http:// boom.cs.berkeley.edu/
Mission
Enabling the construction of data-rich systems at unprecedented scales using a minimum of software.
About
Many say that "The Cloud" will be the next game-changing computing platform. The race is on to define and capture it.
Historically, new platforms take off when independent developers start to make innovative use of their unique features. In the case of Cloud Computing, that means exploiting distributed systems in a datacenter. Up to now there's been no widely-used programming model that lets developers easily coordinate the distributed power of a datacenter.
Enter BOOM, an effort to explore implementing Cloud software using disorderly, data-centric languages. BOOM stands for the Berkeley Orders Of Magnitude project, because we seek to enable people to build systems that are OOM bigger than are building today, with OOM less effort than traditional programming methodologies.
For more, please visit the FAQ page.
Bloom and Dedalus
Bloom is the language from the BOOM project. It is currently available in an alpha release as a DSL in Ruby called "Bud". Bloom is designed to avoid the traditional mismatches between distributed platforms and sequential programming languages. It features a "disorderly" approach to program state and logic, which encourages data-centric parallel thinking, while calling programmer attention to asynchrony. A key aspect of Bloom is the use of the CALM principle to build automatic program analysis and visualization tools for reasoning about coordination and consistency.
Dedalus is a temporal logic language that serves as a clean foundation for Bloom. The key insight in Dedalus is that distributed programming is about time, not about space, and programmers should focus their attention on data, invariants, and changes in time. Issues of spatial layout are set aside where they belong: as performance details that need to be addressed as part of tuning, or managed by an optimizer. Dedalus is an evolution of our earlier Overlog language, which in turn was based in Datalog. Where Overlog had complicated operational semantics, Dedalus is pure temporal logic with no need for the programmer to understand the behavior of the interpreter/compiler.
BOOM Analytics
As a first concrete exercise in disorderly cloud programming, we built BOOM Analytics: an API-compliant reimplementation of Hadoop (BOOM-MR) and the Hadoop File System (BOOM-FS). Both are written in the Overlog declarative language, with some modest use of Java for support. Developed in a relatively short nine-month design cycle, our new implementation performs competitively with the standard Hadoop codebase, with a compact and easily-extendible codebase. Within that timeframe we extended BOOM with new features not yet available in Hadoop, including:
high availability master nodes (via an implementation of MultiPaxos in Overlog)
scale-out of master nodes to multiple machines (via simple data partitioning), and
unique reflection-based monitoring and debugging facilities (via metaprogramming in Overlog)
One key to our approach is that everything is data, i.e. rows in tables that can be queried and manipulated. This includes persistent data (e.g. filesystem metadata), runtime state (e.g. Hadoop scheduler bookkeeping), summary stats (e.g. for advanced straggler scheduling), in-flight msgs and system events, even parsed code. When everything in a system is data, it becomes easy to do things like parallelize computations on the state, make it fault tolerant, and express (and enforce) invariants on legal states of the system.
Please click here to download and run BOOM-FS. A reimplementation of BOOM-FS in Bud is part of the Bud Sandbox