java regular expression.org.apache.kafka.connect.predicates.HasHeaderKey: Matches records which have a header with the given key.org.apache.kafka.connect.predicates.RecordIsTombstone: Matches tombstone records (that is, records with a null value).
Predicate Examples
Example 1:
You have a source connector that produces records to many different topics and
you want to do the following:
- Filter out the records in the
foo topic entirely.
- Apply the
ExtractField transformation with the field name other_field to records in all topics, except the topic bar.
To do this, you need to first filter out the records destined for the topic
foo. The Filter transformation removes records from further processing.
Next, you use the TopicNameMatches predicate to apply the transformation
only to records in topics which match a certain regular expression. The only
configuration property for TopicNameMatches is a Java regular expression
used as a pattern for matching against the topic name. The following example
shows this configuration:
transforms=Filter
transforms.Filter.type=org.apache.kafka.connect.transforms.Filter
transforms.Filter.predicate=IsFoo
predicates=IsFoo
predicates.IsFoo.type=org.apache.kafka.connect.predicates.TopicNameMatches
predicates.IsFoo.pattern=foo
Using this configuration, ExtractField is then applied only when the topic
name of the record is not bar. The reason you can’t use TopicNameMatches
directly is because it would apply the transformation to matching topic names,
not topic names which do not match. The transformation’s implicit negate
configuration properties inverts the set of records which a predicate matches.
This configuration addition is shown below:
transforms=Filter,Extract
transforms.Filter.type=org.apache.kafka.connect.transforms.Filter
transforms.Filter.predicate=IsFoo
transforms.Extract.type=org.apache.kafka.connect.transforms.ExtractField$Key
transforms.Extract.field=other_field
transforms.Extract.predicate=IsBar
transforms.Extract.negate=true
predicates=IsFoo,IsBar
predicates.IsFoo.type=org.apache.kafka.connect.predicates.TopicNameMatches
predicates.IsFoo.pattern=foo
predicates.IsBar.type=org.apache.kafka.connect.predicates.TopicNameMatches
predicates.IsBar.pattern=bar
Example 2:
The following configuration shows how to use a predicate in a transformation
chain with the ExtractField transformation and the negate=true
configuration property:
transforms=t2
transforms.t2.predicate=has-my-prefix
transforms.t2.negate=true
transforms.t2.type=org.apache.kafka.connect.transforms.ExtractField$Key
transforms.t2.field=c1
predicates=has-my-prefix
predicates.has-my-prefix.type=org.apache.kafka.connect.predicates.TopicNameMatch
predicates.has-my-prefix.pattern=my-prefix-.*
The transform t2 is only applied when the predicate has-my-prefix is
false (using the negate=true parameter). The predicate is configured by the
keys with prefix predicates.has-my-prefix. The predicate class is
org.apache.kafka.connect.predicates.TopicNameMatch and it’s pattern
parameter has the value my-prefix-.* . With this configuration, the
transformation is applied only to records where the topic name does not
start with my-prefix-.
Tip
The benefit of defining the predicate separately from the transform is it
makes it easier to apply the same predicate to multiple transforms. For
example, you can have one set of transforms use one predicate and another set
of transforms use the same predicate for negation.
Predicate Properties
| Name |
Description |
Type |
Default |
Valid Values |
Importance |
|---|
TopicNameMatches |
A predicate which is true for records with a topic name that matches the configured regular expression. |
string |
|
non-empty string, valid regex |
medium |
HasHeaderKey |
A predicate which is true for records with at least one header with the configured name. |
string |
|
non-empty string |
medium |
RecordIsTombstone |
A predicate which is true for records which are tombstones (that is, records with a null value). |
|
|
|
medium |