Serializers

Joule ships with various event formatters and serialisers that convert StreamEvent objects to target streaming or storage formats

Serialization Specification

The SerializerSpecification class is used to defined how StreamEvents are serialised for downstream consumption.

Attributes

Attribute	Description	Type
transformer	Convert StreamEvent to a custom domain type	CustomTransformer
formatter	Convert a StreamEvent to a target format such as Json, CSV, Object.	Formatter Default: Json
compress	If resulting serialization process needs to compress payload.	Boolean Default: False
batch	Batch events to process	Boolean Default: False
properties	Specific properties required for custom serialization process	Properties

Example

Simple example whereby RabbitMQ publishes StreamEvent as Json formatted objects. In this example a set of Joule processes would perform inter-process communication to perform a larger use case as a topology.

rabbitPublisher:
  exchange:
    name: quotes_exchange
    type: FANOUT

  serializer:
    formatter:
      json formatter: {}

CustomTransformer Interface

This classed is used when the use case requires a specific domain data type, from Joule, for a downstream consumption. Developers are expected to provide domain specific implementations by implementing the CustomTransformer interface.

/**
 * Transform passed byte array to collection of StreamEvents
 *
 * @param payload collection of events to transform to target types
 * @return collection of T
 * @throws TranslationException is thrown when a translation failure occurs
 */
Collection<T> transform(Collection<StreamEvent> payload) throws TranslationException;

/**
 * Transform a single StreamEvent in to a specific type
 *
 * @param payload an event
 * @return
 * @throws TranslationException
 */
T transform(StreamEvent payload) throws TranslationException;

Example

Class from the nbanking project where StreamEvents are transformed to Quote type.

public class QuoteTransformer implements CustomTransformer<Quote> {

    public QuoteTransformer() {
        // Required
    }

    @Override
    public Collection<Quote> transform(Collection<StreamEvent> payload) throws TranslationException {
        Collection<Quote> quotes = new ArrayList<>();
        if( payload!= null) {
            for(StreamEvent e : payload){
                quotes.add(transform(e));
            }
        }
        return quotes;
    }

    @Override
    public Quote transform(StreamEvent payload) throws TranslationException {
        return new Quote(
                (String)payload.getValue("symbol"),
                (double)payload.getValue("mid"),
                (double)payload.getValue("bid"),
                (double)payload.getValue("ask"),
                (long)payload.getValue("volume"),
                (double)payload.getValue("volatility"),
                (long)payload.getEventTime(),
                (Date)payload.getValue("date")
                );
    }
}

Available Implementations

Format	DSL	Class
avro	avro serializer	AvroDomainSerializer

Avro

This serializer has extra setting to support ability to transport the resulting StreamEvent to the desired the target data domain type using a provided arvo schema. Currently only local schema files are supported with schema registry support on request.

Example

avro serializer:
    schema: /home/myapp/schema/customer.avsc

Attributes

Attribute	Description	Data Type	Required
schema	Path and name of schema file	String
field mapping	Custom mapping of source StreamEvent fields to target domain fields	Map<String,String>

Formatters

Formatters are mainly used for direct storage whereby Data tools such as PySpark, Apache Presto, DuckDB, MongDB, Postgres, MySQL etc,.

Available Implementations

Format	DSL	Class
json	json formatter	JsonStreamEventFormatter
csv	csv formatter	CSVStreamEventFormatter
parquet	parquet formatter	ParquetStreamEventFormatter

Json

Standard json formater converts processed events to a JSON string using specified attributes

Example

json formatter:
  date format: YYYY/MM/dd
  contentType: application/json
  indent output: false

Attributes

Attribute	Description	Data Type	Required
date format	Date format to apply to date fields	String Default: yyyy/MM/dd
indent output	Apply indentation formatting	Boolean Default: false
contentType	Type of content to inform receiving application	String Default: application/json
encoding	Payload encoding method	String Default: UTF-8
ext	File extension	String Default: json

CSV

Standard csv formatter converts processed events to a CSV string using specified attributes

Example

csv formatter:
  contentType: text/csv
  encoding: UTF_8
  delimiter: "|"

Attributes

Attribute	Description	Data Type	Required
date format	Date format to apply to date fields	String Default: yyyy/MM/dd
delimiter	Field delimiter	Character Default: ","
contentType	Type of content to inform receiving application	String Default: text/csv
encoding	Payload encoding method	String Default: UTF-8
ext	File extension	String Default: csv

Parquet

Converts a StreamEvent to an Avro object using a target schema format before writing to a parquet formatted object.

Example

parquet formatter:
  schema path: /home/joule/outputschema.avro
  compression codec: SNAPPY
  temp filedir: /tmp
  contentType: binary/octet-stream
  encoding: UTF_8

Attributes

Attribute	Description	Data Type	Required
schema path	Path location for the Avro output schema	String
compression codec	Algorithm to use to compress file. Available types: UNCOMPRESSED SNAPPY GZIP LZO BROTLI LZ4 ZSTD	String Default: UNCOMPRESSED
contentType	Type of content to inform receiving application	String Default: binary/octet-stream
encoding	Payload encoding method	String Default: UTF_8
ext	File extension	String Default: parquet
temp file directory	Directory path for temp files	String Default: ./tmp

Supporting classes

To support extendability of the platform the AbstractFormatterSpecification class has been provided.