Download JAR files tagged by bigger with all dependencies

the parent pom for all bigger pfabulist projects, with all checks but the license check

Lightweight text file viewer for huge file bigger than 10GiB

This plugin allows to build only submodules that contain changes. For bigger monorepo project this might speed the build speed dramatically.

This bundle allows to use DBpedia as Referenced Site. The build also downloads a small DBPedia index that contains 43k entities. This index can be upgrated to an bigger version by copying a dbpedia.solrindex.zip file into the Stanbol /datafiles folder.

Java UUID Generator (JUG) is a Java library for generating Universally Unique IDentifiers, UUIDs (see http://en.wikipedia.org/wiki/UUID). It can be used either as a component in a bigger application, or as a standalone command line tool. JUG generates UUIDs according to the IETF UUID draft specification. JUG supports 3 original official UUID generation methods as well as later additions (v6, v7)

A scalable, concurrent, in-memory Key Value (KV) map. Oak implements a concurrent Key-Value map that can keep all keys and values off-heap. This enables working with bigger heap sizes than JVM's managed heap. OakMap implements an API similar to the industry standard Java8 ConcurrentNavigableMap API. It provides strong (atomic) semantics for read, write, and read-modify-write, as well as (non-atomic) range query (scan) operations, both forward and backward. OakMap is optimized for big keys and values, in particular, for incremental maintenance of objects (update in-place). It is faster and scales better with additional CPU cores than the popular Java ConcurrentNavigableMap ConcurrentSkipListMap

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.