Changelog

1.3.0

Cascaded Processing
- The concept of a user-defined "stream" was introduced. Similar to CREATE VIEW in SQL, CREATE STREAM name FROM SELECT ... allows to create a stream holding the results of a SELECT query over some input stream.
- In particular, ANALYZE results can be added to a stream in a new column and used further down in the processing pipeline.
- A user can define custom functions in JavaScript and use them in queries using the CREATE FUNCTION statement.
- Multiple data sources can be defined and used one after another for updating/analyzing a model.
Trigger-Based Action
- A user can also define functions without a return value using CREATE TRIGGER FUNCTION and attach them as trigger on a stream using CREATE TRIGGER. This can be used to act based on the contents of a stream, in particular analysis results.
Time-Series Analysis using Sliding Windows
- To analyze time-series data, sliding windows over an input stream (based on either item count or an embedded timestamp) can be computed and data in each window aggregated using a set of provided functions such as standard deviation or histogram.
- The results of this aggregation can be used like any other data stream.
Other
- It is now possible to do feature extraction using user-defined functions.

CREATE DATASOURCE
- A schema should now in general be provided, as in many cases schema inference will lead to errors whenever an empty data batch is encountered.
CREATE MODEL
- The syntax for specifying the label/id column has changed from model_name WITH (label: "class", datum: "name") to model_name (label: class) AS ...
- Feature converters are not specified in the JSON configuration any more, but instead with a column WITH converter syntax.
UPDATE MODEL
- The statement will only establish the connection between stream and model, processing will not start yet. This will be done by START PROCESSING.

This is the first public release. See the documentation for features and usage information.