stream mapping is very similar to the
read mapping, except that it will create a streaming
result used for creating continuous event processing applications
mappings: measurements-raw: kind: stream relation: measurements-raw columns: raw_data: String filter: "raw_data IS NOT NULL" relations: measurements-raw: kind: kafka hosts: - kafka-01 - kafka-02 topics: measurements_raw
Since Flowman 0.18.0, you can also directly specify the relation inside the dataset definition. This saves you
from having to create a separate relation definition in the
relations section. This is only recommended, if you
do not access the target relation otherwise, such that a shared definition would not provide any benefit.
mappings: measurements-raw: kind: stream relation: kind: kafka hosts: - kafka-01 - kafka-02 topics: measurements_raw columns: raw_data: String filter: "raw_data IS NOT NULL"
kind(mandatory) (type: string):
broadcast(optional) (type: boolean) (default: false): Hint for broadcasting the result of this mapping for map-side joins.
cache(optional) (type: string) (default: NONE): Cache mode for the results of this mapping. Supported values are
NONE- Disables caching of teh results of this mapping
DISK_ONLY- Caches the results on disk
MEMORY_ONLY- Caches the results in memory. If not enough memory is available, records will be uncached.
MEMORY_ONLY_SER- Caches the results in memory in a serialized format. If not enough memory is available, records will be uncached.
MEMORY_AND_DISK- Caches the results first in memory and then spills to disk.
MEMORY_AND_DISK_SER- Caches the results first in memory in a serialized format and then spills to disk.
relation(mandatory) (type: string): Specifies the name of the relation to read from.
columns(optional) (type: map:data_type) (default: empty): Specifies the list of columns and types to read from the relation. This schema will be applied to the records after they have been read and interpreted by the underlying source. This schema will also be used as a substitute for schema inference and therefore can be very helpful when using
filter(optional) (type: string) (default: empty): An optional SQL filter expression that is applied for reading only a subset of records. The filter is applied after the schema as specified in
columnsis applied. This means that if you are using
columns, then you can only access these columns in the
main- the only output of the mapping