Awesome

Data-streamer

In order to support the evaluation of stream processing engine a data source that is able to mimic different streaming data characteristics is desirable. Evaluating the engines with different data stream characteristics would provide more insights into the performance of the engine.

This data streaming component is inspired by the works of Van Dongen et al on streaming engines benchmark. In the reference paper, Apache Kafa was used as a data source for a more reliable measurement of latency. However, distributed messaging brokers like Kafka have an overhead of I/O operations since they write the data first to disk before reading and streaming it.

In order to reduce the overhead of the I/O operations, we implemented an in-memory data streaming component which will store the necessary data in memory first before streaming. The data streamer could also be
generalized to stream any kinds of data for evaluation purposes without being bound to a specific dataset.

Configuration of data streamer

The data streamer can be configured with the config.toml file. Currently, only two mode of data streaming characteristics are supported;

• Constant: streams the data at a constant stream data rate determined by the volume parameter
• Periodic: streams the data at a periodic rate, a burst of data followed by low data stream rate. The amount of data streamed during the burst is determined by the volume parameter.

Multiple data sources can be streamed by defining more array of tables with the key [[streamconfigs]]

The config file looks as follows:

log_level="info" 

[[streamconfigs]]
ip = "0.0.0.0"
port = 9000
mode = "Constant"
volume = 1
input_format = "JSON"
output_format = "JSON"
data_folder = "./data/flow"

[[streamconfigs]]
ip = "0.0.0.0"
port = 9001
mode = "Periodic"
volume = 20
input_format = "JSON"
output_format = "JSON"
data_folder = "./data/speed"

Running

To start the data streamer, you could run the following command:

./start.sh

This will start the docker for the data streamer component and listen for client connections at the specified ports.

Stopping

Stopping the data streamer is as simple as running:

./stop.sh