1. Event Based Systems Short intro on Trident
Dr. Emanuel Onica
Faculty of Computer Science, Alexandru Ioan Cuza University of Iaşi

2. Trident – general description
Offers a higher level of abstraction on top of Storm topologies + some extras:
transactional processing - tuples are sent in batches and a successful/failed send send is detected at batch level

3. Trident – general description
state management – a fault-tolerant state is maintained internally in the topology holding information about the batch processing
exactly once processing – every batch receives an ID and is processed exactly once by an operator (in case of fail and resending, the operators which already processed it will skip re-processing)
filtering and aggregation abstractions

4. Trident – topology and spouts
The Trident topology:
TridentTopology topology = new TridentTopology();
Spouts in Trident:
Implement the ITridentSpout interface
Three types:
Non-transactional – same tuple can appear in different batches
Transactional – no batches overlapping, and a batch with a given ID will always have the same tuples
Opaque – no batches overlapping, but batches composition might vary in time (i.e., when re-emitting failed batches tuples can be split differently between these)

5. Trident – topology and spouts
The simplest spout – for testing purposes:
FeederBatchSpout spout =
new FeederBatchSpout (ImmutableList.of (“field1",...,“fieldN"));
Emitting tuples:
spout.feed(ImmutableList.of(new Values("val1", ..., "valN")));
A topology is created through chaining the operations. Some example:
TridentState state = topology.newStream(“stream_name", spout).each(new Fields(“field1", “field2"),new Function(), new Fields(“field3")).groupBy(new Fields(“field3"))
.persistentAggregate(new MemoryMapState.Factory(), new Count(), new Fields("count"));

6. Trident – the topology chain
The data stream is created using newStream("stream_name",spout_instance) .
Various operations can further be applied on a stream:
each(new Values("selector1","selector2",...,"selectorN"),new SomeFilter("some_args"))
//selects a subset of fields and applies the isKeep() method in a filter extending BaseFilter to filter tuples based on the selection; the entire tuple will be forwarded or not
each(new Values("selector1","selector2",...,"selectorN"),new SomeFunction("some_args"),new Values("appended1","appended2",...,"appendedN"))
//selects a subset of fields and applies the execute() method in a function extending BaseFunction to apply a function on the tuples based on the selection; the entire tuple will be forwarded with possible extra values appended

7. Trident – the topology chain
aggregate(new AggregatePrimitive(),new Fields("aggregated_field"))
//aggregates the incoming tuples in a new field using a specific primitive for aggregation (e.g., Count())
groupBy(new Fields(“field_name"))
//similar to groupBy in the original Storm topology (shuffle() also exists)
parallelismHint(number)
//sets the degree of parallelism on the topology up to the first partitioning operation (e.g., groupBy()/shuffle())