Casper Datasets 2.1.5
Simply put, the Casper Datasets library is a memory-based dataset technology.
Casper Datasets enables you to define a typed, n-dimensional dataset, and allows simple sorting, filtering, and aggregation operations.
Within a typical application stack, a data access / business object tier would require developers to create several context-specific pieces of code:
· Objects that represent units of data (typically as a java bean in java)
· A means to map rows from the data store to their objectified counterparts in memory.
· Custom sorters, comparators, and filters to manipulate these objects.
In addition, this would have to be repeated for each object abstraction within an application.
The Casper Datasets library was designed to unify these requirements into a single library that is both simple and intuitive.
Detailed instructions on how to install and use the Casper Datasets utility on your Mac are available HERE.
Casper Datasets is a cross-platform utility capable of running on any operating system that comes with Java support (e.g. Mac OS X, Windows, Linux).
- The following major features are supported:
- In-memory caching of data rows
- Searching and filtering through the dataset based on attributes on any given column. This is accomplished through the use of filter chains, which support the following types of matches: (1) Equality, (2) Regular expressions, (3) Numeric Ranges, (4) Date Ranges.
- Scrolling through query results via a cursor, akin to java.sql.ResultSet
- Indexing of columns for optimized lookup
- Basic aggregation functionality: sums, weighted sums, average, weighted averages
- Relational database adapters to load relational rows effortlessly
- The following import/export features are supported (via CasperDatasetsIo):
- Import/export from collection of POJO beans
- Import/export from delimited (CSV) files
- Import from Excel (XLS/XLSX) files
- The following major additional features are supported (via CasperDatasetsExt):
- Narrowing functionality which converts the columns in a casper dataset to the smallest possible value type of all items while retaining fidelity